System

Abstract

A system is provided.SOLUTION: A system comprising: means for obtaining input from a user; means for analyzing the obtained user input and extracting intent and entities; means for generating an appropriate response based on the extracted intent and entities; means for obtaining relevant information from a database and enhancing the response content; means for displaying the generated response to the user; and means for providing community functionality for sharing information with other users having the same interest.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] Traditional information gathering methods lacked the opportunity for users to have in-depth discussions about their favorite idols or to deepen their personal feelings and understanding. Furthermore, there was a lack of platforms where users could easily interact with other users who shared the same favorite idols. This limited user satisfaction and understanding of their favorite idols. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides the following means: A system is constructed that includes a means for acquiring input from a user, a means for analyzing the acquired user input and extracting intent and entities, a means for generating an appropriate response based on the extracted intent and entities, a means for acquiring related information from a database to enhance the response content, a means for displaying the generated response to the user, and a means for providing a community function for sharing information with other users who share the same interests. This system allows users to discuss their "oshi" at any time and obtain new information and perspectives. It also allows users to easily interact with other users who share the same "oshi."

[0006] "User input" is text or voice data that a user inputs into a system.

[0007] "Parsing" is the process of extracting intent and entities from user input.

[0008] "Intent" is information extracted from user input that indicates what the user wants or is trying to communicate.

[0009] An "entity" is information that refers to a specific object or concept extracted from user input.

[0010] A "response" is the text that the system generates in response to user input.

[0011] The "database" is a system that stores and manages information about users' "favorites."

[0012] "Information acquisition" is the process of collecting information about "oshi" from databases and external APIs.

[0013] "Natural language processing technology" is a technology for analyzing user input and extracting intent and entities.

[0014] "Response generation" is the process of creating an appropriate response based on the analysis results.

[0015] "Community Features" are features that allow users to share information and interact with other users who share the same interests.

[0016] A "platform" is an environment that provides a place where users can talk about their favorites and share information through the system. [Brief explanation of the drawings]

[0017] [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

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] 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).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] The following describes an embodiment of the present invention. The present invention is an interactive system that allows users to have in-depth discussions about their favorites. This system analyzes user input, generates appropriate responses, and provides related information. It also has a community function that allows users to interact with other users who share the same favorites. Specific program processing of the system is explained below in natural language.

[0039] System Configuration

[0040] 1. Server Configuration

[0041] Database (DB): This is the core part of the system and stores a wealth of information about users' favorites.

[0042] Dialogue engine: Manages user interactions and uses natural language processing (NLP) techniques to analyze user input and extract intent and entities.

[0043] Information collection module: Obtains the latest information about "oshi" through external APIs, etc., and updates the database.

[0044] Community management module: Manages information to enable users to interact with each other and, if necessary, matches users with the same "oshi" (favorites).

[0045] 2. Terminal Configuration

[0046] User Interface (UI): The screen through which the user interacts with the system, supporting text and voice input.

[0047] Voice recognition and text input module: Serves as a means of user input and has functions such as converting voice input into text.

[0048] Interactive display module: displays the response received from the server to the user.

[0049] Program Processing

[0050] 1. User Input Processing

[0051] User: The user starts talking about their favorite idol in the UI. For example, they might say, "My favorite idol recently released a new album."

[0052] Terminal: Takes user input and sends the input data to the server.

[0053] 2. Input Analysis and Understanding

[0054] Server: Analyzes input data received from the device. The dialogue engine uses NLP technology to extract user intent (e.g., "I want to talk about the new album") and entities (e.g., "my favorite").

[0055] 3. Generating an appropriate response

[0056] Server: The dialogue engine generates an appropriate response based on the analysis, for example, "Tell me more about that album!"

[0057] 4. Providing information about your favorites

[0058] Server: Retrieves information about the new album from a database. Uses this information to enhance the original response, such as "Tell me more about that album! Your recent reviews were great."

[0059] 5. Viewing the Response

[0060] Terminal: Displays the generated response in the user's UI, where the user can see the response on the interactive screen.

[0061] 6. Community Features

[0062] Server: Registers users with the same "oshi" in a community and provides an environment where they can share information. For example, associates user IDs with topics (new albums) and registers them in the community database.

[0063] Specific examples

[0064] For example, if a user types "My favorite idol recently released a new album," the following happens:

[0065] 1. Get the user's input and send it to the server.

[0066] 2. The server parses the input and extracts intent and entities.

[0067] 3. The dialogue engine generates a response about "new album."

[0068] 4. Retrieve the relevant album information from the database and enrich the response.

[0069] 5. Display the generated response in the user's UI.

[0070] 6. The community feature allows you to share information with other users who are interested in the same album.

[0071] The system of this invention allows users to have in-depth discussions about their favorites and gain new perspectives through the latest information and interactions with other users. This system not only deepens users' understanding and empathy for their favorites, but also enables them to share a variety of information through the community.

[0072] The processing flow will be explained below.

[0073] Step 1:

[0074] The user talks about their favorite idol. For example, they input something like, "My favorite idol recently released a new album."

[0075] Step 2:

[0076] The terminal receives user input. In the case of voice input, the voice recognition module converts the voice into text and obtains the text data.

[0077] Step 3:

[0078] The terminal sends the acquired user input to the server. Specifically, it sends text data to the server via an HTTP request.

[0079] Step 4:

[0080] The server analyzes the input data received from the device, and the dialogue engine uses NLP technology to tokenize the input text and extract intent and entities.

[0081] Step 5:

[0082] The server's dialogue engine generates an appropriate response based on the analysis results. For example, if the extracted intent is about a "new album," it generates a response such as "Tell me more about that album!"

[0083] Step 6:

[0084] The server retrieves relevant information from the database. Based on the intent and entities retrieved by the dialogue engine, the database is queried for additional information about the "new album."

[0085] Step 7:

[0086] The server uses the information it obtains to enhance the response. For example, the response "Tell me more about that album!" can be enhanced to "Tell me more about that album! Your recent reviews have been great."

[0087] Step 8:

[0088] The server sends the final response to the terminal, and returns the data including the response to the terminal as an HTTP response.

[0089] Step 9:

[0090] The device displays the response received from the server in the user's UI. For example, the interactive display module might display a message on the screen saying, "Tell me more about that album! Your recent reviews have been great."

[0091] Step 10:

[0092] The server prepares to share information with other users who are interested in the same "oshi." Specifically, it associates the user ID with the topic (new album) and registers it in the community database.

[0093] Step 11:

[0094] The server matches users who share the same interests through the community function. For example, it creates a list of users who share an interest in the same "new album" and notifies each other of them.

[0095] Through these steps, the system of the present invention allows users to have in-depth discussions about their favorites and obtain new information. It also provides an environment for users to interact with other users who share an interest in the same favorites.

[0096] Example 1

[0097] 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."

[0098] In recent years, the spread of digital content over the Internet has increased opportunities for users to discuss their favorite things. However, systems that allow users to obtain information about their favorite things and share it with other users are still lacking. In particular, there is a need for technological solutions that can naturally analyze the content entered by users, generate appropriate responses, and provide related information to enable deeper communication. There is also a need for an environment where users with similar interests can easily share information.

[0099] 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.

[0100] In this invention, the server includes means for acquiring input from a user, means for analyzing the acquired user input and extracting intent and entities, means for generating an appropriate response based on the extracted intent and entities, means for acquiring related information from a database and enhancing the response content, means for displaying the generated response to the user, means for providing a community function for sharing information with other users who share the same interests, means for acquiring the latest information using an external interface and periodically updating the database, and means for the dialogue engine to utilize natural language processing technology. This allows users to have in-depth discussions about their "oshi," obtain the latest related information, and share information with other users who share the same interests.

[0101] A "user" is an entity that uses this system to input information about their "favorite" and interact with other users.

[0102] "Means for obtaining input" refers to a function for sending text and voice data entered by a user through the device's UI to a server.

[0103] "Means for extracting intent and entities" is a function that uses natural language processing technology to analyze and identify the purpose and subject of interest (intent and entity) of a topic from user input data.

[0104] The "means for generating a response" is the function that creates an appropriate reply based on the extracted intent and entities.

[0105] A "database" is an information storage device that stores information related to a user's "favorites."

[0106] The "means for enhancing response content" is a function that further enriches the generated response based on related information obtained from the database.

[0107] The "means for displaying a response" is a function for displaying the generated response on the user's terminal.

[0108] "Means for providing community functions" refers to functions that allow users who are interested in the same "favorite" to share information and interact with each other.

[0109] An "external interface" is a connection that allows a system to exchange data with external sources.

[0110] "Natural language processing technology" is a series of technologies that use computers to understand, analyze, and generate language used by humans.

[0111] This invention is an interactive system that allows users to discuss their favorites in depth. The system analyzes user input, generates appropriate responses, provides relevant information, and has a community function that allows users to interact with other users who share the same favorites.

[0112] System Configuration

[0113] 1. Server Configuration

[0114] Database (DB): This is the core part of the system and stores a wealth of information about users' favorites.

[0115] Dialogue engine: Manages user interactions and uses natural language processing (NLP) techniques to analyze user input and extract intent and entities.

[0116] Information collection module: Uses an external interface to obtain the latest information about "oshi" and update the database.

[0117] Community management module: Manages information to enable users to interact with each other and, if necessary, matches users with the same "oshi" (favorites).

[0118] 2. Terminal Configuration

[0119] User Interface (UI): The screen through which the user interacts with the system, supporting text and voice input.

[0120] Voice recognition and text input module: Serves as a means of user input and has functions such as converting voice input into text.

[0121] Interactive display module: displays the response received from the server to the user.

[0122] Specific processing of the program

[0123] 1. User Input Processing

[0124] User: The user starts talking about their favorite idol in the UI. For example, they might say, "My favorite idol recently released a new album."

[0125] Terminal: The terminal takes the user's input and sends the input data to the server.

[0126] 2. Input Analysis and Understanding

[0127] Server: Analyzes input data received from the device. The dialogue engine uses NLP technology to extract user intent (e.g., "I want to talk about the new album") and entities (e.g., "my favorite").

[0128] 3. Generating an appropriate response

[0129] Server: The dialogue engine generates an appropriate response based on the analysis, for example, "Tell me more about that album!"

[0130] 4. Providing information about your favorites

[0131] Server: Retrieves information about the new album from a database. Uses this information to enhance the original response, such as "Tell me more about that album! Your recent reviews were great."

[0132] 5. Viewing the Response

[0133] Terminal: Displays the generated response in the user's UI, where the user can see the response on the interactive screen.

[0134] 6. Community Features

[0135] Server: Registers users with the same "oshi" in a community and provides an environment where they can share information. For example, associates user IDs with topics (new albums) and registers them in the community database.

[0136] Prompt Sentence Examples

[0137] Examples of prompts to input to the generative AI model include:

[0138] Something like, "If a user says, 'My favorite idol recently released a new album,' please provide detailed instructions on how to use a dialogue engine to generate a response."

[0139] The system of this invention allows users to have in-depth discussions about their favorites and gain new perspectives through the latest information and interactions with other users. This system not only deepens users' understanding and empathy for their favorites, but also enables them to share a variety of information through the community.

[0140] The specific hardware and software used

[0141] Natural Language Processing (NLP) libraries: TensorFlow, PyTorch

[0142] Database management systems: MySQL, PostgreSQL

[0143] External Interface: RESTful API

[0144] User Interface (UI): HTML, CSS, JavaScript

[0145] Speech recognition module: Google Speech-to-Text API, Microsoft Azure Cognitive Services

[0146] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0147] Step 1:

[0148] User: The user enters text into the UI. For example, they might type, "My favorite idol recently released a new album." Specifically, the user enters text using the keyboard and then presses the "Send" button to send the text to the device.

[0149] Step 2:

[0150] Terminal: Acquires the input text data and sends it to the server. Specifically, the terminal sends the acquired text data to the server using an HTTP POST request. The input is the user's text data, and the output is an HTTP request sent to the server.

[0151] Step 3:

[0152] Server: Received user data is temporarily stored in memory, and the dialogue engine analyzes the data. Specifically, the server saves the received data in a memory buffer and passes it to the dialogue engine for processing. The input is the text data of the HTTP request, and the output is text data prepared for analysis.

[0153] Step 4:

[0154] Server: The dialogue engine uses natural language processing (NLP) techniques to analyze user input and extract intents and entities. Specifically, the dialogue engine performs tokenization, morphological analysis, and grammatical analysis to extract intents and entities in JSON format. The input is prepared text data, and the output is JSON data containing intents and entities.

[0155] Step 5:

[0156] Server: Generates a response based on the extracted intent and entities. The dialogue engine generates a basic response such as "Tell me more about that album!" based on the analysis results. Specifically, the response generation logic generates candidate responses using the analysis results as arguments. The input is JSON data containing the intent and entities, and the output is basic response text.

[0157] Step 6:

[0158] Server: Queries the database to retrieve relevant information. Specifically, the server executes an SQL query to retrieve data about the latest album of "oshi" from the database. The input is the response text and relevant query information, and the output is the additional information returned from the database.

[0159] Step 7:

[0160] Server: Enhances the response based on the information retrieved from the database. Generates a response such as "Tell me more about that album! Your recent reviews were great." Specifically, it inserts the retrieved information into a response template to construct the final response. The input is the basic response text and additional information from the database, and the output is the enhanced response text.

[0161] Step 8:

[0162] Server: Sends the generated response to the terminal. Specifically, the server returns the generated response to the terminal as an HTTP response. The input is the enhanced response text, and the output is the HTTP response sent to the terminal.

[0163] Step 9:

[0164] Terminal: The generated response is displayed in the user's UI. Specifically, the terminal displays the response text in a UI component. The input is the HTTP response from the server, and the output is the response text displayed in the UI.

[0165] Step 10:

[0166] Server: Registers users with the same "favorites" in a community and provides an environment where they can share information. Specifically, it associates user IDs with topics (new albums) and registers them in a community database, then searches for and matches users with common interests. The input is the user's interest information, and the output is the community registration information and matching results.

[0167] (Application example 1)

[0168] 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."

[0169] Traditional dialogue systems do not provide an interactive environment for users to discuss their interests and "oshi" in depth, and interactions with other users are limited. Furthermore, the lack of systems that utilize new devices such as smart glasses results in a suboptimal user experience. Therefore, there is a need to provide a new type of virtual space where users can discuss "oshi" and share their interests.

[0170] 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.

[0171] In this invention, the server includes means for acquiring input from a user, means for analyzing the acquired user input and extracting an intent and an entity, means for generating an appropriate response based on the extracted intent and entity, means for acquiring related information from a database and enhancing the response content, means for displaying the generated response to the user, means for providing a community function for sharing information with other users who share the same interest, and means for displaying the response to the user in a virtual space using smart glasses and enabling interaction with other users. This allows users to talk about their "favorites" through the smart glasses and interact with other users in the virtual space.

[0172] A "means for obtaining user input" is an interface or device that captures text or voice data entered by a user and transmits it to the system.

[0173] "Means for parsing captured user input and extracting intent and entities" means techniques or processes for analyzing user-entered text or voice data and extracting user intent and identifiable entities from that data.

[0174] "Means for generating an appropriate response based on the extracted intent and entity" refers to an algorithm or program for creating an optimal response based on the user's intent and entity information.

[0175] The "means for retrieving relevant information from a database and enhancing the response content" is a system for retrieving information related to the user's intention from a database and incorporating that information into the response to enrich the response content.

[0176] "Means for displaying the generated response to the user" refers to a display or interface that allows the user to see the response generated by the system.

[0177] "Means for providing a community function for sharing information with other users who share the same interests" refers to a system for building and operating an online community where users can empathize with other users and exchange information.

[0178] "Means for displaying responses to a user in a virtual space using smart glasses and enabling the user to interact with other users" refers to technology that utilizes smart glasses to display responses from an interactive system to a user and simultaneously enable the user to communicate with other users in a virtual space.

[0179] The present invention provides an interactive system that allows users to have in-depth discussions about their interests. The system uses smart glasses to provide users with interactive responses and has the ability to interact with other users who share the same interests in a virtual space. Specific embodiments of the system are described below.

[0180] System Configuration

[0181] 1. Server Configuration

[0182] Database (DB): This is the core part of the system and stores a wealth of information about users' "push."

[0183] Dialogue engine: Manages user interactions and uses natural language processing (NLP) techniques to analyze user input and extract intent and entities.

[0184] Information collection module: Obtains the latest information on "push" through external APIs, etc., and updates the database.

[0185] Community management module: Manages information to enable users to interact with each other and, if necessary, matches users with the same interests.

[0186] 2. Terminal Configuration

[0187] User Interface (UI): The screen through which the user interacts with the system, supporting text and voice input.

[0188] Voice recognition and text input module: Serves as a means of user input and has functions such as converting voice input into text.

[0189] Interactive display module: displays the response received from the server to the user.

[0190] Smart glasses: Devices that support viewing and interaction in virtual spaces.

[0191] Program processing explanation

[0192] The server first obtains input from the user. The user's input is captured through the smart glasses' voice recognition and text input module. The obtained user input is sent to the server and analyzed by the dialogue engine. The dialogue engine uses natural language processing technology to extract the user's intent and entities.

[0193] The server then generates an appropriate response based on the extracted intent and entities, leveraging a generative AI model to create the optimal message that addresses the user's interests, and enriching the response with relevant information from a database and adding the latest information using external APIs.

[0194] The generated responses are displayed to the user through the smart glasses from the server, allowing the user to obtain detailed information about their "push" and interact with other users with the same interests in a virtual space. The community management module matches users with the same "push" and provides a forum for information sharing.

[0195] Explanation using concrete examples

[0196] For example, if a user types, "My idol recently released a new album," the following process occurs: First, the user's voice input is converted to text through the smart glasses and sent to the server. The dialogue engine analyzes this input and extracts intent and entities. The server uses a generative AI model to generate a response such as, "Tell me more about that album!" and adds additional information, such as, "The recent reviews were also positive," based on the latest information retrieved from the database and external APIs. The generated response is then displayed on the smart glasses' display.

[0197] An example prompt based on a generative AI model is:

[0198] User: My favorite guy recently released a new album.

[0199] System: Tell us more about the album! It's received some great reviews recently.

[0200] This system allows users to have in-depth discussions about "pushing" and gain new perspectives through the latest information and interactions with other users.

[0201] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0202] Step 1:

[0203] The user inputs either by voice or text. The smart glasses' voice recognition and text input module converts the user's input into text data and sends it to the server. At this stage, the input is the user's speech, and the output is text data.

[0204] Step 2:

[0205] The server analyzes the text data received from the device using a dialogue engine. The dialogue engine uses natural language processing technology to extract the user's intent and entities from the text data. At this stage, the input is text data, and the output is the analyzed intent and entities.

[0206] Step 3:

[0207] The server generates an appropriate response based on the extracted intent and entities. Using a generative AI model, it creates a message that best suits the information the user is looking for and the flow of the conversation. The input at this stage is the intent and entities, and the output is the generated response.

[0208] Step 4:

[0209] The server retrieves relevant information from the database to enhance the generated response. In addition, it retrieves the latest information from an external API through an information collection module and adds it to the response. The input at this stage is the generated response and a database query, and the output is the enhanced response.

[0210] Step 5:

[0211] The server sends the enhanced response to the terminal. The interactive display module of the terminal receives the response and displays it on the display of the smart glasses. At this stage, the input is the enhanced response, and the output is the display on the display of the smart glasses.

[0212] Step 6:

[0213] The server's community management module identifies other users with similar interests and provides an environment for sharing information. Users can interact with each other in a virtual space and discuss common interests. The input at this stage is the user's interest information, and the output is interactions with other users who have been matched.

[0214] 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.

[0215] The following describes an embodiment of the present invention. The present invention is an interactive system that allows users to have in-depth discussions about their favorite characters. This system not only analyzes user input, generates appropriate responses, and provides relevant information, but also combines an emotion engine that recognizes the user's emotions and adjusts responses accordingly. Specific program processing of the system is described below in natural language.

