System

Abstract

A system is provided.SOLUTION: A system comprising: a user authentication means; an information terminal for transmitting a user input; a natural language processing means for analyzing a user utterance; a generative model means for generating a response based on the analyzed user utterance; and an information terminal for providing the generated response to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In modern digital entertainment, users are seeking more personalized experiences. However, conventional virtual idols and interactive entertainment systems have had difficulty properly understanding users' comments and emotions and providing natural dialogue in response to them. Furthermore, they lacked sufficient interaction capabilities to provide interactive content tailored to limited-time events or special themes. This prevented users from fully enjoying the interaction with the virtual idols, diminishing the appeal of interactive entertainment. [Means for solving the problem]

[0005] This invention solves the above-mentioned problems by the following means. Specifically, it provides a system including a user authentication means, an information terminal for transmitting user input, a natural language processing means for analyzing user utterances, a generative model means for generating responses based on the analyzed user utterances, and an information terminal for providing the generated responses to the user. This system makes it possible to appropriately understand the user's utterances and emotions and provide natural dialogue based on them. Furthermore, by providing dialogue content provision means for limited events or special themes and a means for saving dialogue content as a log, users can enjoy unique interactions with AI dolls at any time. In this way, a new type of digital entertainment experience is created and the relationship between users and AI can be deepened.

[0006] "User authentication means" refers to the process of receiving a user's login information and authenticating the user by checking it against a database.

[0007] "Information terminal" means a device through which a user can enter input and through which generated responses can be received and displayed.

[0008] "Natural language processing means" refers to a natural language processing engine used to analyze user utterances.

[0009] "Generative model means" refers to an AI model that generates responses based on the content of statements analyzed by natural language processing means.

[0010] The "interactive content providing means" refers to a process for providing users with interactive content according to a specific event or theme.

[0011] "Log storage means" refers to the process of storing the content of the conversation between the user and the AI ​​dollar as a log in a database. [Brief explanation of the drawings]

[0012] [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

[0013] 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.

[0014] First, the terms used in the following description will be explained.

[0015] 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).

[0016] 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.

[0017] 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.

[0018] 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.

[0019] 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."

[0020] [First embodiment]

[0021] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0022] 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.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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.

[0028] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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."

[0033] This invention is a platform that allows users to interact with AI dollars in real time, and uses generative AI models. Below, we will explain the processing of this system in natural language, and also provide specific examples.

[0034] User authentication method

[0035] 1. Terminal: The user enters their user ID and password on the login screen and presses the send button.

[0036] The terminal sends a login request to the server.

[0037] 2. Server: The server checks the user ID and password received from the terminal against the database.

[0038] The server retrieves the user data from a database and verifies the authentication information.

[0039] 3. Server: If authentication is successful, the server generates a session ID and sends it back to the user.

[0040] The server generates a session ID and returns it to the user.

[0041] 4. Terminal: The terminal stores the session ID received from the server in memory and transitions to the dialogue start screen.

[0042] The terminal retains the session ID and transitions to the dialogue start screen.

[0043] Receive a request to start a conversation

[0044] 1. Terminal: The user presses the interaction start button.

[0045] The terminal sends a dialogue initiation request to the server.

[0046] 2. Server: The server initiates the interactive session and generates the initial message for the AI ​​dollar.

[0047] The server generates an initial message using an AI model and sends it to the terminal.

[0048] 3. Terminal: The terminal displays the AI ​​Dollar's welcome message to the user.

[0049] The terminal will display the AI ​​Dollar initial message on the screen.

[0050] User comment analysis using natural language processing

[0051] 1. User: The user responds to the message from the AI ​​dollar by typing and sending the text.

[0052] The terminal sends a user message to the server.

[0053] 2. Server: The server receives the user's speech and analyzes it using a natural language processing (NLP) engine.

[0054] The server analyzes the content, emotions, and intentions of the statements using an NLP engine.

[0055] 3. Server: The server obtains the analysis results (emotions, intentions) and prepares to generate a response accordingly.

[0056] The server prepares for reaction generation based on the analysis results.

[0057] Reaction formation of AI dollar

[0058] 1. Server: The server uses the generative AI model to generate AI dollar responses based on the analysis results.

[0059] The server uses the analysis results as input and the AI ​​model generates the corresponding response.

[0060] 2. Server: The server sends the generated response to the user terminal.

[0061] The server sends the generated response to the terminal.

[0062] 3. Terminal: The terminal displays the AI ​​dollar response to the user.

[0063] The terminal will display the AI ​​dollar's response on the screen.

[0064] Special event and theme dialogue content provided

[0065] 1. Server: A server provides interactive content during a specific event or based on a special theme.

[0066] The server checks the special event information from a database or API and retrieves the content.

[0067] 2. Server: The server generates special messages based on events and themes.

[0068] The server uses an AI model to generate special messages based on the special content.

[0069] 3. Terminal: The terminal displays a special message.

[0070] The terminal displays a special message to the user.

[0071] Log of conversations

[0072] 1. Server: The server stores user utterances and AI dollar responses for each dialogue session.

[0073] The server generates a log entry of the user's utterance and the AI ​​dollar's response.

[0074] 2. Server: The server stores the generated log entries in a database.

[0075] The server stores the log entries in a database.

[0076] 3. Server: If necessary, the server uses the logs to later analyze the interaction.

[0077] The server uses the stored logs for analysis.

[0078] In this way, users can enjoy natural and personalized interactions with AI Dollars, and unique interactions are possible based on special events or themes, providing a new type of digital entertainment experience.

[0079] The processing flow will be explained below.

[0080] Step 1:

[0081] Terminal: The user enters their user ID and password on the login screen and presses the send button.

[0082] The terminal sends a login request to the server.

[0083] Step 2:

[0084] Server: The server checks the user ID and password received from the terminal against the database.

[0085] The server retrieves the user data from a database and compares it with the entered password.

[0086] Step 3:

[0087] Server: If authentication is successful, the server generates a session ID and returns it to the user.

[0088] The server generates a session ID and sends it to the terminal as a response.

[0089] Step 4:

[0090] Terminal: The terminal stores the session ID received from the server in memory and transitions to the dialogue start screen.

[0091] The terminal stores the session ID in memory and displays a dialogue start screen to the user.

[0092] Step 5:

[0093] Terminal: The user presses the interaction start button.

[0094] The terminal sends a dialogue initiation request to the server.

[0095] Step 6:

[0096] Server: The server initiates the interactive session and generates the initial message for the AI.

[0097] The server generates an initial message to be sent by the AI ​​dollar and sends it to the terminal.

[0098] Step 7:

[0099] Terminal: The terminal displays the AI ​​Dollar's welcome message to the user.

[0100] The terminal will display the AI ​​Dollar initial message on the screen.

[0101] Step 8:

[0102] User: The user responds to the message from the AI ​​dollar by typing and sending the text.

[0103] The terminal sends a user message to the server.

[0104] Step 9:

[0105] Server: The server receives the user's utterance and analyzes it using a natural language processing (NLP) engine.

[0106] The server analyzes the content, sentiment, and intent of the speech using an NLP engine.

[0107] Step 10:

[0108] Server: The server obtains the analysis results (emotions, intentions) and prepares to generate a response accordingly.

[0109] The server prepares to generate an appropriate response based on the analysis results.

[0110] Step 11:

[0111] Server: The server uses the generative AI model to generate AI dollar responses based on the analysis results.

[0112] The server uses the analysis results as input to generate the response content of the AI ​​dollar.

[0113] Step 12:

[0114] Server: The server sends the generated response to the user device.

[0115] The server sends the generated reaction to the terminal as a response.

[0116] Step 13:

[0117] Terminal: The terminal displays the AI ​​dollar response to the user.

[0118] The terminal will display the AI ​​dollar's response on the screen.

[0119] Step 14:

[0120] Servers: Servers provide interactive content during specific events or based on special themes.

[0121] The server checks the database or API for special event information and generates content based on that information.

[0122] Step 15:

[0123] Server: The server generates special messages based on events and themes.

[0124] The server uses an AI model to generate a message based on the special content and sends it to the device.

[0125] Step 16:

[0126] Terminals: Terminals display special messages.

[0127] The terminal displays a special message on the user's screen.

[0128] Step 17:

[0129] Server: The server stores user utterances and AI dollar responses for each dialogue session.

[0130] The server generates a log entry of the user's utterance and the AI ​​dollar's response.

[0131] Step 18:

[0132] Server: The server stores the generated log entries in a database.

[0133] The server stores the log entries in a database.

[0134] Step 19:

[0135] Server: If necessary, the server uses the logs to later analyze the interaction.

[0136] The server uses the stored logs for analysis.

[0137] Example 1

[0138] 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."

[0139] In recent years, dialogue systems using artificial intelligence have become widespread, but they are being required to meet a variety of needs, such as reliable user authentication, natural dialogue, provision of dialogue content according to special events or themes, and logging of dialogue content.However, conventional systems face the challenge of being unable to simultaneously meet all of these needs.

[0140] 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.

[0141] In this invention, the server

[0142] means for verifying user authentication information;

[0143] A means of generating and transmitting a session ID if authentication is successful;

[0144] A means for transmitting user comments and analyzing them using natural language processing means;

[0145] A generative AI model means for generating a response based on the analyzed user utterance;

[0146] A means to provide interactive content for limited events and special themes,

[0147] A means for storing the contents of the dialogue as a log;

[0148] This allows for increased reliability in user authentication, natural and personalized interactions, the provision of content for special events or themes, and the storage of interaction logs.

[0149] "User authentication information" refers to information such as an ID and password that a user enters to verify their identity.

[0150] "Information terminal" is a general term for electronic devices that users use to input and send and receive data.

[0151] The term "server means" refers to a computer system for receiving and processing requests, and is a device that has the functions of verifying data, generating session IDs, and generating and transmitting messages.

[0152] A "session ID" is a unique identifier generated by the server to indicate successful authentication of a user and to manage an interactive session.

[0153] "Natural language processing means" refers to technology that analyzes text data entered by a user and understands their meaning, emotions, and intent.

[0154] A "generative AI model means" is an artificial intelligence model used to generate appropriate responses based on analyzed user utterances.

[0155] "Interactive content based on limited events or special themes" refers to special interactive content provided during specific event periods or based on special themes.

[0156] A "log" is recorded data that includes user utterances and AI dollar responses for each interactive session.

[0157] The present invention is a platform that allows users to interact with AI characters in real time, and uses generative AI models. Detailed embodiments of the system are described below.

[0158] User Authentication

[0159] When the system starts, the user uses an information terminal (e.g., smartphone, tablet, PC) to enter their user ID and password on the login screen and press the send button. The terminal then sends this login request to the server. The server compares the received user ID and password with the database, and if they match, generates a session ID and sends it to the user's terminal. The terminal then stores the session ID in memory and transitions to the dialogue start screen.

[0160] Starting a conversation

[0161] When the user presses the dialogue start button, the device sends a dialogue start request to the server. The server starts a dialogue session and sends a prompt to the generative AI model to generate an initial message. The generated initial message is sent to the user's device and displayed to the user.

[0162] Analysis of user comments

[0163] The user responds to messages from the AI ​​character by inputting text and sending it. The device then sends the user message to the server, which then analyzes the received user message using a natural language processing (NLP) engine to extract the content, emotion, and intent of the message.

[0164] AI character reaction generation

[0165] The server sends a prompt to the generative AI model to generate a response based on the analysis results of the NLP engine. For example, "The user said 'hello,' so please generate a response that says 'hello.'" The generated response is sent to the device via the server and displayed to the user.

[0166] Providing interactive content based on special events and themes

[0167] The server automatically generates interactive content based on specific event periods or special themes. For example, during an event, a special message such as "Happy Birthday! Today is a special day!" is displayed. The server obtains special event information using a database or API and sends prompts to the generative AI model to generate special content.

[0168] Conversation logging and analysis

[0169] The server generates log entries for each interaction session, including user comments and AI character responses, and stores them in a database, allowing for later analysis of the interaction content to improve the service and detect errors.

[0170] Specific examples

[0171] For example, if a user types "hello" and sends it, it will be processed as follows:

[0172] 1. User: Type "Hello" and send.

[0173] 2. Device: Sends "hello" to the server.

[0174] 3. Server: Analyze "hello" using an NLP engine to read the emotion and intent. Recognize it as a "greeting."

[0175] 4. Server: Based on the analysis results, the server sends a prompt to the generative AI model to generate a response to the greeting.

[0176] 5. Server: Sends the generated response "Hello! What would you like to talk about today?" to the user terminal.

[0177] 6. Terminal: Display "Hello! What would you like to talk about today?" to the user.

[0178] This system allows users to enjoy more natural and personalized interactions, and enables unique interactions based on special events or themes.The system cleverly utilizes generative AI models and prompts to provide a new form of digital entertainment.

[0179] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0180] Step 1: Enter and submit user credentials

[0181] 1. User: The user enters the user ID and password on the login screen of the information terminal and presses the send button. The user ID and password are provided as input.

[0182] 2. Terminal: The terminal receives the user's input, generates a login request, and sends it to the server. As an output, a login request is generated.

[0183] Step 2: Verify user authentication

[0184] 1. Server: The server parses the received login request and extracts the user ID and password. The login request is provided as input.

[0185] 2. Server: Retrieves user information from the database and matches it with the entered authentication information. The user information retrieved from the database is used for matching.

[0186] 3. Server: Generates a session ID if the authentication information is correct, or an error message if it is incorrect. As output, a session ID or an error message is generated.

[0187] 4. Server: Sends the session ID or an error message to the terminal. As output, the session ID or an error message is sent to the terminal.

[0188] Step 3: Session ID retention and screen transitions

[0189] 1. Terminal: Parse the session ID or error message received from the server. As input, the session ID or error message is provided.

[0190] 2. Terminal: Keep the session ID in memory and display a success message or transition to the start of the conversation screen. If it is incorrect, display an error message and stay at the login screen. As output, the success or error message is displayed on the screen.

[0191] Step 4: Sending a conversation-initiating request

[0192] 1. User: The user clicks the interaction start button. The click of the interaction start button is provided as input.

[0193] 2. Terminal: Prepares to send a conversation initiation request to the server. As output, a conversation initiation request is generated.

[0194] 3. Terminal: Sends a conversation initiation request to the server. As an output, a conversation initiation request is sent to the server.

[0195] Step 5: Generate and send the initial message

[0196] 1. Server: Receives a conversation initiation request and starts a conversation session. The conversation initiation request is provided as input.

[0197] 2. Server: Sends a prompt to the generative AI model to generate an initial message. The prompt sentence is provided as input.

[0198] 3. Server: Receives the initial message from the generative AI model and sends it to the device. As an output, an initial message is generated and sent to the device.

[0199] Step 6: Displaying a welcome message

[0200] 1. Terminal: Receives the initial message and displays it to the user. As input, the initial message is provided. As output, the initial message is displayed on the screen.

[0201] Step 7: Enter and send user utterances

[0202] 1. User: Enters and sends text in response to a message from an AI character. The user's text is provided as input.

[0203] 2. Terminal: receives user input and prepares it for transmission to the server. As output, a user message is generated.

[0204] 3. Terminal: Sends user messages to the server. As output, the user messages are sent to the server.

[0205] Step 8: Analyzing user utterances

[0206] 1. Server: Receives the user message and starts parsing it in the natural language processing engine. The user message is provided as input.

[0207] 2. Server: Analyzes the message content, sentiment, and intent using an NLP engine. The analysis results are generated as output.

[0208] 3. Server: Retrieves the analysis results and prepares the data for reaction generation. The output is the data for reaction generation.

[0209] Step 9: Generate and send AI character reactions

[0210] 1. Server: Based on the analysis results, the server sends a prompt to the generative AI model to generate a reaction. The prompt sentence for generating a reaction is provided as input.

[0211] 2. Server: Prepares to send the generated responses to the terminal. The generated responses are generated as output.

[0212] 3. Server: Sends the generated responses to the terminal. As output, the generated responses are sent to the terminal.

[0213] Step 10: Viewing the Reaction

[0214] 1. Terminal: Analyzes the received AI character's reaction and displays it to the user. As input, the AI ​​character's reaction is provided. As output, the reaction is displayed on the screen.

[0215] Step 11: Offer special events or themed content

[0216] 1. Server: Checks whether there is a specific event or special themed interactive content. Event information is provided as input.

[0217] 2. Server: Retrieves special event information using a database or API and generates a prompt with limited content. As output, the special event information is retrieved and a prompt statement is generated.

[0218] 3. Server: Sends a prompt with special content to the generative AI model to generate a special message. As input, a prompt with special content is provided. As output, a special message is generated.

[0219] 4. Server: Prepares to send the generated special message to the user terminal. As output, the special message is generated.

[0220] 5. Server: Sends the generated special message to the user terminal. As output, the special message is sent to the terminal.

[0221] 6. Terminal: Receives special messages and displays them to the user. As input, special messages are provided. As output, special messages are displayed on the screen.

[0222] Step 12: Logging interactions

[0223] 1. Server: Generates log entries for each interaction session, including user utterances and AI character responses. As input, the server receives user utterances and AI character responses. As output, it generates a log entry.

[0224] 2. Server: Stores the generated log entries in a database. As an output, the log entries are stored in a database.

[0225] The above is the specific program processing flow of this system.

[0226] (Application example 1)

[0227] 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."

[0228] Conventional dialogue systems generally involve dialogue between users and AI, but lack the functionality to provide dialogue content based on special events or themes. Furthermore, few applications are compatible with multiple devices, limiting the devices that users can use. Furthermore, it is difficult to log and analyze dialogues later, making it difficult to track user behavior and improve services.

[0229] 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.

[0230] In this invention, the server includes a user authentication means, an information terminal means for transmitting user input, and a natural language processing means for analyzing user utterances, which allows users and AI to enjoy unique dialogue content during a specific event or based on a special theme, and further enables compatibility with multiple devices and the saving of dialogue logs for later analysis.

[0231] "User authentication" is the process by which a user verifies the identity used to log into a system.

[0232] An "information terminal that transmits user input" is a device through which a user can enter text, voice, or other forms of input and transmit it to the system.

[0233] "Natural language processing means for analyzing user utterances" is a technology that analyzes the linguistic information entered by the user and understands its content, emotions, and intentions.

[0234] The "generative model means for generating a response based on the analyzed user utterance" is an artificial intelligence technology for generating an appropriate response based on the analysis results.

[0235] The "means for generating dialogue content during a specific event or based on a special theme" is a function for creating dialogue content according to a special event or theme and presenting it to the user.

[0236] An "information terminal that provides the user with the generated response" is a device that displays or audibly conveys the response generated by AI to the user.

[0237] "Means for saving dialogue content as a log" is a function for recording the content of dialogue between the user and AI and saving it for future reference.

[0238] An "interactive application compatible with a variety of devices, including smartphones, head-mounted displays, and smart glasses" is an application that runs on a variety of devices and provides interactive functions between users and AI.

[0239] The present invention provides a system that allows users to interact with AI dollars in real time using a variety of devices. Specific embodiments of this system will be described below.

[0240] The system includes a user authentication means, an information terminal for transmitting user input, a natural language processing means for analyzing user utterances, a generative model means for generating responses based on the analyzed user utterances, a means for generating dialogue content during a specific event period or based on a special theme, an information terminal for providing the generated responses to the user, and a means for saving the dialogue content as a log.

[0241] 1. Hardware and Software

[0242] The hardware required to build the system includes a smartphone, smart glasses, and a head-mounted display, while the software uses Python, Flask (a web framework), an NLP engine (e.g., SpaCy, Transformers), and a generative AI model (e.g., GPT-3).

[0243] 2. Program Processing

[0244] The server first authenticates the user ID and password entered by the user using the user authentication means. If the authentication is successful, it returns a session ID to the user and receives a request to start a dialogue. When the user presses the dialogue start button, the server starts a dialogue session, generates an initial message for the AI ​​dollar, and sends it to the information terminal.

[0245] The user checks the initial message on the information terminal and responds by inputting a response in text or voice. The input user utterance is sent to the server and analyzed by the natural language processing means. The generative model means generates a response based on the analyzed content, emotion, and intention.

[0246] If conversation content based on a specific event period or special theme is required, the server generates special content and provides users with special messages based on that content. This allows users to enjoy unique conversations that are tailored to the event or theme. All conversation content is also saved as a log on the server and can be used for later analysis.

[0247] 3. Specific Examples

[0248] For example, a "Happy New Year" campaign will be held as a limited-time event. AI Dollar will provide special content that will interact with users about their "New Year's resolutions." This special content will be generated based on the following prompts:

[0249] "This is a scenario where a user shares their New Year's resolutions. The AI ​​dollar generates appropriate responses based on what the user says, continuing a fun conversation fit for the New Year."

[0250] As described above, this system allows users to enjoy real-time conversations based on special events or themes across multiple devices, and the content of the conversations is saved as a log so that they can be analyzed later.

[0251] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0252] Step 1:

[0253] The user displays the login screen on their information terminal, enters their user ID and password, and submits it. The entered data is the user ID and password, and is sent from the terminal to the server. The server receives this request and checks the user ID and password against its database.

[0254] Step 2:

[0255] The server retrieves the user information from the database and verifies the authentication information. If the authentication is successful, the server generates a session ID and sends it back to the terminal. This authenticates the user and gives them a session ID to proceed to the next step.

[0256] Step 3:

[0257] The terminal stores the session ID received from the server in memory and switches to the dialogue start screen. The user presses the dialogue start button here and sends a dialogue start request to the server. This request includes the session ID.

[0258] Step 4:

[0259] The server starts an interactive session and generates an initial message for the AI ​​using the generative AI model. The input is the session ID and the prompt required to generate the initial message, and the output is the generated initial message. The server sends this initial message to the terminal.

[0260] Step 5:

[0261] The terminal displays the initial message received from the server on the screen. The user responds to this message by inputting a response in text or voice and sends it. The input data is the user's message, and the terminal sends it to the server.

[0262] Step 6:

[0263] The server receives the user's comments and analyzes them using a natural language processing engine. The input for the analysis is the user's message, and the output is the analysis results, such as the content of the comment, emotions, and intentions. Based on this, the server prepares to generate a response from the AI ​​dollar.

[0264] Step 7:

[0265] The server generates an appropriate AI response using a generative AI model based on the analysis results. The input is the analysis result and the prompt, and the output is the generated response. The server then sends this response to the device.

[0266] Step 8:

[0267] The terminal displays the AI ​​dollar response received from the server to the user, who can then enter a message again to continue the conversation. The process repeats.

[0268] Step 9:

[0269] During and after a conversation session, the server stores the entire conversation as a log. The data stored is the user's statements and the AI ​​dollar's responses, and the server stores this in a database. The log is later used for analysis and service improvement.

[0270] Step 10:

[0271] The server provides special interactive content based on specific event periods or special themes. The prompt text is used to generate the special content, and the generative AI model generates a special response based on it. The server then sends it to the device, allowing the user to enjoy the special interaction.

[0272] 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.

[0273] This invention is a platform that allows users to interact with AI dollars in real time, using a generative AI model and an emotion engine. Below, we will explain the processing of this system in natural language, and also provide concrete examples.