[0216] System Configuration

[0217] 1. Server Configuration

[0218] Database (DB): Stores information about the user's "oshi" and the user's past emotional data.

[0219] Dialogue engine: Manages user interactions and uses natural language processing (NLP) techniques to analyze user input and extract intent and entities.

[0220] Emotion engine: Responsible for inferring emotions from user input and tailoring responses to match those emotions.

[0221] Information collection module: Obtains the latest information about "oshi" through external APIs, etc., and updates the database.

[0222] Community management module: Manages information to enable users to interact with each other and, if necessary, matches users with the same "oshi" (favorites).

[0223] 2. Terminal Configuration

[0224] User Interface (UI): The screen through which the user interacts with the system, supporting text and voice input.

[0225] Speech recognition and text input module: Takes user input and converts it to text in case of voice input.

[0226] Interactive display module: displays the response received from the server to the user.

[0227] Program Processing

[0228] 1. User Input Processing

[0229] User: The user starts talking about their favorite idol in the UI. For example, they might say, "My favorite idol recently released a new album."

[0230] Terminal: Takes user input and sends that data to the server.

[0231] 2. Input Analysis and Understanding

[0232] Server: Analyzes input data received from the device. The dialogue engine uses NLP technology to extract user intent (e.g., "I want to talk about the new album") and entities (e.g., "my favorite").

[0233] 3. Emotional Recognition

[0234] Server: The emotion engine recognizes emotions from user input, for example identifying emotions such as "happy," "excited," and "sad."

[0235] 4. Generating the Response

[0236] Server: The dialogue engine generates an appropriate response based on the analysis and emotion recognition results. For example, if the user's emotion is "excited," the response generated is "That's great! Tell me more about that album!"

[0237] 5. Providing information about your favorites

[0238] Server: Retrieves information about the new album from a database. Uses this information to enhance the original response, for example, "Tell me more about that album! Your recent reviews were great."

[0239] 6. Regulating responses based on emotions

[0240] Server: After receiving additional information, the emotion engine further tailors the response based on the user's emotion. For example, if the user expresses "sadness," it generates a response such as "There are many moving songs on that album."

[0241] 7. Displaying the Response

[0242] Device: The generated response is displayed in the user's UI. For example, the interactive display module might display a message on the screen saying, "Tell me more about that album! Your recent reviews were great."

[0243] 8. Recording Emotional Data

[0244] Server: The emotion engine records the user's emotional data and uses it to improve the user experience during ongoing interactions.

[0245] 9. Community Features

[0246] Server: Registers users with the same "oshi" in a community and provides an environment where they can share information. For example, associates user IDs with topics (new albums) and registers them in the community database.

[0247] Specific examples

[0248] For example, if a user types "My favorite idol recently released a new album," the following happens:

[0249] 1. Get the user's input and send it to the server.

[0250] 2. The server parses the input and extracts intent and entities.

[0251] 3. The server recognizes the emotion "excited" from the input.

[0252] 4. The dialogue engine generates a response based on the analysis and emotion recognition results.

[0253] 5. Retrieve information about new albums from the database to enhance the response.

[0254] 6. The emotion engine tailors the response to "That's great! Tell me more about that album!"

[0255] 7. Display the response in the user's UI.

[0256] 8. The emotion engine records the user's emotional data and uses it for the next conversation.

[0257] 9. The server updates the community database and matches users with similar interests.

[0258] In this way, the system of the present invention analyzes user input, recognizes emotions, generates responses, and provides relevant information. It also continuously records user emotional data to enhance the interaction experience. It also provides a community function, encouraging interaction with other users who share the same "oshi" (favorite). Through this system, users can have in-depth discussions about their "oshi" and gain new information and perspectives.

[0259] The processing flow will be explained below.

[0260] Step 1:

[0261] The user talks about their favorite idol. For example, they input something like, "My favorite idol recently released a new album."

[0262] Step 2:

[0263] The terminal receives user input. In the case of voice input, the voice recognition module converts the voice into text and obtains the text data.

[0264] Step 3:

[0265] The terminal sends the acquired user input to the server. Specifically, it sends text data to the server via an HTTP request.

[0266] Step 4:

[0267] The server analyzes the input data received from the device, and the dialogue engine uses NLP technology to tokenize the input text and extract intent and entities.

[0268] Step 5:

[0269] The server's dialogue engine generates an appropriate response based on the analysis results. For example, if the extracted intent is about a "new album," it generates a response such as "Tell me more about that album!"

[0270] Step 6:

[0271] The server uses an emotion engine to recognize emotions from user input, such as "excitement," "happiness," and "sadness."

[0272] Step 7:

[0273] The server adjusts the response based on the emotion recognition result. For example, if it recognizes "excited," it adjusts the normal response to "That's great! Tell me more about that album!"

[0274] Step 8:

[0275] The server retrieves relevant information from the database. Based on the intent and entities retrieved by the dialogue engine, it retrieves information about "new album" from the database.

[0276] Step 9:

[0277] The server uses the information it obtains to enhance the response, for example, "Tell me more about that album! Your recent reviews have been great."

[0278] Step 10:

[0279] The device displays the response received from the server in the user's UI. For example, the interactive display module might display a message on the screen saying, "Tell me more about that album! Your recent reviews have been great."

[0280] Step 11:

[0281] The server uses an emotion engine to record the user's emotional data, which is used to improve the user experience in future interactions.

[0282] Step 12:

[0283] The server provides a community function, allowing users with the same "favorites" or interests to register in a community and share information.

[0284] Step 13:

[0285] The server matches users within the community and allows them to share information with others who share the same interests, such as their opinions and thoughts on a new album.

[0286] Through these steps, the system of the present invention allows users to have in-depth discussions about their favorites and gain new information. It also recognizes users' emotions and generates responses based on them, providing a more personalized experience. It also provides an environment where users can interact with other users who share the same favorites.

[0287] Example 2

[0288] 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."

[0289] While conventional dialogue systems can analyze user input and generate appropriate responses, they lack the ability to generate responses that take into account the user's emotions and share information with other users who share the same interests. Therefore, there is a need to improve the user experience and provide more personalized responses and community functions.

[0290] 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.

[0291] In this invention, the server includes means for analyzing a user input and extracting an intention and an entity, means for recognizing an emotion from the user input, means for generating an appropriate response based on the extracted intention and entity and the recognized emotion, means for retrieving related information from a database and enhancing the response content, means for adjusting the response content based on the user's emotion, means for recording the user's emotion data, and means for providing a community function for sharing information with other users who share the same interest, thereby enabling the generation of a response tailored to the user's emotion and the sharing of information among users who share the same interest.

[0292] "Means of acquisition" refers to the ability to input user input into the system as voice or text data.

[0293] "Means of analyzing and extracting intent and entities" refers to the function of using natural language processing technology to analyze the meaning of user input data and identify specific actions or targets.

[0294] "Means for recognizing emotions" refers to the function of determining and identifying the user's emotional state from input data.

[0295] "Means for generating an appropriate response" refers to the function of generating a reply to the user based on the analyzed intent and recognized emotion.

[0296] "Means of obtaining relevant information and enhancing response content" refers to the function of obtaining relevant data from databases within the system or external interfaces and enriching the information provided to users.

[0297] "Means for adjusting response content" refers to the ability to modify and optimize the generated response based on the perceived user sentiment.

[0298] "Means for displaying to the user" refers to the ability to visually or audibly present the generated response to the user.

[0299] "Means for recording emotional data" refers to a feature that continuously collects and stores data about a user's emotional state.

[0300] "Means for providing community functions" refers to functions that provide an environment where users with similar interests can share information and communicate with each other.

[0301] This invention provides an interactive system that allows users to discuss their favorites. The system not only analyzes user input to generate appropriate responses and provide relevant information, but also recognizes user emotions and adjusts responses accordingly.

[0302] System configuration overview

[0303] Server Configuration

[0304] 1. Database: Stores information about users' favorites and their past emotional data. For example, a database management system such as MySQL or MongoDB is used.

[0305] 2. Dialogue Engine: Manages user interactions and analyzes user input using Natural Language Processing (NLP) techniques, such as spaCy or Google Cloud Natural Language API, to extract intent and entities.

[0306] 3. Emotion engine: Infers emotions from user input and tailors responses to match those emotions. This leverages emotion recognition tools such as the BERT model and Amazon Comprehend.

[0307] 4. Information collection module: Obtains the latest information about "oshi" through external APIs and updates the database. For example, it uses Twitter API or News API.

[0308] 5. Community management module: Manages information so that users can interact with each other and, if necessary, matches users with the same "oshi" (favorites).

[0309] Device Configuration

[0310] 1. User Interface (UI): Provides a screen for users to interact with the system and supports text and voice input. Examples include web browsers and mobile apps.

[0311] 2. Speech recognition and text input module: Takes user input and converts it to text in the case of voice input. This may use a speech recognition service such as the Google Speech-to-Text API.

[0312] 3. Interaction display module: displays the response received from the server to the user, for example, as a text message in a chat window.

[0313] Program processing overview

[0314] The specific processing of this system will be explained below.

[0315] Processing User Input

[0316] User: The user starts talking about their favorite idol in the UI. For example, they might say, "My favorite idol recently released a new album."

[0317] Terminal: The terminal takes the user's input and sends the data to the server, converting it to text using voice recognition technology in the case of voice input.

[0318] Parsing and understanding input

[0319] Server: Analyzes input data received from the device. The dialogue engine uses NLP technology to extract the user's intent and entities.

[0320] Emotion recognition

[0321] Server: The emotion engine recognizes emotions from user input, for example identifying emotions such as "happy," "excited," and "sad."

[0322] Response generation and adjustment

[0323] Server: The dialogue engine generates an appropriate response based on the analysis and emotion recognition results. It may use a generative AI model to form the response. For example, it generates a response like, "That's great! Tell me more about that album!"

[0324] Server: Retrieve information about the new album from the database and complete the response, for example, including additional information like "Tell me more about that album! Your recent reviews were great."

[0325] Viewing the response

[0326] Terminal: The generated response is displayed in the user's UI. For example, the interactive display module might display a message on the screen saying, "Tell me more about that album! Your recent reviews were great."

[0327] Emotional data recording and community features

[0328] Server: The emotion engine records the user's emotional data and uses it to improve the user experience in future interactions. In addition, the server registers users with the same "oshi" as its users in a community, providing an environment where they can share information.

[0329] Specific examples

[0330] For example, if a user types "My favorite idol recently released a new album," the following happens:

[0331] 1. Get the user's input and send it to the server.

[0332] 2. The server parses the input and extracts intent and entities.

[0333] 3. The server recognizes the emotion "excited" from the input.

[0334] 4. The dialogue engine generates the response, "That's great! Tell me more about that album!"

[0335] 5. Retrieve information about the new album from the database and complete the response with, "The recent reviews were great."

[0336] 6. Display the generated response in the user's UI.

[0337] 7. Provide a community function to record emotional data and share information with other users who share the same interests.

[0338] Prompt Sentence Examples

[0339] Here are some example prompts to input to the generative AI model:

[0340] User: My favorite artist recently released a new album.

[0341] Server: That's great! Tell us more about the album! It's had some great reviews recently.

[0342] Through this system, users can have in-depth discussions about their favorites and gain new information and perspectives.

[0343] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0344] The flow of this system's program processing

[0345] Step 1:

[0346] Users provide topics about their favorites.

[0347] Input: The user says to the UI, "My favorite idol recently released a new album."

[0348] Specific action: The user speaks into a microphone or types into a text field.

[0349] Step 2:

[0350] The terminal obtains the user's input.

[0351] Input: User voice or text data.

[0352] What it does: The device converts voice input to text using the Google Speech-to-Text API. For text input, it retrieves the text directly from the UI.

[0353] Output: The converted or retrieved text data.

[0354] Step 3:

[0355] The terminal sends the input data to the server.

[0356] Input: The converted or retrieved text data.

[0357] Specific operation: The terminal sends data to the server as an HTTP request.

[0358] Output: The text data sent to the server.

[0359] Step 4:

[0360] The server parses the input data and extracts intent and entities.

[0361] Input: Text data received from the terminal.

[0362] What it does: The server uses a natural language processing engine (e.g., spaCy or Google Cloud Natural Language API) to parse the text and extract intent and entities.

[0363] Output: Extracted intent and entity data.

[0364] Step 5:

[0365] The server recognizes the user's emotions.

[0366] Input: Extracted intent and entity data.

[0367] Specific operation: The server analyzes the user's emotions using emotion recognition tools such as the BERT model and Amazon Comprehend.

[0368] Output: Recognized emotion data.

[0369] Step 6:

[0370] The server generates an appropriate response.

[0371] Input: Extracted intent and entity data, and recognized emotion data.

[0372] What it does: The dialogue engine uses a generative AI model (e.g., OpenAI GPT-3) to generate a response based on user input and sentiment. The prompt is "User: My favorite artist recently released a new album. Server: That's great! Tell me more about it!"

[0373] Output: The generated response text.

[0374] Step 7:

[0375] The server retrieves relevant information from a database to complete the response.

[0376] Input: The generated response text.

[0377] What happens next: The server performs a database query to retrieve additional information about the new album.

[0378] Output: The completed response text.

[0379] Step 8:

[0380] The server adjusts the response based on the emotion.

[0381] Input: The completed response text.

[0382] What it does: The emotion engine fine-tunes the final response based on the user's emotional state. For example, if the user expresses "sadness," it adjusts the response to "There are many touching songs on that album."

[0383] Output: The final response text.

[0384] Step 9:

[0385] The terminal displays the final response to the user.

[0386] Input: The final response text.

[0387] Specific operation: The dialogue display module displays the response text in a chat window on the UI.

[0388] Output: A text message that the user can see or hear.

[0389] Step 10:

[0390] The server records the emotion data.

[0391] Input: Recognized emotion data.

[0392] Specific operation: The emotion engine stores emotion data in a database in an appropriate format.

[0393] Output: Recorded emotion data.

[0394] Step 11:

[0395] The server updates the community database.

[0396] Input: User intent and perceived emotion, along with associated album information.

[0397] Specific operation: The server associates the user ID with topic information and inserts it into the community database, which supports matching with other users who share the same interests.

[0398] Output: Updated community database.

[0399] summary

[0400] Through these steps, the system supports users in conversations about their favorites, provides personalized responses that take their emotions into account, provides relevant information, and uses community features to encourage interaction with other users who share the same interests.

[0401] (Application example 2)

[0402] 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."

[0403] Current content distribution services lack interactive systems that allow users to have in-depth conversations about specific artists or creators and receive responses that reflect their own emotions. Furthermore, systems that provide users with real-time access to the latest content they desire and enable users with similar interests to effectively share information with each other are lacking. Therefore, new technological approaches are needed to increase user satisfaction and improve engagement.

[0404] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for recognizing emotions from user input and adjusting responses to match the user's emotions, means for providing the latest content information in real time, and means for providing a community function for sharing information with other users who share the same interests. This enables users to receive interactive responses tailored to their emotions, obtain new content information in real time, and easily share information with other users who share the same interests.

[0405] A "means for obtaining input from a user" is anything that allows a user to input information into a system, including text input and voice input.

[0406] "Means for analyzing captured user input and extracting intent and entities" refers to the process of analyzing input information from a user and identifying its intent (purpose) and entities (relevant key elements).

[0407] "Means for generating an appropriate response based on the extracted intent and entities" is a function that generates appropriate responses or information for the user according to the intent and entities obtained through analysis.

[0408] "Means for retrieving relevant information from a database and enhancing the response content" refers to the process of retrieving necessary information from a database and enhancing the response content to form the most appropriate answer to a user's question or request.

[0409] "Means for displaying the generated response to the user" means a method for providing the system-generated response to the user visually or audibly.

[0410] "Means for providing a community function for sharing information with other users who share the same interests" refers to a function that provides a forum for users who share the same interests to share information and interact with each other.

[0411] "Means for recognizing emotions from user input and adjusting responses to match the user's emotions" refers to technology that analyzes emotions from user input and flexibly changes the response content according to those emotions.

[0412] "Means for providing the latest content information in real time" refers to a function that obtains the latest content information from the Internet and other data sources and provides it to users in a timely manner.

[0413] The present invention is an interactive system that recognizes a user's emotions and generates and provides appropriate responses to the user. This system allows users to have in-depth discussions about specific artists or creators and receive responses that are in tune with their emotions.

[0414] System Configuration

[0415] Server Configuration

[0416] 1. Database (DB): Stores information about the user's "oshi" and past emotional data, allowing responses to be enhanced based on previously stored information.

[0417] 2. Dialogue engine: Manages interactions with users and uses natural language processing (NLP) techniques to analyze user input and extract intent and entities.

[0418] 3. Emotion engine: Responsible for inferring emotions from user input and tailoring responses to match those emotions.

[0419] 4. Information collection module: This module obtains the latest information about the "oshi" through external APIs, etc., and updates the database.

[0420] 5. Community management module: Manages information to enable users to interact with each other and, if necessary, matches users with the same "oshi" (favorites).

[0421] Device Configuration

[0422] 1. User Interface (UI): The screen through which the user interacts with the system, supporting text and voice input.

[0423] 2. Speech recognition and text input module: Takes user input and converts it to text in case of voice input.

[0424] 3. Interactive display module: displays the response received from the server to the user.

[0425] Detailed explanation of the process

[0426] 1. Getting user input:

[0427] The user begins speaking to the system through their device, for example, by entering text or voice, "My favorite idol recently released a new album."

[0428] 2. Input analysis and intent extraction:

[0429] The server's dialogue engine uses NLP technology to analyze user input received from the device and extract intent and entities.

[0430] 3. Emotion Recognition:

[0431] The emotion engine recognizes emotions from user input, for example identifying emotions such as "excited," "happy," or "sad."

[0432] 4. Generate response:

[0433] The server's dialogue engine generates an appropriate response based on the analysis and emotion recognition results. For example, if the user is excited, it generates the response "That's great! Tell me more about that album!"

[0434] 5. Additional Information:

[0435] The database retrieves the latest information about the target "oshi" and enriches the response, for example, "Tell me more about that album! The recent reviews were great."

[0436] 6. View the response:

[0437] The generated response is displayed to the user through an interactive display module, where the user can view the response on the screen.

[0438] 7. Emotional Data Recording:

[0439] The emotion engine records user emotional data and uses it to improve the user experience during ongoing interactions.

[0440] 8. Providing Community Features:

[0441] The server updates the community database and matches users with other users who share the same interests, allowing them to share new information and perspectives.

[0442] Examples and prompts

[0443] For example, if a user types, "My favorite idol recently released a new album," the system will respond as follows:

[0444] "That's great! Tell me more about that album!" (if the user is excited)

[0445] "Tell me more about that album! I've seen some great reviews recently." (If you've added the latest information)

[0446] This allows users to receive responses that are in tune with their emotions, obtain new content information in real time, and easily share information with other users who share the same interests.

[0447] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0448] Step 1: Getting User Input

[0449] The user inputs text or voice through the device's UI. For example, the user might input, "My favorite artist recently released a new album." The device receives this input and converts it into data to send to the server. In the case of voice input, the voice is converted into text by the voice recognition and text input module. The input data is in the form of text data.

[0450] Step 2: Parse input and extract intent

[0451] The server receives user input sent from the device, and the dialogue engine uses NLP technology to analyze the user input and extract intent (questions or desired information) and entities (such as specific artist or content names).

[0452] Type: "My idol recently released a new album."

[0453] Output: Intent = "I want to talk about the album", Entity = "Oshi"

[0454] Step 3: Recognize emotions

[0455] The emotion engine on the server recognizes emotions from the analyzed user input and identifies emotions such as "excitement," "happiness," and "sadness" based on the analysis results.

[0456] Type: "My idol recently released a new album."

[0457] Output: emotion = "excited"

[0458] Step 4: Generate a response

[0459] The server's dialogue engine generates an appropriate response based on the analysis and emotion recognition results. For example, if the user's emotion is "excited," it generates the response "That's great! Tell me more about that album!"

[0460] Input: Intent = "I want to talk about the album", Entity = "oshi", Emotion = "excited"

[0461] output:initial response="That's great! Tell me more about that album!"

[0462] Step 5: Provide additional information

[0463] The server retrieves the latest information about the target "oshi" from a database to enhance the response. For example, it retrieves the latest album information using an external API and generates a response such as "Tell me more about that album! Your recent reviews have been great."

[0464] Input:initial response="That's great! Tell me more about that album!"

[0465] Output: Enhanced Response = "That's great! Tell me more about that album! I saw some great reviews recently."

[0466] Step 6: View the response

[0467] The server generates a response and sends it to the terminal, where an interactive display module displays the response to the user, who can view the response on their screen.

[0468] Input:Enhanced response="That's great! Tell me more about that album! I saw some great reviews recently."

[0469] Output: The message displayed to the user

[0470] Step 7: Recording Emotional Data

[0471] The emotion engine on the server records the user's emotion data and uses it to improve the user experience during ongoing interactions. This recorded data is used in future interactions.

[0472] Input: emotion = "excited"

[0473] Output: Recorded emotion data

[0474] Step 8: Providing community features

[0475] The server updates the community database and matches users with the same interests. This feature allows users to share information with other users who are interested in the same "oshi."

[0476] Input: User ID, Interest = "Favorite"

[0477] Output: Community database updates, matching user information

[0478] Through the above processing steps, users can receive interactive responses that are in tune with their emotions, obtain the latest content information in real time, and easily share information with other users who share the same interests.

[0479] 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.

[0480] 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.

[0481] 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.

[0482] [Second embodiment]

[0483] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0484] 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.

[0485] 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).

[0486] 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.

[0487] 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.

[0488] 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).

[0489] 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.

[0490] 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.

[0491] 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.

[0492] 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.

[0493] In the smart glasses 214, 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.

[0494] 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."

[0495] The following describes an embodiment of the present invention. The present invention is an interactive system that allows users to have in-depth discussions about their favorites. This system analyzes user input, generates appropriate responses, and provides related information. It also has a community function that allows users to interact with other users who share the same favorites. Specific program processing of the system is explained below in natural language.

[0496] System Configuration

[0497] 1. Server Configuration

[0498] Database (DB): This is the core part of the system and stores a wealth of information about users' favorites.

[0499] Dialogue engine: Manages user interactions and uses natural language processing (NLP) techniques to analyze user input and extract intent and entities.

[0500] Information collection module: Obtains the latest information about "oshi" through external APIs, etc., and updates the database.

[0501] Community management module: Manages information to enable users to interact with each other and, if necessary, matches users with the same "oshi" (favorites).

[0502] 2. Terminal Configuration

[0503] User Interface (UI): The screen through which the user interacts with the system, supporting text and voice input.

[0504] Voice recognition and text input module: Serves as a means of user input and has functions such as converting voice input into text.

[0505] Interactive display module: displays the response received from the server to the user.

[0506] Program Processing

[0507] 1. User Input Processing

[0508] User: The user starts talking about their favorite idol in the UI. For example, they might say, "My favorite idol recently released a new album."

[0509] Terminal: Takes user input and sends the input data to the server.

[0510] 2. Input Analysis and Understanding

[0511] Server: Analyzes input data received from the device. The dialogue engine uses NLP technology to extract user intent (e.g., "I want to talk about the new album") and entities (e.g., "my favorite").

[0512] 3. Generating an appropriate response

[0513] Server: The dialogue engine generates an appropriate response based on the analysis, for example, "Tell me more about that album!"

[0514] 4. Providing information about your favorites

[0515] Server: Retrieves information about the new album from a database. Uses this information to enhance the original response, such as "Tell me more about that album! Your recent reviews were great."

[0516] 5. Viewing the Response

[0517] Terminal: Displays the generated response in the user's UI, where the user can see the response on the interactive screen.

[0518] 6. Community Features

[0519] Server: Registers users with the same "oshi" in a community and provides an environment where they can share information. For example, associates user IDs with topics (new albums) and registers them in the community database.

[0520] Specific examples

[0521] For example, if a user types "My favorite idol recently released a new album," the following happens:

[0522] 1. Get the user's input and send it to the server.

[0523] 2. The server parses the input and extracts intent and entities.

[0524] 3. The dialogue engine generates a response about "new album."

[0525] 4. Retrieve the relevant album information from the database and enrich the response.

[0526] 5. Display the generated response in the user's UI.

[0527] 6. The community feature allows you to share information with other users who are interested in the same album.

[0528] The system of this invention allows users to have in-depth discussions about their favorites and gain new perspectives through the latest information and interactions with other users. This system not only deepens users' understanding and empathy for their favorites, but also enables them to share a variety of information through the community.

[0529] The processing flow will be explained below.

[0530] Step 1:

[0531] The user talks about their favorite idol. For example, they input something like, "My favorite idol recently released a new album."

[0532] Step 2:

[0533] The terminal receives user input. In the case of voice input, the voice recognition module converts the voice into text and obtains the text data.

[0534] Step 3:

[0535] The terminal sends the acquired user input to the server. Specifically, it sends text data to the server via an HTTP request.

[0536] Step 4:

[0537] The server analyzes the input data received from the device, and the dialogue engine uses NLP technology to tokenize the input text and extract intent and entities.

[0538] Step 5:

[0539] The server's dialogue engine generates an appropriate response based on the analysis results. For example, if the extracted intent is about a "new album," it generates a response such as "Tell me more about that album!"

[0540] Step 6:

[0541] The server retrieves relevant information from the database. Based on the intent and entities retrieved by the dialogue engine, the database is queried for additional information about the "new album."

[0542] Step 7:

[0543] The server uses the information it obtains to enhance the response. For example, the response "Tell me more about that album!" can be enhanced to "Tell me more about that album! Your recent reviews have been great."

[0544] Step 8:

[0545] The server sends the final response to the terminal, and returns the data including the response to the terminal as an HTTP response.

[0546] Step 9:

[0547] The device displays the response received from the server in the user's UI. For example, the interactive display module might display a message on the screen saying, "Tell me more about that album! Your recent reviews have been great."

[0548] Step 10:

[0549] The server prepares to share information with other users who are interested in the same "oshi." Specifically, it associates the user ID with the topic (new album) and registers it in the community database.

[0550] Step 11:

[0551] The server matches users who share the same interests through the community function. For example, it creates a list of users who share an interest in the same "new album" and notifies each other of them.

[0552] Through these steps, the system of the present invention allows users to have in-depth discussions about their favorites and obtain new information. It also provides an environment for users to interact with other users who share an interest in the same favorites.

[0553] Example 1

[0554] 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."

[0555] In recent years, the spread of digital content over the Internet has increased opportunities for users to discuss their favorite things. However, systems that allow users to obtain information about their favorite things and share it with other users are still lacking. In particular, there is a need for technological solutions that can naturally analyze the content entered by users, generate appropriate responses, and provide related information to enable deeper communication. There is also a need for an environment where users with similar interests can easily share information.

[0556] 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.

[0557] In this invention, the server includes means for acquiring input from a user, means for analyzing the acquired user input and extracting intent and entities, means for generating an appropriate response based on the extracted intent and entities, means for acquiring related information from a database and enhancing the response content, means for displaying the generated response to the user, means for providing a community function for sharing information with other users who share the same interests, means for acquiring the latest information using an external interface and periodically updating the database, and means for the dialogue engine to utilize natural language processing technology. This allows users to have in-depth discussions about their "oshi," obtain the latest related information, and share information with other users who share the same interests.

[0558] A "user" is an entity that uses this system to input information about their "favorite" and interact with other users.

[0559] "Means for obtaining input" refers to a function for sending text and voice data entered by a user through the device's UI to a server.

[0560] "Means for extracting intent and entities" is a function that uses natural language processing technology to analyze and identify the purpose and subject of interest (intent and entity) of a topic from user input data.

[0561] The "means for generating a response" is the function that creates an appropriate reply based on the extracted intent and entities.

[0562] A "database" is an information storage device that stores information related to a user's "favorites."

[0563] The "means for enhancing response content" is a function that further enriches the generated response based on related information obtained from the database.

[0564] The "means for displaying a response" is a function for displaying the generated response on the user's terminal.

[0565] "Means for providing community functions" refers to functions that allow users who are interested in the same "favorite" to share information and interact with each other.

[0566] An "external interface" is a connection that allows a system to exchange data with external sources.

[0567] "Natural language processing technology" is a series of technologies that use computers to understand, analyze, and generate language used by humans.

[0568] This invention is an interactive system that allows users to discuss their favorites in depth. The system analyzes user input, generates appropriate responses, provides relevant information, and has a community function that allows users to interact with other users who share the same favorites.

[0569] System Configuration

[0570] 1. Server Configuration

[0571] Database (DB): This is the core part of the system and stores a wealth of information about users' favorites.

[0572] Dialogue engine: Manages user interactions and uses natural language processing (NLP) techniques to analyze user input and extract intent and entities.

[0573] Information collection module: Uses an external interface to obtain the latest information about "oshi" and update the database.

[0574] Community management module: Manages information to enable users to interact with each other and, if necessary, matches users with the same "oshi" (favorites).

[0575] 2. Terminal Configuration

[0576] User Interface (UI): The screen through which the user interacts with the system, supporting text and voice input.

[0577] Voice recognition and text input module: Serves as a means of user input and has functions such as converting voice input into text.

[0578] Interactive display module: displays the response received from the server to the user.

[0579] Specific processing of the program

[0580] 1. User Input Processing

[0581] User: The user starts talking about their favorite idol in the UI. For example, they might say, "My favorite idol recently released a new album."

[0582] Terminal: The terminal takes the user's input and sends the input data to the server.

[0583] 2. Input Analysis and Understanding

[0584] Server: Analyzes input data received from the device. The dialogue engine uses NLP technology to extract user intent (e.g., "I want to talk about the new album") and entities (e.g., "my favorite").

[0585] 3. Generating an appropriate response

[0586] Server: The dialogue engine generates an appropriate response based on the analysis, for example, "Tell me more about that album!"

[0587] 4. Providing information about your favorites

[0588] Server: Retrieves information about the new album from a database. Uses this information to enhance the original response, such as "Tell me more about that album! Your recent reviews were great."

[0589] 5. Viewing the Response

[0590] Terminal: Displays the generated response in the user's UI, where the user can see the response on the interactive screen.

[0591] 6. Community Features

[0592] Server: Registers users with the same "oshi" in a community and provides an environment where they can share information. For example, associates user IDs with topics (new albums) and registers them in the community database.

[0593] Prompt Sentence Examples

[0594] Examples of prompts to input to the generative AI model include:

[0595] Something like, "If a user says, 'My favorite idol recently released a new album,' please provide detailed instructions on how to use a dialogue engine to generate a response."

[0596] The system of this invention allows users to have in-depth discussions about their favorites and gain new perspectives through the latest information and interactions with other users. This system not only deepens users' understanding and empathy for their favorites, but also enables them to share a variety of information through the community.

[0597] The specific hardware and software used

[0598] Natural Language Processing (NLP) libraries: TensorFlow, PyTorch

[0599] Database management systems: MySQL, PostgreSQL

[0600] External Interface: RESTful API

[0601] User Interface (UI): HTML, CSS, JavaScript

[0602] Speech recognition module: Google Speech-to-Text API, Microsoft Azure Cognitive Services

[0603] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0604] Step 1:

[0605] User: The user enters text into the UI. For example, they might type, "My favorite idol recently released a new album." Specifically, the user enters text using the keyboard and then presses the "Send" button to send the text to the device.

[0606] Step 2:

[0607] Terminal: Acquires the input text data and sends it to the server. Specifically, the terminal sends the acquired text data to the server using an HTTP POST request. The input is the user's text data, and the output is an HTTP request sent to the server.

[0608] Step 3:

[0609] Server: Received user data is temporarily stored in memory, and the dialogue engine analyzes the data. Specifically, the server saves the received data in a memory buffer and passes it to the dialogue engine for processing. The input is the text data of the HTTP request, and the output is text data prepared for analysis.

[0610] Step 4:

[0611] Server: The dialogue engine uses natural language processing (NLP) techniques to analyze user input and extract intents and entities. Specifically, the dialogue engine performs tokenization, morphological analysis, and grammatical analysis to extract intents and entities in JSON format. The input is prepared text data, and the output is JSON data containing intents and entities.

[0612] Step 5:

[0613] Server: Generates a response based on the extracted intent and entities. The dialogue engine generates a basic response such as "Tell me more about that album!" based on the analysis results. Specifically, the response generation logic generates candidate responses using the analysis results as arguments. The input is JSON data containing the intent and entities, and the output is basic response text.

[0614] Step 6:

[0615] Server: Queries the database to retrieve relevant information. Specifically, the server executes an SQL query to retrieve data about the latest album of "oshi" from the database. The input is the response text and relevant query information, and the output is the additional information returned from the database.

[0616] Step 7:

[0617] Server: Enhances the response based on the information retrieved from the database. Generates a response such as "Tell me more about that album! Your recent reviews were great." Specifically, it inserts the retrieved information into a response template to construct the final response. The input is the basic response text and additional information from the database, and the output is the enhanced response text.

[0618] Step 8:

[0619] Server: Sends the generated response to the terminal. Specifically, the server returns the generated response to the terminal as an HTTP response. The input is the enhanced response text, and the output is the HTTP response sent to the terminal.

[0620] Step 9:

[0621] Terminal: The generated response is displayed in the user's UI. Specifically, the terminal displays the response text in a UI component. The input is the HTTP response from the server, and the output is the response text displayed in the UI.

[0622] Step 10:

[0623] Server: Registers users with the same "favorites" in a community and provides an environment where they can share information. Specifically, it associates user IDs with topics (new albums) and registers them in a community database, then searches for and matches users with common interests. The input is the user's interest information, and the output is the community registration information and matching results.

[0624] (Application example 1)

[0625] 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."

[0626] Traditional dialogue systems do not provide an interactive environment for users to discuss their interests and "oshi" in depth, and interactions with other users are limited. Furthermore, the lack of systems that utilize new devices such as smart glasses results in a suboptimal user experience. Therefore, there is a need to provide a new type of virtual space where users can discuss "oshi" and share their interests.

[0627] 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.

[0628] In this invention, the server includes means for acquiring input from a user, means for analyzing the acquired user input and extracting an intent and an entity, means for generating an appropriate response based on the extracted intent and entity, means for acquiring related information from a database and enhancing the response content, means for displaying the generated response to the user, means for providing a community function for sharing information with other users who share the same interest, and means for displaying the response to the user in a virtual space using smart glasses and enabling interaction with other users. This allows users to talk about their "favorites" through the smart glasses and interact with other users in the virtual space.

[0629] A "means for obtaining user input" is an interface or device that captures text or voice data entered by a user and transmits it to the system.

[0630] "Means for parsing captured user input and extracting intent and entities" means techniques or processes for analyzing user-entered text or voice data and extracting user intent and identifiable entities from that data.

[0631] "Means for generating an appropriate response based on the extracted intent and entity" refers to an algorithm or program for creating an optimal response based on the user's intent and entity information.

[0632] The "means for retrieving relevant information from a database and enhancing the response content" is a system for retrieving information related to the user's intention from a database and incorporating that information into the response to enrich the response content.

[0633] "Means for displaying the generated response to the user" refers to a display or interface that allows the user to see the response generated by the system.

[0634] "Means for providing a community function for sharing information with other users who share the same interests" refers to a system for building and operating an online community where users can empathize with other users and exchange information.

[0635] "Means for displaying responses to a user in a virtual space using smart glasses and enabling the user to interact with other users" refers to technology that utilizes smart glasses to display responses from an interactive system to a user and simultaneously enable the user to communicate with other users in a virtual space.

[0636] The present invention provides an interactive system that allows users to have in-depth discussions about their interests. The system uses smart glasses to provide users with interactive responses and has the ability to interact with other users who share the same interests in a virtual space. Specific embodiments of the system are described below.

[0637] System Configuration

[0638] 1. Server Configuration

[0639] Database (DB): This is the core part of the system and stores a wealth of information about users' "push."

[0640] Dialogue engine: Manages user interactions and uses natural language processing (NLP) techniques to analyze user input and extract intent and entities.

[0641] Information collection module: Obtains the latest information on "push" through external APIs, etc., and updates the database.

[0642] Community management module: Manages information to enable users to interact with each other and, if necessary, matches users with the same interests.

[0643] 2. Terminal Configuration

[0644] User Interface (UI): The screen through which the user interacts with the system, supporting text and voice input.

[0645] Voice recognition and text input module: Serves as a means of user input and has functions such as converting voice input into text.

[0646] Interactive display module: displays the response received from the server to the user.

[0647] Smart glasses: Devices that support viewing and interaction in virtual spaces.

[0648] Program processing explanation

[0649] The server first obtains input from the user. The user's input is captured through the smart glasses' voice recognition and text input module. The obtained user input is sent to the server and analyzed by the dialogue engine. The dialogue engine uses natural language processing technology to extract the user's intent and entities.

[0650] The server then generates an appropriate response based on the extracted intent and entities, leveraging a generative AI model to create the optimal message that addresses the user's interests, and enriching the response with relevant information from a database and adding the latest information using external APIs.

[0651] The generated responses are displayed to the user through the smart glasses from the server, allowing the user to obtain detailed information about their "push" and interact with other users with the same interests in a virtual space. The community management module matches users with the same "push" and provides a forum for information sharing.

[0652] Explanation using concrete examples

[0653] For example, if a user types, "My idol recently released a new album," the following process occurs: First, the user's voice input is converted to text through the smart glasses and sent to the server. The dialogue engine analyzes this input and extracts intent and entities. The server uses a generative AI model to generate a response such as, "Tell me more about that album!" and adds additional information, such as, "The recent reviews were also positive," based on the latest information retrieved from the database and external APIs. The generated response is then displayed on the smart glasses' display.

[0654] An example prompt based on a generative AI model is:

[0655] User: My favorite guy recently released a new album.

[0656] System: Tell us more about the album! It's received some great reviews recently.

[0657] This system allows users to have in-depth discussions about "pushing" and gain new perspectives through the latest information and interactions with other users.

[0658] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0659] Step 1:

[0660] The user inputs either by voice or text. The smart glasses' voice recognition and text input module converts the user's input into text data and sends it to the server. At this stage, the input is the user's speech, and the output is text data.

[0661] Step 2:

[0662] The server analyzes the text data received from the device using a dialogue engine. The dialogue engine uses natural language processing technology to extract the user's intent and entities from the text data. At this stage, the input is text data, and the output is the analyzed intent and entities.

[0663] Step 3:

[0664] The server generates an appropriate response based on the extracted intent and entities. Using a generative AI model, it creates a message that best suits the information the user is looking for and the flow of the conversation. The input at this stage is the intent and entities, and the output is the generated response.

[0665] Step 4:

[0666] The server retrieves relevant information from the database to enhance the generated response. In addition, it retrieves the latest information from an external API through an information collection module and adds it to the response. The input at this stage is the generated response and a database query, and the output is the enhanced response.

[0667] Step 5:

[0668] The server sends the enhanced response to the terminal. The interactive display module of the terminal receives the response and displays it on the display of the smart glasses. At this stage, the input is the enhanced response, and the output is the display on the display of the smart glasses.

[0669] Step 6:

[0670] The server's community management module identifies other users with similar interests and provides an environment for sharing information. Users can interact with each other in a virtual space and discuss common interests. The input at this stage is the user's interest information, and the output is interactions with other users who have been matched.

[0671] 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.

[0672] The following describes an embodiment of the present invention. The present invention is an interactive system that allows users to have in-depth discussions about their favorite characters. This system not only analyzes user input, generates appropriate responses, and provides relevant information, but also combines an emotion engine that recognizes the user's emotions and adjusts responses accordingly. Specific program processing of the system is described below in natural language.