[0274] User authentication method

[0275] 1. Terminal: The user enters their user ID and password on the login screen and presses the send button.

[0276] The terminal sends a login request to the server.

[0277] 2. Server: The server checks the user ID and password received from the terminal against the database.

[0278] The server retrieves the user data from a database and compares it with the entered password.

[0279] 3. Server: If authentication is successful, the server generates a session ID and sends it back to the user.

[0280] The server generates a session ID and sends it to the terminal as a response.

[0281] 4. Terminal: The terminal stores the session ID received from the server in memory and transitions to the dialogue start screen.

[0282] The terminal holds the session ID and displays the dialogue start screen to the user.

[0283] Receive a request to start a conversation

[0284] 1. Terminal: The user presses the interaction start button.

[0285] The terminal sends a dialogue initiation request to the server.

[0286] 2. Server: The server initiates the interactive session and generates the initial message for the AI ​​dollar.

[0287] The server generates an initial message to be sent by the AI ​​dollar and sends it to the terminal.

[0288] 3. Terminal: The terminal displays the AI ​​Dollar's welcome message to the user.

[0289] The terminal will display the AI ​​Dollar initial message on the screen.

[0290] Analyzing user comments using natural language processing and using an emotion engine

[0291] 1. User: The user responds to the message from the AI ​​dollar by typing and sending the text.

[0292] The terminal sends a user message to the server.

[0293] 2. Server: The server receives the user's speech and analyzes it using a natural language processing (NLP) engine.

[0294] The server analyzes the content, sentiment, and intent of the speech using an NLP engine.

[0295] 3. Server: The server sends the analysis results to the emotion engine for detailed emotion analysis.

[0296] The server further analyzes the user's emotions using an emotion engine and obtains the results.

[0297] Reaction formation of AI dollar

[0298] 1. Server: The server uses the generative AI model to generate responses from the AI ​​dollar based on the analysis results and the emotional information obtained from the emotion engine.

[0299] The server generates an appropriate response based on the analysis results and emotional information.

[0300] 2. Server: The server sends the generated response to the user terminal.

[0301] The server sends the generated reaction to the terminal as a response.

[0302] 3. Terminal: The terminal displays the AI ​​dollar response to the user.

[0303] The terminal will display the AI ​​dollar's response on the screen.

[0304] Special event and theme dialogue content provided

[0305] 1. Server: A server provides interactive content during a specific event or based on a special theme.

[0306] The server checks the database or API for special event information and generates content based on that information.

[0307] 2. Server: The server generates special messages based on events and themes.

[0308] The server uses an AI model to generate a message based on the special content and sends it to the device.

[0309] 3. Terminal: The terminal displays a special message.

[0310] The terminal displays a special message on the user's screen.

[0311] Log of conversations

[0312] 1. Server: The server stores user utterances, AI responses, and emotion data from the emotion engine for each dialogue session.

[0313] The server generates log entries based on user comments, AI dollar responses, and emotional data.

[0314] 2. Server: The server stores the generated log entries in a database.

[0315] The server stores the log entries in a database.

[0316] 3. Server: If necessary, the server uses the logs to later analyze the interaction.

[0317] The server uses the stored logs for analysis.

[0318] In this way, users can enjoy natural and personalized interactions with AI Dollars, and unique interactions are possible based on special events or themes. In addition, the emotion engine allows AI Dollars to better understand users' emotions and respond accordingly, providing a new type of digital entertainment experience.

[0319] The processing flow will be explained below.

[0320] Step 1:

[0321] Terminal: The user enters their user ID and password on the login screen and presses the send button.

[0322] The terminal sends a login request to the server.

[0323] Step 2:

[0324] Server: The server checks the user ID and password received from the terminal against the database.

[0325] The server retrieves the user data from a database and compares it with the entered password.

[0326] Step 3:

[0327] Server: If authentication is successful, the server generates a session ID and returns it to the user.

[0328] The server generates a session ID and sends it to the terminal as a response.

[0329] Step 4:

[0330] Terminal: The terminal stores the session ID received from the server in memory and transitions to the dialogue start screen.

[0331] The terminal holds the session ID and displays the dialogue start screen to the user.

[0332] Step 5:

[0333] Terminal: The user presses the interaction start button.

[0334] The terminal sends a dialogue initiation request to the server.

[0335] Step 6:

[0336] Server: The server initiates the interactive session and generates the initial message for the AI.

[0337] The server generates an initial message to be sent by the AI ​​dollar and sends it to the terminal.

[0338] Step 7:

[0339] Terminal: The terminal displays the AI ​​Dollar's welcome message to the user.

[0340] The terminal will display the AI ​​Dollar initial message on the screen.

[0341] Step 8:

[0342] User: The user responds to the message from the AI ​​dollar by typing and sending the text.

[0343] The terminal sends a user message to the server.

[0344] Step 9:

[0345] Server: The server receives the user's utterance and analyzes it using a natural language processing (NLP) engine.

[0346] The server analyzes the content, sentiment, and intent of the speech using an NLP engine.

[0347] Step 10:

[0348] Server: The server sends the analysis results to the emotion engine for detailed emotion analysis.

[0349] The server further analyzes the user's emotions using an emotion engine and obtains the results.

[0350] Step 11:

[0351] Server: The server uses the generative AI model to generate responses from the AI ​​dollar based on the analysis results and emotional information obtained from the emotion engine.

[0352] The server generates the AI ​​dollar's response based on the analysis results and emotional information.

[0353] Step 12:

[0354] Server: The server sends the generated response to the user device.

[0355] The server sends the generated reaction to the terminal as a response.

[0356] Step 13:

[0357] Terminal: The terminal displays the AI ​​dollar response to the user.

[0358] The terminal will display the AI ​​dollar's response on the screen.

[0359] Step 14:

[0360] Servers: Servers provide interactive content during specific events or based on special themes.

[0361] The server checks the database or API for special event information and generates content based on that information.

[0362] Step 15:

[0363] Server: The server generates special messages based on events and themes.

[0364] The server uses an AI model to generate a message based on the special content and sends it to the device.

[0365] Step 16:

[0366] Terminals: Terminals display special messages.

[0367] The terminal displays a special message on the user's screen.

[0368] Step 17:

[0369] Server: The server stores user utterances, AI responses, and emotion data from the emotion engine for each dialogue session.

[0370] The server generates log entries based on user comments, AI dollar responses, and emotional data.

[0371] Step 18:

[0372] Server: The server stores the generated log entries in a database.

[0373] The server stores the log entries in a database.

[0374] Step 19:

[0375] Server: If necessary, the server uses the logs to later analyze the interaction.

[0376] The server uses the stored logs for analysis.

[0377] Example 2

[0378] 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."

[0379] Current dialogue systems struggle to accurately understand user sentiment and generate appropriate responses based on it. Furthermore, they lack the ability to provide special event or themed content, limiting the user experience. They also lack the means to effectively store dialogue content for later analysis.

[0380] 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.

[0381] In this invention, the server includes a user authentication means, an information terminal through which a user inputs and transmits information, a natural language processing means for analyzing user utterances, a generative AI model means for generating a response based on the analyzed user utterances, an information terminal for providing the generated response to the user, a sentiment analysis means for analyzing the sentiment of the user utterances, a means for adjusting the response to be generated based on the sentiment analysis, and a means for generating an initial message at the start of an interaction session. This makes it possible to accurately understand the user's sentiment and generate an appropriate response based on that sentiment. Furthermore, by providing dialogue content according to special events or themes and saving the dialogue content as a log for later analysis, a richer user experience can be provided.

[0382] "User authentication means" refers to a means for verifying whether a user is a legitimate user by checking the user ID and password.

[0383] An "information terminal" is a device that allows a user to input and transmit information, and includes, for example, a personal computer, a smartphone, a tablet, and the like.

[0384] "Natural language processing" refers to technology for analyzing user utterances and understanding their content and intent. This includes text analysis, semantic analysis, and context understanding.

[0385] A "generative AI model means" is an artificial intelligence algorithm or model for generating appropriate responses based on analyzed user utterances.

[0386] "Emotion analysis means" is a technology that analyzes the emotions contained in a user's speech and identifies their emotional state. This includes emotion detection and emotion classification.

[0387] The "means for adjusting the response" is a technology for adjusting the response generated based on the emotion analysis results and providing an appropriate response that matches the user's emotional state.

[0388] "Means for generating an initial message" refers to technology for generating the first message that the AI ​​issues at the start of an interaction session.

[0389] The "means for providing dialogue content according to limited events or special themes" is a means for generating special dialogue content based on a specific event period or theme and providing it to users.

[0390] "Means for saving dialogue content as a log" refers to a means for saving the dialogue content between the user and the AI ​​and the analysis results in a database or the like so that they can be referenced and analyzed later.

[0391] This invention is a platform that allows users to interact with artificial intelligence (AI) characters in real time. This platform operates by combining multiple functions including user authentication means, natural language processing means, emotion analysis means, and generative AI model means.

[0392] First, the user uses an information terminal (for example, a PC or smartphone) to enter their user ID and password on the login screen. When the user presses the send button, the information is sent from the terminal to the server. The server compares the received information with a database and performs authentication. If authentication is successful, the server generates a session ID and returns it to the terminal. The terminal retains this session ID and displays the dialogue start screen to the user.

[0393] Next, the user presses the Start Dialogue button, which sends a dialogue start request to the server, which then starts a new dialogue session. Using a generative AI model (e.g., "AI-GPT"), the server generates an initial message and sends it to the device. The device then displays this initial message to the user.

[0394] When a user replies to a message from an AI character, the message is sent from the device to a server. The server analyzes the received message using a natural language processing (NLP) engine (e.g., "NLP-Analyzer") to understand the content and intent of the message. The analysis results are then sent to an emotion analysis engine (e.g., "Emotion-X") for detailed emotion analysis. Based on the obtained emotion data, a generative AI model generates an appropriate response. This response is then sent to the device and displayed to the user.

[0395] In addition, the server will prepare exclusive interactive content and generate special messages based on specific event periods or special themes, allowing users to enjoy a constantly new experience.

[0396] Furthermore, the server stores the dialogue content, user comments, AI character responses, and emotional data as logs, which allows for later analysis of the user's dialogue behavior.

[0397] As a specific example, when a user logs in by entering "user123" and "password123" on the login screen, the server returns a session ID and the dialogue start screen is displayed on the device. When the user presses the dialogue start button, an AI character displays the initial message "Hello! How was your day?" If the user replies "I'm a little tired today," the server analyzes this message with an NLP engine and identifies the emotion of "tired" with an emotion analysis engine. The generative AI model generates a response saying "That must have been tough. It's important to take some time to rest," and displays this on the device.

[0398] An example of a prompt might be:

[0399] Please enter the prompt to send the API request for login authentication.

[0400] "Explain how to integrate an NLP engine with a sentiment engine to perform sentiment analysis of user input."

[0401] In this way, users can enjoy a richer, more personalized interaction experience using generative AI models and sentiment analysis engines, and unique interaction content is provided based on events and special themes, ensuring a constantly fresh entertainment experience.

[0402] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0403] User authentication method

[0404] Step 1: Enter and submit your login details

[0405] User: The user enters their user ID and password on the login screen and presses the submit button.

[0406] Input: User ID, Password

[0407] What happens: The user enters information into the text boxes and clicks the "Login" button.

[0408] Output: Login request (user ID, password)

[0409] Step 2: Submitting authentication information

[0410] Terminal: Sends the entered information to the server.

[0411] Input: Login request (user ID, password)

[0412] Specific operation: Sends the user ID and password to the server using an HTTP POST request.

[0413] Output: Authentication request to the server

[0414] Step 3: Verify credentials

[0415] Server: The server queries the database for the received user ID and password and performs verification.

[0416] Input: Authentication request to the server

[0417] What happens: The server performs a database query to compare the password associated with the user ID with the submitted password.

[0418] Output: Authentication result (success / failure)

[0419] Step 4: Generate and send a session ID

[0420] Server: If authentication is successful, a session ID is generated and sent back to the device.

[0421] Input: Authentication result (success)

[0422] Specific operation: A session ID is generated using a UUID or similar and sent back to the device as an HTTP response.

[0423] Output: Session ID

[0424] Step 5: Receiving and maintaining a session ID

[0425] Terminal: The terminal stores the session ID received from the server in its memory.

[0426] Input: Session ID

[0427] Specific behavior: Saves the session ID in local storage or memory.

[0428] Output: Persisted session ID

[0429] Step 6: Display the conversation start screen

[0430] Terminal: Transition to the dialogue start screen.

[0431] Input: Persisted session ID

[0432] Specific Behavior: Switch to UI indicating successful login.

[0433] Output: Start screen

[0434] Receive a request to start a conversation

[0435] Step 1: Press the Start Dialogue button

[0436] User: The user presses the start button.

[0437] Input: User operation (pressing the interaction start button)

[0438] Specific action: The user clicks the start button.

[0439] Output: Conversation initiating request

[0440] Step 2: Sending a conversation-initiating request

[0441] Terminal: Sends a dialogue initiation request to the server.

[0442] Input: Conversation-initiating request

[0443] Specific behavior: Sends a conversation initiation request to the server using an HTTP GET or POST request.

[0444] Output: A conversation initiating request to the server

[0445] Step 3: Starting an interactive session

[0446] Server: The server starts a new interactive session and generates the AI ​​dollar's initial message.

[0447] Input: A request to start a conversation with the server

[0448] Specific operation: Generate an initial message using a generative AI model (e.g., "AI-GPT").

[0449] Output: Initial message

[0450] Step 4: Sending the initial message

[0451] Server: Sends an initial message to the device.

[0452] Input: initial message

[0453] Specific operation: Sends an initial message to the terminal as an HTTP response.

[0454] Output: Initial message to terminal

[0455] Step 5: Displaying a welcome message

[0456] Terminal: Displays the received initial message to the user.

[0457] Input: initial message to terminal

[0458] Specific behavior: Display an initial message on the UI.

[0459] Output: Shows the initial message.

[0460] Analyzing user comments using natural language processing and using an emotion engine

[0461] Step 1: Enter and send user utterances

[0462] User: The user responds to the message from the AI ​​dollar by typing and sending a message.

[0463] Input: User message

[0464] Specific actions: Enter a message in the text area and click the "Send" button.

[0465] Output: User utterances

[0466] Step 2: Sending a User Message

[0467] Terminal: Sends user messages to the server.

[0468] Input: User utterance

[0469] Specific behavior: Sends a message to the server using an HTTP POST request.

[0470] Output: User message to the server

[0471] Step 3: Analyzing user utterances

[0472] Server: Analyzes received user messages using a natural language processing (NLP) engine.

[0473] Input: User message to server

[0474] Specific behavior: Analyzes speech content, sentiment, and intent using an NLP engine (e.g., "NLP-Analyzer").

[0475] Output: Analysis results

[0476] Step 4: Perform sentiment analysis

[0477] Server: The analysis results are sent to the sentiment analysis engine for detailed sentiment analysis.

[0478] Input: Analysis results

[0479] Specific operation: Obtain detailed emotional data using the emotion analysis engine "Emotion-X."

[0480] Output: Detailed emotion data

[0481] Reaction formation of AI dollar

[0482] Step 1: Generate the reaction

[0483] Server: Uses a generative AI model to generate responses based on analysis results and emotional data.

[0484] Input: Analysis results, detailed emotion data

[0485] Specific operation: A prompt sentence is input into a generative AI model (e.g., "AI-GPT"), which generates an appropriate response.

[0486] Output: The generated reaction

[0487] Step 2: Sending a response

[0488] Server: Sends the generated responses to the device.

[0489] Input: Generated reactions

[0490] Specific operation: Sends the generated response to the terminal as an HTTP response.

[0491] Output: Response to terminal

[0492] Step 3: View the reaction

[0493] Terminal: Displays the response of the received AI dollar to the user.

[0494] Input: Response to terminal

[0495] Specific behavior: Displays AI dollar reactions on the UI.

[0496] Output: Display of AI dollar response

[0497] Special event and theme dialogue content provided

[0498] Step 1: Prepare special content

[0499] Servers: Prepare interactive content for specific events or special themes.

[0500] Input: Event information, theme information

[0501] What it does: Retrieves event information from a database or external API and generates special content.

[0502] Output: Special Content

[0503] Step 2: Generate a special message

[0504] Server: Generates special messages based on active events and themes.

[0505] Input: Special Content

[0506] What it does: Uses a generative AI model to generate a special message and send it to the device.

[0507] Output: special message

[0508] Step 3: Send and display special messages

[0509] Terminal: Display a special message to the user.

[0510] Input: Special message

[0511] Specific behavior: Display a special message in the UI.

[0512] Output: Display a special message

[0513] Log of conversations

[0514] Step 1: Generate a log entry

[0515] Server: Generates log entries for each interaction session, including user utterances, AI responses, and emotion data.

[0516] Input: User utterances, AI dollar responses, sentiment data

[0517] Specific operation: Create a single log entry containing the dialogue content and emotion data.

[0518] Output: The generated log entries

[0519] Step 2: Save the logs

[0520] Server: Stores the generated log entries in a database.

[0521] Input: Generated log entry

[0522] What it does: Executes a query to store interaction log entries in a database.

[0523] Output: Saved logs

[0524] Step 3: Leverage the logs

[0525] Server: The stored logs are used for analysis and improvement as needed.

[0526] Input: Saved logs

[0527] What happens: Log entries are reviewed using analytics tools and used to improve the system and enhance the user experience.

[0528] Output: Analysis results

[0529] (Application example 2)

[0530] 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."

[0531] In conventional virtual stores, users could only browse a list of products, making it difficult to receive personalized guidance. Furthermore, there was a lack of appropriate product suggestions tailored to the user's emotions and needs, resulting in a poor user experience. Furthermore, the provision of content based on special events or themes was limited, limiting the improvement of user satisfaction.

[0532] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes user authentication means, an information terminal that transmits user input, natural language processing means that analyzes user utterances, generative model means that generate a response based on the analyzed user utterances, an information terminal that provides the generated response to the user, emotion analysis means that analyzes user emotions, and product recommendation means that suggests specific products to the user based on the emotion analysis results. This enables the user to receive individual guidance and appropriate product suggestions based on their emotions and needs, improving the quality of the user experience in the virtual store.

[0533] "User authentication means" refers to a process or device that verifies the identity of a user when accessing a system.

[0534] An "information terminal that transmits user input" is a device that transmits data that is input by a user through operation to a server or the like.

[0535] "Natural language processing means for analyzing user utterances" refers to technology or devices for analyzing text entered by a user and understanding its content.

[0536] "Generative model means" refers to a technique or device for generating appropriate responses based on analyzed user utterances.

[0537] The "information terminal that provides the generated response to the user" refers to a device that displays the generated response to the user.

[0538] "Emotion analysis means" refers to technology or devices that analyze the emotions of users based on their comments and determine their state.

[0539] "Product recommendation means" refers to technology or devices for suggesting specific products to users based on the results of emotion analysis.

[0540] A system for implementing this invention includes user authentication means, an information terminal for transmitting user input, natural language processing means for analyzing user utterances, generative model means, an information terminal for providing the generated response to the user, emotion analysis means, and product recommendation means. A program for realizing this system operates as follows.

[0541] First, the user logs in to the information terminal from a smartphone or head-mounted display (HMD) and is authenticated through the authentication means. The user authentication means is a process in which the user enters their user ID and password and sends that information to the server. The server compares the user's ID with the database, and if the user is authenticated as a legitimate user, it generates a session ID and sends it back to the information terminal.

[0542] Next, the user presses the dialogue start button to start a dialogue with the AI ​​dollar. The server, which receives the dialogue start request, generates an initial message for the AI ​​dollar and sends it to the information terminal. The user enters text in reply to that message and sends it back to the server.

[0543] The server analyzes the text sent by the user using natural language processing means to understand the content of the statement. For natural language processing, Google Cloud Natural Language API or spaCy are used, for example. The analysis results are sent to sentiment analysis means, where more detailed sentiment analysis is performed. IBM Watson Tone Analyzer can be used for this sentiment analysis.

[0544] Based on the results of the sentiment analysis, the server generates an appropriate response using a generative model, such as OpenAI's GPT-3 or GPT-4. The generated response is sent to the information terminal and displayed to the user.

[0545] It also has a product recommendation feature that suggests specific products to users based on the results of sentiment analysis. For example, if a user says, "I'm looking for a dress," the AI ​​dollar will suggest, "We have several dresses that would be suitable for a summer party. How about this blue dress or this black dress?"

[0546] Furthermore, when there is information about a specific event or sale, the server generates a message according to the limited event or special theme and notifies the user. This special content includes introductions to special products and discount information.

[0547] All of these interactions are saved as logs, which will be used for future analysis and to improve the user experience.

[0548] For example, if a user says, "I'm looking for a dress that suits tonight's party," the AI ​​dollar will respond as follows:

[0549] "It's a perfect dress for a party! I'll show you some popular items. How about this turquoise dress or a black dress?"

[0550] In this way, users can enjoy natural and personalized interactions with AI Dollar and efficiently search for suitable products. The following are examples of prompt sentences:

[0551] User: I'm looking for a dress for tonight's party.

[0552] AI Dollar: A perfect dress for a party! Let me show you some popular items. How about this turquoise dress or a black dress?

[0553] In this way, the present invention can improve the quality of the user experience.

[0554] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0555] Step 1: User authentication

[0556] 1. Input: The user enters their user ID and password into the information terminal (smartphone or HMD).

[0557] 2. Processing: The terminal sends the entered information to the server.

[0558] 3. Data processing: The server checks the user ID and password in the database.

[0559] 4. Output: If authentication is successful, the server generates a session ID and sends it to the terminal.

[0560] Step 2: Conversation-initiating request

[0561] 1. Input: The user presses the interaction start button displayed on the terminal.

[0562] 2. Processing: The terminal sends a dialogue start request to the server.

[0563] 3. Data Calculation: The server initiates the interactive session and generates the initial message for the AI ​​dollar.

[0564] 4. Output: Sends the initial message to the terminal and is displayed to the user.

[0565] Step 3: User comment analysis

[0566] 1. Input: The user inputs text in response to a message from the AI ​​dollar and sends it.

[0567] 2. Processing: The device sends the user's text to the server.

[0568] 3. Data calculation: The server analyzes the user's speech using natural language processing tools (e.g., Google Cloud Natural Language API or spaCy).

[0569] 4. Output: The content, intent, and sentiment of the speech are analyzed and sent to a sentiment analyzer.

[0570] Step 4: Sentiment Analysis

[0571] 1. Input: Analysis results sent from natural language processing means.

[0572] 2. Processing: The server performs further sentiment analysis using sentiment analysis tools (e.g. IBM Watson Tone Analyzer).

[0573] 3. Data calculation: Determine the user's emotional state.

[0574] 4. Output: Send the sentiment analysis results to the generative modeling means.

[0575] Step 5: Response Generation

[0576] 1. Input: Sentiment analysis results and analysis results from natural language processing tools.

[0577] 2. Processing: The server generates an appropriate response using a generative model (e.g., OpenAI GPT-3 or GPT-4).