[0673] System Configuration

[0674] 1. Server Configuration

[0675] Database (DB): Stores information about the user's "oshi" and the user's past emotional data.

[0676] Dialogue engine: Manages user interactions and uses natural language processing (NLP) techniques to analyze user input and extract intent and entities.

[0677] Emotion engine: Responsible for inferring emotions from user input and tailoring responses to match those emotions.

[0678] Information collection module: Obtains the latest information about "oshi" through external APIs, etc., and updates the database.

[0679] Community management module: Manages information to enable users to interact with each other and, if necessary, matches users with the same "oshi" (favorites).

[0680] 2. Terminal Configuration

[0681] User Interface (UI): The screen through which the user interacts with the system, supporting text and voice input.

[0682] Speech recognition and text input module: Takes user input and converts it to text in case of voice input.

[0683] Interactive display module: displays the response received from the server to the user.

[0684] Program Processing

[0685] 1. User Input Processing

[0686] User: The user starts talking about their favorite idol in the UI. For example, they might say, "My favorite idol recently released a new album."

[0687] Terminal: Takes user input and sends that data to the server.

[0688] 2. Input Analysis and Understanding

[0689] Server: Analyzes input data received from the device. The dialogue engine uses NLP technology to extract user intent (e.g., "I want to talk about the new album") and entities (e.g., "my favorite").

[0690] 3. Emotional Recognition

[0691] Server: The emotion engine recognizes emotions from user input, for example identifying emotions such as "happy," "excited," and "sad."

[0692] 4. Generating the Response

[0693] Server: The dialogue engine generates an appropriate response based on the analysis and emotion recognition results. For example, if the user's emotion is "excited," the response generated is "That's great! Tell me more about that album!"

[0694] 5. Providing information about your favorites

[0695] Server: Retrieves information about the new album from a database. Uses this information to enhance the original response, for example, "Tell me more about that album! Your recent reviews were great."

[0696] 6. Regulating responses based on emotions

[0697] Server: After receiving additional information, the emotion engine further tailors the response based on the user's emotion. For example, if the user expresses "sadness," it generates a response such as "There are many moving songs on that album."

[0698] 7. Displaying the Response

[0699] Device: The generated response is displayed in the user's UI. For example, the interactive display module might display a message on the screen saying, "Tell me more about that album! Your recent reviews were great."

[0700] 8. Recording Emotional Data

[0701] Server: The emotion engine records the user's emotional data and uses it to improve the user experience during ongoing interactions.

[0702] 9. Community Features

[0703] Server: Registers users with the same "oshi" in a community and provides an environment where they can share information. For example, associates user IDs with topics (new albums) and registers them in the community database.

[0704] Specific examples

[0705] For example, if a user types "My favorite idol recently released a new album," the following happens:

[0706] 1. Get the user's input and send it to the server.

[0707] 2. The server parses the input and extracts intent and entities.

[0708] 3. The server recognizes the emotion "excited" from the input.

[0709] 4. The dialogue engine generates a response based on the analysis and emotion recognition results.

[0710] 5. Retrieve information about new albums from the database to enhance the response.

[0711] 6. The emotion engine tailors the response to "That's great! Tell me more about that album!"

[0712] 7. Display the response in the user's UI.

[0713] 8. The emotion engine records the user's emotional data and uses it for the next conversation.

[0714] 9. The server updates the community database and matches users with similar interests.

[0715] In this way, the system of the present invention analyzes user input, recognizes emotions, generates responses, and provides relevant information. It also continuously records user emotional data to enhance the interaction experience. It also provides a community function, encouraging interaction with other users who share the same "oshi" (favorite). Through this system, users can have in-depth discussions about their "oshi" and gain new information and perspectives.

[0716] The processing flow will be explained below.

[0717] Step 1:

[0718] The user talks about their favorite idol. For example, they input something like, "My favorite idol recently released a new album."

[0719] Step 2:

[0720] The terminal receives user input. In the case of voice input, the voice recognition module converts the voice into text and obtains the text data.

[0721] Step 3:

[0722] The terminal sends the acquired user input to the server. Specifically, it sends text data to the server via an HTTP request.

[0723] Step 4:

[0724] The server analyzes the input data received from the device, and the dialogue engine uses NLP technology to tokenize the input text and extract intent and entities.

[0725] Step 5:

[0726] The server's dialogue engine generates an appropriate response based on the analysis results. For example, if the extracted intent is about a "new album," it generates a response such as "Tell me more about that album!"

[0727] Step 6:

[0728] The server uses an emotion engine to recognize emotions from user input, such as "excitement," "happiness," and "sadness."

[0729] Step 7:

[0730] The server adjusts the response based on the emotion recognition result. For example, if it recognizes "excited," it adjusts the normal response to "That's great! Tell me more about that album!"

[0731] Step 8:

[0732] The server retrieves relevant information from the database. Based on the intent and entities retrieved by the dialogue engine, it retrieves information about "new album" from the database.

[0733] Step 9:

[0734] The server uses the information it obtains to enhance the response, for example, "Tell me more about that album! Your recent reviews have been great."

[0735] Step 10:

[0736] The device displays the response received from the server in the user's UI. For example, the interactive display module might display a message on the screen saying, "Tell me more about that album! Your recent reviews have been great."

[0737] Step 11:

[0738] The server uses an emotion engine to record the user's emotional data, which is used to improve the user experience in future interactions.

[0739] Step 12:

[0740] The server provides a community function, allowing users with the same "favorites" or interests to register in a community and share information.

[0741] Step 13:

[0742] The server matches users within the community and allows them to share information with others who share the same interests, such as their opinions and thoughts on a new album.

[0743] Through these steps, the system of the present invention allows users to have in-depth discussions about their favorites and gain new information. It also recognizes users' emotions and generates responses based on them, providing a more personalized experience. It also provides an environment where users can interact with other users who share the same favorites.

[0744] Example 2

[0745] 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."

[0746] While conventional dialogue systems can analyze user input and generate appropriate responses, they lack the ability to generate responses that take into account the user's emotions and share information with other users who share the same interests. Therefore, there is a need to improve the user experience and provide more personalized responses and community functions.

[0747] 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.

[0748] In this invention, the server includes means for analyzing a user input and extracting an intention and an entity, means for recognizing an emotion from the user input, means for generating an appropriate response based on the extracted intention and entity and the recognized emotion, means for retrieving related information from a database and enhancing the response content, means for adjusting the response content based on the user's emotion, means for recording the user's emotion data, and means for providing a community function for sharing information with other users who share the same interest, thereby enabling the generation of a response tailored to the user's emotion and the sharing of information among users who share the same interest.

[0749] "Means of acquisition" refers to the ability to input user input into the system as voice or text data.

[0750] "Means of analyzing and extracting intent and entities" refers to the function of using natural language processing technology to analyze the meaning of user input data and identify specific actions or targets.

[0751] "Means for recognizing emotions" refers to the function of determining and identifying the user's emotional state from input data.

[0752] "Means for generating an appropriate response" refers to the function of generating a reply to the user based on the analyzed intent and recognized emotion.

[0753] "Means of obtaining relevant information and enhancing response content" refers to the function of obtaining relevant data from databases within the system or external interfaces and enriching the information provided to users.

[0754] "Means for adjusting response content" refers to the ability to modify and optimize the generated response based on the perceived user sentiment.

[0755] "Means for displaying to the user" refers to the ability to visually or audibly present the generated response to the user.

[0756] "Means for recording emotional data" refers to a feature that continuously collects and stores data about a user's emotional state.

[0757] "Means for providing community functions" refers to functions that provide an environment where users with similar interests can share information and communicate with each other.

[0758] This invention provides an interactive system that allows users to discuss their favorites. The system not only analyzes user input to generate appropriate responses and provide relevant information, but also recognizes user emotions and adjusts responses accordingly.

[0759] System configuration overview

[0760] Server Configuration

[0761] 1. Database: Stores information about users' favorites and their past emotional data. For example, a database management system such as MySQL or MongoDB is used.

[0762] 2. Dialogue Engine: Manages user interactions and analyzes user input using Natural Language Processing (NLP) techniques, such as spaCy or Google Cloud Natural Language API, to extract intent and entities.

[0763] 3. Emotion engine: Infers emotions from user input and tailors responses to match those emotions. This leverages emotion recognition tools such as the BERT model and Amazon Comprehend.

[0764] 4. Information collection module: Obtains the latest information about "oshi" through external APIs and updates the database. For example, it uses Twitter API or News API.

[0765] 5. Community management module: Manages information so that users can interact with each other and, if necessary, matches users with the same "oshi" (favorites).

[0766] Device Configuration

[0767] 1. User Interface (UI): Provides a screen for users to interact with the system and supports text and voice input. Examples include web browsers and mobile apps.

[0768] 2. Speech recognition and text input module: Takes user input and converts it to text in the case of voice input. This may use a speech recognition service such as the Google Speech-to-Text API.

[0769] 3. Interaction display module: displays the response received from the server to the user, for example, as a text message in a chat window.

[0770] Program processing overview

[0771] The specific processing of this system will be explained below.

[0772] Processing User Input

[0773] User: The user starts talking about their favorite idol in the UI. For example, they might say, "My favorite idol recently released a new album."

[0774] Terminal: The terminal takes the user's input and sends the data to the server, converting it to text using voice recognition technology in the case of voice input.

[0775] Parsing and understanding input

[0776] Server: Analyzes input data received from the device. The dialogue engine uses NLP technology to extract the user's intent and entities.

[0777] Emotion recognition

[0778] Server: The emotion engine recognizes emotions from user input, for example identifying emotions such as "happy," "excited," and "sad."

[0779] Response generation and adjustment

[0780] Server: The dialogue engine generates an appropriate response based on the analysis and emotion recognition results. It may use a generative AI model to form the response. For example, it generates a response like, "That's great! Tell me more about that album!"

[0781] Server: Retrieve information about the new album from the database and complete the response, for example, including additional information like "Tell me more about that album! Your recent reviews were great."

[0782] Viewing the response

[0783] Terminal: The generated response is displayed in the user's UI. For example, the interactive display module might display a message on the screen saying, "Tell me more about that album! Your recent reviews were great."

[0784] Emotional data recording and community features

[0785] Server: The emotion engine records the user's emotional data and uses it to improve the user experience in future interactions. In addition, the server registers users with the same "oshi" as its users in a community, providing an environment where they can share information.

[0786] Specific examples

[0787] For example, if a user types "My favorite idol recently released a new album," the following happens:

[0788] 1. Get the user's input and send it to the server.

[0789] 2. The server parses the input and extracts intent and entities.

[0790] 3. The server recognizes the emotion "excited" from the input.

[0791] 4. The dialogue engine generates the response, "That's great! Tell me more about that album!"

[0792] 5. Retrieve information about the new album from the database and complete the response with, "The recent reviews were great."

[0793] 6. Display the generated response in the user's UI.

[0794] 7. Provide a community function to record emotional data and share information with other users who share the same interests.

[0795] Prompt Sentence Examples

[0796] Here are some example prompts to input to the generative AI model:

[0797] User: My favorite artist recently released a new album.

[0798] Server: That's great! Tell us more about the album! It's had some great reviews recently.

[0799] Through this system, users can have in-depth discussions about their favorites and gain new information and perspectives.

[0800] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0801] The flow of this system's program processing

[0802] Step 1:

[0803] Users provide topics about their favorites.

[0804] Input: The user says to the UI, "My favorite idol recently released a new album."

[0805] Specific action: The user speaks into a microphone or types into a text field.

[0806] Step 2:

[0807] The terminal obtains the user's input.

[0808] Input: User voice or text data.

[0809] What it does: The device converts voice input to text using the Google Speech-to-Text API. For text input, it retrieves the text directly from the UI.

[0810] Output: The converted or retrieved text data.

[0811] Step 3:

[0812] The terminal sends the input data to the server.

[0813] Input: The converted or retrieved text data.

[0814] Specific operation: The terminal sends data to the server as an HTTP request.

[0815] Output: The text data sent to the server.

[0816] Step 4:

[0817] The server parses the input data and extracts intent and entities.

[0818] Input: Text data received from the terminal.

[0819] What it does: The server uses a natural language processing engine (e.g., spaCy or Google Cloud Natural Language API) to parse the text and extract intent and entities.

[0820] Output: Extracted intent and entity data.

[0821] Step 5:

[0822] The server recognizes the user's emotions.

[0823] Input: Extracted intent and entity data.

[0824] Specific operation: The server analyzes the user's emotions using emotion recognition tools such as the BERT model and Amazon Comprehend.

[0825] Output: Recognized emotion data.

[0826] Step 6:

[0827] The server generates an appropriate response.

[0828] Input: Extracted intent and entity data, and recognized emotion data.

[0829] What it does: The dialogue engine uses a generative AI model (e.g., OpenAI GPT-3) to generate a response based on user input and sentiment. The prompt is "User: My favorite artist recently released a new album. Server: That's great! Tell me more about it!"

[0830] Output: The generated response text.

[0831] Step 7:

[0832] The server retrieves relevant information from a database to complete the response.

[0833] Input: The generated response text.

[0834] What happens next: The server performs a database query to retrieve additional information about the new album.

[0835] Output: The completed response text.

[0836] Step 8:

[0837] The server adjusts the response based on the emotion.

[0838] Input: The completed response text.

[0839] What it does: The emotion engine fine-tunes the final response based on the user's emotional state. For example, if the user expresses "sadness," it adjusts the response to "There are many touching songs on that album."

[0840] Output: The final response text.

[0841] Step 9:

[0842] The terminal displays the final response to the user.

[0843] Input: The final response text.

[0844] Specific operation: The dialogue display module displays the response text in a chat window on the UI.

[0845] Output: A text message that the user can see or hear.

[0846] Step 10:

[0847] The server records the emotion data.

[0848] Input: Recognized emotion data.

[0849] Specific operation: The emotion engine stores emotion data in a database in an appropriate format.

[0850] Output: Recorded emotion data.

[0851] Step 11:

[0852] The server updates the community database.

[0853] Input: User intent and perceived emotion, along with associated album information.

[0854] Specific operation: The server associates the user ID with topic information and inserts it into the community database, which supports matching with other users who share the same interests.

[0855] Output: Updated community database.

[0856] summary

[0857] Through these steps, the system supports users in conversations about their favorites, provides personalized responses that take their emotions into account, provides relevant information, and uses community features to encourage interaction with other users who share the same interests.

[0858] (Application example 2)

[0859] 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."

[0860] Current content distribution services lack interactive systems that allow users to have in-depth conversations about specific artists or creators and receive responses that reflect their own emotions. Furthermore, systems that provide users with real-time access to the latest content they desire and enable users with similar interests to effectively share information with each other are lacking. Therefore, new technological approaches are needed to increase user satisfaction and improve engagement.

[0861] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for recognizing emotions from user input and adjusting responses to match the user's emotions, means for providing the latest content information in real time, and means for providing a community function for sharing information with other users who share the same interests. This enables users to receive interactive responses tailored to their emotions, obtain new content information in real time, and easily share information with other users who share the same interests.

[0862] A "means for obtaining input from a user" is anything that allows a user to input information into a system, including text input and voice input.

[0863] "Means for analyzing captured user input and extracting intent and entities" refers to the process of analyzing input information from a user and identifying its intent (purpose) and entities (relevant key elements).

[0864] "Means for generating an appropriate response based on the extracted intent and entities" is a function that generates appropriate responses or information for the user according to the intent and entities obtained through analysis.

[0865] "Means for retrieving relevant information from a database and enhancing the response content" refers to the process of retrieving necessary information from a database and enhancing the response content to form the most appropriate answer to a user's question or request.

[0866] "Means for displaying the generated response to the user" means a method for providing the system-generated response to the user visually or audibly.

[0867] "Means for providing a community function for sharing information with other users who share the same interests" refers to a function that provides a forum for users who share the same interests to share information and interact with each other.

[0868] "Means for recognizing emotions from user input and adjusting responses to match the user's emotions" refers to technology that analyzes emotions from user input and flexibly changes the response content according to those emotions.

[0869] "Means for providing the latest content information in real time" refers to a function that obtains the latest content information from the Internet and other data sources and provides it to users in a timely manner.

[0870] The present invention is an interactive system that recognizes a user's emotions and generates and provides appropriate responses to the user. This system allows users to have in-depth discussions about specific artists or creators and receive responses that are in tune with their emotions.

[0871] System Configuration

[0872] Server Configuration

[0873] 1. Database (DB): Stores information about the user's "oshi" and past emotional data, allowing responses to be enhanced based on previously stored information.

[0874] 2. Dialogue engine: Manages interactions with users and uses natural language processing (NLP) techniques to analyze user input and extract intent and entities.

[0875] 3. Emotion engine: Responsible for inferring emotions from user input and tailoring responses to match those emotions.

[0876] 4. Information collection module: This module obtains the latest information about the "oshi" through external APIs, etc., and updates the database.

[0877] 5. Community management module: Manages information to enable users to interact with each other and, if necessary, matches users with the same "oshi" (favorites).

[0878] Device Configuration

[0879] 1. User Interface (UI): The screen through which the user interacts with the system, supporting text and voice input.

[0880] 2. Speech recognition and text input module: Takes user input and converts it to text in case of voice input.

[0881] 3. Interactive display module: displays the response received from the server to the user.

[0882] Detailed explanation of the process

[0883] 1. Getting user input:

[0884] The user begins speaking to the system through their device, for example, by entering text or voice, "My favorite idol recently released a new album."

[0885] 2. Input analysis and intent extraction:

[0886] The server's dialogue engine uses NLP technology to analyze user input received from the device and extract intent and entities.

[0887] 3. Emotion Recognition:

[0888] The emotion engine recognizes emotions from user input, for example identifying emotions such as "excited," "happy," or "sad."

[0889] 4. Generate response:

[0890] The server's dialogue engine generates an appropriate response based on the analysis and emotion recognition results. For example, if the user is excited, it generates the response "That's great! Tell me more about that album!"

[0891] 5. Additional Information:

[0892] The database retrieves the latest information about the target "oshi" and enriches the response, for example, "Tell me more about that album! The recent reviews were great."

[0893] 6. View the response:

[0894] The generated response is displayed to the user through an interactive display module, where the user can view the response on the screen.

[0895] 7. Emotional Data Recording:

[0896] The emotion engine records user emotional data and uses it to improve the user experience during ongoing interactions.

[0897] 8. Providing Community Features:

[0898] The server updates the community database and matches users with other users who share the same interests, allowing them to share new information and perspectives.

[0899] Examples and prompts

[0900] For example, if a user types, "My favorite idol recently released a new album," the system will respond as follows:

[0901] "That's great! Tell me more about that album!" (if the user is excited)

[0902] "Tell me more about that album! I've seen some great reviews recently." (If you've added the latest information)

[0903] This allows users to receive responses that are in tune with their emotions, obtain new content information in real time, and easily share information with other users who share the same interests.

[0904] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0905] Step 1: Getting User Input

[0906] The user inputs text or voice through the device's UI. For example, the user might input, "My favorite artist recently released a new album." The device receives this input and converts it into data to send to the server. In the case of voice input, the voice is converted into text by the voice recognition and text input module. The input data is in the form of text data.

[0907] Step 2: Parse input and extract intent

[0908] The server receives user input sent from the device, and the dialogue engine uses NLP technology to analyze the user input and extract intent (questions or desired information) and entities (specific artist or content names, etc.).

[0909] Type: "My idol recently released a new album."

[0910] Output: Intent = "I want to talk about the album", Entity = "Oshi"

[0911] Step 3: Recognize emotions

[0912] The emotion engine on the server recognizes emotions from the analyzed user input and identifies emotions such as "excitement," "happiness," and "sadness" based on the analysis results.

[0913] Type: "My idol recently released a new album."

[0914] Output: emotion = "excited"

[0915] Step 4: Generate a response

[0916] The server's dialogue engine generates an appropriate response based on the analysis and emotion recognition results. For example, if the user's emotion is "excited," it generates the response "That's great! Tell me more about that album!"