[0578] 3. Data calculation: Generate the optimal response in text format based on the analysis results.

[0579] 4. Output: Send the generated response to the terminal.

[0580] Step 6: Display the response

[0581] 1. Input: The generated response sent by the server.

[0582] 2. Processing: The terminal displays the generated response to the user.

[0583] 3. Output: User confirms AI Dollar's response.

[0584] Step 7: Product Recommendation

[0585] 1. Input: Sentiment analysis results and user comments.

[0586] 2. Processing: The server uses the product recommendation means to suggest suitable products.

[0587] 3. Data calculation: Generate a list of products based on sentiment analysis and speech content.

[0588] 4. Output: Display the product recommendations to the user.

[0589] Step 8: Special Event Notifications

[0590] 1. Input: Specific event or sale information in the system.

[0591] 2. Processing: The server generates messages for limited events or special themes.

[0592] 3. Data Calculation: Generate special messages based on event information.

[0593] 4. Output: Notify the user with a special message.

[0594] Step 9: Save conversation logs

[0595] 1. Input: User utterances, AI dollar responses, and sentiment data.

[0596] 2. Processing: The server stores the conversation as a log.

[0597] 3. Data calculation: Generates log entries and stores them in a database.

[0598] 4. Output: The saved logs are stored as data for future analysis.

[0599] 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.

[0600] 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.

[0601] 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.

[0602] [Second embodiment]

[0603] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0604] 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.

[0605] 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).

[0606] 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.

[0607] 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.

[0608] 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).

[0609] 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.

[0610] 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.

[0611] 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.

[0612] 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.

[0613] 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.

[0614] 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."

[0615] This invention is a platform that allows users to interact with AI dollars in real time, and uses generative AI models. Below, we will explain the processing of this system in natural language, and also provide specific examples.

[0616] User authentication method

[0617] 1. Terminal: The user enters their user ID and password on the login screen and presses the send button.

[0618] The terminal sends a login request to the server.

[0619] 2. Server: The server checks the user ID and password received from the terminal against the database.

[0620] The server retrieves the user data from a database and verifies the authentication information.

[0621] 3. Server: If authentication is successful, the server generates a session ID and sends it back to the user.

[0622] The server generates a session ID and returns it to the user.

[0623] 4. Terminal: The terminal stores the session ID received from the server in memory and transitions to the dialogue start screen.

[0624] The terminal retains the session ID and transitions to the dialogue start screen.

[0625] Receive a request to start a conversation

[0626] 1. Terminal: The user presses the interaction start button.

[0627] The terminal sends a dialogue initiation request to the server.

[0628] 2. Server: The server initiates the interactive session and generates the initial message for the AI ​​dollar.

[0629] The server generates an initial message using an AI model and sends it to the terminal.

[0630] 3. Terminal: The terminal displays the AI ​​Dollar's welcome message to the user.

[0631] The terminal will display the AI ​​Dollar initial message on the screen.

[0632] User comment analysis using natural language processing

[0633] 1. User: The user responds to the message from the AI ​​dollar by typing and sending the text.

[0634] The terminal sends a user message to the server.

[0635] 2. Server: The server receives the user's speech and analyzes it using a natural language processing (NLP) engine.

[0636] The server analyzes the content, emotions, and intentions of the statements using an NLP engine.

[0637] 3. Server: The server obtains the analysis results (emotions, intentions) and prepares to generate a response accordingly.

[0638] The server prepares for reaction generation based on the analysis results.

[0639] Reaction formation of AI dollar

[0640] 1. Server: The server uses the generative AI model to generate AI dollar responses based on the analysis results.

[0641] The server uses the analysis results as input and the AI ​​model generates the corresponding response.

[0642] 2. Server: The server sends the generated response to the user terminal.

[0643] The server sends the generated response to the terminal.

[0644] 3. Terminal: The terminal displays the AI ​​dollar response to the user.

[0645] The terminal will display the AI ​​dollar's response on the screen.

[0646] Special event and theme dialogue content provided

[0647] 1. Server: A server provides interactive content during a specific event or based on a special theme.

[0648] The server checks the special event information from a database or API and retrieves the content.

[0649] 2. Server: The server generates special messages based on events and themes.

[0650] The server uses an AI model to generate special messages based on the special content.

[0651] 3. Terminal: The terminal displays a special message.

[0652] The terminal displays a special message to the user.

[0653] Log of conversations

[0654] 1. Server: The server stores user utterances and AI dollar responses for each dialogue session.

[0655] The server generates a log entry of the user's utterance and the AI ​​dollar's response.

[0656] 2. Server: The server stores the generated log entries in a database.

[0657] The server stores the log entries in a database.

[0658] 3. Server: If necessary, the server uses the logs to later analyze the interaction.

[0659] The server uses the stored logs for analysis.

[0660] In this way, users can enjoy natural and personalized interactions with AI Dollars, and unique interactions are possible based on special events or themes, providing a new type of digital entertainment experience.

[0661] The processing flow will be explained below.

[0662] Step 1:

[0663] Terminal: The user enters their user ID and password on the login screen and presses the send button.

[0664] The terminal sends a login request to the server.

[0665] Step 2:

[0666] Server: The server checks the user ID and password received from the terminal against the database.

[0667] The server retrieves the user data from a database and compares it with the entered password.

[0668] Step 3:

[0669] Server: If authentication is successful, the server generates a session ID and returns it to the user.

[0670] The server generates a session ID and sends it to the terminal as a response.

[0671] Step 4:

[0672] Terminal: The terminal stores the session ID received from the server in memory and transitions to the dialogue start screen.

[0673] The terminal stores the session ID in memory and displays a dialogue start screen to the user.

[0674] Step 5:

[0675] Terminal: The user presses the interaction start button.

[0676] The terminal sends a dialogue initiation request to the server.

[0677] Step 6:

[0678] Server: The server initiates the interactive session and generates the initial message for the AI.

[0679] The server generates an initial message to be sent by the AI ​​dollar and sends it to the terminal.

[0680] Step 7:

[0681] Terminal: The terminal displays the AI ​​Dollar's welcome message to the user.

[0682] The terminal will display the AI ​​Dollar initial message on the screen.

[0683] Step 8:

[0684] User: The user responds to the message from the AI ​​dollar by typing and sending the text.

[0685] The terminal sends a user message to the server.

[0686] Step 9:

[0687] Server: The server receives the user's utterance and analyzes it using a natural language processing (NLP) engine.

[0688] The server analyzes the content, sentiment, and intent of the speech using an NLP engine.

[0689] Step 10:

[0690] Server: The server obtains the analysis results (emotions, intentions) and prepares to generate a response accordingly.

[0691] The server prepares to generate an appropriate response based on the analysis results.

[0692] Step 11:

[0693] Server: The server uses the generative AI model to generate AI dollar responses based on the analysis results.

[0694] The server uses the analysis results as input to generate the response content of the AI ​​dollar.

[0695] Step 12:

[0696] Server: The server sends the generated response to the user device.

[0697] The server sends the generated reaction to the terminal as a response.

[0698] Step 13:

[0699] Terminal: The terminal displays the AI ​​dollar response to the user.

[0700] The terminal will display the AI ​​dollar's response on the screen.

[0701] Step 14:

[0702] Servers: Servers provide interactive content during specific events or based on special themes.

[0703] The server checks the database or API for special event information and generates content based on that information.

[0704] Step 15:

[0705] Server: The server generates special messages based on events and themes.

[0706] The server uses an AI model to generate a message based on the special content and sends it to the device.

[0707] Step 16:

[0708] Terminals: Terminals display special messages.

[0709] The terminal displays a special message on the user's screen.

[0710] Step 17:

[0711] Server: The server stores user utterances and AI dollar responses for each dialogue session.

[0712] The server generates a log entry of the user's utterance and the AI ​​dollar's response.

[0713] Step 18:

[0714] Server: The server stores the generated log entries in a database.

[0715] The server stores the log entries in a database.

[0716] Step 19:

[0717] Server: If necessary, the server uses the logs to later analyze the interaction.

[0718] The server uses the stored logs for analysis.

[0719] Example 1

[0720] 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."

[0721] In recent years, dialogue systems using artificial intelligence have become widespread, but they are being required to meet a variety of needs, such as reliable user authentication, natural dialogue, provision of dialogue content according to special events or themes, and logging of dialogue content.However, conventional systems face the challenge of being unable to simultaneously meet all of these needs.

[0722] 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.

[0723] In this invention, the server

[0724] means for verifying user authentication information;

[0725] A means of generating and transmitting a session ID if authentication is successful;

[0726] A means for transmitting user comments and analyzing them using natural language processing means;

[0727] A generative AI model means for generating a response based on the analyzed user utterance;

[0728] A means to provide interactive content for limited events and special themes,

[0729] A means for storing the contents of the dialogue as a log;

[0730] This allows for increased reliability in user authentication, natural and personalized interactions, the provision of content for special events or themes, and the storage of interaction logs.

[0731] "User authentication information" refers to information such as an ID and password that a user enters to verify their identity.

[0732] "Information terminal" is a general term for electronic devices that users use to input and send and receive data.

[0733] The term "server means" refers to a computer system for receiving and processing requests, and is a device that has the functions of verifying data, generating session IDs, and generating and transmitting messages.

[0734] A "session ID" is a unique identifier generated by the server to indicate successful authentication of a user and to manage an interactive session.

[0735] "Natural language processing means" refers to technology that analyzes text data entered by a user and understands their meaning, emotions, and intent.

[0736] A "generative AI model means" is an artificial intelligence model used to generate appropriate responses based on analyzed user utterances.

[0737] "Interactive content based on limited events or special themes" refers to special interactive content provided during specific event periods or based on special themes.

[0738] A "log" is recorded data that includes user utterances and AI dollar responses for each interactive session.

[0739] The present invention is a platform that allows users to interact with AI characters in real time, and uses generative AI models. Detailed embodiments of the system are described below.

[0740] User Authentication

[0741] When the system starts, the user uses an information terminal (e.g., smartphone, tablet, PC) to enter their user ID and password on the login screen and press the send button. The terminal then sends this login request to the server. The server compares the received user ID and password with the database, and if they match, generates a session ID and sends it to the user's terminal. The terminal then stores the session ID in memory and transitions to the dialogue start screen.

[0742] Starting a conversation

[0743] When the user presses the dialogue start button, the device sends a dialogue start request to the server. The server starts a dialogue session and sends a prompt to the generative AI model to generate an initial message. The generated initial message is sent to the user's device and displayed to the user.

[0744] Analysis of user comments

[0745] The user responds to messages from the AI ​​character by inputting text and sending it. The device then sends the user message to the server, which then analyzes the received user message using a natural language processing (NLP) engine to extract the content, emotion, and intent of the message.

[0746] AI character reaction generation

[0747] The server sends a prompt to the generative AI model to generate a response based on the analysis results of the NLP engine. For example, "The user said 'hello,' so please generate a response that says 'hello.'" The generated response is sent to the device via the server and displayed to the user.

[0748] Providing interactive content based on special events and themes

[0749] The server automatically generates interactive content based on specific event periods or special themes. For example, during an event, a special message such as "Happy Birthday! Today is a special day!" is displayed. The server obtains special event information using a database or API and sends prompts to the generative AI model to generate special content.

[0750] Conversation logging and analysis

[0751] The server generates log entries for each interaction session, including user comments and AI character responses, and stores them in a database, allowing for later analysis of the interaction content to improve the service and detect errors.

[0752] Specific examples

[0753] For example, if a user types "hello" and sends it, it will be processed as follows:

[0754] 1. User: Type "Hello" and send.

[0755] 2. Device: Sends "hello" to the server.

[0756] 3. Server: Analyze "hello" using an NLP engine to read the emotion and intent. Recognize it as a "greeting."

[0757] 4. Server: Based on the analysis results, the server sends a prompt to the generative AI model to generate a response to the greeting.

[0758] 5. Server: Sends the generated response "Hello! What would you like to talk about today?" to the user terminal.

[0759] 6. Terminal: Display "Hello! What would you like to talk about today?" to the user.

[0760] This system allows users to enjoy more natural and personalized interactions, and enables unique interactions based on special events or themes.The system cleverly utilizes generative AI models and prompts to provide a new form of digital entertainment.

[0761] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0762] Step 1: Enter and submit user credentials

[0763] 1. User: The user enters the user ID and password on the login screen of the information terminal and presses the send button. The user ID and password are provided as input.

[0764] 2. Terminal: The terminal receives the user's input, generates a login request, and sends it to the server. As an output, a login request is generated.

[0765] Step 2: Verify user authentication

[0766] 1. Server: The server parses the received login request and extracts the user ID and password. The login request is provided as input.

[0767] 2. Server: Retrieves user information from the database and matches it with the entered authentication information. The user information retrieved from the database is used for matching.

[0768] 3. Server: Generates a session ID if the authentication information is correct, or an error message if it is incorrect. As output, a session ID or an error message is generated.

[0769] 4. Server: Sends the session ID or an error message to the terminal. As output, the session ID or an error message is sent to the terminal.

[0770] Step 3: Session ID retention and screen transitions

[0771] 1. Terminal: Parse the session ID or error message received from the server. As input, the session ID or error message is provided.

[0772] 2. Terminal: Keep the session ID in memory and display a success message or transition to the start of the conversation screen. If it is incorrect, display an error message and stay at the login screen. As output, the success or error message is displayed on the screen.

[0773] Step 4: Sending a conversation-initiating request

[0774] 1. User: The user clicks the interaction start button. The click of the interaction start button is provided as input.

[0775] 2. Terminal: Prepares to send a conversation initiation request to the server. As output, a conversation initiation request is generated.

[0776] 3. Terminal: Sends a conversation initiation request to the server. As an output, a conversation initiation request is sent to the server.

[0777] Step 5: Generate and send the initial message

[0778] 1. Server: Receives a conversation initiation request and starts a conversation session. The conversation initiation request is provided as input.

[0779] 2. Server: Sends a prompt to the generative AI model to generate an initial message. The prompt sentence is provided as input.

[0780] 3. Server: Receives the initial message from the generative AI model and sends it to the device. As an output, an initial message is generated and sent to the device.

[0781] Step 6: Displaying a welcome message

[0782] 1. Terminal: Receives the initial message and displays it to the user. As input, the initial message is provided. As output, the initial message is displayed on the screen.

[0783] Step 7: Enter and send user utterances

[0784] 1. User: Enters and sends text in response to a message from an AI character. The user's text is provided as input.

[0785] 2. Terminal: receives user input and prepares it for transmission to the server. As output, a user message is generated.

[0786] 3. Terminal: Sends user messages to the server. As output, the user messages are sent to the server.

[0787] Step 8: Analyzing user utterances

[0788] 1. Server: Receives the user message and starts parsing it in the natural language processing engine. The user message is provided as input.

[0789] 2. Server: Analyzes the message content, sentiment, and intent using an NLP engine. The analysis results are generated as output.

[0790] 3. Server: Retrieves the analysis results and prepares the data for reaction generation. The output is the data for reaction generation.

[0791] Step 9: Generate and send AI character reactions

[0792] 1. Server: Based on the analysis results, the server sends a prompt to the generative AI model to generate a reaction. The prompt sentence for generating a reaction is provided as input.

[0793] 2. Server: Prepares to send the generated responses to the terminal. The generated responses are generated as output.

[0794] 3. Server: Sends the generated responses to the terminal. As output, the generated responses are sent to the terminal.

[0795] Step 10: Viewing the Reaction

[0796] 1. Terminal: Analyzes the received AI character's reaction and displays it to the user. As input, the AI ​​character's reaction is provided. As output, the reaction is displayed on the screen.

[0797] Step 11: Offer special events or themed content

[0798] 1. Server: Checks whether there is a specific event or special themed interactive content. Event information is provided as input.

[0799] 2. Server: Retrieves special event information using a database or API and generates a prompt with limited content. As output, the special event information is retrieved and a prompt statement is generated.

[0800] 3. Server: Sends a prompt with special content to the generative AI model to generate a special message. As input, a prompt with special content is provided. As output, a special message is generated.

[0801] 4. Server: Prepares to send the generated special message to the user terminal. As output, the special message is generated.

[0802] 5. Server: Sends the generated special message to the user terminal. As output, the special message is sent to the terminal.

[0803] 6. Terminal: Receives special messages and displays them to the user. As input, special messages are provided. As output, special messages are displayed on the screen.

[0804] Step 12: Logging interactions

[0805] 1. Server: Generates log entries for each interaction session, including user utterances and AI character responses. As input, the server receives user utterances and AI character responses. As output, it generates a log entry.

[0806] 2. Server: Stores the generated log entries in a database. As an output, the log entries are stored in a database.

[0807] The above is the specific program processing flow of this system.

[0808] (Application example 1)

[0809] 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."

[0810] Conventional dialogue systems generally involve dialogue between users and AI, but lack the functionality to provide dialogue content based on special events or themes. Furthermore, few applications are compatible with multiple devices, limiting the devices that users can use. Furthermore, it is difficult to log and analyze dialogues later, making it difficult to track user behavior and improve services.

[0811] 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.

[0812] In this invention, the server includes a user authentication means, an information terminal means for transmitting user input, and a natural language processing means for analyzing user utterances, which allows users and AI to enjoy unique dialogue content during a specific event or based on a special theme, and further enables compatibility with multiple devices and the saving of dialogue logs for later analysis.

[0813] "User authentication" is the process by which a user verifies the identity used to log into a system.

[0814] An "information terminal that transmits user input" is a device through which a user can enter text, voice, or other forms of input and transmit it to the system.

[0815] "Natural language processing means for analyzing user utterances" is a technology that analyzes the linguistic information entered by the user and understands its content, emotions, and intentions.

[0816] The "generative model means for generating a response based on the analyzed user utterance" is an artificial intelligence technology for generating an appropriate response based on the analysis results.

[0817] The "means for generating dialogue content during a specific event or based on a special theme" is a function for creating dialogue content according to a special event or theme and presenting it to the user.

[0818] An "information terminal that provides the user with the generated response" is a device that displays or audibly conveys the response generated by AI to the user.

[0819] "Means for saving dialogue content as a log" is a function for recording the content of dialogue between the user and AI and saving it for future reference.

[0820] An "interactive application compatible with a variety of devices, including smartphones, head-mounted displays, and smart glasses" is an application that runs on a variety of devices and provides interactive functions between users and AI.

[0821] The present invention provides a system that allows users to interact with AI dollars in real time using a variety of devices. Specific embodiments of this system will be described below.

[0822] The system includes a user authentication means, an information terminal for transmitting user input, a natural language processing means for analyzing user utterances, a generative model means for generating responses based on the analyzed user utterances, a means for generating dialogue content during a specific event period or based on a special theme, an information terminal for providing the generated responses to the user, and a means for saving the dialogue content as a log.

[0823] 1. Hardware and Software

[0824] The hardware required to build the system includes a smartphone, smart glasses, and a head-mounted display, while the software uses Python, Flask (a web framework), an NLP engine (e.g., SpaCy, Transformers), and a generative AI model (e.g., GPT-3).

[0825] 2. Program Processing

[0826] The server first authenticates the user ID and password entered by the user using the user authentication means. If the authentication is successful, it returns a session ID to the user and receives a request to start a dialogue. When the user presses the dialogue start button, the server starts a dialogue session, generates an initial message for the AI ​​dollar, and sends it to the information terminal.

[0827] The user checks the initial message on the information terminal and responds by inputting a response in text or voice. The input user utterance is sent to the server and analyzed by the natural language processing means. The generative model means generates a response based on the analyzed content, emotion, and intention.

[0828] If conversation content based on a specific event period or special theme is required, the server generates special content and provides users with special messages based on that content. This allows users to enjoy unique conversations that are tailored to the event or theme. All conversation content is also saved as a log on the server and can be used for later analysis.

[0829] 3. Specific Examples

[0830] For example, a "Happy New Year" campaign will be held as a limited-time event. AI Dollar will provide special content that will interact with users about their "New Year's resolutions." This special content will be generated based on the following prompts:

[0831] "This is a scenario where a user shares their New Year's resolutions. The AI ​​dollar generates appropriate responses based on what the user says, continuing a fun conversation fit for the New Year."

[0832] As described above, this system allows users to enjoy real-time conversations based on special events or themes across multiple devices, and the content of the conversations is saved as a log so that they can be analyzed later.

[0833] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0834] Step 1:

[0835] The user displays the login screen on their information terminal, enters their user ID and password, and submits it. The entered data is the user ID and password, and is sent from the terminal to the server. The server receives this request and checks the user ID and password against its database.

[0836] Step 2:

[0837] The server retrieves the user information from the database and verifies the authentication information. If the authentication is successful, the server generates a session ID and sends it back to the terminal. This authenticates the user and gives them a session ID to proceed to the next step.

[0838] Step 3:

[0839] The terminal stores the session ID received from the server in memory and switches to the dialogue start screen. The user presses the dialogue start button here and sends a dialogue start request to the server. This request includes the session ID.

[0840] Step 4:

[0841] The server starts an interactive session and generates an initial message for the AI ​​using the generative AI model. The input is the session ID and the prompt required to generate the initial message, and the output is the generated initial message. The server sends this initial message to the terminal.

[0842] Step 5:

[0843] The terminal displays the initial message received from the server on the screen. The user responds to this message by inputting a response in text or voice and sends it. The input data is the user's message, and the terminal sends it to the server.

[0844] Step 6:

[0845] The server receives the user's comments and analyzes them using a natural language processing engine. The input for the analysis is the user's message, and the output is the analysis results, such as the content of the comment, emotions, and intentions. Based on this, the server prepares to generate a response from the AI ​​dollar.

[0846] Step 7:

[0847] The server generates an appropriate AI response using a generative AI model based on the analysis results. The input is the analysis result and the prompt, and the output is the generated response. The server then sends this response to the device.

[0848] Step 8:

[0849] The terminal displays the AI ​​dollar response received from the server to the user, who can then enter a message again to continue the conversation. The process repeats.

[0850] Step 9:

[0851] During and after a conversation session, the server stores the entire conversation as a log. The data stored is the user's statements and the AI ​​dollar's responses, and the server stores this in a database. The log is later used for analysis and service improvement.

[0852] Step 10:

[0853] The server provides special interactive content based on specific event periods or special themes. The prompt text is used to generate the special content, and the generative AI model generates a special response based on it. The server then sends it to the device, allowing the user to enjoy the special interaction.

[0854] 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.

[0855] This invention is a platform that allows users to interact with AI dollars in real time, using a generative AI model and an emotion engine. Below, we will explain the processing of this system in natural language, and also provide concrete examples.

[0856] User authentication method

[0857] 1. Terminal: The user enters their user ID and password on the login screen and presses the send button.

[0858] The terminal sends a login request to the server.

[0859] 2. Server: The server checks the user ID and password received from the terminal against the database.

[0860] The server retrieves the user data from a database and compares it with the entered password.

[0861] 3. Server: If authentication is successful, the server generates a session ID and sends it back to the user.

[0862] The server generates a session ID and sends it to the terminal as a response.

[0863] 4. Terminal: The terminal stores the session ID received from the server in memory and transitions to the dialogue start screen.

[0864] The terminal holds the session ID and displays the dialogue start screen to the user.

[0865] Receive a request to start a conversation

[0866] 1. Terminal: The user presses the interaction start button.

[0867] The terminal sends a dialogue initiation request to the server.

[0868] 2. Server: The server initiates the interactive session and generates the initial message for the AI ​​dollar.

[0869] The server generates an initial message to be sent by the AI ​​dollar and sends it to the terminal.

[0870] 3. Terminal: The terminal displays the AI ​​Dollar's welcome message to the user.

[0871] The terminal will display the AI ​​Dollar initial message on the screen.

[0872] Analyzing user comments using natural language processing and using an emotion engine

[0873] 1. User: The user responds to the message from the AI ​​dollar by typing and sending the text.

[0874] The terminal sends a user message to the server.

[0875] 2. Server: The server receives the user's speech and analyzes it using a natural language processing (NLP) engine.

[0876] The server analyzes the content, sentiment, and intent of the speech using an NLP engine.

[0877] 3. Server: The server sends the analysis results to the emotion engine for detailed emotion analysis.

[0878] The server further analyzes the user's emotions using an emotion engine and obtains the results.

[0879] Reaction formation of AI dollar

[0880] 1. Server: The server uses the generative AI model to generate responses from the AI ​​dollar based on the analysis results and the emotional information obtained from the emotion engine.

[0881] The server generates an appropriate response based on the analysis results and emotional information.

[0882] 2. Server: The server sends the generated response to the user terminal.

[0883] The server sends the generated reaction to the terminal as a response.

[0884] 3. Terminal: The terminal displays the AI ​​dollar response to the user.

[0885] The terminal will display the AI ​​dollar's response on the screen.

[0886] Special event and theme dialogue content provided

[0887] 1. Server: A server provides interactive content during a specific event or based on a special theme.

[0888] The server checks the database or API for special event information and generates content based on that information.

[0889] 2. Server: The server generates special messages based on events and themes.

[0890] The server uses an AI model to generate a message based on the special content and sends it to the device.

[0891] 3. Terminal: The terminal displays a special message.

[0892] The terminal displays a special message on the user's screen.

[0893] Log of conversations

[0894] 1. Server: The server stores user utterances, AI responses, and emotion data from the emotion engine for each dialogue session.

[0895] The server generates log entries based on user comments, AI dollar responses, and emotional data.

[0896] 2. Server: The server stores the generated log entries in a database.

[0897] The server stores the log entries in a database.

[0898] 3. Server: If necessary, the server uses the logs to later analyze the interaction.

[0899] The server uses the stored logs for analysis.

[0900] In this way, users can enjoy natural and personalized interactions with AI Dollars, and unique interactions are possible based on special events or themes. In addition, the emotion engine allows AI Dollars to better understand users' emotions and respond accordingly, providing a new type of digital entertainment experience.

[0901] The processing flow will be explained below.

[0902] Step 1:

[0903] Terminal: The user enters their user ID and password on the login screen and presses the send button.

[0904] The terminal sends a login request to the server.

[0905] Step 2:

[0906] Server: The server checks the user ID and password received from the terminal against the database.

[0907] The server retrieves the user data from a database and compares it with the entered password.

[0908] Step 3:

[0909] Server: If authentication is successful, the server generates a session ID and returns it to the user.

[0910] The server generates a session ID and sends it to the terminal as a response.

[0911] Step 4:

[0912] Terminal: The terminal stores the session ID received from the server in memory and transitions to the dialogue start screen.

[0913] The terminal holds the session ID and displays the dialogue start screen to the user.

[0914] Step 5:

[0915] Terminal: The user presses the interaction start button.

[0916] The terminal sends a dialogue initiation request to the server.

[0917] Step 6:

[0918] Server: The server initiates the interactive session and generates the initial message for the AI.

[0919] The server generates an initial message to be sent by the AI ​​dollar and sends it to the terminal.

[0920] Step 7:

[0921] Terminal: The terminal displays the AI ​​Dollar's welcome message to the user.

[0922] The terminal will display the AI ​​Dollar initial message on the screen.

[0923] Step 8:

[0924] User: The user responds to the message from the AI ​​dollar by typing and sending the text.

[0925] The terminal sends a user message to the server.

[0926] Step 9:

[0927] Server: The server receives the user's utterance and analyzes it using a natural language processing (NLP) engine.

[0928] The server analyzes the content, sentiment, and intent of the speech using an NLP engine.

[0929] Step 10:

[0930] Server: The server sends the analysis results to the emotion engine for detailed emotion analysis.

[0931] The server further analyzes the user's emotions using an emotion engine and obtains the results.

[0932] Step 11:

[0933] Server: The server uses the generative AI model to generate responses from the AI ​​dollar based on the analysis results and emotional information obtained from the emotion engine.

[0934] The server generates the AI ​​dollar's response based on the analysis results and emotional information.

[0935] Step 12:

[0936] Server: The server sends the generated response to the user device.

[0937] The server sends the generated reaction to the terminal as a response.

[0938] Step 13:

[0939] Terminal: The terminal displays the AI ​​dollar response to the user.

[0940] The terminal will display the AI ​​dollar's response on the screen.

[0941] Step 14:

[0942] Servers: Servers provide interactive content during specific events or based on special themes.

[0943] The server checks the database or API for special event information and generates content based on that information.

[0944] Step 15:

[0945] Server: The server generates special messages based on events and themes.

[0946] The server uses an AI model to generate a message based on the special content and sends it to the device.

[0947] Step 16:

[0948] Terminals: Terminals display special messages.

[0949] The terminal displays a special message on the user's screen.

[0950] Step 17:

[0951] Server: The server stores user utterances, AI responses, and emotion data from the emotion engine for each dialogue session.

[0952] The server generates log entries based on user comments, AI dollar responses, and emotional data.

[0953] Step 18:

[0954] Server: The server stores the generated log entries in a database.

[0955] The server stores the log entries in a database.

[0956] Step 19:

[0957] Server: If necessary, the server uses the logs to later analyze the interaction.

[0958] The server uses the stored logs for analysis.

[0959] Example 2

[0960] 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."

[0961] Current dialogue systems struggle to accurately understand user sentiment and generate appropriate responses based on it. Furthermore, they lack the ability to provide special event or themed content, limiting the user experience. They also lack the means to effectively store dialogue content for later analysis.

[0962] 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.

[0963] In this invention, the server includes a user authentication means, an information terminal through which a user inputs and transmits information, a natural language processing means for analyzing user utterances, a generative AI model means for generating a response based on the analyzed user utterances, an information terminal for providing the generated response to the user, a sentiment analysis means for analyzing the sentiment of the user utterances, a means for adjusting the response to be generated based on the sentiment analysis, and a means for generating an initial message at the start of an interaction session. This makes it possible to accurately understand the user's sentiment and generate an appropriate response based on that sentiment. Furthermore, by providing dialogue content according to special events or themes and saving the dialogue content as a log for later analysis, a richer user experience can be provided.

[0964] "User authentication means" refers to a means for verifying whether a user is a legitimate user by checking the user ID and password.

[0965] An "information terminal" is a device that allows a user to input and transmit information, and includes, for example, a personal computer, a smartphone, a tablet, and the like.

[0966] "Natural language processing" refers to technology for analyzing user utterances and understanding their content and intent. This includes text analysis, semantic analysis, and context understanding.

[0967] A "generative AI model means" is an artificial intelligence algorithm or model for generating appropriate responses based on analyzed user utterances.

[0968] "Emotion analysis means" is a technology that analyzes the emotions contained in a user's speech and identifies their emotional state. This includes emotion detection and emotion classification.

[0969] The "means for adjusting the response" is a technology for adjusting the response generated based on the emotion analysis results and providing an appropriate response that matches the user's emotional state.

[0970] "Means for generating an initial message" refers to technology for generating the first message that the AI ​​issues at the start of an interaction session.

[0971] The "means for providing dialogue content according to limited events or special themes" is a means for generating special dialogue content based on a specific event period or theme and providing it to users.

[0972] "Means for saving dialogue content as a log" refers to a means for saving the dialogue content between the user and the AI ​​and the analysis results in a database or the like so that they can be referenced and analyzed later.

[0973] This invention is a platform that allows users to interact with artificial intelligence (AI) characters in real time. This platform operates by combining multiple functions including user authentication means, natural language processing means, emotion analysis means, and generative AI model means.

[0974] First, the user uses an information terminal (for example, a PC or smartphone) to enter their user ID and password on the login screen. When the user presses the send button, the information is sent from the terminal to the server. The server compares the received information with a database and performs authentication. If authentication is successful, the server generates a session ID and returns it to the terminal. The terminal retains this session ID and displays the dialogue start screen to the user.

[0975] Next, the user presses the Start Dialogue button, which sends a dialogue start request to the server, which then starts a new dialogue session. Using a generative AI model (e.g., "AI-GPT"), the server generates an initial message and sends it to the device. The device then displays this initial message to the user.

[0976] When a user replies to a message from an AI character, the message is sent from the device to a server. The server analyzes the received message using a natural language processing (NLP) engine (e.g., "NLP-Analyzer") to understand the content and intent of the message. The analysis results are then sent to an emotion analysis engine (e.g., "Emotion-X") for detailed emotion analysis. Based on the obtained emotion data, a generative AI model generates an appropriate response. This response is then sent to the device and displayed to the user.

[0977] In addition, the server will prepare exclusive interactive content and generate special messages based on specific event periods or special themes, allowing users to enjoy a constantly new experience.

[0978] Furthermore, the server stores the dialogue content, user comments, AI character responses, and emotional data as logs, which allows for later analysis of the user's dialogue behavior.

[0979] As a specific example, when a user logs in by entering "user123" and "password123" on the login screen, the server returns a session ID and the dialogue start screen is displayed on the device. When the user presses the dialogue start button, an AI character displays the initial message "Hello! How was your day?" If the user replies "I'm a little tired today," the server analyzes this message with an NLP engine and identifies the emotion of "tired" with an emotion analysis engine. The generative AI model generates a response saying "That must have been tough. It's important to take some time to rest," and displays this on the device.

[0980] An example of a prompt might be:

[0981] Please enter the prompt to send the API request for login authentication.

[0982] "Explain how to integrate an NLP engine with a sentiment engine to perform sentiment analysis of user input."

[0983] In this way, users can enjoy a richer, more personalized interaction experience using generative AI models and sentiment analysis engines, and unique interaction content is provided based on events and special themes, ensuring a constantly fresh entertainment experience.

[0984] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0985] User authentication method

[0986] Step 1: Enter and submit your login details

[0987] User: The user enters their user ID and password on the login screen and presses the submit button.

[0988] Input: User ID, Password

[0989] What happens: The user enters information into the text boxes and clicks the "Login" button.

[0990] Output: Login request (user ID, password)

[0991] Step 2: Submitting authentication information

[0992] Terminal: Sends the entered information to the server.

[0993] Input: Login request (user ID, password)

[0994] Specific operation: Sends the user ID and password to the server using an HTTP POST request.

[0995] Output: Authentication request to the server

[0996] Step 3: Verify credentials

[0997] Server: The server queries the database for the received user ID and password and performs verification.

[0998] Input: Authentication request to the server

[0999] What happens: The server performs a database query to compare the password associated with the user ID with the submitted password.

[1000] Output: Authentication result (success / failure)

[1001] Step 4: Generate and send a session ID

[1002] Server: If authentication is successful, a session ID is generated and sent back to the device.

[1003] Input: Authentication result (success)

[1004] Specific operation: A session ID is generated using a UUID or similar and sent back to the device as an HTTP response.

[1005] Output: Session ID

[1006] Step 5: Receiving and maintaining a session ID

[1007] Terminal: The terminal stores the session ID received from the server in its memory.

[1008] Input: Session ID

[1009] Specific behavior: Saves the session ID in local storage or memory.

[1010] Output: Persisted session ID

[1011] Step 6: Display the conversation start screen

[1012] Terminal: Transition to the dialogue start screen.

[1013] Input: Persisted session ID

[1014] Specific Behavior: Switch to UI indicating successful login.

[1015] Output: Start screen

[1016] Receive a request to start a conversation

[1017] Step 1: Press the Start Dialogue button

[1018] User: The user presses the start button.

[1019] Input: User operation (pressing the interaction start button)

[1020] Specific action: The user clicks the start button.

[1021] Output: Conversation initiating request

[1022] Step 2: Sending a conversation-initiating request

[1023] Terminal: Sends a dialogue initiation request to the server.

[1024] Input: Conversation-initiating request

[1025] Specific behavior: Sends a conversation initiation request to the server using an HTTP GET or POST request.

[1026] Output: A conversation initiating request to the server

[1027] Step 3: Starting an interactive session

[1028] Server: The server starts a new interactive session and generates the AI ​​dollar's initial message.

[1029] Input: A request to start a conversation with the server

[1030] Specific operation: Generate an initial message using a generative AI model (e.g., "AI-GPT").

[1031] Output: Initial message

[1032] Step 4: Sending the initial message

[1033] Server: Sends an initial message to the device.

[1034] Input: initial message

[1035] Specific operation: Sends an initial message to the terminal as an HTTP response.

[1036] Output: Initial message to terminal

[1037] Step 5: Displaying a welcome message

[1038] Terminal: Displays the received initial message to the user.

[1039] Input: initial message to terminal

[1040] Specific behavior: Display an initial message on the UI.

[1041] Output: Shows the initial message.

[1042] Analyzing user comments using natural language processing and using an emotion engine

[1043] Step 1: Enter and send user utterances

[1044] User: The user responds to the message from the AI ​​dollar by typing and sending a message.

[1045] Input: User message

[1046] Specific actions: Enter a message in the text area and click the "Send" button.

[1047] Output: User utterances

[1048] Step 2: Sending a User Message

[1049] Terminal: Sends user messages to the server.

[1050] Input: User utterance

[1051] Specific behavior: Sends a message to the server using an HTTP POST request.

[1052] Output: User message to the server

[1053] Step 3: Analyzing user utterances

[1054] Server: Analyzes received user messages using a natural language processing (NLP) engine.

[1055] Input: User message to server

[1056] Specific behavior: Analyzes speech content, sentiment, and intent using an NLP engine (e.g., "NLP-Analyzer").

[1057] Output: Analysis results

[1058] Step 4: Perform sentiment analysis

[1059] Server: The analysis results are sent to the sentiment analysis engine for detailed sentiment analysis.

[1060] Input: Analysis results

[1061] Specific operation: Obtain detailed emotional data using the emotion analysis engine "Emotion-X."

[1062] Output: Detailed emotion data

[1063] Reaction formation of AI dollar

[1064] Step 1: Generate the reaction

[1065] Server: Uses a generative AI model to generate responses based on analysis results and emotional data.

[1066] Input: Analysis results, detailed emotion data

[1067] Specific operation: A prompt sentence is input into a generative AI model (e.g., "AI-GPT"), which generates an appropriate response.

[1068] Output: The generated reaction

[1069] Step 2: Sending a response

[1070] Server: Sends the generated responses to the device.

[1071] Input: Generated reactions

[1072] Specific operation: Sends the generated response to the terminal as an HTTP response.

[1073] Output: Response to terminal

[1074] Step 3: View the reaction

[1075] Terminal: Displays the response of the received AI dollar to the user.

[1076] Input: Response to terminal

[1077] Specific behavior: Displays AI dollar reactions on the UI.

[1078] Output: Display of AI dollar response

[1079] Special event and theme dialogue content provided

[1080] Step 1: Prepare special content

[1081] Servers: Prepare interactive content for specific events or special themes.

[1082] Input: Event information, theme information

[1083] What it does: Retrieves event information from a database or external API and generates special content.

[1084] Output: Special Content

[1085] Step 2: Generate a special message

[1086] Server: Generates special messages based on active events and themes.

[1087] Input: Special Content

[1088] What it does: Uses a generative AI model to generate a special message and send it to the device.

[1089] Output: special message

[1090] Step 3: Send and display special messages

[1091] Terminal: Display a special message to the user.

[1092] Input: Special message

[1093] Specific behavior: Display a special message in the UI.

[1094] Output: Display a special message

[1095] Log of conversations

[1096] Step 1: Generate a log entry

[1097] Server: Generates log entries for each interaction session, including user utterances, AI responses, and emotion data.

[1098] Input: User utterances, AI dollar responses, sentiment data

[1099] Specific operation: Create a single log entry containing the dialogue content and emotion data.

[1100] Output: The generated log entries

[1101] Step 2: Save the logs

[1102] Server: Stores the generated log entries in a database.

[1103] Input: Generated log entry

[1104] What it does: Executes a query to store interaction log entries in a database.

[1105] Output: Saved logs

[1106] Step 3: Leverage the logs

[1107] Server: The stored logs are used for analysis and improvement as needed.

[1108] Input: Saved logs

[1109] What happens: Log entries are reviewed using analytics tools and used to improve the system and enhance the user experience.

[1110] Output: Analysis results

[1111] (Application example 2)

[1112] 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."

[1113] In conventional virtual stores, users could only browse a list of products, making it difficult to receive personalized guidance. Furthermore, there was a lack of appropriate product suggestions tailored to the user's emotions and needs, resulting in a poor user experience. Furthermore, the provision of content based on special events or themes was limited, limiting the improvement of user satisfaction.

[1114] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes user authentication means, an information terminal that transmits user input, natural language processing means that analyzes user utterances, generative model means that generate a response based on the analyzed user utterances, an information terminal that provides the generated response to the user, emotion analysis means that analyzes user emotions, and product recommendation means that suggests specific products to the user based on the emotion analysis results. This enables the user to receive individual guidance and appropriate product suggestions based on their emotions and needs, improving the quality of the user experience in the virtual store.

[1115] "User authentication means" refers to a process or device that verifies the identity of a user when accessing a system.

[1116] An "information terminal that transmits user input" is a device that transmits data that is input by a user through operation to a server or the like.

[1117] "Natural language processing means for analyzing user utterances" refers to technology or devices for analyzing text entered by a user and understanding its content.

[1118] "Generative model means" refers to a technique or device for generating appropriate responses based on analyzed user utterances.

[1119] The "information terminal that provides the generated response to the user" refers to a device that displays the generated response to the user.

[1120] "Emotion analysis means" refers to technology or devices that analyze the emotions of users based on their comments and determine their state.

[1121] "Product recommendation means" refers to technology or devices for suggesting specific products to users based on the results of emotion analysis.

[1122] A system for implementing this invention includes user authentication means, an information terminal for transmitting user input, natural language processing means for analyzing user utterances, generative model means, an information terminal for providing the generated response to the user, emotion analysis means, and product recommendation means. A program for realizing this system operates as follows.

[1123] First, the user logs in to the information terminal from a smartphone or head-mounted display (HMD) and is authenticated through the authentication means. The user authentication means is a process in which the user enters their user ID and password and sends that information to the server. The server compares the user's ID with the database, and if the user is authenticated as a legitimate user, it generates a session ID and sends it back to the information terminal.

[1124] Next, the user presses the dialogue start button to start a dialogue with the AI ​​dollar. The server, which receives the dialogue start request, generates an initial message for the AI ​​dollar and sends it to the information terminal. The user enters text in reply to that message and sends it back to the server.

[1125] The server analyzes the text sent by the user using natural language processing means to understand the content of the statement. For natural language processing, Google Cloud Natural Language API or spaCy are used, for example. The analysis results are sent to sentiment analysis means, where more detailed sentiment analysis is performed. IBM Watson Tone Analyzer can be used for this sentiment analysis.

[1126] Based on the results of the sentiment analysis, the server generates an appropriate response using a generative model, such as OpenAI's GPT-3 or GPT-4. The generated response is sent to the information terminal and displayed to the user.

[1127] It also has a product recommendation feature that suggests specific products to users based on the results of sentiment analysis. For example, if a user says, "I'm looking for a dress," the AI ​​dollar will suggest, "We have several dresses that would be suitable for a summer party. How about this blue dress or this black dress?"

[1128] Furthermore, when there is information about a specific event or sale, the server generates a message according to the limited event or special theme and notifies the user. This special content includes introductions to special products and discount information.

[1129] All of these interactions are saved as logs, which will be used for future analysis and to improve the user experience.

[1130] For example, if a user says, "I'm looking for a dress that suits tonight's party," the AI ​​dollar will respond as follows:

[1131] "It's a perfect dress for a party! I'll show you some popular items. How about this turquoise dress or a black dress?"

[1132] In this way, users can enjoy natural and personalized interactions with AI Dollar and efficiently search for suitable products. The following are examples of prompt sentences:

[1133] User: I'm looking for a dress for tonight's party.

[1134] AI Dollar: A perfect dress for a party! Let me show you some popular items. How about this turquoise dress or a black dress?

[1135] In this way, the present invention can improve the quality of the user experience.

[1136] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1137] Step 1: User authentication

[1138] 1. Input: The user enters their user ID and password into the information terminal (smartphone or HMD).

[1139] 2. Processing: The terminal sends the entered information to the server.

[1140] 3. Data processing: The server checks the user ID and password in the database.

[1141] 4. Output: If authentication is successful, the server generates a session ID and sends it to the terminal.

[1142] Step 2: Conversation-initiating request

[1143] 1. Input: The user presses the interaction start button displayed on the terminal.

[1144] 2. Processing: The terminal sends a dialogue start request to the server.

[1145] 3. Data Calculation: The server initiates the interactive session and generates the initial message for the AI ​​dollar.

[1146] 4. Output: Sends the initial message to the terminal and is displayed to the user.

[1147] Step 3: User comment analysis

[1148] 1. Input: The user inputs text in response to a message from the AI ​​dollar and sends it.

[1149] 2. Processing: The device sends the user's text to the server.

[1150] 3. Data calculation: The server analyzes the user's speech using natural language processing tools (e.g., Google Cloud Natural Language API or spaCy).

[1151] 4. Output: The content, intent, and sentiment of the speech are analyzed and sent to a sentiment analyzer.

[1152] Step 4: Sentiment Analysis

[1153] 1. Input: Analysis results sent from natural language processing means.

[1154] 2. Processing: The server performs further sentiment analysis using sentiment analysis tools (e.g. IBM Watson Tone Analyzer).

[1155] 3. Data calculation: Determine the user's emotional state.

[1156] 4. Output: Send the sentiment analysis results to the generative modeling means.

[1157] Step 5: Response Generation

[1158] 1. Input: Sentiment analysis results and analysis results from natural language processing tools.

[1159] 2. Processing: The server generates an appropriate response using a generative model (e.g., OpenAI GPT-3 or GPT-4).

[1160] 3. Data calculation: Generate the optimal response in text format based on the analysis results.

[1161] 4. Output: Send the generated response to the terminal.

[1162] Step 6: Display the response

[1163] 1. Input: The generated response sent by the server.

[1164] 2. Processing: The terminal displays the generated response to the user.

[1165] 3. Output: User confirms AI Dollar's response.

[1166] Step 7: Product Recommendation

[1167] 1. Input: Sentiment analysis results and user comments.

[1168] 2. Processing: The server uses the product recommendation means to suggest suitable products.

[1169] 3. Data calculation: Generate a list of products based on sentiment analysis and speech content.

[1170] 4. Output: Display the product recommendations to the user.