[0917] Input: Intent = "I want to talk about the album", Entity = "oshi", Emotion = "excited"

[0918] output:initial response="That's great! Tell me more about that album!"

[0919] Step 5: Provide additional information

[0920] The server retrieves the latest information about the target "oshi" from a database to enhance the response. For example, it retrieves the latest album information using an external API and generates a response such as "Tell me more about that album! Your recent reviews have been great."

[0921] Input:initial response="That's great! Tell me more about that album!"

[0922] Output: Enhanced Response = "That's great! Tell me more about that album! I saw some great reviews recently."

[0923] Step 6: View the response

[0924] The server generates a response and sends it to the terminal, where an interactive display module displays the response to the user, who can view the response on their screen.

[0925] Input:Enhanced response="That's great! Tell me more about that album! I saw some great reviews recently."

[0926] Output: The message displayed to the user

[0927] Step 7: Recording Emotional Data

[0928] The emotion engine on the server records the user's emotion data and uses it to improve the user experience during ongoing interactions. This recorded data is used in future interactions.

[0929] Input: emotion = "excited"

[0930] Output: Recorded emotion data

[0931] Step 8: Providing community features

[0932] The server updates the community database and matches users with the same interests. This feature allows users to share information with other users who are interested in the same "oshi."

[0933] Input: User ID, Interest = "Favorite"

[0934] Output: Community database updates, matching user information

[0935] Through the above processing steps, users can receive interactive responses that are in tune with their emotions, obtain the latest content information in real time, and easily share information with other users who share the same interests.

[0936] 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.

[0937] 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.

[0938] 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.

[0939] [Third embodiment]

[0940] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0941] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0942] 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).

[0943] 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.

[0944] 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.

[0945] 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).

[0946] 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.

[0947] 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.

[0948] 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.

[0949] 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.

[0950] 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.

[0951] 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."

[0952] The following describes an embodiment of the present invention. The present invention is an interactive system that allows users to have in-depth discussions about their favorites. This system analyzes user input, generates appropriate responses, and provides related information. It also has a community function that allows users to interact with other users who share the same favorites. Specific program processing of the system is explained below in natural language.

[0953] System Configuration

[0954] 1. Server Configuration

[0955] Database (DB): This is the core part of the system and stores a wealth of information about users' favorites.

[0956] Dialogue engine: Manages user interactions and uses natural language processing (NLP) techniques to analyze user input and extract intent and entities.

[0957] Information collection module: Obtains the latest information about "oshi" through external APIs, etc., and updates the database.

[0958] Community management module: Manages information to enable users to interact with each other and, if necessary, matches users with the same "oshi" (favorites).

[0959] 2. Terminal Configuration

[0960] User Interface (UI): The screen through which the user interacts with the system, supporting text and voice input.

[0961] Voice recognition and text input module: Serves as a means of user input and has functions such as converting voice input into text.

[0962] Interactive display module: displays the response received from the server to the user.

[0963] Program Processing

[0964] 1. User Input Processing

[0965] User: The user starts talking about their favorite idol in the UI. For example, they might say, "My favorite idol recently released a new album."

[0966] Terminal: Takes user input and sends the input data to the server.

[0967] 2. Input Analysis and Understanding

[0968] Server: Analyzes input data received from the device. The dialogue engine uses NLP technology to extract user intent (e.g., "I want to talk about the new album") and entities (e.g., "my favorite").

[0969] 3. Generating an appropriate response

[0970] Server: The dialogue engine generates an appropriate response based on the analysis, for example, "Tell me more about that album!"

[0971] 4. Providing information about your favorites

[0972] Server: Retrieves information about the new album from a database. Uses this information to enhance the original response, such as "Tell me more about that album! Your recent reviews were great."

[0973] 5. Viewing the Response

[0974] Terminal: Displays the generated response in the user's UI, where the user can see the response on the interactive screen.

[0975] 6. Community Features

[0976] Server: Registers users with the same "oshi" in a community and provides an environment where they can share information. For example, associates user IDs with topics (new albums) and registers them in the community database.

[0977] Specific examples

[0978] For example, if a user types "My favorite idol recently released a new album," the following happens:

[0979] 1. Get the user's input and send it to the server.

[0980] 2. The server parses the input and extracts intent and entities.

[0981] 3. The dialogue engine generates a response about "new album."

[0982] 4. Retrieve the relevant album information from the database and enrich the response.

[0983] 5. Display the generated response in the user's UI.

[0984] 6. The community feature allows you to share information with other users who are interested in the same album.

[0985] The system of this invention allows users to have in-depth discussions about their favorites and gain new perspectives through the latest information and interactions with other users. This system not only deepens users' understanding and empathy for their favorites, but also enables them to share a variety of information through the community.

[0986] The processing flow will be explained below.

[0987] Step 1:

[0988] The user talks about their favorite idol. For example, they input something like, "My favorite idol recently released a new album."

[0989] Step 2:

[0990] The terminal receives user input. In the case of voice input, the voice recognition module converts the voice into text and obtains the text data.

[0991] Step 3:

[0992] The terminal sends the acquired user input to the server. Specifically, it sends text data to the server via an HTTP request.

[0993] Step 4:

[0994] The server analyzes the input data received from the device, and the dialogue engine uses NLP technology to tokenize the input text and extract intent and entities.

[0995] Step 5:

[0996] The server's dialogue engine generates an appropriate response based on the analysis results. For example, if the extracted intent is about a "new album," it generates a response such as "Tell me more about that album!"

[0997] Step 6:

[0998] The server retrieves relevant information from the database. Based on the intent and entities retrieved by the dialogue engine, the database is queried for additional information about the "new album."

[0999] Step 7:

[1000] The server uses the information it obtains to enhance the response. For example, the response "Tell me more about that album!" can be enhanced to "Tell me more about that album! Your recent reviews have been great."

[1001] Step 8:

[1002] The server sends the final response to the terminal, and returns the data including the response to the terminal as an HTTP response.

[1003] Step 9:

[1004] The device displays the response received from the server in the user's UI. For example, the interactive display module might display a message on the screen saying, "Tell me more about that album! Your recent reviews have been great."

[1005] Step 10:

[1006] The server prepares to share information with other users who are interested in the same "oshi." Specifically, it associates the user ID with the topic (new album) and registers it in the community database.

[1007] Step 11:

[1008] The server matches users who share the same interests through the community function. For example, it creates a list of users who share an interest in the same "new album" and notifies each other of them.

[1009] Through these steps, the system of the present invention allows users to have in-depth discussions about their favorites and obtain new information. It also provides an environment for users to interact with other users who share an interest in the same favorites.

[1010] Example 1

[1011] 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."

[1012] In recent years, the spread of digital content over the Internet has increased opportunities for users to discuss their favorite things. However, systems that allow users to obtain information about their favorite things and share it with other users are still lacking. In particular, there is a need for technological solutions that can naturally analyze the content entered by users, generate appropriate responses, and provide related information to enable deeper communication. There is also a need for an environment where users with similar interests can easily share information.

[1013] 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.

[1014] In this invention, the server includes means for acquiring input from a user, means for analyzing the acquired user input and extracting intent and entities, means for generating an appropriate response based on the extracted intent and entities, means for acquiring related information from a database and enhancing the response content, means for displaying the generated response to the user, means for providing a community function for sharing information with other users who share the same interests, means for acquiring the latest information using an external interface and periodically updating the database, and means for the dialogue engine to utilize natural language processing technology. This allows users to have in-depth discussions about their "oshi," obtain the latest related information, and share information with other users who share the same interests.

[1015] A "user" is an entity that uses this system to input information about their "favorite" and interact with other users.

[1016] "Means for obtaining input" refers to a function for sending text and voice data entered by a user through the device's UI to a server.

[1017] "Means for extracting intent and entities" is a function that uses natural language processing technology to analyze and identify the purpose and subject of interest (intent and entity) of a topic from user input data.

[1018] The "means for generating a response" is the function that creates an appropriate reply based on the extracted intent and entities.

[1019] A "database" is an information storage device that stores information related to a user's "favorites."

[1020] The "means for enhancing response content" is a function that further enriches the generated response based on related information obtained from the database.

[1021] The "means for displaying a response" is a function for displaying the generated response on the user's terminal.

[1022] "Means for providing community functions" refers to functions that allow users who are interested in the same "favorite" to share information and interact with each other.

[1023] An "external interface" is a connection that allows a system to exchange data with external sources.

[1024] "Natural language processing technology" is a series of technologies that use computers to understand, analyze, and generate language used by humans.

[1025] This invention is an interactive system that allows users to discuss their favorites in depth. The system analyzes user input, generates appropriate responses, provides relevant information, and has a community function that allows users to interact with other users who share the same favorites.

[1026] System Configuration

[1027] 1. Server Configuration

[1028] Database (DB): This is the core part of the system and stores a wealth of information about users' favorites.

[1029] Dialogue engine: Manages user interactions and uses natural language processing (NLP) techniques to analyze user input and extract intent and entities.

[1030] Information collection module: Uses an external interface to obtain the latest information about "oshi" and update the database.

[1031] Community management module: Manages information to enable users to interact with each other and, if necessary, matches users with the same "oshi" (favorites).

[1032] 2. Terminal Configuration

[1033] User Interface (UI): The screen through which the user interacts with the system, supporting text and voice input.

[1034] Voice recognition and text input module: Serves as a means of user input and has functions such as converting voice input into text.

[1035] Interactive display module: displays the response received from the server to the user.

[1036] Specific processing of the program

[1037] 1. User Input Processing

[1038] User: The user starts talking about their favorite idol in the UI. For example, they might say, "My favorite idol recently released a new album."

[1039] Terminal: The terminal takes the user's input and sends the input data to the server.

[1040] 2. Input Analysis and Understanding

[1041] Server: Analyzes input data received from the device. The dialogue engine uses NLP technology to extract user intent (e.g., "I want to talk about the new album") and entities (e.g., "my favorite").

[1042] 3. Generating an appropriate response

[1043] Server: The dialogue engine generates an appropriate response based on the analysis, for example, "Tell me more about that album!"

[1044] 4. Providing information about your favorites

[1045] Server: Retrieves information about the new album from a database. Uses this information to enhance the original response, such as "Tell me more about that album! Your recent reviews were great."

[1046] 5. Viewing the Response

[1047] Terminal: Displays the generated response in the user's UI, where the user can see the response on the interactive screen.

[1048] 6. Community Features

[1049] Server: Registers users with the same "oshi" in a community and provides an environment where they can share information. For example, associates user IDs with topics (new albums) and registers them in the community database.

[1050] Prompt Sentence Examples

[1051] Examples of prompts to input to the generative AI model include:

[1052] Something like, "If a user says, 'My favorite idol recently released a new album,' please provide detailed instructions on how to use a dialogue engine to generate a response."

[1053] The system of this invention allows users to have in-depth discussions about their favorites and gain new perspectives through the latest information and interactions with other users. This system not only deepens users' understanding and empathy for their favorites, but also enables them to share a variety of information through the community.

[1054] The specific hardware and software used

[1055] Natural Language Processing (NLP) libraries: TensorFlow, PyTorch

[1056] Database management systems: MySQL, PostgreSQL

[1057] External Interface: RESTful API

[1058] User Interface (UI): HTML, CSS, JavaScript

[1059] Speech recognition module: Google Speech-to-Text API, Microsoft Azure Cognitive Services

[1060] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1061] Step 1:

[1062] User: The user enters text into the UI. For example, they might type, "My favorite idol recently released a new album." Specifically, the user enters text using the keyboard and then presses the "Send" button to send the text to the device.

[1063] Step 2:

[1064] Terminal: Acquires the input text data and sends it to the server. Specifically, the terminal sends the acquired text data to the server using an HTTP POST request. The input is the user's text data, and the output is an HTTP request sent to the server.

[1065] Step 3:

[1066] Server: Received user data is temporarily stored in memory, and the dialogue engine analyzes the data. Specifically, the server saves the received data in a memory buffer and passes it to the dialogue engine for processing. The input is the text data of the HTTP request, and the output is text data prepared for analysis.

[1067] Step 4:

[1068] Server: The dialogue engine uses natural language processing (NLP) techniques to analyze user input and extract intents and entities. Specifically, the dialogue engine performs tokenization, morphological analysis, and grammatical analysis to extract intents and entities in JSON format. The input is prepared text data, and the output is JSON data containing intents and entities.

[1069] Step 5:

[1070] Server: Generates a response based on the extracted intent and entities. The dialogue engine generates a basic response such as "Tell me more about that album!" based on the analysis results. Specifically, the response generation logic generates candidate responses using the analysis results as arguments. The input is JSON data containing the intent and entities, and the output is basic response text.

[1071] Step 6:

[1072] Server: Queries the database to retrieve relevant information. Specifically, the server executes an SQL query to retrieve data about the latest album of "oshi" from the database. The input is the response text and relevant query information, and the output is the additional information returned from the database.

[1073] Step 7:

[1074] Server: Enhances the response based on the information retrieved from the database. Generates a response such as "Tell me more about that album! Your recent reviews were great." Specifically, it inserts the retrieved information into a response template to construct the final response. The input is the basic response text and additional information from the database, and the output is the enhanced response text.

[1075] Step 8:

[1076] Server: Sends the generated response to the terminal. Specifically, the server returns the generated response to the terminal as an HTTP response. The input is the enhanced response text, and the output is the HTTP response sent to the terminal.

[1077] Step 9:

[1078] Terminal: The generated response is displayed in the user's UI. Specifically, the terminal displays the response text in a UI component. The input is the HTTP response from the server, and the output is the response text displayed in the UI.

[1079] Step 10:

[1080] Server: Registers users with the same "favorites" in a community and provides an environment where they can share information. Specifically, it associates user IDs with topics (new albums) and registers them in a community database, then searches for and matches users with common interests. The input is the user's interest information, and the output is the community registration information and matching results.

[1081] (Application example 1)

[1082] 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."

[1083] Traditional dialogue systems do not provide an interactive environment for users to discuss their interests and "oshi" in depth, and interactions with other users are limited. Furthermore, the lack of systems that utilize new devices such as smart glasses results in a suboptimal user experience. Therefore, there is a need to provide a new type of virtual space where users can discuss "oshi" and share their interests.

[1084] 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.

[1085] In this invention, the server includes means for acquiring input from a user, means for analyzing the acquired user input and extracting an intent and an entity, means for generating an appropriate response based on the extracted intent and entity, means for acquiring related information from a database and enhancing the response content, means for displaying the generated response to the user, means for providing a community function for sharing information with other users who share the same interest, and means for displaying the response to the user in a virtual space using smart glasses and enabling interaction with other users. This allows users to talk about their "favorites" through the smart glasses and interact with other users in the virtual space.

[1086] A "means for obtaining user input" is an interface or device that captures text or voice data entered by a user and transmits it to the system.

[1087] "Means for parsing captured user input and extracting intent and entities" means techniques or processes for analyzing user-entered text or voice data and extracting user intent and identifiable entities from that data.

[1088] "Means for generating an appropriate response based on the extracted intent and entity" refers to an algorithm or program for creating an optimal response based on the user's intent and entity information.

[1089] The "means for retrieving relevant information from a database and enhancing the response content" is a system for retrieving information related to the user's intention from a database and incorporating that information into the response to enrich the response content.

[1090] "Means for displaying the generated response to the user" refers to a display or interface that allows the user to see the response generated by the system.

[1091] "Means for providing a community function for sharing information with other users who share the same interests" refers to a system for building and operating an online community where users can empathize with other users and exchange information.

[1092] "Means for displaying responses to a user in a virtual space using smart glasses and enabling the user to interact with other users" refers to technology that utilizes smart glasses to display responses from an interactive system to a user and simultaneously enable the user to communicate with other users in a virtual space.

[1093] The present invention provides an interactive system that allows users to have in-depth discussions about their interests. The system uses smart glasses to provide users with interactive responses and has the ability to interact with other users who share the same interests in a virtual space. Specific embodiments of the system are described below.

[1094] System Configuration

[1095] 1. Server Configuration

[1096] Database (DB): This is the core part of the system and stores a wealth of information about users' "push."

[1097] Dialogue engine: Manages user interactions and uses natural language processing (NLP) techniques to analyze user input and extract intent and entities.

[1098] Information collection module: Obtains the latest information on "push" through external APIs, etc., and updates the database.

[1099] Community management module: Manages information to enable users to interact with each other and, if necessary, matches users with the same interests.

[1100] 2. Terminal Configuration

[1101] User Interface (UI): The screen through which the user interacts with the system, supporting text and voice input.

[1102] Voice recognition and text input module: Serves as a means of user input and has functions such as converting voice input into text.

[1103] Interactive display module: displays the response received from the server to the user.

[1104] Smart glasses: Devices that support viewing and interaction in virtual spaces.

[1105] Program processing explanation

[1106] The server first obtains input from the user. The user's input is captured through the smart glasses' voice recognition and text input module. The obtained user input is sent to the server and analyzed by the dialogue engine. The dialogue engine uses natural language processing technology to extract the user's intent and entities.

[1107] The server then generates an appropriate response based on the extracted intent and entities, leveraging a generative AI model to create the optimal message that addresses the user's interests, and enriching the response with relevant information from a database and adding the latest information using external APIs.

[1108] The generated responses are displayed to the user through the smart glasses from the server, allowing the user to obtain detailed information about their "push" and interact with other users with the same interests in a virtual space. The community management module matches users with the same "push" and provides a forum for information sharing.

[1109] Explanation using concrete examples

[1110] For example, if a user types, "My idol recently released a new album," the following process occurs: First, the user's voice input is converted to text through the smart glasses and sent to the server. The dialogue engine analyzes this input and extracts intent and entities. The server uses a generative AI model to generate a response such as, "Tell me more about that album!" and adds additional information, such as, "The recent reviews were also positive," based on the latest information retrieved from the database and external APIs. The generated response is then displayed on the smart glasses' display.

[1111] An example prompt based on a generative AI model is:

[1112] User: My favorite guy recently released a new album.

[1113] System: Tell us more about the album! It's received some great reviews recently.

[1114] This system allows users to have in-depth discussions about "pushing" and gain new perspectives through the latest information and interactions with other users.

[1115] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1116] Step 1:

[1117] The user inputs either by voice or text. The smart glasses' voice recognition and text input module converts the user's input into text data and sends it to the server. At this stage, the input is the user's speech, and the output is text data.

[1118] Step 2:

[1119] The server analyzes the text data received from the device using a dialogue engine. The dialogue engine uses natural language processing technology to extract the user's intent and entities from the text data. At this stage, the input is text data, and the output is the analyzed intent and entities.

[1120] Step 3:

[1121] The server generates an appropriate response based on the extracted intent and entities. Using a generative AI model, it creates a message that best suits the information the user is looking for and the flow of the conversation. The input at this stage is the intent and entities, and the output is the generated response.

[1122] Step 4:

[1123] The server retrieves relevant information from the database to enhance the generated response. In addition, it retrieves the latest information from an external API through an information collection module and adds it to the response. The input at this stage is the generated response and a database query, and the output is the enhanced response.

[1124] Step 5:

[1125] The server sends the enhanced response to the terminal. The interactive display module of the terminal receives the response and displays it on the display of the smart glasses. At this stage, the input is the enhanced response, and the output is the display on the display of the smart glasses.

[1126] Step 6:

[1127] The server's community management module identifies other users with similar interests and provides an environment for sharing information. Users can interact with each other in a virtual space and discuss common interests. The input at this stage is the user's interest information, and the output is interactions with other users who have been matched.

[1128] 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.

[1129] The following describes an embodiment of the present invention. The present invention is an interactive system that allows users to have in-depth discussions about their favorite characters. This system not only analyzes user input, generates appropriate responses, and provides relevant information, but also combines an emotion engine that recognizes the user's emotions and adjusts responses accordingly. Specific program processing of the system is described below in natural language.