[1171] Step 8: Special Event Notifications

[1172] 1. Input: Specific event or sale information in the system.

[1173] 2. Processing: The server generates messages for limited events or special themes.

[1174] 3. Data Calculation: Generate special messages based on event information.

[1175] 4. Output: Notify the user with a special message.

[1176] Step 9: Save conversation logs

[1177] 1. Input: User utterances, AI dollar responses, and sentiment data.

[1178] 2. Processing: The server stores the conversation as a log.

[1179] 3. Data calculation: Generates log entries and stores them in a database.

[1180] 4. Output: The saved logs are stored as data for future analysis.

[1181] 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.

[1182] 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.

[1183] 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.

[1184] [Third embodiment]

[1185] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1186] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1187] 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).

[1188] 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.

[1189] 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.

[1190] 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).

[1191] 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.

[1192] 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.

[1193] 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.

[1194] 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.

[1195] 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.

[1196] 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."

[1197] This invention is a platform that allows users to interact with AI dollars in real time, and uses generative AI models. Below, we will explain the processing of this system in natural language, and also provide specific examples.

[1198] User authentication method

[1199] 1. Terminal: The user enters their user ID and password on the login screen and presses the send button.

[1200] The terminal sends a login request to the server.

[1201] 2. Server: The server checks the user ID and password received from the terminal against the database.

[1202] The server retrieves the user data from a database and verifies the authentication information.

[1203] 3. Server: If authentication is successful, the server generates a session ID and sends it back to the user.

[1204] The server generates a session ID and returns it to the user.

[1205] 4. Terminal: The terminal stores the session ID received from the server in memory and transitions to the dialogue start screen.

[1206] The terminal retains the session ID and transitions to the dialogue start screen.

[1207] Receive a request to start a conversation

[1208] 1. Terminal: The user presses the interaction start button.

[1209] The terminal sends a dialogue initiation request to the server.

[1210] 2. Server: The server initiates the interactive session and generates the initial message for the AI ​​dollar.

[1211] The server generates an initial message using an AI model and sends it to the terminal.

[1212] 3. Terminal: The terminal displays the AI ​​Dollar's welcome message to the user.

[1213] The terminal will display the AI ​​Dollar initial message on the screen.

[1214] User comment analysis using natural language processing

[1215] 1. User: The user responds to the message from the AI ​​dollar by typing and sending the text.

[1216] The terminal sends a user message to the server.

[1217] 2. Server: The server receives the user's speech and analyzes it using a natural language processing (NLP) engine.

[1218] The server analyzes the content, emotions, and intentions of the statements using an NLP engine.

[1219] 3. Server: The server obtains the analysis results (emotions, intentions) and prepares to generate a response accordingly.

[1220] The server prepares for reaction generation based on the analysis results.

[1221] Reaction formation of AI dollar

[1222] 1. Server: The server uses the generative AI model to generate AI dollar responses based on the analysis results.

[1223] The server uses the analysis results as input and the AI ​​model generates the corresponding response.

[1224] 2. Server: The server sends the generated response to the user terminal.

[1225] The server sends the generated response to the terminal.

[1226] 3. Terminal: The terminal displays the AI ​​dollar response to the user.

[1227] The terminal will display the AI ​​dollar's response on the screen.

[1228] Special event and theme dialogue content provided

[1229] 1. Server: A server provides interactive content during a specific event or based on a special theme.

[1230] The server checks the special event information from a database or API and retrieves the content.

[1231] 2. Server: The server generates special messages based on events and themes.

[1232] The server uses an AI model to generate special messages based on the special content.

[1233] 3. Terminal: The terminal displays a special message.

[1234] The terminal displays a special message to the user.

[1235] Log of conversations

[1236] 1. Server: The server stores user utterances and AI dollar responses for each dialogue session.

[1237] The server generates a log entry of the user's utterance and the AI ​​dollar's response.

[1238] 2. Server: The server stores the generated log entries in a database.

[1239] The server stores the log entries in a database.

[1240] 3. Server: If necessary, the server uses the logs to later analyze the interaction.

[1241] The server uses the stored logs for analysis.

[1242] In this way, users can enjoy natural and personalized interactions with AI Dollars, and unique interactions are possible based on special events or themes, providing a new type of digital entertainment experience.

[1243] The processing flow will be explained below.

[1244] Step 1:

[1245] Terminal: The user enters their user ID and password on the login screen and presses the send button.

[1246] The terminal sends a login request to the server.

[1247] Step 2:

[1248] Server: The server checks the user ID and password received from the terminal against the database.

[1249] The server retrieves the user data from a database and compares it with the entered password.

[1250] Step 3:

[1251] Server: If authentication is successful, the server generates a session ID and returns it to the user.

[1252] The server generates a session ID and sends it to the terminal as a response.

[1253] Step 4:

[1254] Terminal: The terminal stores the session ID received from the server in memory and transitions to the dialogue start screen.

[1255] The terminal stores the session ID in memory and displays a dialogue start screen to the user.

[1256] Step 5:

[1257] Terminal: The user presses the interaction start button.

[1258] The terminal sends a dialogue initiation request to the server.

[1259] Step 6:

[1260] Server: The server initiates the interactive session and generates the initial message for the AI.

[1261] The server generates an initial message to be sent by the AI ​​dollar and sends it to the terminal.

[1262] Step 7:

[1263] Terminal: The terminal displays the AI ​​Dollar's welcome message to the user.

[1264] The terminal will display the AI ​​Dollar initial message on the screen.

[1265] Step 8:

[1266] User: The user responds to the message from the AI ​​dollar by typing and sending the text.

[1267] The terminal sends a user message to the server.

[1268] Step 9:

[1269] Server: The server receives the user's utterance and analyzes it using a natural language processing (NLP) engine.

[1270] The server analyzes the content, sentiment, and intent of the speech using an NLP engine.

[1271] Step 10:

[1272] Server: The server obtains the analysis results (emotions, intentions) and prepares to generate a response accordingly.

[1273] The server prepares to generate an appropriate response based on the analysis results.

[1274] Step 11:

[1275] Server: The server uses the generative AI model to generate AI dollar responses based on the analysis results.

[1276] The server uses the analysis results as input to generate the response content of the AI ​​dollar.

[1277] Step 12:

[1278] Server: The server sends the generated response to the user device.

[1279] The server sends the generated reaction to the terminal as a response.

[1280] Step 13:

[1281] Terminal: The terminal displays the AI ​​dollar response to the user.

[1282] The terminal will display the AI ​​dollar's response on the screen.

[1283] Step 14:

[1284] Servers: Servers provide interactive content during specific events or based on special themes.

[1285] The server checks the database or API for special event information and generates content based on that information.

[1286] Step 15:

[1287] Server: The server generates special messages based on events and themes.

[1288] The server uses an AI model to generate a message based on the special content and sends it to the device.

[1289] Step 16:

[1290] Terminals: Terminals display special messages.

[1291] The terminal displays a special message on the user's screen.

[1292] Step 17:

[1293] Server: The server stores user utterances and AI dollar responses for each dialogue session.

[1294] The server generates a log entry of the user's utterance and the AI ​​dollar's response.

[1295] Step 18:

[1296] Server: The server stores the generated log entries in a database.

[1297] The server stores the log entries in a database.

[1298] Step 19:

[1299] Server: If necessary, the server uses the logs to later analyze the interaction.

[1300] The server uses the stored logs for analysis.

[1301] Example 1

[1302] 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."

[1303] In recent years, dialogue systems using artificial intelligence have become widespread, but they are being required to meet a variety of needs, such as reliable user authentication, natural dialogue, provision of dialogue content according to special events or themes, and logging of dialogue content.However, conventional systems face the challenge of being unable to simultaneously meet all of these needs.

[1304] 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.

[1305] In this invention, the server

[1306] means for verifying user authentication information;

[1307] A means of generating and transmitting a session ID if authentication is successful;

[1308] A means for transmitting user comments and analyzing them using natural language processing means;

[1309] A generative AI model means for generating a response based on the analyzed user utterance;

[1310] A means to provide interactive content for limited events and special themes,

[1311] A means for storing the contents of the dialogue as a log;

[1312] This allows for increased reliability in user authentication, natural and personalized interactions, the provision of content for special events or themes, and the storage of interaction logs.

[1313] "User authentication information" refers to information such as an ID and password that a user enters to verify their identity.

[1314] "Information terminal" is a general term for electronic devices that users use to input and send and receive data.

[1315] The term "server means" refers to a computer system for receiving and processing requests, and is a device that has the functions of verifying data, generating session IDs, and generating and transmitting messages.

[1316] A "session ID" is a unique identifier generated by the server to indicate successful authentication of a user and to manage an interactive session.

[1317] "Natural language processing means" refers to technology that analyzes text data entered by a user and understands their meaning, emotions, and intent.

[1318] A "generative AI model means" is an artificial intelligence model used to generate appropriate responses based on analyzed user utterances.

[1319] "Interactive content based on limited events or special themes" refers to special interactive content provided during specific event periods or based on special themes.

[1320] A "log" is recorded data that includes user utterances and AI dollar responses for each interactive session.

[1321] The present invention is a platform that allows users to interact with AI characters in real time, and uses generative AI models. Detailed embodiments of the system are described below.

[1322] User Authentication

[1323] When the system starts, the user uses an information terminal (e.g., smartphone, tablet, PC) to enter their user ID and password on the login screen and press the send button. The terminal then sends this login request to the server. The server compares the received user ID and password with the database, and if they match, generates a session ID and sends it to the user's terminal. The terminal then stores the session ID in memory and transitions to the dialogue start screen.

[1324] Starting a conversation

[1325] When the user presses the dialogue start button, the device sends a dialogue start request to the server. The server starts a dialogue session and sends a prompt to the generative AI model to generate an initial message. The generated initial message is sent to the user's device and displayed to the user.

[1326] Analysis of user comments

[1327] The user responds to messages from the AI ​​character by inputting text and sending it. The device then sends the user message to the server, which then analyzes the received user message using a natural language processing (NLP) engine to extract the content, emotion, and intent of the message.

[1328] AI character reaction generation

[1329] The server sends a prompt to the generative AI model to generate a response based on the analysis results of the NLP engine. For example, "The user said 'hello,' so please generate a response that says 'hello.'" The generated response is sent to the device via the server and displayed to the user.

[1330] Providing interactive content based on special events and themes

[1331] The server automatically generates interactive content based on specific event periods or special themes. For example, during an event, a special message such as "Happy Birthday! Today is a special day!" is displayed. The server obtains special event information using a database or API and sends prompts to the generative AI model to generate special content.

[1332] Conversation logging and analysis

[1333] The server generates log entries for each interaction session, including user comments and AI character responses, and stores them in a database, allowing for later analysis of the interaction content to improve the service and detect errors.

[1334] Specific examples

[1335] For example, if a user types "hello" and sends it, it will be processed as follows:

[1336] 1. User: Type "Hello" and send.

[1337] 2. Device: Sends "hello" to the server.

[1338] 3. Server: Analyze "hello" using an NLP engine to read the emotion and intent. Recognize it as a "greeting."

[1339] 4. Server: Based on the analysis results, the server sends a prompt to the generative AI model to generate a response to the greeting.

[1340] 5. Server: Sends the generated response "Hello! What would you like to talk about today?" to the user terminal.

[1341] 6. Terminal: Display "Hello! What would you like to talk about today?" to the user.

[1342] This system allows users to enjoy more natural and personalized interactions, and enables unique interactions based on special events or themes.The system cleverly utilizes generative AI models and prompts to provide a new form of digital entertainment.

[1343] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1344] Step 1: Enter and submit user credentials

[1345] 1. User: The user enters the user ID and password on the login screen of the information terminal and presses the send button. The user ID and password are provided as input.

[1346] 2. Terminal: The terminal receives the user's input, generates a login request, and sends it to the server. As an output, a login request is generated.

[1347] Step 2: Verify user authentication

[1348] 1. Server: The server parses the received login request and extracts the user ID and password. The login request is provided as input.

[1349] 2. Server: Retrieves user information from the database and matches it with the entered authentication information. The user information retrieved from the database is used for matching.

[1350] 3. Server: Generates a session ID if the authentication information is correct, or an error message if it is incorrect. As output, a session ID or an error message is generated.

[1351] 4. Server: Sends the session ID or an error message to the terminal. As output, the session ID or an error message is sent to the terminal.

[1352] Step 3: Session ID retention and screen transitions

[1353] 1. Terminal: Parse the session ID or error message received from the server. As input, the session ID or error message is provided.

[1354] 2. Terminal: Keep the session ID in memory and display a success message or transition to the start of the conversation screen. If it is incorrect, display an error message and stay at the login screen. As output, the success or error message is displayed on the screen.

[1355] Step 4: Sending a conversation-initiating request

[1356] 1. User: The user clicks the interaction start button. The click of the interaction start button is provided as input.

[1357] 2. Terminal: Prepares to send a conversation initiation request to the server. As output, a conversation initiation request is generated.

[1358] 3. Terminal: Sends a conversation initiation request to the server. As an output, a conversation initiation request is sent to the server.

[1359] Step 5: Generate and send the initial message

[1360] 1. Server: Receives a conversation initiation request and starts a conversation session. The conversation initiation request is provided as input.

[1361] 2. Server: Sends a prompt to the generative AI model to generate an initial message. The prompt sentence is provided as input.

[1362] 3. Server: Receives the initial message from the generative AI model and sends it to the device. As an output, an initial message is generated and sent to the device.

[1363] Step 6: Displaying a welcome message

[1364] 1. Terminal: Receives the initial message and displays it to the user. As input, the initial message is provided. As output, the initial message is displayed on the screen.

[1365] Step 7: Enter and send user utterances

[1366] 1. User: Enters and sends text in response to a message from an AI character. The user's text is provided as input.

[1367] 2. Terminal: receives user input and prepares it for transmission to the server. As output, a user message is generated.

[1368] 3. Terminal: Sends user messages to the server. As output, the user messages are sent to the server.

[1369] Step 8: Analyzing user utterances

[1370] 1. Server: Receives the user message and starts parsing it in the natural language processing engine. The user message is provided as input.

[1371] 2. Server: Analyzes the message content, sentiment, and intent using an NLP engine. The analysis results are generated as output.

[1372] 3. Server: Retrieves the analysis results and prepares the data for reaction generation. The output is the data for reaction generation.

[1373] Step 9: Generate and send AI character reactions

[1374] 1. Server: Based on the analysis results, the server sends a prompt to the generative AI model to generate a reaction. The prompt sentence for generating a reaction is provided as input.

[1375] 2. Server: Prepares to send the generated responses to the terminal. The generated responses are generated as output.

[1376] 3. Server: Sends the generated responses to the terminal. As output, the generated responses are sent to the terminal.

[1377] Step 10: Viewing the Reaction

[1378] 1. Terminal: Analyzes the received AI character's reaction and displays it to the user. As input, the AI ​​character's reaction is provided. As output, the reaction is displayed on the screen.

[1379] Step 11: Offer special events or themed content

[1380] 1. Server: Checks whether there is a specific event or special themed interactive content. Event information is provided as input.

[1381] 2. Server: Retrieves special event information using a database or API and generates a prompt with limited content. As output, the special event information is retrieved and a prompt statement is generated.

[1382] 3. Server: Sends a prompt with special content to the generative AI model to generate a special message. As input, a prompt with special content is provided. As output, a special message is generated.

[1383] 4. Server: Prepares to send the generated special message to the user terminal. As output, the special message is generated.

[1384] 5. Server: Sends the generated special message to the user terminal. As output, the special message is sent to the terminal.

[1385] 6. Terminal: Receives special messages and displays them to the user. As input, special messages are provided. As output, special messages are displayed on the screen.

[1386] Step 12: Logging interactions

[1387] 1. Server: Generates log entries for each interaction session, including user utterances and AI character responses. As input, the server receives user utterances and AI character responses. As output, it generates a log entry.

[1388] 2. Server: Stores the generated log entries in a database. As an output, the log entries are stored in a database.

[1389] The above is the specific program processing flow of this system.

[1390] (Application example 1)

[1391] 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."

[1392] Conventional dialogue systems generally involve dialogue between users and AI, but lack the functionality to provide dialogue content based on special events or themes. Furthermore, few applications are compatible with multiple devices, limiting the devices that users can use. Furthermore, it is difficult to log and analyze dialogues later, making it difficult to track user behavior and improve services.

[1393] 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.

[1394] In this invention, the server includes a user authentication means, an information terminal means for transmitting user input, and a natural language processing means for analyzing user utterances, which allows users and AI to enjoy unique dialogue content during a specific event or based on a special theme, and further enables compatibility with multiple devices and the saving of dialogue logs for later analysis.

[1395] "User authentication" is the process by which a user verifies the identity used to log into a system.

[1396] An "information terminal that transmits user input" is a device through which a user can enter text, voice, or other forms of input and transmit it to the system.

[1397] "Natural language processing means for analyzing user utterances" is a technology that analyzes the linguistic information entered by the user and understands its content, emotions, and intentions.

[1398] The "generative model means for generating a response based on the analyzed user utterance" is an artificial intelligence technology for generating an appropriate response based on the analysis results.

[1399] The "means for generating dialogue content during a specific event or based on a special theme" is a function for creating dialogue content according to a special event or theme and presenting it to the user.

[1400] An "information terminal that provides the user with the generated response" is a device that displays or audibly conveys the response generated by AI to the user.

[1401] "Means for saving dialogue content as a log" is a function for recording the content of dialogue between the user and AI and saving it for future reference.

[1402] An "interactive application compatible with a variety of devices, including smartphones, head-mounted displays, and smart glasses" is an application that runs on a variety of devices and provides interactive functions between users and AI.

[1403] The present invention provides a system that allows users to interact with AI dollars in real time using a variety of devices. Specific embodiments of this system will be described below.

[1404] The system includes a user authentication means, an information terminal for transmitting user input, a natural language processing means for analyzing user utterances, a generative model means for generating responses based on the analyzed user utterances, a means for generating dialogue content during a specific event period or based on a special theme, an information terminal for providing the generated responses to the user, and a means for saving the dialogue content as a log.

[1405] 1. Hardware and Software

[1406] The hardware required to build the system includes a smartphone, smart glasses, and a head-mounted display, while the software uses Python, Flask (a web framework), an NLP engine (e.g., SpaCy, Transformers), and a generative AI model (e.g., GPT-3).

[1407] 2. Program Processing

[1408] The server first authenticates the user ID and password entered by the user using the user authentication means. If the authentication is successful, it returns a session ID to the user and receives a request to start a dialogue. When the user presses the dialogue start button, the server starts a dialogue session, generates an initial message for the AI ​​dollar, and sends it to the information terminal.

[1409] The user checks the initial message on the information terminal and responds by inputting a response in text or voice. The input user utterance is sent to the server and analyzed by the natural language processing means. The generative model means generates a response based on the analyzed content, emotion, and intention.

[1410] If conversation content based on a specific event period or special theme is required, the server generates special content and provides users with special messages based on that content. This allows users to enjoy unique conversations that are tailored to the event or theme. All conversation content is also saved as a log on the server and can be used for later analysis.

[1411] 3. Specific Examples

[1412] For example, a "Happy New Year" campaign will be held as a limited-time event. AI Dollar will provide special content that will interact with users about their "New Year's resolutions." This special content will be generated based on the following prompts:

[1413] "This is a scenario where a user shares their New Year's resolutions. The AI ​​dollar generates appropriate responses based on what the user says, continuing a fun conversation fit for the New Year."

[1414] As described above, this system allows users to enjoy real-time conversations based on special events or themes across multiple devices, and the content of the conversations is saved as a log so that they can be analyzed later.

[1415] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1416] Step 1:

[1417] The user displays the login screen on their information terminal, enters their user ID and password, and submits it. The entered data is the user ID and password, and is sent from the terminal to the server. The server receives this request and checks the user ID and password against its database.

[1418] Step 2:

[1419] The server retrieves the user information from the database and verifies the authentication information. If the authentication is successful, the server generates a session ID and sends it back to the terminal. This authenticates the user and gives them a session ID to proceed to the next step.

[1420] Step 3:

[1421] The terminal stores the session ID received from the server in memory and switches to the dialogue start screen. The user presses the dialogue start button here and sends a dialogue start request to the server. This request includes the session ID.

[1422] Step 4:

[1423] The server starts an interactive session and generates an initial message for the AI ​​using the generative AI model. The input is the session ID and the prompt required to generate the initial message, and the output is the generated initial message. The server sends this initial message to the terminal.

[1424] Step 5:

[1425] The terminal displays the initial message received from the server on the screen. The user responds to this message by inputting a response in text or voice and sends it. The input data is the user's message, and the terminal sends it to the server.

[1426] Step 6:

[1427] The server receives the user's comments and analyzes them using a natural language processing engine. The input for the analysis is the user's message, and the output is the analysis results, such as the content of the comment, emotions, and intentions. Based on this, the server prepares to generate a response from the AI ​​dollar.

[1428] Step 7:

[1429] The server generates an appropriate AI response using a generative AI model based on the analysis results. The input is the analysis result and the prompt, and the output is the generated response. The server then sends this response to the device.

[1430] Step 8:

[1431] The terminal displays the AI ​​dollar response received from the server to the user, who can then enter a message again to continue the conversation. The process repeats.

[1432] Step 9:

[1433] During and after a conversation session, the server stores the entire conversation as a log. The data stored is the user's statements and the AI ​​dollar's responses, and the server stores this in a database. The log is later used for analysis and service improvement.

[1434] Step 10:

[1435] The server provides special interactive content based on specific event periods or special themes. The prompt text is used to generate the special content, and the generative AI model generates a special response based on it. The server then sends it to the device, allowing the user to enjoy the special interaction.

[1436] 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.

[1437] This invention is a platform that allows users to interact with AI dollars in real time, using a generative AI model and an emotion engine. Below, we will explain the processing of this system in natural language, and also provide concrete examples.

[1438] User authentication method

[1439] 1. Terminal: The user enters their user ID and password on the login screen and presses the send button.

[1440] The terminal sends a login request to the server.

[1441] 2. Server: The server checks the user ID and password received from the terminal against the database.

[1442] The server retrieves the user data from a database and compares it with the entered password.

[1443] 3. Server: If authentication is successful, the server generates a session ID and sends it back to the user.

[1444] The server generates a session ID and sends it to the terminal as a response.

[1445] 4. Terminal: The terminal stores the session ID received from the server in memory and transitions to the dialogue start screen.

[1446] The terminal holds the session ID and displays the dialogue start screen to the user.

[1447] Receive a request to start a conversation

[1448] 1. Terminal: The user presses the interaction start button.

[1449] The terminal sends a dialogue initiation request to the server.

[1450] 2. Server: The server initiates the interactive session and generates the initial message for the AI ​​dollar.

[1451] The server generates an initial message to be sent by the AI ​​dollar and sends it to the terminal.

[1452] 3. Terminal: The terminal displays the AI ​​Dollar's welcome message to the user.

[1453] The terminal will display the AI ​​Dollar initial message on the screen.

[1454] Analyzing user comments using natural language processing and using an emotion engine

[1455] 1. User: The user responds to the message from the AI ​​dollar by typing and sending the text.