[1130] System Configuration

[1131] 1. Server Configuration

[1132] Database (DB): Stores information about the user's "oshi" and the user's past emotional data.

[1133] Dialogue engine: Manages user interactions and uses natural language processing (NLP) techniques to analyze user input and extract intent and entities.

[1134] Emotion engine: Responsible for inferring emotions from user input and tailoring responses to match those emotions.

[1135] Information collection module: Obtains the latest information about "oshi" through external APIs, etc., and updates the database.

[1136] Community management module: Manages information to enable users to interact with each other and, if necessary, matches users with the same "oshi" (favorites).

[1137] 2. Terminal Configuration

[1138] User Interface (UI): The screen through which the user interacts with the system, supporting text and voice input.

[1139] Speech recognition and text input module: Takes user input and converts it to text in case of voice input.

[1140] Interactive display module: displays the response received from the server to the user.

[1141] Program Processing

[1142] 1. User Input Processing

[1143] User: The user starts talking about their favorite idol in the UI. For example, they might say, "My favorite idol recently released a new album."

[1144] Terminal: Takes user input and sends that data to the server.

[1145] 2. Input Analysis and Understanding

[1146] Server: Analyzes input data received from the device. The dialogue engine uses NLP technology to extract user intent (e.g., "I want to talk about the new album") and entities (e.g., "my favorite").

[1147] 3. Emotional Recognition

[1148] Server: The emotion engine recognizes emotions from user input, for example identifying emotions such as "happy," "excited," and "sad."

[1149] 4. Generating the Response

[1150] Server: The dialogue engine generates an appropriate response based on the analysis and emotion recognition results. For example, if the user's emotion is "excited," the response generated is "That's great! Tell me more about that album!"

[1151] 5. Providing information about your favorites

[1152] Server: Retrieves information about the new album from a database. Uses this information to enhance the original response, for example, "Tell me more about that album! Your recent reviews were great."

[1153] 6. Regulating responses based on emotions

[1154] Server: After receiving additional information, the emotion engine further tailors the response based on the user's emotion. For example, if the user expresses "sadness," it generates a response such as "There are many moving songs on that album."

[1155] 7. Displaying the Response

[1156] Device: The generated response is displayed in the user's UI. For example, the interactive display module might display a message on the screen saying, "Tell me more about that album! Your recent reviews were great."

[1157] 8. Recording Emotional Data

[1158] Server: The emotion engine records the user's emotional data and uses it to improve the user experience during ongoing interactions.

[1159] 9. Community Features

[1160] Server: Registers users with the same "oshi" in a community and provides an environment where they can share information. For example, associates user IDs with topics (new albums) and registers them in the community database.

[1161] Specific examples

[1162] For example, if a user types "My favorite idol recently released a new album," the following happens:

[1163] 1. Get the user's input and send it to the server.

[1164] 2. The server parses the input and extracts intent and entities.

[1165] 3. The server recognizes the emotion "excited" from the input.

[1166] 4. The dialogue engine generates a response based on the analysis and emotion recognition results.

[1167] 5. Retrieve information about new albums from the database to enhance the response.

[1168] 6. The emotion engine tailors the response to "That's great! Tell me more about that album!"

[1169] 7. Display the response in the user's UI.

[1170] 8. The emotion engine records the user's emotional data and uses it for the next conversation.

[1171] 9. The server updates the community database and matches users with similar interests.

[1172] In this way, the system of the present invention analyzes user input, recognizes emotions, generates responses, and provides relevant information. It also continuously records user emotional data to enhance the interaction experience. It also provides a community function, encouraging interaction with other users who share the same "oshi" (favorite). Through this system, users can have in-depth discussions about their "oshi" and gain new information and perspectives.

[1173] The processing flow will be explained below.

[1174] Step 1:

[1175] The user talks about their favorite idol. For example, they input something like, "My favorite idol recently released a new album."

[1176] Step 2:

[1177] The terminal receives user input. In the case of voice input, the voice recognition module converts the voice into text and obtains the text data.

[1178] Step 3:

[1179] The terminal sends the acquired user input to the server. Specifically, it sends text data to the server via an HTTP request.

[1180] Step 4:

[1181] The server analyzes the input data received from the device, and the dialogue engine uses NLP technology to tokenize the input text and extract intent and entities.

[1182] Step 5:

[1183] The server's dialogue engine generates an appropriate response based on the analysis results. For example, if the extracted intent is about a "new album," it generates a response such as "Tell me more about that album!"

[1184] Step 6:

[1185] The server uses an emotion engine to recognize emotions from user input, such as "excitement," "happiness," and "sadness."

[1186] Step 7:

[1187] The server adjusts the response based on the emotion recognition result. For example, if it recognizes "excited," it adjusts the normal response to "That's great! Tell me more about that album!"

[1188] Step 8:

[1189] The server retrieves relevant information from the database. Based on the intent and entities retrieved by the dialogue engine, it retrieves information about "new album" from the database.

[1190] Step 9:

[1191] The server uses the information it obtains to enhance the response, for example, "Tell me more about that album! Your recent reviews have been great."

[1192] Step 10:

[1193] The device displays the response received from the server in the user's UI. For example, the interactive display module might display a message on the screen saying, "Tell me more about that album! Your recent reviews have been great."

[1194] Step 11:

[1195] The server uses an emotion engine to record the user's emotional data, which is used to improve the user experience in future interactions.

[1196] Step 12:

[1197] The server provides a community function, allowing users with the same "favorites" or interests to register in a community and share information.

[1198] Step 13:

[1199] The server matches users within the community and allows them to share information with others who share the same interests, such as their opinions and thoughts on a new album.

[1200] Through these steps, the system of the present invention allows users to have in-depth discussions about their favorites and gain new information. It also recognizes users' emotions and generates responses based on them, providing a more personalized experience. It also provides an environment where users can interact with other users who share the same favorites.

[1201] Example 2

[1202] 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."

[1203] While conventional dialogue systems can analyze user input and generate appropriate responses, they lack the ability to generate responses that take into account the user's emotions and share information with other users who share the same interests. Therefore, there is a need to improve the user experience and provide more personalized responses and community functions.

[1204] 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.

[1205] In this invention, the server includes means for analyzing a user input and extracting an intention and an entity, means for recognizing an emotion from the user input, means for generating an appropriate response based on the extracted intention and entity and the recognized emotion, means for retrieving related information from a database and enhancing the response content, means for adjusting the response content based on the user's emotion, means for recording the user's emotion data, and means for providing a community function for sharing information with other users who share the same interest, thereby enabling the generation of a response tailored to the user's emotion and the sharing of information among users who share the same interest.

[1206] "Means of acquisition" refers to the ability to input user input into the system as voice or text data.

[1207] "Means of analyzing and extracting intent and entities" refers to the function of using natural language processing technology to analyze the meaning of user input data and identify specific actions or targets.

[1208] "Means for recognizing emotions" refers to the function of determining and identifying the user's emotional state from input data.

[1209] "Means for generating an appropriate response" refers to the function of generating a reply to the user based on the analyzed intent and recognized emotion.

[1210] "Means of obtaining relevant information and enhancing response content" refers to the function of obtaining relevant data from databases within the system or external interfaces and enriching the information provided to users.

[1211] "Means for adjusting response content" refers to the ability to modify and optimize the generated response based on the perceived user sentiment.

[1212] "Means for displaying to the user" refers to the ability to visually or audibly present the generated response to the user.

[1213] "Means for recording emotional data" refers to a feature that continuously collects and stores data about a user's emotional state.

[1214] "Means for providing community functions" refers to functions that provide an environment where users with similar interests can share information and communicate with each other.

[1215] This invention provides an interactive system that allows users to discuss their favorites. The system not only analyzes user input to generate appropriate responses and provide relevant information, but also recognizes user emotions and adjusts responses accordingly.

[1216] System configuration overview

[1217] Server Configuration

[1218] 1. Database: Stores information about users' favorites and their past emotional data. For example, a database management system such as MySQL or MongoDB is used.

[1219] 2. Dialogue Engine: Manages user interactions and analyzes user input using Natural Language Processing (NLP) techniques, such as spaCy or Google Cloud Natural Language API, to extract intent and entities.

[1220] 3. Emotion engine: Infers emotions from user input and tailors responses to match those emotions. This leverages emotion recognition tools such as the BERT model and Amazon Comprehend.

[1221] 4. Information collection module: Obtains the latest information about "oshi" through external APIs and updates the database. For example, it uses Twitter API or News API.

[1222] 5. Community management module: Manages information so that users can interact with each other and, if necessary, matches users with the same "oshi" (favorites).

[1223] Device Configuration

[1224] 1. User Interface (UI): Provides a screen for users to interact with the system and supports text and voice input. Examples include web browsers and mobile apps.

[1225] 2. Speech recognition and text input module: Takes user input and converts it to text in the case of voice input. This may use a speech recognition service such as the Google Speech-to-Text API.

[1226] 3. Interaction display module: displays the response received from the server to the user, for example, as a text message in a chat window.

[1227] Program processing overview

[1228] The specific processing of this system will be explained below.

[1229] Processing User Input

[1230] User: The user starts talking about their favorite idol in the UI. For example, they might say, "My favorite idol recently released a new album."

[1231] Terminal: The terminal takes the user's input and sends the data to the server, converting it to text using voice recognition technology in the case of voice input.

[1232] Parsing and understanding input

[1233] Server: Analyzes input data received from the device. The dialogue engine uses NLP technology to extract the user's intent and entities.

[1234] Emotion recognition

[1235] Server: The emotion engine recognizes emotions from user input, for example identifying emotions such as "happy," "excited," and "sad."

[1236] Response generation and adjustment

[1237] Server: The dialogue engine generates an appropriate response based on the analysis and emotion recognition results. It may use a generative AI model to form the response. For example, it generates a response like, "That's great! Tell me more about that album!"

[1238] Server: Retrieve information about the new album from the database and complete the response, for example, including additional information like "Tell me more about that album! Your recent reviews were great."

[1239] Viewing the response

[1240] Terminal: The generated response is displayed in the user's UI. For example, the interactive display module might display a message on the screen saying, "Tell me more about that album! Your recent reviews were great."

[1241] Emotional data recording and community features

[1242] Server: The emotion engine records the user's emotional data and uses it to improve the user experience in future interactions. In addition, the server registers users with the same "oshi" as its users in a community, providing an environment where they can share information.

[1243] Specific examples

[1244] For example, if a user types "My favorite idol recently released a new album," the following happens:

[1245] 1. Get the user's input and send it to the server.

[1246] 2. The server parses the input and extracts intent and entities.

[1247] 3. The server recognizes the emotion "excited" from the input.

[1248] 4. The dialogue engine generates the response, "That's great! Tell me more about that album!"

[1249] 5. Retrieve information about the new album from the database and complete the response with, "The recent reviews were great."

[1250] 6. Display the generated response in the user's UI.

[1251] 7. Provide a community function to record emotional data and share information with other users who share the same interests.

[1252] Prompt Sentence Examples

[1253] Here are some example prompts to input to the generative AI model:

[1254] User: My favorite artist recently released a new album.

[1255] Server: That's great! Tell us more about the album! It's had some great reviews recently.

[1256] Through this system, users can have in-depth discussions about their favorites and gain new information and perspectives.

[1257] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1258] The flow of this system's program processing

[1259] Step 1:

[1260] Users provide topics about their favorites.

[1261] Input: The user says to the UI, "My favorite idol recently released a new album."

[1262] Specific action: The user speaks into a microphone or types into a text field.

[1263] Step 2:

[1264] The terminal obtains the user's input.

[1265] Input: User voice or text data.

[1266] What it does: The device converts voice input to text using the Google Speech-to-Text API. For text input, it retrieves the text directly from the UI.

[1267] Output: The converted or retrieved text data.

[1268] Step 3:

[1269] The terminal sends the input data to the server.

[1270] Input: The converted or retrieved text data.

[1271] Specific operation: The terminal sends data to the server as an HTTP request.

[1272] Output: The text data sent to the server.

[1273] Step 4:

[1274] The server parses the input data and extracts intent and entities.

[1275] Input: Text data received from the terminal.

[1276] What it does: The server uses a natural language processing engine (e.g., spaCy or Google Cloud Natural Language API) to parse the text and extract intent and entities.

[1277] Output: Extracted intent and entity data.

[1278] Step 5:

[1279] The server recognizes the user's emotions.

[1280] Input: Extracted intent and entity data.

[1281] Specific operation: The server analyzes the user's emotions using emotion recognition tools such as the BERT model and Amazon Comprehend.

[1282] Output: Recognized emotion data.

[1283] Step 6:

[1284] The server generates an appropriate response.

[1285] Input: Extracted intent and entity data, and recognized emotion data.

[1286] What it does: The dialogue engine uses a generative AI model (e.g., OpenAI GPT-3) to generate a response based on user input and sentiment. The prompt is "User: My favorite artist recently released a new album. Server: That's great! Tell me more about it!"

[1287] Output: The generated response text.

[1288] Step 7:

[1289] The server retrieves relevant information from a database to complete the response.

[1290] Input: The generated response text.

[1291] What happens next: The server performs a database query to retrieve additional information about the new album.

[1292] Output: The completed response text.

[1293] Step 8:

[1294] The server adjusts the response based on the emotion.

[1295] Input: The completed response text.

[1296] What it does: The emotion engine fine-tunes the final response based on the user's emotional state. For example, if the user expresses "sadness," it adjusts the response to "There are many touching songs on that album."

[1297] Output: The final response text.

[1298] Step 9:

[1299] The terminal displays the final response to the user.

[1300] Input: The final response text.

[1301] Specific operation: The dialogue display module displays the response text in a chat window on the UI.

[1302] Output: A text message that the user can see or hear.

[1303] Step 10:

[1304] The server records the emotion data.

[1305] Input: Recognized emotion data.

[1306] Specific operation: The emotion engine stores emotion data in a database in an appropriate format.

[1307] Output: Recorded emotion data.

[1308] Step 11:

[1309] The server updates the community database.

[1310] Input: User intent and perceived emotion, along with associated album information.

[1311] Specific operation: The server associates the user ID with topic information and inserts it into the community database, which supports matching with other users who share the same interests.

[1312] Output: Updated community database.

[1313] summary

[1314] Through these steps, the system supports users in conversations about their favorites, provides personalized responses that take their emotions into account, provides relevant information, and uses community features to encourage interaction with other users who share the same interests.

[1315] (Application example 2)

[1316] 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."

[1317] Current content distribution services lack interactive systems that allow users to have in-depth conversations about specific artists or creators and receive responses that reflect their own emotions. Furthermore, systems that provide users with real-time access to the latest content they desire and enable users with similar interests to effectively share information with each other are lacking. Therefore, new technological approaches are needed to increase user satisfaction and improve engagement.

[1318] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for recognizing emotions from user input and adjusting responses to match the user's emotions, means for providing the latest content information in real time, and means for providing a community function for sharing information with other users who share the same interests. This enables users to receive interactive responses tailored to their emotions, obtain new content information in real time, and easily share information with other users who share the same interests.

[1319] A "means for obtaining input from a user" is anything that allows a user to input information into a system, including text input and voice input.

[1320] "Means for analyzing captured user input and extracting intent and entities" refers to the process of analyzing input information from a user and identifying its intent (purpose) and entities (relevant key elements).

[1321] "Means for generating an appropriate response based on the extracted intent and entities" is a function that generates appropriate responses or information for the user according to the intent and entities obtained through analysis.

[1322] "Means for retrieving relevant information from a database and enhancing the response content" refers to the process of retrieving necessary information from a database and enhancing the response content to form the most appropriate answer to a user's question or request.

[1323] "Means for displaying the generated response to the user" means a method for providing the system-generated response to the user visually or audibly.

[1324] "Means for providing a community function for sharing information with other users who share the same interests" refers to a function that provides a forum for users who share the same interests to share information and interact with each other.

[1325] "Means for recognizing emotions from user input and adjusting responses to match the user's emotions" refers to technology that analyzes emotions from user input and flexibly changes the response content according to those emotions.

[1326] "Means for providing the latest content information in real time" refers to a function that obtains the latest content information from the Internet and other data sources and provides it to users in a timely manner.

[1327] The present invention is an interactive system that recognizes a user's emotions and generates and provides appropriate responses to the user. This system allows users to have in-depth discussions about specific artists or creators and receive responses that are in tune with their emotions.

[1328] System Configuration

[1329] Server Configuration

[1330] 1. Database (DB): Stores information about the user's "oshi" and past emotional data, allowing responses to be enhanced based on previously stored information.

[1331] 2. Dialogue engine: Manages interactions with users and uses natural language processing (NLP) techniques to analyze user input and extract intent and entities.

[1332] 3. Emotion engine: Responsible for inferring emotions from user input and tailoring responses to match those emotions.

[1333] 4. Information collection module: This module obtains the latest information about the "oshi" through external APIs, etc., and updates the database.

[1334] 5. Community management module: Manages information to enable users to interact with each other and, if necessary, matches users with the same "oshi" (favorites).

[1335] Device Configuration

[1336] 1. User Interface (UI): The screen through which the user interacts with the system, supporting text and voice input.

[1337] 2. Speech recognition and text input module: Takes user input and converts it to text in case of voice input.

[1338] 3. Interactive display module: displays the response received from the server to the user.

[1339] Detailed explanation of the process

[1340] 1. Getting user input:

[1341] The user begins speaking to the system through their device, for example, by entering text or voice, "My favorite idol recently released a new album."

[1342] 2. Input analysis and intent extraction:

[1343] The server's dialogue engine uses NLP technology to analyze user input received from the device and extract intent and entities.

[1344] 3. Emotion Recognition:

[1345] The emotion engine recognizes emotions from user input, for example identifying emotions such as "excited," "happy," or "sad."

[1346] 4. Generate response:

[1347] The server's dialogue engine generates an appropriate response based on the analysis and emotion recognition results. For example, if the user is excited, it generates the response "That's great! Tell me more about that album!"

[1348] 5. Additional Information:

[1349] The database retrieves the latest information about the target "oshi" and enriches the response, for example, "Tell me more about that album! The recent reviews were great."

[1350] 6. View the response:

[1351] The generated response is displayed to the user through an interactive display module, where the user can view the response on the screen.

[1352] 7. Emotional Data Recording:

[1353] The emotion engine records user emotional data and uses it to improve the user experience during ongoing interactions.

[1354] 8. Providing Community Features:

[1355] The server updates the community database and matches users with other users who share the same interests, allowing them to share new information and perspectives.

[1356] Examples and prompts

[1357] For example, if a user types, "My favorite idol recently released a new album," the system will respond as follows:

[1358] "That's great! Tell me more about that album!" (if the user is excited)

[1359] "Tell me more about that album! I've seen some great reviews recently." (If you've added the latest information)

[1360] This allows users to receive responses that are in tune with their emotions, obtain new content information in real time, and easily share information with other users who share the same interests.

[1361] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1362] Step 1: Getting User Input

[1363] The user inputs text or voice through the device's UI. For example, the user might input, "My favorite artist recently released a new album." The device receives this input and converts it into data to send to the server. In the case of voice input, the voice is converted into text by the voice recognition and text input module. The input data is in the form of text data.

[1364] Step 2: Parse input and extract intent

[1365] The server receives user input sent from the device, and the dialogue engine uses NLP technology to analyze the user input and extract intent (questions or desired information) and entities (such as specific artist or content names).

[1366] Type: "My idol recently released a new album."

[1367] Output: Intent = "I want to talk about the album", Entity = "Oshi"

[1368] Step 3: Recognize emotions

[1369] The emotion engine on the server recognizes emotions from the analyzed user input and identifies emotions such as "excitement," "happiness," and "sadness" based on the analysis results.

[1370] Type: "My idol recently released a new album."

[1371] Output: emotion = "excited"

[1372] Step 4: Generate a response

[1373] The server's dialogue engine generates an appropriate response based on the analysis and emotion recognition results. For example, if the user's emotion is "excited," it generates the response "That's great! Tell me more about that album!"