[1456] The terminal sends a user message to the server.

[1457] 2. Server: The server receives the user's speech and analyzes it using a natural language processing (NLP) engine.

[1458] The server analyzes the content, sentiment, and intent of the speech using an NLP engine.

[1459] 3. Server: The server sends the analysis results to the emotion engine for detailed emotion analysis.

[1460] The server further analyzes the user's emotions using an emotion engine and obtains the results.

[1461] Reaction formation of AI dollar

[1462] 1. Server: The server uses the generative AI model to generate responses from the AI ​​dollar based on the analysis results and the emotional information obtained from the emotion engine.

[1463] The server generates an appropriate response based on the analysis results and emotional information.

[1464] 2. Server: The server sends the generated response to the user terminal.

[1465] The server sends the generated reaction to the terminal as a response.

[1466] 3. Terminal: The terminal displays the AI ​​dollar response to the user.

[1467] The terminal will display the AI ​​dollar's response on the screen.

[1468] Special event and theme dialogue content provided

[1469] 1. Server: A server provides interactive content during a specific event or based on a special theme.

[1470] The server checks the database or API for special event information and generates content based on that information.

[1471] 2. Server: The server generates special messages based on events and themes.

[1472] The server uses an AI model to generate a message based on the special content and sends it to the device.

[1473] 3. Terminal: The terminal displays a special message.

[1474] The terminal displays a special message on the user's screen.

[1475] Log of conversations

[1476] 1. Server: The server stores user utterances, AI responses, and emotion data from the emotion engine for each dialogue session.

[1477] The server generates log entries based on user comments, AI dollar responses, and emotional data.

[1478] 2. Server: The server stores the generated log entries in a database.

[1479] The server stores the log entries in a database.

[1480] 3. Server: If necessary, the server uses the logs to later analyze the interaction.

[1481] The server uses the stored logs for analysis.

[1482] In this way, users can enjoy natural and personalized interactions with AI Dollars, and unique interactions are possible based on special events or themes. In addition, the emotion engine allows AI Dollars to better understand users' emotions and respond accordingly, providing a new type of digital entertainment experience.

[1483] The processing flow will be explained below.

[1484] Step 1:

[1485] Terminal: The user enters their user ID and password on the login screen and presses the send button.

[1486] The terminal sends a login request to the server.

[1487] Step 2:

[1488] Server: The server checks the user ID and password received from the terminal against the database.

[1489] The server retrieves the user data from a database and compares it with the entered password.

[1490] Step 3:

[1491] Server: If authentication is successful, the server generates a session ID and returns it to the user.

[1492] The server generates a session ID and sends it to the terminal as a response.

[1493] Step 4:

[1494] Terminal: The terminal stores the session ID received from the server in memory and transitions to the dialogue start screen.

[1495] The terminal holds the session ID and displays the dialogue start screen to the user.

[1496] Step 5:

[1497] Terminal: The user presses the interaction start button.

[1498] The terminal sends a dialogue initiation request to the server.

[1499] Step 6:

[1500] Server: The server initiates the interactive session and generates the initial message for the AI.

[1501] The server generates an initial message to be sent by the AI ​​dollar and sends it to the terminal.

[1502] Step 7:

[1503] Terminal: The terminal displays the AI ​​Dollar's welcome message to the user.

[1504] The terminal will display the AI ​​Dollar initial message on the screen.

[1505] Step 8:

[1506] User: The user responds to the message from the AI ​​dollar by typing and sending the text.

[1507] The terminal sends a user message to the server.

[1508] Step 9:

[1509] Server: The server receives the user's utterance and analyzes it using a natural language processing (NLP) engine.

[1510] The server analyzes the content, sentiment, and intent of the speech using an NLP engine.

[1511] Step 10:

[1512] Server: The server sends the analysis results to the emotion engine for detailed emotion analysis.

[1513] The server further analyzes the user's emotions using an emotion engine and obtains the results.

[1514] Step 11:

[1515] Server: The server uses the generative AI model to generate responses from the AI ​​dollar based on the analysis results and emotional information obtained from the emotion engine.

[1516] The server generates the AI ​​dollar's response based on the analysis results and emotional information.

[1517] Step 12:

[1518] Server: The server sends the generated response to the user device.

[1519] The server sends the generated reaction to the terminal as a response.

[1520] Step 13:

[1521] Terminal: The terminal displays the AI ​​dollar response to the user.

[1522] The terminal will display the AI ​​dollar's response on the screen.

[1523] Step 14:

[1524] Servers: Servers provide interactive content during specific events or based on special themes.

[1525] The server checks the database or API for special event information and generates content based on that information.

[1526] Step 15:

[1527] Server: The server generates special messages based on events and themes.

[1528] The server uses an AI model to generate a message based on the special content and sends it to the device.

[1529] Step 16:

[1530] Terminals: Terminals display special messages.

[1531] The terminal displays a special message on the user's screen.

[1532] Step 17:

[1533] Server: The server stores user utterances, AI responses, and emotion data from the emotion engine for each dialogue session.

[1534] The server generates log entries based on user comments, AI dollar responses, and emotional data.

[1535] Step 18:

[1536] Server: The server stores the generated log entries in a database.

[1537] The server stores the log entries in a database.

[1538] Step 19:

[1539] Server: If necessary, the server uses the logs to later analyze the interaction.

[1540] The server uses the stored logs for analysis.

[1541] Example 2

[1542] 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."

[1543] Current dialogue systems struggle to accurately understand user sentiment and generate appropriate responses based on it. Furthermore, they lack the ability to provide special event or themed content, limiting the user experience. They also lack the means to effectively store dialogue content for later analysis.

[1544] 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.

[1545] In this invention, the server includes a user authentication means, an information terminal through which a user inputs and transmits information, a natural language processing means for analyzing user utterances, a generative AI model means for generating a response based on the analyzed user utterances, an information terminal for providing the generated response to the user, a sentiment analysis means for analyzing the sentiment of the user utterances, a means for adjusting the response to be generated based on the sentiment analysis, and a means for generating an initial message at the start of an interaction session. This makes it possible to accurately understand the user's sentiment and generate an appropriate response based on that sentiment. Furthermore, by providing dialogue content according to special events or themes and saving the dialogue content as a log for later analysis, a richer user experience can be provided.

[1546] "User authentication means" refers to a means for verifying whether a user is a legitimate user by checking the user ID and password.

[1547] An "information terminal" is a device that allows a user to input and transmit information, and includes, for example, a personal computer, a smartphone, a tablet, and the like.

[1548] "Natural language processing" refers to technology for analyzing user utterances and understanding their content and intent. This includes text analysis, semantic analysis, and context understanding.

[1549] A "generative AI model means" is an artificial intelligence algorithm or model for generating appropriate responses based on analyzed user utterances.

[1550] "Emotion analysis means" is a technology that analyzes the emotions contained in a user's speech and identifies their emotional state. This includes emotion detection and emotion classification.

[1551] The "means for adjusting the response" is a technology for adjusting the response generated based on the emotion analysis results and providing an appropriate response that matches the user's emotional state.

[1552] "Means for generating an initial message" refers to technology for generating the first message that the AI ​​issues at the start of an interaction session.

[1553] The "means for providing dialogue content according to limited events or special themes" is a means for generating special dialogue content based on a specific event period or theme and providing it to users.

[1554] "Means for saving dialogue content as a log" refers to a means for saving the dialogue content between the user and the AI ​​and the analysis results in a database or the like so that they can be referenced and analyzed later.

[1555] This invention is a platform that allows users to interact with artificial intelligence (AI) characters in real time. This platform operates by combining multiple functions including user authentication means, natural language processing means, emotion analysis means, and generative AI model means.

[1556] First, the user uses an information terminal (for example, a PC or smartphone) to enter their user ID and password on the login screen. When the user presses the send button, the information is sent from the terminal to the server. The server compares the received information with a database and performs authentication. If authentication is successful, the server generates a session ID and returns it to the terminal. The terminal retains this session ID and displays the dialogue start screen to the user.

[1557] Next, the user presses the Start Dialogue button, which sends a dialogue start request to the server, which then starts a new dialogue session. Using a generative AI model (e.g., "AI-GPT"), the server generates an initial message and sends it to the device. The device then displays this initial message to the user.

[1558] When a user replies to a message from an AI character, the message is sent from the device to a server. The server analyzes the received message using a natural language processing (NLP) engine (e.g., "NLP-Analyzer") to understand the content and intent of the message. The analysis results are then sent to an emotion analysis engine (e.g., "Emotion-X") for detailed emotion analysis. Based on the obtained emotion data, a generative AI model generates an appropriate response. This response is then sent to the device and displayed to the user.

[1559] In addition, the server will prepare exclusive interactive content and generate special messages based on specific event periods or special themes, allowing users to enjoy a constantly new experience.

[1560] Furthermore, the server stores the dialogue content, user comments, AI character responses, and emotional data as logs, which allows for later analysis of the user's dialogue behavior.

[1561] As a specific example, when a user logs in by entering "user123" and "password123" on the login screen, the server returns a session ID and the dialogue start screen is displayed on the device. When the user presses the dialogue start button, an AI character displays the initial message "Hello! How was your day?" If the user replies "I'm a little tired today," the server analyzes this message with an NLP engine and identifies the emotion of "tired" with an emotion analysis engine. The generative AI model generates a response saying "That must have been tough. It's important to take some time to rest," and displays this on the device.

[1562] An example of a prompt might be:

[1563] Please enter the prompt to send the API request for login authentication.

[1564] "Explain how to integrate an NLP engine with a sentiment engine to perform sentiment analysis of user input."

[1565] In this way, users can enjoy a richer, more personalized interaction experience using generative AI models and sentiment analysis engines, and unique interaction content is provided based on events and special themes, ensuring a constantly fresh entertainment experience.

[1566] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1567] User authentication method

[1568] Step 1: Enter and submit your login details

[1569] User: The user enters their user ID and password on the login screen and presses the submit button.

[1570] Input: User ID, Password

[1571] What happens: The user enters information into the text boxes and clicks the "Login" button.

[1572] Output: Login request (user ID, password)

[1573] Step 2: Submitting authentication information

[1574] Terminal: Sends the entered information to the server.

[1575] Input: Login request (user ID, password)

[1576] Specific operation: Sends the user ID and password to the server using an HTTP POST request.

[1577] Output: Authentication request to the server

[1578] Step 3: Verify credentials

[1579] Server: The server queries the database for the received user ID and password and performs verification.

[1580] Input: Authentication request to the server

[1581] What happens: The server performs a database query to compare the password associated with the user ID with the submitted password.

[1582] Output: Authentication result (success / failure)

[1583] Step 4: Generate and send a session ID

[1584] Server: If authentication is successful, a session ID is generated and sent back to the device.

[1585] Input: Authentication result (success)

[1586] Specific operation: A session ID is generated using a UUID or similar and sent back to the device as an HTTP response.

[1587] Output: Session ID

[1588] Step 5: Receiving and maintaining a session ID

[1589] Terminal: The terminal stores the session ID received from the server in its memory.

[1590] Input: Session ID

[1591] Specific behavior: Saves the session ID in local storage or memory.

[1592] Output: Persisted session ID

[1593] Step 6: Display the conversation start screen

[1594] Terminal: Transition to the dialogue start screen.

[1595] Input: Persisted session ID

[1596] Specific Behavior: Switch to UI indicating successful login.

[1597] Output: Start screen

[1598] Receive a request to start a conversation

[1599] Step 1: Press the Start Dialogue button

[1600] User: The user presses the start button.

[1601] Input: User operation (pressing the interaction start button)

[1602] Specific action: The user clicks the start button.

[1603] Output: Conversation initiating request

[1604] Step 2: Sending a conversation-initiating request

[1605] Terminal: Sends a dialogue initiation request to the server.

[1606] Input: Conversation-initiating request

[1607] Specific behavior: Sends a conversation initiation request to the server using an HTTP GET or POST request.

[1608] Output: A conversation initiating request to the server

[1609] Step 3: Starting an interactive session

[1610] Server: The server starts a new interactive session and generates the AI ​​dollar's initial message.

[1611] Input: A request to start a conversation with the server

[1612] Specific operation: Generate an initial message using a generative AI model (e.g., "AI-GPT").

[1613] Output: Initial message

[1614] Step 4: Sending the initial message

[1615] Server: Sends an initial message to the device.

[1616] Input: initial message

[1617] Specific operation: Sends an initial message to the terminal as an HTTP response.

[1618] Output: Initial message to terminal

[1619] Step 5: Displaying a welcome message

[1620] Terminal: Displays the received initial message to the user.

[1621] Input: initial message to terminal

[1622] Specific behavior: Display an initial message on the UI.

[1623] Output: Shows the initial message.

[1624] Analyzing user comments using natural language processing and using an emotion engine

[1625] Step 1: Enter and send user utterances

[1626] User: The user responds to the message from the AI ​​dollar by typing and sending a message.

[1627] Input: User message

[1628] Specific actions: Enter a message in the text area and click the "Send" button.

[1629] Output: User utterances

[1630] Step 2: Sending a User Message

[1631] Terminal: Sends user messages to the server.

[1632] Input: User utterance

[1633] Specific behavior: Sends a message to the server using an HTTP POST request.

[1634] Output: User message to the server

[1635] Step 3: Analyzing user utterances

[1636] Server: Analyzes received user messages using a natural language processing (NLP) engine.

[1637] Input: User message to server

[1638] Specific behavior: Analyzes speech content, sentiment, and intent using an NLP engine (e.g., "NLP-Analyzer").

[1639] Output: Analysis results

[1640] Step 4: Perform sentiment analysis

[1641] Server: The analysis results are sent to the sentiment analysis engine for detailed sentiment analysis.

[1642] Input: Analysis results

[1643] Specific operation: Obtain detailed emotional data using the emotion analysis engine "Emotion-X."

[1644] Output: Detailed emotion data

[1645] Reaction formation of AI dollar

[1646] Step 1: Generate the reaction

[1647] Server: Uses a generative AI model to generate responses based on analysis results and emotional data.

[1648] Input: Analysis results, detailed emotion data

[1649] Specific operation: A prompt sentence is input into a generative AI model (e.g., "AI-GPT"), which generates an appropriate response.

[1650] Output: The generated reaction

[1651] Step 2: Sending a response

[1652] Server: Sends the generated responses to the device.

[1653] Input: Generated reactions

[1654] Specific operation: Sends the generated response to the terminal as an HTTP response.

[1655] Output: Response to terminal

[1656] Step 3: View the reaction

[1657] Terminal: Displays the response of the received AI dollar to the user.

[1658] Input: Response to terminal

[1659] Specific behavior: Displays AI dollar reactions on the UI.

[1660] Output: Display of AI dollar response

[1661] Special event and theme dialogue content provided

[1662] Step 1: Prepare special content

[1663] Servers: Prepare interactive content for specific events or special themes.

[1664] Input: Event information, theme information

[1665] What it does: Retrieves event information from a database or external API and generates special content.

[1666] Output: Special Content

[1667] Step 2: Generate a special message

[1668] Server: Generates special messages based on active events and themes.

[1669] Input: Special Content

[1670] What it does: Uses a generative AI model to generate a special message and send it to the device.

[1671] Output: special message

[1672] Step 3: Send and display special messages

[1673] Terminal: Display a special message to the user.

[1674] Input: Special message

[1675] Specific behavior: Display a special message in the UI.

[1676] Output: Display a special message

[1677] Log of conversations

[1678] Step 1: Generate a log entry

[1679] Server: Generates log entries for each interaction session, including user utterances, AI responses, and emotion data.

[1680] Input: User utterances, AI dollar responses, sentiment data

[1681] Specific operation: Create a single log entry containing the dialogue content and emotion data.

[1682] Output: The generated log entries

[1683] Step 2: Save the logs

[1684] Server: Stores the generated log entries in a database.

[1685] Input: Generated log entry

[1686] What it does: Executes a query to store interaction log entries in a database.

[1687] Output: Saved logs

[1688] Step 3: Leverage the logs

[1689] Server: The stored logs are used for analysis and improvement as needed.

[1690] Input: Saved logs

[1691] What happens: Log entries are reviewed using analytics tools and used to improve the system and enhance the user experience.

[1692] Output: Analysis results

[1693] (Application example 2)

[1694] 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."

[1695] In conventional virtual stores, users could only browse a list of products, making it difficult to receive personalized guidance. Furthermore, there was a lack of appropriate product suggestions tailored to the user's emotions and needs, resulting in a poor user experience. Furthermore, the provision of content based on special events or themes was limited, limiting the improvement of user satisfaction.

[1696] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes user authentication means, an information terminal that transmits user input, natural language processing means that analyzes user utterances, generative model means that generate a response based on the analyzed user utterances, an information terminal that provides the generated response to the user, emotion analysis means that analyzes user emotions, and product recommendation means that suggests specific products to the user based on the emotion analysis results. This enables the user to receive individual guidance and appropriate product suggestions based on their emotions and needs, improving the quality of the user experience in the virtual store.

[1697] "User authentication means" refers to a process or device that verifies the identity of a user when accessing a system.

[1698] An "information terminal that transmits user input" is a device that transmits data that is input by a user through operation to a server or the like.

[1699] "Natural language processing means for analyzing user utterances" refers to technology or devices for analyzing text entered by a user and understanding its content.

[1700] "Generative model means" refers to a technique or device for generating appropriate responses based on analyzed user utterances.

[1701] The "information terminal that provides the generated response to the user" refers to a device that displays the generated response to the user.

[1702] "Emotion analysis means" refers to technology or devices that analyze the emotions of users based on their comments and determine their state.

[1703] "Product recommendation means" refers to technology or devices for suggesting specific products to users based on the results of emotion analysis.

[1704] A system for implementing this invention includes user authentication means, an information terminal for transmitting user input, natural language processing means for analyzing user utterances, generative model means, an information terminal for providing the generated response to the user, emotion analysis means, and product recommendation means. A program for realizing this system operates as follows.

[1705] First, the user logs in to the information terminal from a smartphone or head-mounted display (HMD) and is authenticated through the authentication means. The user authentication means is a process in which the user enters their user ID and password and sends that information to the server. The server compares the user's ID with the database, and if the user is authenticated as a legitimate user, it generates a session ID and sends it back to the information terminal.

[1706] Next, the user presses the dialogue start button to start a dialogue with the AI ​​dollar. The server, which receives the dialogue start request, generates an initial message for the AI ​​dollar and sends it to the information terminal. The user enters text in reply to that message and sends it back to the server.

[1707] The server analyzes the text sent by the user using natural language processing means to understand the content of the statement. For natural language processing, Google Cloud Natural Language API or spaCy are used, for example. The analysis results are sent to sentiment analysis means, where more detailed sentiment analysis is performed. IBM Watson Tone Analyzer can be used for this sentiment analysis.

[1708] Based on the results of the sentiment analysis, the server generates an appropriate response using a generative model, such as OpenAI's GPT-3 or GPT-4. The generated response is sent to the information terminal and displayed to the user.

[1709] It also has a product recommendation feature that suggests specific products to users based on the results of sentiment analysis. For example, if a user says, "I'm looking for a dress," the AI ​​dollar will suggest, "We have several dresses that would be suitable for a summer party. How about this blue dress or this black dress?"

[1710] Furthermore, when there is information about a specific event or sale, the server generates a message according to the limited event or special theme and notifies the user. This special content includes introductions to special products and discount information.

[1711] All of these interactions are saved as logs, which will be used for future analysis and to improve the user experience.

[1712] For example, if a user says, "I'm looking for a dress that suits tonight's party," the AI ​​dollar will respond as follows:

[1713] "It's a perfect dress for a party! I'll show you some popular items. How about this turquoise dress or a black dress?"

[1714] In this way, users can enjoy natural and personalized interactions with AI Dollar and efficiently search for suitable products. The following are examples of prompt sentences:

[1715] User: I'm looking for a dress for tonight's party.

[1716] AI Dollar: A perfect dress for a party! Let me show you some popular items. How about this turquoise dress or a black dress?

[1717] In this way, the present invention can improve the quality of the user experience.

[1718] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1719] Step 1: User authentication

[1720] 1. Input: The user enters their user ID and password into the information terminal (smartphone or HMD).

[1721] 2. Processing: The terminal sends the entered information to the server.

[1722] 3. Data processing: The server checks the user ID and password in the database.

[1723] 4. Output: If authentication is successful, the server generates a session ID and sends it to the terminal.

[1724] Step 2: Conversation-initiating request

[1725] 1. Input: The user presses the interaction start button displayed on the terminal.

[1726] 2. Processing: The terminal sends a dialogue start request to the server.

[1727] 3. Data Calculation: The server initiates the interactive session and generates the initial message for the AI ​​dollar.

[1728] 4. Output: Sends the initial message to the terminal and is displayed to the user.

[1729] Step 3: User comment analysis

[1730] 1. Input: The user inputs text in response to a message from the AI ​​dollar and sends it.

[1731] 2. Processing: The device sends the user's text to the server.

[1732] 3. Data calculation: The server analyzes the user's speech using natural language processing tools (e.g., Google Cloud Natural Language API or spaCy).

[1733] 4. Output: The content, intent, and sentiment of the speech are analyzed and sent to a sentiment analyzer.

[1734] Step 4: Sentiment Analysis

[1735] 1. Input: Analysis results sent from natural language processing means.

[1736] 2. Processing: The server performs further sentiment analysis using sentiment analysis tools (e.g. IBM Watson Tone Analyzer).

[1737] 3. Data calculation: Determine the user's emotional state.

[1738] 4. Output: Send the sentiment analysis results to the generative modeling means.

[1739] Step 5: Response Generation

[1740] 1. Input: Sentiment analysis results and analysis results from natural language processing tools.

[1741] 2. Processing: The server generates an appropriate response using a generative model (e.g., OpenAI GPT-3 or GPT-4).

[1742] 3. Data calculation: Generate the optimal response in text format based on the analysis results.

[1743] 4. Output: Send the generated response to the terminal.

[1744] Step 6: Display the response

[1745] 1. Input: The generated response sent by the server.

[1746] 2. Processing: The terminal displays the generated response to the user.

[1747] 3. Output: User confirms AI Dollar's response.

[1748] Step 7: Product Recommendation

[1749] 1. Input: Sentiment analysis results and user comments.

[1750] 2. Processing: The server uses the product recommendation means to suggest suitable products.

[1751] 3. Data calculation: Generate a list of products based on sentiment analysis and speech content.

[1752] 4. Output: Display the product recommendations to the user.

[1753] Step 8: Special Event Notifications

[1754] 1. Input: Specific event or sale information in the system.

[1755] 2. Processing: The server generates messages for limited events or special themes.

[1756] 3. Data Calculation: Generate special messages based on event information.

[1757] 4. Output: Notify the user with a special message.

[1758] Step 9: Save conversation logs

[1759] 1. Input: User utterances, AI dollar responses, and sentiment data.

[1760] 2. Processing: The server stores the conversation as a log.

[1761] 3. Data calculation: Generates log entries and stores them in a database.

[1762] 4. Output: The saved logs are stored as data for future analysis.

[1763] 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.

[1764] 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.

[1765] 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.

[1766] [Fourth embodiment]

[1767] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1768] 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.

[1769] 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).

[1770] 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.

[1771] 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.

[1772] 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).

[1773] 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.

[1774] 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.

[1775] 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.

[1776] 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.

[1777] 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.

[1778] 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.

[1779] 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."

[1780] This invention is a platform that allows users to interact with AI dollars in real time, and uses generative AI models. Below, we will explain the processing of this system in natural language, and also provide specific examples.

[1781] User authentication method

[1782] 1. Terminal: The user enters their user ID and password on the login screen and presses the send button.

[1783] The terminal sends a login request to the server.

[1784] 2. Server: The server checks the user ID and password received from the terminal against the database.

[1785] The server retrieves the user data from a database and verifies the authentication information.

[1786] 3. Server: If authentication is successful, the server generates a session ID and sends it back to the user.

[1787] The server generates a session ID and returns it to the user.

[1788] 4. Terminal: The terminal stores the session ID received from the server in memory and transitions to the dialogue start screen.

[1789] The terminal retains the session ID and transitions to the dialogue start screen.

[1790] Receive a request to start a conversation

[1791] 1. Terminal: The user presses the interaction start button.

[1792] The terminal sends a dialogue initiation request to the server.

[1793] 2. Server: The server initiates the interactive session and generates the initial message for the AI ​​dollar.

[1794] The server generates an initial message using an AI model and sends it to the terminal.

[1795] 3. Terminal: The terminal displays the AI ​​Dollar's welcome message to the user.

[1796] The terminal will display the AI ​​Dollar initial message on the screen.

[1797] User comment analysis using natural language processing

[1798] 1. User: The user responds to the message from the AI ​​dollar by typing and sending the text.

[1799] The terminal sends a user message to the server.

[1800] 2. Server: The server receives the user's speech and analyzes it using a natural language processing (NLP) engine.

[1801] The server analyzes the content, emotions, and intentions of the statements using an NLP engine.

[1802] 3. Server: The server obtains the analysis results (emotions, intentions) and prepares to generate a response accordingly.

[1803] The server prepares for reaction generation based on the analysis results.

[1804] Reaction formation of AI dollar

[1805] 1. Server: The server uses the generative AI model to generate AI dollar responses based on the analysis results.

[1806] The server uses the analysis results as input and the AI ​​model generates the corresponding response.

[1807] 2. Server: The server sends the generated response to the user terminal.

[1808] The server sends the generated response to the terminal.

[1809] 3. Terminal: The terminal displays the AI ​​dollar response to the user.

[1810] The terminal will display the AI ​​dollar's response on the screen.

[1811] Special event and theme dialogue content provided

[1812] 1. Server: A server provides interactive content during a specific event or based on a special theme.

[1813] The server checks the special event information from a database or API and retrieves the content.

[1814] 2. Server: The server generates special messages based on events and themes.

[1815] The server uses an AI model to generate special messages based on the special content.

[1816] 3. Terminal: The terminal displays a special message.

[1817] The terminal displays a special message to the user.

[1818] Log of conversations

[1819] 1. Server: The server stores user utterances and AI dollar responses for each dialogue session.

[1820] The server generates a log entry of the user's utterance and the AI ​​dollar's response.

[1821] 2. Server: The server stores the generated log entries in a database.

[1822] The server stores the log entries in a database.

[1823] 3. Server: If necessary, the server uses the logs to later analyze the interaction.

[1824] The server uses the stored logs for analysis.

[1825] In this way, users can enjoy natural and personalized interactions with AI Dollars, and unique interactions are possible based on special events or themes, providing a new type of digital entertainment experience.

[1826] The processing flow will be explained below.

[1827] Step 1:

[1828] Terminal: The user enters their user ID and password on the login screen and presses the send button.

[1829] The terminal sends a login request to the server.

[1830] Step 2:

[1831] Server: The server checks the user ID and password received from the terminal against the database.

[1832] The server retrieves the user data from a database and compares it with the entered password.

[1833] Step 3:

[1834] Server: If authentication is successful, the server generates a session ID and returns it to the user.

[1835] The server generates a session ID and sends it to the terminal as a response.

[1836] Step 4:

[1837] Terminal: The terminal stores the session ID received from the server in memory and transitions to the dialogue start screen.

[1838] The terminal stores the session ID in memory and displays a dialogue start screen to the user.

[1839] Step 5:

[1840] Terminal: The user presses the interaction start button.

[1841] The terminal sends a dialogue initiation request to the server.

[1842] Step 6:

[1843] Server: The server initiates the interactive session and generates the initial message for the AI.

[1844] The server generates an initial message to be sent by the AI ​​dollar and sends it to the terminal.

[1845] Step 7:

[1846] Terminal: The terminal displays the AI ​​Dollar's welcome message to the user.

[1847] The terminal will display the AI ​​Dollar initial message on the screen.

[1848] Step 8:

[1849] User: The user responds to the message from the AI ​​dollar by typing and sending the text.

[1850] The terminal sends a user message to the server.

[1851] Step 9:

[1852] Server: The server receives the user's utterance and analyzes it using a natural language processing (NLP) engine.

[1853] The server analyzes the content, sentiment, and intent of the speech using an NLP engine.

[1854] Step 10:

[1855] Server: The server obtains the analysis results (emotions, intentions) and prepares to generate a response accordingly.

[1856] The server prepares to generate an appropriate response based on the analysis results.

[1857] Step 11:

[1858] Server: The server uses the generative AI model to generate AI dollar responses based on the analysis results.

[1859] The server uses the analysis results as input to generate the response content of the AI ​​dollar.

[1860] Step 12:

[1861] Server: The server sends the generated response to the user device.

[1862] The server sends the generated reaction to the terminal as a response.

[1863] Step 13:

[1864] Terminal: The terminal displays the AI ​​dollar response to the user.

[1865] The terminal will display the AI ​​dollar's response on the screen.

[1866] Step 14:

[1867] Servers: Servers provide interactive content during specific events or based on special themes.

[1868] The server checks the database or API for special event information and generates content based on that information.

[1869] Step 15:

[1870] Server: The server generates special messages based on events and themes.

[1871] The server uses an AI model to generate a message based on the special content and sends it to the device.

[1872] Step 16:

[1873] Terminals: Terminals display special messages.

[1874] The terminal displays a special message on the user's screen.

[1875] Step 17:

[1876] Server: The server stores user utterances and AI dollar responses for each dialogue session.

[1877] The server generates a log entry of the user's utterance and the AI ​​dollar's response.

[1878] Step 18:

[1879] Server: The server stores the generated log entries in a database.

[1880] The server stores the log entries in a database.

[1881] Step 19:

[1882] Server: If necessary, the server uses the logs to later analyze the interaction.

[1883] The server uses the stored logs for analysis.

[1884] Example 1

[1885] 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."

[1886] In recent years, dialogue systems using artificial intelligence have become widespread, but they are being required to meet a variety of needs, such as reliable user authentication, natural dialogue, provision of dialogue content according to special events or themes, and logging of dialogue content.However, conventional systems face the challenge of being unable to simultaneously meet all of these needs.

[1887] 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.

[1888] In this invention, the server

[1889] means for verifying user authentication information;

[1890] A means of generating and transmitting a session ID if authentication is successful;

[1891] A means for transmitting user comments and analyzing them using natural language processing means;

[1892] A generative AI model means for generating a response based on the analyzed user utterance;

[1893] A means to provide interactive content for limited events and special themes,

[1894] A means for storing the contents of the dialogue as a log;

[1895] This allows for increased reliability in user authentication, natural and personalized interactions, the provision of content for special events or themes, and the storage of interaction logs.

[1896] "User authentication information" refers to information such as an ID and password that a user enters to verify their identity.

[1897] "Information terminal" is a general term for electronic devices that users use to input and send and receive data.

[1898] The term "server means" refers to a computer system for receiving and processing requests, and is a device that has the functions of verifying data, generating session IDs, and generating and transmitting messages.

[1899] A "session ID" is a unique identifier generated by the server to indicate successful authentication of a user and to manage an interactive session.

[1900] "Natural language processing means" refers to technology that analyzes text data entered by a user and understands their meaning, emotions, and intent.

[1901] A "generative AI model means" is an artificial intelligence model used to generate appropriate responses based on analyzed user utterances.

[1902] "Interactive content based on limited events or special themes" refers to special interactive content provided during specific event periods or based on special themes.

[1903] A "log" is recorded data that includes user utterances and AI dollar responses for each interactive session.

[1904] The present invention is a platform that allows users to interact with AI characters in real time, and uses generative AI models. Detailed embodiments of the system are described below.

[1905] User Authentication

[1906] When the system starts, the user uses an information terminal (e.g., smartphone, tablet, PC) to enter their user ID and password on the login screen and press the send button. The terminal then sends this login request to the server. The server compares the received user ID and password with the database, and if they match, generates a session ID and sends it to the user's terminal. The terminal then stores the session ID in memory and transitions to the dialogue start screen.

[1907] Starting a conversation

[1908] When the user presses the dialogue start button, the device sends a dialogue start request to the server. The server starts a dialogue session and sends a prompt to the generative AI model to generate an initial message. The generated initial message is sent to the user's device and displayed to the user.

[1909] Analysis of user comments

[1910] The user responds to messages from the AI ​​character by inputting text and sending it. The device then sends the user message to the server, which then analyzes the received user message using a natural language processing (NLP) engine to extract the content, emotion, and intent of the message.

[1911] AI character reaction generation

[1912] The server sends a prompt to the generative AI model to generate a response based on the analysis results of the NLP engine. For example, "The user said 'hello,' so please generate a response that says 'hello.'" The generated response is sent to the device via the server and displayed to the user.

[1913] Providing interactive content based on special events and themes

[1914] The server automatically generates interactive content based on specific event periods or special themes. For example, during an event, a special message such as "Happy Birthday! Today is a special day!" is displayed. The server obtains special event information using a database or API and sends prompts to the generative AI model to generate special content.

[1915] Conversation logging and analysis

[1916] The server generates log entries for each interaction session, including user comments and AI character responses, and stores them in a database, allowing for later analysis of the interaction content to improve the service and detect errors.

[1917] Specific examples

[1918] For example, if a user types "hello" and sends it, it will be processed as follows:

[1919] 1. User: Type "Hello" and send.

[1920] 2. Device: Sends "hello" to the server.

[1921] 3. Server: Analyze "hello" using an NLP engine to read the emotion and intent. Recognize it as a "greeting."

[1922] 4. Server: Based on the analysis results, the server sends a prompt to the generative AI model to generate a response to the greeting.

[1923] 5. Server: Sends the generated response "Hello! What would you like to talk about today?" to the user terminal.

[1924] 6. Terminal: Display "Hello! What would you like to talk about today?" to the user.

[1925] This system allows users to enjoy more natural and personalized interactions, and enables unique interactions based on special events or themes.The system cleverly utilizes generative AI models and prompts to provide a new form of digital entertainment.

[1926] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1927] Step 1: Enter and submit user credentials

[1928] 1. User: The user enters the user ID and password on the login screen of the information terminal and presses the send button. The user ID and password are provided as input.

[1929] 2. Terminal: The terminal receives the user's input, generates a login request, and sends it to the server. As an output, a login request is generated.

[1930] Step 2: Verify user authentication

[1931] 1. Server: The server parses the received login request and extracts the user ID and password. The login request is provided as input.

[1932] 2. Server: Retrieves user information from the database and matches it with the entered authentication information. The user information retrieved from the database is used for matching.

[1933] 3. Server: Generates a session ID if the authentication information is correct, or an error message if it is incorrect. As output, a session ID or an error message is generated.

[1934] 4. Server: Sends the session ID or an error message to the terminal. As output, the session ID or an error message is sent to the terminal.

[1935] Step 3: Session ID retention and screen transitions

[1936] 1. Terminal: Parse the session ID or error message received from the server. As input, the session ID or error message is provided.

[1937] 2. Terminal: Keep the session ID in memory and display a success message or transition to the start of the conversation screen. If it is incorrect, display an error message and stay at the login screen. As output, the success or error message is displayed on the screen.

[1938] Step 4: Sending a conversation-initiating request

[1939] 1. User: The user clicks the interaction start button. The click of the interaction start button is provided as input.

[1940] 2. Terminal: Prepares to send a conversation initiation request to the server. As output, a conversation initiation request is generated.

[1941] 3. Terminal: Sends a conversation initiation request to the server. As an output, a conversation initiation request is sent to the server.

[1942] Step 5: Generate and send the initial message

[1943] 1. Server: Receives a conversation initiation request and starts a conversation session. The conversation initiation request is provided as input.

[1944] 2. Server: Sends a prompt to the generative AI model to generate an initial message. The prompt sentence is provided as input.

[1945] 3. Server: Receives the initial message from the generative AI model and sends it to the device. As an output, an initial message is generated and sent to the device.

[1946] Step 6: Displaying a welcome message

[1947] 1. Terminal: Receives the initial message and displays it to the user. As input, the initial message is provided. As output, the initial message is displayed on the screen.

[1948] Step 7: Enter and send user utterances

[1949] 1. User: Enters and sends text in response to a message from an AI character. The user's text is provided as input.

[1950] 2. Terminal: receives user input and prepares it for transmission to the server. As output, a user message is generated.

[1951] 3. Terminal: Sends user messages to the server. As output, the user messages are sent to the server.

[1952] Step 8: Analyzing user utterances

[1953] 1. Server: Receives the user message and starts parsing it in the natural language processing engine. The user message is provided as input.

[1954] 2. Server: Analyzes the message content, sentiment, and intent using an NLP engine. The analysis results are generated as output.

[1955] 3. Server: Retrieves the analysis results and prepares the data for reaction generation. The output is the data for reaction generation.

[1956] Step 9: Generate and send AI character reactions

[1957] 1. Server: Based on the analysis results, the server sends a prompt to the generative AI model to generate a reaction. The prompt sentence for generating a reaction is provided as input.

[1958] 2. Server: Prepares to send the generated responses to the terminal. The generated responses are generated as output.

[1959] 3. Server: Sends the generated responses to the terminal. As output, the generated responses are sent to the terminal.

[1960] Step 10: Viewing the Reaction

[1961] 1. Terminal: Analyzes the received AI character's reaction and displays it to the user. As input, the AI ​​character's reaction is provided. As output, the reaction is displayed on the screen.

[1962] Step 11: Offer special events or themed content

[1963] 1. Server: Checks whether there is a specific event or special themed interactive content. Event information is provided as input.

[1964] 2. Server: Retrieves special event information using a database or API and generates a prompt with limited content. As output, the special event information is retrieved and a prompt statement is generated.

[1965] 3. Server: Sends a prompt with special content to the generative AI model to generate a special message. As input, a prompt with special content is provided. As output, a special message is generated.

[1966] 4. Server: Prepares to send the generated special message to the user terminal. As output, the special message is generated.

[1967] 5. Server: Sends the generated special message to the user terminal. As output, the special message is sent to the terminal.

[1968] 6. Terminal: Receives special messages and displays them to the user. As input, special messages are provided. As output, special messages are displayed on the screen.

[1969] Step 12: Logging interactions

[1970] 1. Server: Generates log entries for each interaction session, including user utterances and AI character responses. As input, the server receives user utterances and AI character responses. As output, it generates a log entry.

[1971] 2. Server: Stores the generated log entries in a database. As an output, the log entries are stored in a database.

[1972] The above is the specific program processing flow of this system.

[1973] (Application example 1)

[1974] 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."

[1975] Conventional dialogue systems generally involve dialogue between users and AI, but lack the functionality to provide dialogue content based on special events or themes. Furthermore, few applications are compatible with multiple devices, limiting the devices that users can use. Furthermore, it is difficult to log and analyze dialogues later, making it difficult to track user behavior and improve services.

[1976] 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.

[1977] In this invention, the server includes a user authentication means, an information terminal means for transmitting user input, and a natural language processing means for analyzing user utterances, which allows users and AI to enjoy unique dialogue content during a specific event or based on a special theme, and further enables compatibility with multiple devices and the saving of dialogue logs for later analysis.

[1978] "User authentication" is the process by which a user verifies the identity used to log into a system.

[1979] An "information terminal that transmits user input" is a device through which a user can enter text, voice, or other forms of input and transmit it to the system.

[1980] "Natural language processing means for analyzing user utterances" is a technology that analyzes the linguistic information entered by the user and understands its content, emotions, and intentions.

[1981] The "generative model means for generating a response based on the analyzed user utterance" is an artificial intelligence technology for generating an appropriate response based on the analysis results.

[1982] The "means for generating dialogue content during a specific event or based on a special theme" is a function for creating dialogue content according to a special event or theme and presenting it to the user.

[1983] An "information terminal that provides the user with the generated response" is a device that displays or audibly conveys the response generated by AI to the user.

[1984] "Means for saving dialogue content as a log" is a function for recording the content of dialogue between the user and AI and saving it for future reference.

[1985] An "interactive application compatible with a variety of devices, including smartphones, head-mounted displays, and smart glasses" is an application that runs on a variety of devices and provides interactive functions between users and AI.

[1986] The present invention provides a system that allows users to interact with AI dollars in real time using a variety of devices. Specific embodiments of this system will be described below.

[1987] The system includes a user authentication means, an information terminal for transmitting user input, a natural language processing means for analyzing user utterances, a generative model means for generating responses based on the analyzed user utterances, a means for generating dialogue content during a specific event period or based on a special theme, an information terminal for providing the generated responses to the user, and a means for saving the dialogue content as a log.

[1988] 1. Hardware and Software

[1989] The hardware required to build the system includes a smartphone, smart glasses, and a head-mounted display, while the software uses Python, Flask (a web framework), an NLP engine (e.g., SpaCy, Transformers), and a generative AI model (e.g., GPT-3).

[1990] 2. Program Processing

[1991] The server first authenticates the user ID and password entered by the user using the user authentication means. If the authentication is successful, it returns a session ID to the user and receives a request to start a dialogue. When the user presses the dialogue start button, the server starts a dialogue session, generates an initial message for the AI ​​dollar, and sends it to the information terminal.

[1992] The user checks the initial message on the information terminal and responds by inputting a response in text or voice. The input user utterance is sent to the server and analyzed by the natural language processing means. The generative model means generates a response based on the analyzed content, emotion, and intention.

[1993] If conversation content based on a specific event period or special theme is required, the server generates special content and provides users with special messages based on that content. This allows users to enjoy unique conversations that are tailored to the event or theme. All conversation content is also saved as a log on the server and can be used for later analysis.

[1994] 3. Specific Examples

[1995] For example, a "Happy New Year" campaign will be held as a limited-time event. AI Dollar will provide special content that will interact with users about their "New Year's resolutions." This special content will be generated based on the following prompts:

[1996] "This is a scenario where a user shares their New Year's resolutions. The AI ​​dollar generates appropriate responses based on what the user says, continuing a fun conversation fit for the New Year."

[1997] As described above, this system allows users to enjoy real-time conversations based on special events or themes across multiple devices, and the content of the conversations is saved as a log so that they can be analyzed later.

[1998] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1999] Step 1:

[2000] The user displays the login screen on their information terminal, enters their user ID and password, and submits it. The entered data is the user ID and password, and is sent from the terminal to the server. The server receives this request and checks the user ID and password against its database.

[2001] Step 2:

[2002] The server retrieves the user information from the database and verifies the authentication information. If the authentication is successful, the server generates a session ID and sends it back to the terminal. This authenticates the user and gives them a session ID to proceed to the next step.

[2003] Step 3:

[2004] The terminal stores the session ID received from the server in memory and switches to the dialogue start screen. The user presses the dialogue start button here and sends a dialogue start request to the server. This request includes the session ID.

[2005] Step 4:

[2006] The server starts an interactive session and generates an initial message for the AI ​​using the generative AI model. The input is the session ID and the prompt required to generate the initial message, and the output is the generated initial message. The server sends this initial message to the terminal.

[2007] Step 5:

[2008] The terminal displays the initial message received from the server on the screen. The user responds to this message by inputting a response in text or voice and sends it. The input data is the user's message, and the terminal sends it to the server.

[2009] Step 6:

[2010] The server receives the user's comments and analyzes them using a natural language processing engine. The input for the analysis is the user's message, and the output is the analysis results, such as the content of the comment, emotions, and intentions. Based on this, the server prepares to generate a response from the AI ​​dollar.

[2011] Step 7:

[2012] The server generates an appropriate AI response using a generative AI model based on the analysis results. The input is the analysis result and the prompt, and the output is the generated response. The server then sends this response to the device.

[2013] Step 8:

[2014] The terminal displays the AI ​​dollar response received from the server to the user, who can then enter a message again to continue the conversation. The process repeats.

[2015] Step 9:

[2016] During and after a conversation session, the server stores the entire conversation as a log. The data stored is the user's statements and the AI ​​dollar's responses, and the server stores this in a database. The log is later used for analysis and service improvement.

[2017] Step 10:

[2018] The server provides special interactive content based on specific event periods or special themes. The prompt text is used to generate the special content, and the generative AI model generates a special response based on it. The server then sends it to the device, allowing the user to enjoy the special interaction.

[2019] 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.

[2020] This invention is a platform that allows users to interact with AI dollars in real time, using a generative AI model and an emotion engine. Below, we will explain the processing of this system in natural language, and also provide concrete examples.

[2021] User authentication method

[2022] 1. Terminal: The user enters their user ID and password on the login screen and presses the send button.

[2023] The terminal sends a login request to the server.

[2024] 2. Server: The server checks the user ID and password received from the terminal against the database.

[2025] The server retrieves the user data from a database and compares it with the entered password.

[2026] 3. Server: If authentication is successful, the server generates a session ID and sends it back to the user.

[2027] The server generates a session ID and sends it to the terminal as a response.

[2028] 4. Terminal: The terminal stores the session ID received from the server in memory and transitions to the dialogue start screen.

[2029] The terminal holds the session ID and displays the dialogue start screen to the user.

[2030] Receive a request to start a conversation

[2031] 1. Terminal: The user presses the interaction start button.

[2032] The terminal sends a dialogue initiation request to the server.

[2033] 2. Server: The server initiates the interactive session and generates the initial message for the AI ​​dollar.

[2034] The server generates an initial message to be sent by the AI ​​dollar and sends it to the terminal.

[2035] 3. Terminal: The terminal displays the AI ​​Dollar's welcome message to the user.

[2036] The terminal will display the AI ​​Dollar initial message on the screen.

[2037] Analyzing user comments using natural language processing and using an emotion engine

[2038] 1. User: The user responds to the message from the AI ​​dollar by typing and sending the text.

[2039] The terminal sends a user message to the server.

[2040] 2. Server: The server receives the user's speech and analyzes it using a natural language processing (NLP) engine.

[2041] The server analyzes the content, sentiment, and intent of the speech using an NLP engine.

[2042] 3. Server: The server sends the analysis results to the emotion engine for detailed emotion analysis.

[2043] The server further analyzes the user's emotions using an emotion engine and obtains the results.

[2044] Reaction formation of AI dollar

[2045] 1. Server: The server uses the generative AI model to generate responses from the AI ​​dollar based on the analysis results and the emotional information obtained from the emotion engine.