[1374] Input: Intent = "I want to talk about the album", Entity = "oshi", Emotion = "excited"

[1375] output:initial response="That's great! Tell me more about that album!"

[1376] Step 5: Provide additional information

[1377] The server retrieves the latest information about the target "oshi" from a database to enhance the response. For example, it retrieves the latest album information using an external API and generates a response such as "Tell me more about that album! Your recent reviews have been great."

[1378] Input:initial response="That's great! Tell me more about that album!"

[1379] Output: Enhanced Response = "That's great! Tell me more about that album! I saw some great reviews recently."

[1380] Step 6: View the response

[1381] The server generates a response and sends it to the terminal, where an interactive display module displays the response to the user, who can view the response on their screen.

[1382] Input:Enhanced response="That's great! Tell me more about that album! I saw some great reviews recently."

[1383] Output: The message displayed to the user

[1384] Step 7: Recording Emotional Data

[1385] The emotion engine on the server records the user's emotion data and uses it to improve the user experience during ongoing interactions. This recorded data is used in future interactions.

[1386] Input: emotion = "excited"

[1387] Output: Recorded emotion data

[1388] Step 8: Providing community features

[1389] The server updates the community database and matches users with the same interests. This feature allows users to share information with other users who are interested in the same "oshi."

[1390] Input: User ID, Interest = "Favorite"

[1391] Output: Community database updates, matching user information

[1392] Through the above processing steps, users can receive interactive responses that are in tune with their emotions, obtain the latest content information in real time, and easily share information with other users who share the same interests.

[1393] 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.

[1394] 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.

[1395] 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.

[1396] [Fourth embodiment]

[1397] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1398] 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.

[1399] 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).

[1400] 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.

[1401] 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.

[1402] 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).

[1403] 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.

[1404] 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.

[1405] 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.

[1406] 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.

[1407] 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.

[1408] 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.

[1409] 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."

[1410] The following describes an embodiment of the present invention. The present invention is an interactive system that allows users to have in-depth discussions about their favorites. This system analyzes user input, generates appropriate responses, and provides related information. It also has a community function that allows users to interact with other users who share the same favorites. Specific program processing of the system is explained below in natural language.

[1411] System Configuration

[1412] 1. Server Configuration

[1413] Database (DB): This is the core part of the system and stores a wealth of information about users' favorites.

[1414] Dialogue engine: Manages user interactions and uses natural language processing (NLP) techniques to analyze user input and extract intent and entities.

[1415] Information collection module: Obtains the latest information about "oshi" through external APIs, etc., and updates the database.

[1416] Community management module: Manages information to enable users to interact with each other and, if necessary, matches users with the same "oshi" (favorites).

[1417] 2. Terminal Configuration

[1418] User Interface (UI): The screen through which the user interacts with the system, supporting text and voice input.

[1419] Voice recognition and text input module: Serves as a means of user input and has functions such as converting voice input into text.

[1420] Interactive display module: displays the response received from the server to the user.

[1421] Program Processing

[1422] 1. User Input Processing

[1423] User: The user starts talking about their favorite idol in the UI. For example, they might say, "My favorite idol recently released a new album."

[1424] Terminal: Takes user input and sends the input data to the server.

[1425] 2. Input Analysis and Understanding

[1426] Server: Analyzes input data received from the device. The dialogue engine uses NLP technology to extract user intent (e.g., "I want to talk about the new album") and entities (e.g., "my favorite").

[1427] 3. Generating an appropriate response

[1428] Server: The dialogue engine generates an appropriate response based on the analysis, for example, "Tell me more about that album!"

[1429] 4. Providing information about your favorites

[1430] Server: Retrieves information about the new album from a database. Uses this information to enhance the original response, such as "Tell me more about that album! Your recent reviews were great."

[1431] 5. Viewing the Response

[1432] Terminal: Displays the generated response in the user's UI, where the user can see the response on the interactive screen.

[1433] 6. Community Features

[1434] Server: Registers users with the same "oshi" in a community and provides an environment where they can share information. For example, associates user IDs with topics (new albums) and registers them in the community database.

[1435] Specific examples

[1436] For example, if a user types "My favorite idol recently released a new album," the following happens:

[1437] 1. Get the user's input and send it to the server.

[1438] 2. The server parses the input and extracts intent and entities.

[1439] 3. The dialogue engine generates a response about "new album."

[1440] 4. Retrieve the relevant album information from the database and enrich the response.

[1441] 5. Display the generated response in the user's UI.

[1442] 6. The community feature allows you to share information with other users who are interested in the same album.

[1443] The system of this invention allows users to have in-depth discussions about their favorites and gain new perspectives through the latest information and interactions with other users. This system not only deepens users' understanding and empathy for their favorites, but also enables them to share a variety of information through the community.

[1444] The processing flow will be explained below.

[1445] Step 1:

[1446] The user talks about their favorite idol. For example, they input something like, "My favorite idol recently released a new album."

[1447] Step 2:

[1448] The terminal receives user input. In the case of voice input, the voice recognition module converts the voice into text and obtains the text data.

[1449] Step 3:

[1450] The terminal sends the acquired user input to the server. Specifically, it sends text data to the server via an HTTP request.

[1451] Step 4:

[1452] The server analyzes the input data received from the device, and the dialogue engine uses NLP technology to tokenize the input text and extract intent and entities.

[1453] Step 5:

[1454] The server's dialogue engine generates an appropriate response based on the analysis results. For example, if the extracted intent is about a "new album," it generates a response such as "Tell me more about that album!"

[1455] Step 6:

[1456] The server retrieves relevant information from the database. Based on the intent and entities retrieved by the dialogue engine, the database is queried for additional information about the "new album."

[1457] Step 7:

[1458] The server uses the information it obtains to enhance the response. For example, the response "Tell me more about that album!" can be enhanced to "Tell me more about that album! Your recent reviews have been great."

[1459] Step 8:

[1460] The server sends the final response to the terminal, and returns the data including the response to the terminal as an HTTP response.

[1461] Step 9:

[1462] The device displays the response received from the server in the user's UI. For example, the interactive display module might display a message on the screen saying, "Tell me more about that album! Your recent reviews have been great."

[1463] Step 10:

[1464] The server prepares to share information with other users who are interested in the same "oshi." Specifically, it associates the user ID with the topic (new album) and registers it in the community database.

[1465] Step 11:

[1466] The server matches users who share the same interests through the community function. For example, it creates a list of users who share an interest in the same "new album" and notifies each other of them.

[1467] Through these steps, the system of the present invention allows users to have in-depth discussions about their favorites and obtain new information. It also provides an environment for users to interact with other users who share an interest in the same favorites.

[1468] Example 1

[1469] 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."

[1470] In recent years, the spread of digital content over the Internet has increased opportunities for users to discuss their favorite things. However, systems that allow users to obtain information about their favorite things and share it with other users are still lacking. In particular, there is a need for technological solutions that can naturally analyze the content entered by users, generate appropriate responses, and provide related information to enable deeper communication. There is also a need for an environment where users with similar interests can easily share information.

[1471] 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.

[1472] In this invention, the server includes means for acquiring input from a user, means for analyzing the acquired user input and extracting intent and entities, means for generating an appropriate response based on the extracted intent and entities, means for acquiring related information from a database and enhancing the response content, means for displaying the generated response to the user, means for providing a community function for sharing information with other users who share the same interests, means for acquiring the latest information using an external interface and periodically updating the database, and means for the dialogue engine to utilize natural language processing technology. This allows users to have in-depth discussions about their "oshi," obtain the latest related information, and share information with other users who share the same interests.

[1473] A "user" is an entity that uses this system to input information about their "favorite" and interact with other users.

[1474] "Means for obtaining input" refers to a function for sending text and voice data entered by a user through the device's UI to a server.

[1475] "Means for extracting intent and entities" is a function that uses natural language processing technology to analyze and identify the purpose and subject of interest (intent and entity) of a topic from user input data.

[1476] The "means for generating a response" is the function that creates an appropriate reply based on the extracted intent and entities.

[1477] A "database" is an information storage device that stores information related to a user's "favorites."

[1478] The "means for enhancing response content" is a function that further enriches the generated response based on related information obtained from the database.

[1479] The "means for displaying a response" is a function for displaying the generated response on the user's terminal.

[1480] "Means for providing community functions" refers to functions that allow users who are interested in the same "favorite" to share information and interact with each other.

[1481] An "external interface" is a connection that allows a system to exchange data with external sources.

[1482] "Natural language processing technology" is a series of technologies that use computers to understand, analyze, and generate language used by humans.

[1483] This invention is an interactive system that allows users to discuss their favorites in depth. The system analyzes user input, generates appropriate responses, provides relevant information, and has a community function that allows users to interact with other users who share the same favorites.

[1484] System Configuration

[1485] 1. Server Configuration

[1486] Database (DB): This is the core part of the system and stores a wealth of information about users' favorites.

[1487] Dialogue engine: Manages user interactions and uses natural language processing (NLP) techniques to analyze user input and extract intent and entities.

[1488] Information collection module: Uses an external interface to obtain the latest information about "oshi" and update the database.

[1489] Community management module: Manages information to enable users to interact with each other and, if necessary, matches users with the same "oshi" (favorites).

[1490] 2. Terminal Configuration

[1491] User Interface (UI): The screen through which the user interacts with the system, supporting text and voice input.

[1492] Voice recognition and text input module: Serves as a means of user input and has functions such as converting voice input into text.

[1493] Interactive display module: displays the response received from the server to the user.

[1494] Specific processing of the program

[1495] 1. User Input Processing

[1496] User: The user starts talking about their favorite idol in the UI. For example, they might say, "My favorite idol recently released a new album."

[1497] Terminal: The terminal takes the user's input and sends the input data to the server.

[1498] 2. Input Analysis and Understanding

[1499] Server: Analyzes input data received from the device. The dialogue engine uses NLP technology to extract user intent (e.g., "I want to talk about the new album") and entities (e.g., "my favorite").

[1500] 3. Generating an appropriate response

[1501] Server: The dialogue engine generates an appropriate response based on the analysis, for example, "Tell me more about that album!"

[1502] 4. Providing information about your favorites

[1503] Server: Retrieves information about the new album from a database. Uses this information to enhance the original response, such as "Tell me more about that album! Your recent reviews were great."

[1504] 5. Viewing the Response

[1505] Terminal: Displays the generated response in the user's UI, where the user can see the response on the interactive screen.

[1506] 6. Community Features

[1507] Server: Registers users with the same "oshi" in a community and provides an environment where they can share information. For example, associates user IDs with topics (new albums) and registers them in the community database.

[1508] Prompt Sentence Examples

[1509] Examples of prompts to input to the generative AI model include:

[1510] Something like, "If a user says, 'My favorite idol recently released a new album,' please provide detailed instructions on how to use a dialogue engine to generate a response."

[1511] The system of this invention allows users to have in-depth discussions about their favorites and gain new perspectives through the latest information and interactions with other users. This system not only deepens users' understanding and empathy for their favorites, but also enables them to share a variety of information through the community.

[1512] The specific hardware and software used

[1513] Natural Language Processing (NLP) libraries: TensorFlow, PyTorch

[1514] Database management systems: MySQL, PostgreSQL

[1515] External Interface: RESTful API

[1516] User Interface (UI): HTML, CSS, JavaScript

[1517] Speech recognition module: Google Speech-to-Text API, Microsoft Azure Cognitive Services

[1518] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1519] Step 1:

[1520] User: The user enters text into the UI. For example, they might type, "My favorite idol recently released a new album." Specifically, the user enters text using the keyboard and then presses the "Send" button to send the text to the device.

[1521] Step 2:

[1522] Terminal: Acquires the input text data and sends it to the server. Specifically, the terminal sends the acquired text data to the server using an HTTP POST request. The input is the user's text data, and the output is an HTTP request sent to the server.

[1523] Step 3:

[1524] Server: Received user data is temporarily stored in memory, and the dialogue engine analyzes the data. Specifically, the server saves the received data in a memory buffer and passes it to the dialogue engine for processing. The input is the text data of the HTTP request, and the output is text data prepared for analysis.

[1525] Step 4:

[1526] Server: The dialogue engine uses natural language processing (NLP) techniques to analyze user input and extract intents and entities. Specifically, the dialogue engine performs tokenization, morphological analysis, and grammatical analysis to extract intents and entities in JSON format. The input is prepared text data, and the output is JSON data containing intents and entities.

[1527] Step 5:

[1528] Server: Generates a response based on the extracted intent and entities. The dialogue engine generates a basic response such as "Tell me more about that album!" based on the analysis results. Specifically, the response generation logic generates candidate responses using the analysis results as arguments. The input is JSON data containing the intent and entities, and the output is basic response text.

[1529] Step 6:

[1530] Server: Queries the database to retrieve relevant information. Specifically, the server executes an SQL query to retrieve data about the latest album of "oshi" from the database. The input is the response text and relevant query information, and the output is the additional information returned from the database.

[1531] Step 7:

[1532] Server: Enhances the response based on the information retrieved from the database. Generates a response such as "Tell me more about that album! Your recent reviews were great." Specifically, it inserts the retrieved information into a response template to construct the final response. The input is the basic response text and additional information from the database, and the output is the enhanced response text.

[1533] Step 8:

[1534] Server: Sends the generated response to the terminal. Specifically, the server returns the generated response to the terminal as an HTTP response. The input is the enhanced response text, and the output is the HTTP response sent to the terminal.

[1535] Step 9:

[1536] Terminal: The generated response is displayed in the user's UI. Specifically, the terminal displays the response text in a UI component. The input is the HTTP response from the server, and the output is the response text displayed in the UI.

[1537] Step 10:

[1538] Server: Registers users with the same "favorites" in a community and provides an environment where they can share information. Specifically, it associates user IDs with topics (new albums) and registers them in a community database, then searches for and matches users with common interests. The input is the user's interest information, and the output is the community registration information and matching results.

[1539] (Application example 1)

[1540] 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."

[1541] Traditional dialogue systems do not provide an interactive environment for users to discuss their interests and "oshi" in depth, and interactions with other users are limited. Furthermore, the lack of systems that utilize new devices such as smart glasses results in a suboptimal user experience. Therefore, there is a need to provide a new type of virtual space where users can discuss "oshi" and share their interests.

[1542] 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.

[1543] In this invention, the server includes means for acquiring input from a user, means for analyzing the acquired user input and extracting an intent and an entity, means for generating an appropriate response based on the extracted intent and entity, means for acquiring related information from a database and enhancing the response content, means for displaying the generated response to the user, means for providing a community function for sharing information with other users who share the same interest, and means for displaying the response to the user in a virtual space using smart glasses and enabling interaction with other users. This allows users to talk about their "favorites" through the smart glasses and interact with other users in the virtual space.

[1544] A "means for obtaining user input" is an interface or device that captures text or voice data entered by a user and transmits it to the system.

[1545] "Means for parsing captured user input and extracting intent and entities" means techniques or processes for analyzing user-entered text or voice data and extracting user intent and identifiable entities from that data.

[1546] "Means for generating an appropriate response based on the extracted intent and entity" refers to an algorithm or program for creating an optimal response based on the user's intent and entity information.

[1547] The "means for retrieving relevant information from a database and enhancing the response content" is a system for retrieving information related to the user's intention from a database and incorporating that information into the response to enrich the response content.

[1548] "Means for displaying the generated response to the user" refers to a display or interface that allows the user to see the response generated by the system.

[1549] "Means for providing a community function for sharing information with other users who share the same interests" refers to a system for building and operating an online community where users can empathize with other users and exchange information.

[1550] "Means for displaying responses to a user in a virtual space using smart glasses and enabling the user to interact with other users" refers to technology that utilizes smart glasses to display responses from an interactive system to a user and simultaneously enable the user to communicate with other users in a virtual space.

[1551] The present invention provides an interactive system that allows users to have in-depth discussions about their interests. The system uses smart glasses to provide users with interactive responses and has the ability to interact with other users who share the same interests in a virtual space. Specific embodiments of the system are described below.

[1552] System Configuration

[1553] 1. Server Configuration

[1554] Database (DB): This is the core part of the system and stores a wealth of information about users' "push."

[1555] Dialogue engine: Manages user interactions and uses natural language processing (NLP) techniques to analyze user input and extract intent and entities.

[1556] Information collection module: Obtains the latest information on "push" through external APIs, etc., and updates the database.

[1557] Community management module: Manages information to enable users to interact with each other and, if necessary, matches users with the same interests.

[1558] 2. Terminal Configuration

[1559] User Interface (UI): The screen through which the user interacts with the system, supporting text and voice input.

[1560] Voice recognition and text input module: Serves as a means of user input and has functions such as converting voice input into text.

[1561] Interactive display module: displays the response received from the server to the user.

[1562] Smart glasses: Devices that support viewing and interaction in virtual spaces.

[1563] Program processing explanation

[1564] The server first obtains input from the user. The user's input is captured through the smart glasses' voice recognition and text input module. The obtained user input is sent to the server and analyzed by the dialogue engine. The dialogue engine uses natural language processing technology to extract the user's intent and entities.

[1565] The server then generates an appropriate response based on the extracted intent and entities, leveraging a generative AI model to create the optimal message that addresses the user's interests, and enriching the response with relevant information from the database and adding the latest information using external APIs.

[1566] The generated responses are displayed to the user through smart glasses from the server, allowing the user to obtain detailed information about their "push" and interact with other users with the same interests in a virtual space. The community management module matches users with the same "push" and provides a forum for information sharing.

[1567] Explanation using concrete examples

[1568] For example, if a user types, "My idol recently released a new album," the following process occurs: First, the user's voice input is converted to text through the smart glasses and sent to the server. The dialogue engine analyzes this input and extracts intent and entities. The server uses a generative AI model to generate a response such as, "Tell me more about that album!" and adds additional information, such as, "The recent reviews were also positive," based on the latest information retrieved from the database and external APIs. The generated response is then displayed on the smart glasses' display.

[1569] An example prompt based on a generative AI model is:

[1570] User: My favorite guy recently released a new album.

[1571] System: Tell us more about the album! It's received some great reviews recently.

[1572] This system allows users to have in-depth discussions about "pushing" and gain new perspectives through the latest information and interactions with other users.

[1573] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1574] Step 1:

[1575] The user inputs either by voice or text. The smart glasses' voice recognition and text input module converts the user's input into text data and sends it to the server. At this stage, the input is the user's speech, and the output is text data.

[1576] Step 2:

[1577] The server analyzes the text data received from the device using a dialogue engine. The dialogue engine uses natural language processing technology to extract the user's intent and entities from the text data. At this stage, the input is text data, and the output is the analyzed intent and entities.

[1578] Step 3:

[1579] The server generates an appropriate response based on the extracted intent and entities. Using a generative AI model, it creates a message that best suits the information the user is looking for and the flow of the conversation. The input at this stage is the intent and entities, and the output is the generated response.

[1580] Step 4:

[1581] The server retrieves relevant information from the database to enhance the generated response. In addition, it retrieves the latest information from an external API through an information collection module and adds it to the response. The input at this stage is the generated response and a database query, and the output is the enhanced response.

[1582] Step 5:

[1583] The server sends the enhanced response to the terminal. The interactive display module of the terminal receives the response and displays it on the display of the smart glasses. At this stage, the input is the enhanced response, and the output is the display on the display of the smart glasses.

[1584] Step 6:

[1585] The server's community management module identifies other users with similar interests and provides an environment for sharing information. Users can interact with each other in a virtual space and discuss common interests. The input at this stage is the user's interest information, and the output is interactions with other users who have been matched.

[1586] 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.

[1587] The following describes an embodiment of the present invention. The present invention is an interactive system that allows users to have in-depth discussions about their favorite characters. This system not only analyzes user input, generates appropriate responses, and provides relevant information, but also combines an emotion engine that recognizes the user's emotions and adjusts responses accordingly. Specific program processing of the system is described below in natural language.