[2046] The server generates an appropriate response based on the analysis results and emotional information.

[2047] 2. Server: The server sends the generated response to the user terminal.

[2048] The server sends the generated reaction to the terminal as a response.

[2049] 3. Terminal: The terminal displays the AI ​​dollar response to the user.

[2050] The terminal will display the AI ​​dollar's response on the screen.

[2051] Special event and theme dialogue content provided

[2052] 1. Server: A server provides interactive content during a specific event or based on a special theme.

[2053] The server checks the database or API for special event information and generates content based on that information.

[2054] 2. Server: The server generates special messages based on events and themes.

[2055] The server uses an AI model to generate a message based on the special content and sends it to the device.

[2056] 3. Terminal: The terminal displays a special message.

[2057] The terminal displays a special message on the user's screen.

[2058] Log of conversations

[2059] 1. Server: The server stores user utterances, AI responses, and emotion data from the emotion engine for each dialogue session.

[2060] The server generates log entries based on user comments, AI dollar responses, and emotional data.

[2061] 2. Server: The server stores the generated log entries in a database.

[2062] The server stores the log entries in a database.

[2063] 3. Server: If necessary, the server uses the logs to later analyze the interaction.

[2064] The server uses the stored logs for analysis.

[2065] In this way, users can enjoy natural and personalized interactions with AI Dollars, and unique interactions are possible based on special events or themes. In addition, the emotion engine allows AI Dollars to better understand users' emotions and respond accordingly, providing a new type of digital entertainment experience.

[2066] The processing flow will be explained below.

[2067] Step 1:

[2068] Terminal: The user enters their user ID and password on the login screen and presses the send button.

[2069] The terminal sends a login request to the server.

[2070] Step 2:

[2071] Server: The server checks the user ID and password received from the terminal against the database.

[2072] The server retrieves the user data from a database and compares it with the entered password.

[2073] Step 3:

[2074] Server: If authentication is successful, the server generates a session ID and returns it to the user.

[2075] The server generates a session ID and sends it to the terminal as a response.

[2076] Step 4:

[2077] Terminal: The terminal stores the session ID received from the server in memory and transitions to the dialogue start screen.

[2078] The terminal holds the session ID and displays the dialogue start screen to the user.

[2079] Step 5:

[2080] Terminal: The user presses the interaction start button.

[2081] The terminal sends a dialogue initiation request to the server.

[2082] Step 6:

[2083] Server: The server initiates the interactive session and generates the initial message for the AI.

[2084] The server generates an initial message to be sent by the AI ​​dollar and sends it to the terminal.

[2085] Step 7:

[2086] Terminal: The terminal displays the AI ​​Dollar's welcome message to the user.

[2087] The terminal will display the AI ​​Dollar initial message on the screen.

[2088] Step 8:

[2089] User: The user responds to the message from the AI ​​dollar by typing and sending the text.

[2090] The terminal sends a user message to the server.

[2091] Step 9:

[2092] Server: The server receives the user's utterance and analyzes it using a natural language processing (NLP) engine.

[2093] The server analyzes the content, sentiment, and intent of the speech using an NLP engine.

[2094] Step 10:

[2095] Server: The server sends the analysis results to the emotion engine for detailed emotion analysis.

[2096] The server further analyzes the user's emotions using an emotion engine and obtains the results.

[2097] Step 11:

[2098] Server: The server uses the generative AI model to generate responses from the AI ​​dollar based on the analysis results and emotional information obtained from the emotion engine.

[2099] The server generates the AI ​​dollar's response based on the analysis results and emotional information.

[2100] Step 12:

[2101] Server: The server sends the generated response to the user device.

[2102] The server sends the generated reaction to the terminal as a response.

[2103] Step 13:

[2104] Terminal: The terminal displays the AI ​​dollar response to the user.

[2105] The terminal will display the AI ​​dollar's response on the screen.

[2106] Step 14:

[2107] Servers: Servers provide interactive content during specific events or based on special themes.

[2108] The server checks the database or API for special event information and generates content based on that information.

[2109] Step 15:

[2110] Server: The server generates special messages based on events and themes.

[2111] The server uses an AI model to generate a message based on the special content and sends it to the device.

[2112] Step 16:

[2113] Terminals: Terminals display special messages.

[2114] The terminal displays a special message on the user's screen.

[2115] Step 17:

[2116] Server: The server stores user utterances, AI responses, and emotion data from the emotion engine for each dialogue session.

[2117] The server generates log entries based on user comments, AI dollar responses, and emotional data.

[2118] Step 18:

[2119] Server: The server stores the generated log entries in a database.

[2120] The server stores the log entries in a database.

[2121] Step 19:

[2122] Server: If necessary, the server uses the logs to later analyze the interaction.

[2123] The server uses the stored logs for analysis.

[2124] Example 2

[2125] 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."

[2126] Current dialogue systems struggle to accurately understand user sentiment and generate appropriate responses based on it. Furthermore, they lack the ability to provide special event or themed content, limiting the user experience. They also lack the means to effectively store dialogue content for later analysis.

[2127] 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.

[2128] In this invention, the server includes a user authentication means, an information terminal through which a user inputs and transmits information, a natural language processing means for analyzing user utterances, a generative AI model means for generating a response based on the analyzed user utterances, an information terminal for providing the generated response to the user, a sentiment analysis means for analyzing the sentiment of the user utterances, a means for adjusting the response to be generated based on the sentiment analysis, and a means for generating an initial message at the start of an interaction session. This makes it possible to accurately understand the user's sentiment and generate an appropriate response based on that sentiment. Furthermore, by providing dialogue content according to special events or themes and saving the dialogue content as a log for later analysis, a richer user experience can be provided.

[2129] "User authentication means" refers to a means for verifying whether a user is a legitimate user by checking the user ID and password.

[2130] An "information terminal" is a device that allows a user to input and transmit information, and includes, for example, a personal computer, a smartphone, a tablet, and the like.

[2131] "Natural language processing" refers to technology for analyzing user utterances and understanding their content and intent. This includes text analysis, semantic analysis, and context understanding.

[2132] A "generative AI model means" is an artificial intelligence algorithm or model for generating appropriate responses based on analyzed user utterances.

[2133] "Emotion analysis means" is a technology that analyzes the emotions contained in a user's speech and identifies their emotional state. This includes emotion detection and emotion classification.

[2134] The "means for adjusting the response" is a technology for adjusting the response generated based on the emotion analysis results and providing an appropriate response that matches the user's emotional state.

[2135] "Means for generating an initial message" refers to technology for generating the first message that the AI ​​issues at the start of an interaction session.

[2136] The "means for providing dialogue content according to limited events or special themes" is a means for generating special dialogue content based on a specific event period or theme and providing it to users.

[2137] "Means for saving dialogue content as a log" refers to a means for saving the dialogue content between the user and the AI ​​and the analysis results in a database or the like so that they can be referenced and analyzed later.

[2138] This invention is a platform that allows users to interact with artificial intelligence (AI) characters in real time. This platform operates by combining multiple functions including user authentication means, natural language processing means, emotion analysis means, and generative AI model means.

[2139] First, the user uses an information terminal (for example, a PC or smartphone) to enter their user ID and password on the login screen. When the user presses the send button, the information is sent from the terminal to the server. The server compares the received information with a database and performs authentication. If authentication is successful, the server generates a session ID and returns it to the terminal. The terminal retains this session ID and displays the dialogue start screen to the user.

[2140] Next, the user presses the Start Dialogue button, which sends a dialogue start request to the server, which then starts a new dialogue session. Using a generative AI model (e.g., "AI-GPT"), the server generates an initial message and sends it to the device. The device then displays this initial message to the user.

[2141] When a user replies to a message from an AI character, the message is sent from the device to a server. The server analyzes the received message using a natural language processing (NLP) engine (e.g., "NLP-Analyzer") to understand the content and intent of the message. The analysis results are then sent to an emotion analysis engine (e.g., "Emotion-X") for detailed emotion analysis. Based on the obtained emotion data, a generative AI model generates an appropriate response. This response is then sent to the device and displayed to the user.

[2142] In addition, the server will prepare exclusive interactive content and generate special messages based on specific event periods or special themes, allowing users to enjoy a constantly new experience.

[2143] Furthermore, the server stores the dialogue content, user comments, AI character responses, and emotional data as logs, which allows for later analysis of the user's dialogue behavior.

[2144] As a specific example, when a user logs in by entering "user123" and "password123" on the login screen, the server returns a session ID and the dialogue start screen is displayed on the device. When the user presses the dialogue start button, an AI character displays the initial message "Hello! How was your day?" If the user replies "I'm a little tired today," the server analyzes this message with an NLP engine and identifies the emotion of "tired" with an emotion analysis engine. The generative AI model generates a response saying "That must have been tough. It's important to take some time to rest," and displays this on the device.

[2145] An example of a prompt might be:

[2146] Please enter the prompt to send the API request for login authentication.

[2147] "Explain how to integrate an NLP engine with a sentiment engine to perform sentiment analysis of user input."

[2148] In this way, users can enjoy a richer, more personalized interaction experience using generative AI models and sentiment analysis engines, and unique interaction content is provided based on events and special themes, ensuring a constantly fresh entertainment experience.

[2149] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2150] User authentication method

[2151] Step 1: Enter and submit your login details

[2152] User: The user enters their user ID and password on the login screen and presses the submit button.

[2153] Input: User ID, Password

[2154] What happens: The user enters information into the text boxes and clicks the "Login" button.

[2155] Output: Login request (user ID, password)

[2156] Step 2: Submitting authentication information

[2157] Terminal: Sends the entered information to the server.

[2158] Input: Login request (user ID, password)

[2159] Specific operation: Sends the user ID and password to the server using an HTTP POST request.

[2160] Output: Authentication request to the server

[2161] Step 3: Verify credentials

[2162] Server: The server queries the database for the received user ID and password and performs verification.

[2163] Input: Authentication request to the server

[2164] What happens: The server performs a database query to compare the password associated with the user ID with the submitted password.

[2165] Output: Authentication result (success / failure)

[2166] Step 4: Generate and send a session ID

[2167] Server: If authentication is successful, a session ID is generated and sent back to the device.

[2168] Input: Authentication result (success)

[2169] Specific operation: A session ID is generated using a UUID or similar and sent back to the device as an HTTP response.

[2170] Output: Session ID

[2171] Step 5: Receiving and maintaining a session ID

[2172] Terminal: The terminal stores the session ID received from the server in its memory.

[2173] Input: Session ID

[2174] Specific behavior: Saves the session ID in local storage or memory.

[2175] Output: Persisted session ID

[2176] Step 6: Display the conversation start screen

[2177] Terminal: Transition to the dialogue start screen.

[2178] Input: Persisted session ID

[2179] Specific Behavior: Switch to UI indicating successful login.

[2180] Output: Start screen

[2181] Receive a request to start a conversation

[2182] Step 1: Press the Start Dialogue button

[2183] User: The user presses the start button.

[2184] Input: User operation (pressing the interaction start button)

[2185] Specific action: The user clicks the start button.

[2186] Output: Conversation initiating request

[2187] Step 2: Sending a conversation-initiating request

[2188] Terminal: Sends a dialogue initiation request to the server.

[2189] Input: Conversation-initiating request

[2190] Specific behavior: Sends a conversation initiation request to the server using an HTTP GET or POST request.

[2191] Output: A conversation initiating request to the server

[2192] Step 3: Starting an interactive session

[2193] Server: The server starts a new interactive session and generates the AI ​​dollar's initial message.

[2194] Input: A request to start a conversation with the server

[2195] Specific operation: Generate an initial message using a generative AI model (e.g., "AI-GPT").

[2196] Output: Initial message

[2197] Step 4: Sending the initial message

[2198] Server: Sends an initial message to the device.

[2199] Input: initial message

[2200] Specific operation: Sends an initial message to the terminal as an HTTP response.

[2201] Output: Initial message to terminal

[2202] Step 5: Displaying a welcome message

[2203] Terminal: Displays the received initial message to the user.

[2204] Input: initial message to terminal

[2205] Specific behavior: Display an initial message on the UI.

[2206] Output: Shows the initial message.

[2207] Analyzing user comments using natural language processing and using an emotion engine

[2208] Step 1: Enter and send user utterances

[2209] User: The user responds to the message from the AI ​​dollar by typing and sending a message.

[2210] Input: User message

[2211] Specific actions: Enter a message in the text area and click the "Send" button.

[2212] Output: User utterances

[2213] Step 2: Sending a User Message

[2214] Terminal: Sends user messages to the server.

[2215] Input: User utterance

[2216] Specific behavior: Sends a message to the server using an HTTP POST request.

[2217] Output: User message to the server

[2218] Step 3: Analyzing user utterances

[2219] Server: Analyzes received user messages using a natural language processing (NLP) engine.

[2220] Input: User message to server

[2221] Specific behavior: Analyzes speech content, sentiment, and intent using an NLP engine (e.g., "NLP-Analyzer").

[2222] Output: Analysis results

[2223] Step 4: Perform sentiment analysis

[2224] Server: The analysis results are sent to the sentiment analysis engine for detailed sentiment analysis.

[2225] Input: Analysis results

[2226] Specific operation: Obtain detailed emotional data using the emotion analysis engine "Emotion-X."

[2227] Output: Detailed emotion data

[2228] Reaction formation of AI dollar

[2229] Step 1: Generate the reaction

[2230] Server: Uses a generative AI model to generate responses based on analysis results and emotional data.

[2231] Input: Analysis results, detailed emotion data

[2232] Specific operation: A prompt sentence is input into a generative AI model (e.g., "AI-GPT"), which generates an appropriate response.

[2233] Output: The generated reaction

[2234] Step 2: Sending a response

[2235] Server: Sends the generated responses to the device.

[2236] Input: Generated reactions

[2237] Specific operation: Sends the generated response to the terminal as an HTTP response.

[2238] Output: Response to terminal

[2239] Step 3: View the reaction

[2240] Terminal: Displays the response of the received AI dollar to the user.

[2241] Input: Response to terminal

[2242] Specific behavior: Displays AI dollar reactions on the UI.

[2243] Output: Display of AI dollar response

[2244] Special event and theme dialogue content provided

[2245] Step 1: Prepare special content

[2246] Servers: Prepare interactive content for specific events or special themes.

[2247] Input: Event information, theme information

[2248] What it does: Retrieves event information from a database or external API and generates special content.

[2249] Output: Special Content

[2250] Step 2: Generate a special message

[2251] Server: Generates special messages based on active events and themes.

[2252] Input: Special Content

[2253] What it does: Uses a generative AI model to generate a special message and send it to the device.

[2254] Output: special message

[2255] Step 3: Send and display special messages

[2256] Terminal: Display a special message to the user.

[2257] Input: Special message

[2258] Specific behavior: Display a special message in the UI.

[2259] Output: Display a special message

[2260] Log of conversations

[2261] Step 1: Generate a log entry

[2262] Server: Generates log entries for each interaction session, including user utterances, AI responses, and emotion data.

[2263] Input: User utterances, AI dollar responses, sentiment data

[2264] Specific operation: Create a single log entry containing the dialogue content and emotion data.

[2265] Output: The generated log entries

[2266] Step 2: Save the logs

[2267] Server: Stores the generated log entries in a database.

[2268] Input: Generated log entry

[2269] What it does: Executes a query to store interaction log entries in a database.

[2270] Output: Saved logs

[2271] Step 3: Leverage the logs

[2272] Server: The stored logs are used for analysis and improvement as needed.

[2273] Input: Saved logs

[2274] What happens: Log entries are reviewed using analytics tools and used to improve the system and enhance the user experience.

[2275] Output: Analysis results

[2276] (Application example 2)

[2277] 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."

[2278] In conventional virtual stores, users could only browse a list of products, making it difficult to receive personalized guidance. Furthermore, there was a lack of appropriate product suggestions tailored to the user's emotions and needs, resulting in a poor user experience. Furthermore, the provision of content based on special events or themes was limited, limiting the improvement of user satisfaction.

[2279] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes user authentication means, an information terminal that transmits user input, natural language processing means that analyzes user utterances, generative model means that generate a response based on the analyzed user utterances, an information terminal that provides the generated response to the user, emotion analysis means that analyzes user emotions, and product recommendation means that suggests specific products to the user based on the emotion analysis results. This enables the user to receive individual guidance and appropriate product suggestions based on their emotions and needs, improving the quality of the user experience in the virtual store.

[2280] "User authentication means" refers to a process or device that verifies the identity of a user when accessing a system.

[2281] An "information terminal that transmits user input" is a device that transmits data that is input by a user through operation to a server or the like.

[2282] "Natural language processing means for analyzing user utterances" refers to technology or devices for analyzing text entered by a user and understanding its content.

[2283] "Generative model means" refers to a technique or device for generating appropriate responses based on analyzed user utterances.

[2284] The "information terminal that provides the generated response to the user" refers to a device that displays the generated response to the user.

[2285] "Emotion analysis means" refers to technology or devices that analyze the emotions of users based on their comments and determine their state.

[2286] "Product recommendation means" refers to technology or devices for suggesting specific products to users based on the results of emotion analysis.

[2287] A system for implementing this invention includes user authentication means, an information terminal for transmitting user input, natural language processing means for analyzing user utterances, generative model means, an information terminal for providing the generated response to the user, emotion analysis means, and product recommendation means. A program for realizing this system operates as follows.

[2288] First, the user logs in to the information terminal from a smartphone or head-mounted display (HMD) and is authenticated through the authentication means. The user authentication means is a process in which the user enters their user ID and password and sends that information to the server. The server compares the user's ID with the database, and if the user is authenticated as a legitimate user, it generates a session ID and sends it back to the information terminal.

[2289] Next, the user presses the dialogue start button to start a dialogue with the AI ​​dollar. The server, which receives the dialogue start request, generates an initial message for the AI ​​dollar and sends it to the information terminal. The user enters text in reply to that message and sends it back to the server.

[2290] The server analyzes the text sent by the user using natural language processing means to understand the content of the statement. For natural language processing, Google Cloud Natural Language API or spaCy are used, for example. The analysis results are sent to sentiment analysis means, where more detailed sentiment analysis is performed. IBM Watson Tone Analyzer can be used for this sentiment analysis.

[2291] Based on the results of the sentiment analysis, the server generates an appropriate response using a generative model, such as OpenAI's GPT-3 or GPT-4. The generated response is sent to the information terminal and displayed to the user.

[2292] It also has a product recommendation feature that suggests specific products to users based on the results of sentiment analysis. For example, if a user says, "I'm looking for a dress," the AI ​​dollar will suggest, "We have several dresses that would be suitable for a summer party. How about this blue dress or this black dress?"

[2293] Furthermore, when there is information about a specific event or sale, the server generates a message according to the limited event or special theme and notifies the user. This special content includes introductions to special products and discount information.

[2294] All of these interactions are saved as logs, which will be used for future analysis and to improve the user experience.

[2295] For example, if a user says, "I'm looking for a dress that suits tonight's party," the AI ​​dollar will respond as follows:

[2296] "It's a perfect dress for a party! I'll show you some popular items. How about this turquoise dress or a black dress?"

[2297] In this way, users can enjoy natural and personalized interactions with AI Dollar and efficiently search for suitable products. The following are examples of prompt sentences:

[2298] User: I'm looking for a dress for tonight's party.

[2299] AI Dollar: A perfect dress for a party! Let me show you some popular items. How about this turquoise dress or a black dress?

[2300] In this way, the present invention can improve the quality of the user experience.

[2301] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2302] Step 1: User authentication

[2303] 1. Input: The user enters their user ID and password into the information terminal (smartphone or HMD).

[2304] 2. Processing: The terminal sends the entered information to the server.

[2305] 3. Data processing: The server checks the user ID and password in the database.

[2306] 4. Output: If authentication is successful, the server generates a session ID and sends it to the terminal.

[2307] Step 2: Conversation-initiating request

[2308] 1. Input: The user presses the interaction start button displayed on the terminal.

[2309] 2. Processing: The terminal sends a dialogue start request to the server.

[2310] 3. Data Calculation: The server initiates the interactive session and generates the initial message for the AI ​​dollar.

[2311] 4. Output: Sends the initial message to the terminal and is displayed to the user.

[2312] Step 3: User comment analysis

[2313] 1. Input: The user inputs text in response to a message from the AI ​​dollar and sends it.

[2314] 2. Processing: The device sends the user's text to the server.

[2315] 3. Data calculation: The server analyzes the user's speech using natural language processing tools (e.g., Google Cloud Natural Language API or spaCy).

[2316] 4. Output: The content, intent, and sentiment of the speech are analyzed and sent to a sentiment analyzer.

[2317] Step 4: Sentiment Analysis

[2318] 1. Input: Analysis results sent from natural language processing means.

[2319] 2. Processing: The server performs further sentiment analysis using sentiment analysis tools (e.g. IBM Watson Tone Analyzer).

[2320] 3. Data calculation: Determine the user's emotional state.

[2321] 4. Output: Send the sentiment analysis results to the generative modeling means.

[2322] Step 5: Response Generation

[2323] 1. Input: Sentiment analysis results and analysis results from natural language processing tools.

[2324] 2. Processing: The server generates an appropriate response using a generative model (e.g., OpenAI GPT-3 or GPT-4).

[2325] 3. Data calculation: Generate the optimal response in text format based on the analysis results.

[2326] 4. Output: Send the generated response to the terminal.

[2327] Step 6: Display the response

[2328] 1. Input: The generated response sent by the server.

[2329] 2. Processing: The terminal displays the generated response to the user.

[2330] 3. Output: User confirms AI Dollar's response.

[2331] Step 7: Product Recommendation

[2332] 1. Input: Sentiment analysis results and user comments.

[2333] 2. Processing: The server uses the product recommendation means to suggest suitable products.

[2334] 3. Data calculation: Generate a list of products based on sentiment analysis and speech content.

[2335] 4. Output: Display the product recommendations to the user.

[2336] Step 8: Special Event Notifications

[2337] 1. Input: Specific event or sale information in the system.

[2338] 2. Processing: The server generates messages for limited events or special themes.

[2339] 3. Data Calculation: Generate special messages based on event information.

[2340] 4. Output: Notify the user with a special message.

[2341] Step 9: Save conversation logs

[2342] 1. Input: User utterances, AI dollar responses, and sentiment data.

[2343] 2. Processing: The server stores the conversation as a log.

[2344] 3. Data calculation: Generates log entries and stores them in a database.

[2345] 4. Output: The saved logs are stored as data for future analysis.

[2346] 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.

[2347] 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.

[2348] 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.

[2349] 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.

[2350] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2351] 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.

[2352] 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).

[2353] 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.

[2354] 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."

[2355] 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.

[2356] 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).

[2357] 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.

[2358] 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 ...

Claims

1. User authentication means; an information terminal for transmitting user input; natural language processing means for analyzing user utterances; a generative model means for generating a response based on the analyzed user utterance; an information terminal that provides the generated response to the user; A system including:

2. 2. The system according to claim 1, further comprising means for providing interactive content in response to limited events or special themes.

3. 2. The system according to claim 1, further comprising means for saving the content of the dialogue as a log.

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