[1588] System Configuration

[1589] 1. Server Configuration

[1590] Database (DB): Stores information about the user's "oshi" and the user's past emotional data.

[1591] Dialogue engine: Manages user interactions and uses natural language processing (NLP) techniques to analyze user input and extract intent and entities.

[1592] Emotion engine: Responsible for inferring emotions from user input and tailoring responses to match those emotions.

[1593] Information collection module: Obtains the latest information about "oshi" through external APIs, etc., and updates the database.

[1594] Community management module: Manages information to enable users to interact with each other and, if necessary, matches users with the same "oshi" (favorites).

[1595] 2. Terminal Configuration

[1596] User Interface (UI): The screen through which the user interacts with the system, supporting text and voice input.

[1597] Speech recognition and text input module: Takes user input and converts it to text in case of voice input.

[1598] Interactive display module: displays the response received from the server to the user.

[1599] Program Processing

[1600] 1. User Input Processing

[1601] User: The user starts talking about their favorite idol in the UI. For example, they might say, "My favorite idol recently released a new album."

[1602] Terminal: Takes user input and sends that data to the server.

[1603] 2. Input Analysis and Understanding

[1604] Server: Analyzes input data received from the device. The dialogue engine uses NLP technology to extract user intent (e.g., "I want to talk about the new album") and entities (e.g., "my favorite").

[1605] 3. Emotional Recognition

[1606] Server: The emotion engine recognizes emotions from user input, for example identifying emotions such as "happy," "excited," and "sad."

[1607] 4. Generating the Response

[1608] Server: The dialogue engine generates an appropriate response based on the analysis and emotion recognition results. For example, if the user's emotion is "excited," the response generated is "That's great! Tell me more about that album!"

[1609] 5. Providing information about your favorites

[1610] Server: Retrieves information about the new album from a database. Uses this information to enhance the original response, for example, "Tell me more about that album! Your recent reviews were great."

[1611] 6. Regulating responses based on emotions

[1612] Server: After receiving additional information, the emotion engine further tailors the response based on the user's emotion. For example, if the user expresses "sadness," it generates a response such as "There are many moving songs on that album."

[1613] 7. Displaying the Response

[1614] Device: The generated response is displayed in the user's UI. For example, the interactive display module might display a message on the screen saying, "Tell me more about that album! Your recent reviews were great."

[1615] 8. Recording Emotional Data

[1616] Server: The emotion engine records the user's emotional data and uses it to improve the user experience during ongoing interactions.

[1617] 9. Community Features

[1618] Server: Registers users with the same "oshi" in a community and provides an environment where they can share information. For example, associates user IDs with topics (new albums) and registers them in the community database.

[1619] Specific examples

[1620] For example, if a user types "My favorite idol recently released a new album," the following happens:

[1621] 1. Get the user's input and send it to the server.

[1622] 2. The server parses the input and extracts intent and entities.

[1623] 3. The server recognizes the emotion "excited" from the input.

[1624] 4. The dialogue engine generates a response based on the analysis and emotion recognition results.

[1625] 5. Retrieve information about new albums from the database to enhance the response.

[1626] 6. The emotion engine tailors the response to "That's great! Tell me more about that album!"

[1627] 7. Display the response in the user's UI.

[1628] 8. The emotion engine records the user's emotional data and uses it for the next conversation.

[1629] 9. The server updates the community database and matches users with similar interests.

[1630] In this way, the system of the present invention analyzes user input, recognizes emotions, generates responses, and provides relevant information. It also continuously records user emotional data to enhance the interaction experience. It also provides a community function, encouraging interaction with other users who share the same "oshi" (favorite). Through this system, users can have in-depth discussions about their "oshi" and gain new information and perspectives.

[1631] The processing flow will be explained below.

[1632] Step 1:

[1633] The user talks about their favorite idol. For example, they input something like, "My favorite idol recently released a new album."

[1634] Step 2:

[1635] The terminal receives user input. In the case of voice input, the voice recognition module converts the voice into text and obtains the text data.

[1636] Step 3:

[1637] The terminal sends the acquired user input to the server. Specifically, it sends text data to the server via an HTTP request.

[1638] Step 4:

[1639] The server analyzes the input data received from the device, and the dialogue engine uses NLP technology to tokenize the input text and extract intent and entities.

[1640] Step 5:

[1641] The server's dialogue engine generates an appropriate response based on the analysis results. For example, if the extracted intent is about a "new album," it generates a response such as "Tell me more about that album!"

[1642] Step 6:

[1643] The server uses an emotion engine to recognize emotions from user input, such as "excitement," "happiness," and "sadness."

[1644] Step 7:

[1645] The server adjusts the response based on the emotion recognition result. For example, if it recognizes "excited," it adjusts the normal response to "That's great! Tell me more about that album!"

[1646] Step 8:

[1647] The server retrieves relevant information from the database. Based on the intent and entities retrieved by the dialogue engine, it retrieves information about "new album" from the database.

[1648] Step 9:

[1649] The server uses the information it obtains to enhance the response, for example, "Tell me more about that album! Your recent reviews have been great."

[1650] Step 10:

[1651] The device displays the response received from the server in the user's UI. For example, the interactive display module might display a message on the screen saying, "Tell me more about that album! Your recent reviews have been great."

[1652] Step 11:

[1653] The server uses an emotion engine to record the user's emotional data, which is used to improve the user experience in future interactions.

[1654] Step 12:

[1655] The server provides a community function, allowing users with the same "favorites" or interests to register in a community and share information.

[1656] Step 13:

[1657] The server matches users within the community and allows them to share information with others who share the same interests, such as their opinions and thoughts on a new album.

[1658] Through these steps, the system of the present invention allows users to have in-depth discussions about their favorites and gain new information. It also recognizes users' emotions and generates responses based on them, providing a more personalized experience. It also provides an environment where users can interact with other users who share the same favorites.

[1659] Example 2

[1660] 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."

[1661] While conventional dialogue systems can analyze user input and generate appropriate responses, they lack the ability to generate responses that take into account the user's emotions and share information with other users who share the same interests. Therefore, there is a need to improve the user experience and provide more personalized responses and community functions.

[1662] 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.

[1663] In this invention, the server includes means for analyzing a user input and extracting an intention and an entity, means for recognizing an emotion from the user input, means for generating an appropriate response based on the extracted intention and entity and the recognized emotion, means for retrieving related information from a database and enhancing the response content, means for adjusting the response content based on the user's emotion, means for recording the user's emotion data, and means for providing a community function for sharing information with other users who share the same interest, thereby enabling the generation of a response tailored to the user's emotion and the sharing of information among users who share the same interest.

[1664] "Means of acquisition" refers to the ability to input user input into the system as voice or text data.

[1665] "Means of analyzing and extracting intent and entities" refers to the function of using natural language processing technology to analyze the meaning of user input data and identify specific actions or targets.

[1666] "Means for recognizing emotions" refers to the function of determining and identifying the user's emotional state from input data.

[1667] "Means for generating an appropriate response" refers to the function of generating a reply to the user based on the analyzed intent and recognized emotion.

[1668] "Means of obtaining relevant information and enhancing response content" refers to the function of obtaining relevant data from databases within the system or external interfaces and enriching the information provided to users.

[1669] "Means for adjusting response content" refers to the ability to modify and optimize the generated response based on the perceived user sentiment.

[1670] "Means for displaying to the user" refers to the ability to visually or audibly present the generated response to the user.

[1671] "Means for recording emotional data" refers to a feature that continuously collects and stores data about a user's emotional state.

[1672] "Means for providing community functions" refers to functions that provide an environment where users with similar interests can share information and communicate with each other.

[1673] This invention provides an interactive system that allows users to discuss their favorites. The system not only analyzes user input to generate appropriate responses and provide relevant information, but also recognizes user emotions and adjusts responses accordingly.

[1674] System configuration overview

[1675] Server Configuration

[1676] 1. Database: Stores information about users' favorites and their past emotional data. For example, a database management system such as MySQL or MongoDB is used.

[1677] 2. Dialogue Engine: Manages user interactions and analyzes user input using Natural Language Processing (NLP) techniques, such as spaCy or Google Cloud Natural Language API, to extract intent and entities.

[1678] 3. Emotion engine: Infers emotions from user input and tailors responses to match those emotions. This leverages emotion recognition tools such as the BERT model and Amazon Comprehend.

[1679] 4. Information collection module: Obtains the latest information about "oshi" through external APIs and updates the database. For example, it uses Twitter API or News API.

[1680] 5. Community management module: Manages information so that users can interact with each other and, if necessary, matches users with the same "oshi" (favorites).

[1681] Device Configuration

[1682] 1. User Interface (UI): Provides a screen for users to interact with the system and supports text and voice input. Examples include web browsers and mobile apps.

[1683] 2. Speech recognition and text input module: Takes user input and converts it to text in the case of voice input. This may use a speech recognition service such as the Google Speech-to-Text API.

[1684] 3. Interaction display module: displays the response received from the server to the user, for example, as a text message in a chat window.

[1685] Program processing overview

[1686] The specific processing of this system will be explained below.

[1687] Processing User Input

[1688] User: The user starts talking about their favorite idol in the UI. For example, they might say, "My favorite idol recently released a new album."

[1689] Terminal: The terminal takes the user's input and sends the data to the server, converting it to text using voice recognition technology in the case of voice input.

[1690] Parsing and understanding input

[1691] Server: Analyzes input data received from the device. The dialogue engine uses NLP technology to extract the user's intent and entities.

[1692] Emotion recognition

[1693] Server: The emotion engine recognizes emotions from user input, for example identifying emotions such as "happy," "excited," and "sad."

[1694] Response generation and adjustment

[1695] Server: The dialogue engine generates an appropriate response based on the analysis and emotion recognition results. It may use a generative AI model to form the response. For example, it generates a response like, "That's great! Tell me more about that album!"

[1696] Server: Retrieve information about the new album from the database and complete the response, for example, including additional information like "Tell me more about that album! Your recent reviews were great."

[1697] Viewing the response

[1698] Terminal: The generated response is displayed in the user's UI. For example, the interactive display module might display a message on the screen saying, "Tell me more about that album! Your recent reviews were great."

[1699] Emotional data recording and community features

[1700] Server: The emotion engine records the user's emotional data and uses it to improve the user experience in future interactions. In addition, the server registers users with the same "oshi" as its users in a community, providing an environment where they can share information.

[1701] Specific examples

[1702] For example, if a user types "My favorite idol recently released a new album," the following happens:

[1703] 1. Get the user's input and send it to the server.

[1704] 2. The server parses the input and extracts intent and entities.

[1705] 3. The server recognizes the emotion "excited" from the input.

[1706] 4. The dialogue engine generates the response, "That's great! Tell me more about that album!"

[1707] 5. Retrieve information about the new album from the database and complete the response with, "The recent reviews were great."

[1708] 6. Display the generated response in the user's UI.

[1709] 7. Provide a community function to record emotional data and share information with other users who share the same interests.

[1710] Prompt Sentence Examples

[1711] Here are some example prompts to input to the generative AI model:

[1712] User: My favorite artist recently released a new album.

[1713] Server: That's great! Tell us more about the album! It's had some great reviews recently.

[1714] Through this system, users can have in-depth discussions about their favorites and gain new information and perspectives.

[1715] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1716] The flow of this system's program processing

[1717] Step 1:

[1718] Users provide topics about their favorites.

[1719] Input: The user says to the UI, "My favorite idol recently released a new album."

[1720] Specific action: The user speaks into a microphone or types into a text field.

[1721] Step 2:

[1722] The terminal obtains the user's input.

[1723] Input: User voice or text data.

[1724] What it does: The device converts voice input to text using the Google Speech-to-Text API. For text input, it retrieves the text directly from the UI.

[1725] Output: The converted or retrieved text data.

[1726] Step 3:

[1727] The terminal sends the input data to the server.

[1728] Input: The converted or retrieved text data.

[1729] Specific operation: The terminal sends data to the server as an HTTP request.

[1730] Output: The text data sent to the server.

[1731] Step 4:

[1732] The server parses the input data and extracts intent and entities.

[1733] Input: Text data received from the terminal.

[1734] What it does: The server uses a natural language processing engine (e.g., spaCy or Google Cloud Natural Language API) to parse the text and extract intent and entities.

[1735] Output: Extracted intent and entity data.

[1736] Step 5:

[1737] The server recognizes the user's emotions.

[1738] Input: Extracted intent and entity data.

[1739] Specific operation: The server analyzes the user's emotions using emotion recognition tools such as the BERT model and Amazon Comprehend.

[1740] Output: Recognized emotion data.

[1741] Step 6:

[1742] The server generates an appropriate response.

[1743] Input: Extracted intent and entity data, and recognized emotion data.

[1744] What it does: The dialogue engine uses a generative AI model (e.g., OpenAI GPT-3) to generate a response based on user input and sentiment. The prompt is "User: My favorite artist recently released a new album. Server: That's great! Tell me more about it!"

[1745] Output: The generated response text.

[1746] Step 7:

[1747] The server retrieves relevant information from a database to complete the response.

[1748] Input: The generated response text.

[1749] What happens next: The server performs a database query to retrieve additional information about the new album.

[1750] Output: The completed response text.

[1751] Step 8:

[1752] The server adjusts the response based on the emotion.

[1753] Input: The completed response text.

[1754] What it does: The emotion engine fine-tunes the final response based on the user's emotional state. For example, if the user expresses "sadness," it adjusts the response to "There are many touching songs on that album."

[1755] Output: The final response text.

[1756] Step 9:

[1757] The terminal displays the final response to the user.

[1758] Input: The final response text.

[1759] Specific operation: The dialogue display module displays the response text in a chat window on the UI.

[1760] Output: A text message that the user can see or hear.

[1761] Step 10:

[1762] The server records the emotion data.

[1763] Input: Recognized emotion data.

[1764] Specific operation: The emotion engine stores emotion data in a database in an appropriate format.

[1765] Output: Recorded emotion data.

[1766] Step 11:

[1767] The server updates the community database.

[1768] Input: User intent and perceived emotion, along with associated album information.

[1769] Specific operation: The server associates the user ID with topic information and inserts it into the community database, which supports matching with other users who share the same interests.

[1770] Output: Updated community database.

[1771] summary

[1772] Through these steps, the system supports users in conversations about their favorites, provides personalized responses that take their emotions into account, provides relevant information, and uses community features to encourage interaction with other users who share the same interests.

[1773] (Application example 2)

[1774] 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."

[1775] Current content distribution services lack interactive systems that allow users to have in-depth conversations about specific artists or creators and receive responses that reflect their own emotions. Furthermore, systems that provide users with real-time access to the latest content they desire and enable users with similar interests to effectively share information with each other are lacking. Therefore, new technological approaches are needed to increase user satisfaction and improve engagement.

[1776] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for recognizing emotions from user input and adjusting responses to match the user's emotions, means for providing the latest content information in real time, and means for providing a community function for sharing information with other users who share the same interests. This enables users to receive interactive responses tailored to their emotions, obtain new content information in real time, and easily share information with other users who share the same interests.

[1777] A "means for obtaining input from a user" is anything that allows a user to input information into a system, including text input and voice input.

[1778] "Means for analyzing captured user input and extracting intent and entities" refers to the process of analyzing input information from a user and identifying its intent (purpose) and entities (relevant key elements).

[1779] "Means for generating an appropriate response based on the extracted intent and entities" is a function that generates appropriate responses or information for the user according to the intent and entities obtained through analysis.

[1780] "Means for retrieving relevant information from a database and enhancing the response content" refers to the process of retrieving necessary information from a database and enhancing the response content to form the most appropriate answer to a user's question or request.

[1781] "Means for displaying the generated response to the user" means a method for providing the system-generated response to the user visually or audibly.

[1782] "Means for providing a community function for sharing information with other users who share the same interests" refers to a function that provides a forum for users who share the same interests to share information and interact with each other.

[1783] "Means for recognizing emotions from user input and adjusting responses to match the user's emotions" refers to technology that analyzes emotions from user input and flexibly changes the response content according to those emotions.

[1784] "Means for providing the latest content information in real time" refers to a function that obtains the latest content information from the Internet and other data sources and provides it to users in a timely manner.

[1785] The present invention is an interactive system that recognizes a user's emotions and generates and provides appropriate responses to the user. This system allows users to have in-depth discussions about specific artists or creators and receive responses that are in tune with their emotions.

[1786] System Configuration

[1787] Server Configuration

[1788] 1. Database (DB): Stores information about the user's "oshi" and past emotional data, allowing responses to be enhanced based on previously stored information.

[1789] 2. Dialogue engine: Manages interactions with users and uses natural language processing (NLP) techniques to analyze user input and extract intent and entities.

[1790] 3. Emotion engine: Responsible for inferring emotions from user input and tailoring responses to match those emotions.

[1791] 4. Information collection module: This module obtains the latest information about the "oshi" through external APIs, etc., and updates the database.

[1792] 5. Community management module: Manages information to enable users to interact with each other and, if necessary, matches users with the same "oshi" (favorites).

[1793] Device Configuration

[1794] 1. User Interface (UI): The screen through which the user interacts with the system, supporting text and voice input.

[1795] 2. Speech recognition and text input module: Takes user input and converts it to text in case of voice input.

[1796] 3. Interactive display module: displays the response received from the server to the user.

[1797] Detailed explanation of the process

[1798] 1. Getting user input:

[1799] The user begins speaking to the system through their device, for example, by entering text or voice, "My favorite idol recently released a new album."

[1800] 2. Input analysis and intent extraction:

[1801] The server's dialogue engine uses NLP technology to analyze user input received from the device and extract intent and entities.

[1802] 3. Emotion Recognition:

[1803] The emotion engine recognizes emotions from user input, for example identifying emotions such as "excited," "happy," or "sad."

[1804] 4. Generate response:

[1805] The server's dialogue engine generates an appropriate response based on the analysis and emotion recognition results. For example, if the user is excited, it generates the response "That's great! Tell me more about that album!"

[1806] 5. Additional Information:

[1807] The database retrieves the latest information about the target "oshi" and enriches the response, for example, "Tell me more about that album! The recent reviews were great."

[1808] 6. View the response:

[1809] The generated response is displayed to the user through an interactive display module, where the user can view the response on the screen.

[1810] 7. Emotional Data Recording:

[1811] The emotion engine records user emotional data and uses it to improve the user experience during ongoing interactions.

[1812] 8. Providing Community Features:

[1813] The server updates the community database and matches users with other users who share the same interests, allowing them to share new information and perspectives.

[1814] Examples and prompts

[1815] For example, if a user types, "My favorite idol recently released a new album," the system will respond as follows:

[1816] "That's great! Tell me more about that album!" (if the user is excited)

[1817] "Tell me more about that album! I've seen some great reviews recently." (If you've added the latest information)

[1818] This allows users to receive responses that are in tune with their emotions, obtain new content information in real time, and easily share information with other users who share the same interests.

[1819] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1820] Step 1: Getting User Input

[1821] The user inputs text or voice through the device's UI. For example, the user might input, "My favorite artist recently released a new album." The device receives this input and converts it into data to send to the server. In the case of voice input, the voice is converted into text by the voice recognition and text input module. The input data is in the form of text data.

[1822] Step 2: Parse input and extract intent

[1823] The server receives user input sent from the device, and the dialogue engine uses NLP technology to analyze the user input and extract intent (questions or desired information) and entities (such as specific artist or content names).

[1824] Type: "My idol recently released a new album."

[1825] Output: Intent = "I want to talk about the album", Entity = "Oshi"

[1826] Step 3: Recognize emotions

[1827] The emotion engine on the server recognizes emotions from the analyzed user input and identifies emotions such as "excitement," "happiness," and "sadness" based on the analysis results.

[1828] Type: "My idol recently released a new album."

[1829] Output: emotion = "excited"

[1830] Step 4: Generate a response

[1831] The server's dialogue engine generates an appropriate response based on the analysis and emotion recognition results. For example, if the user's emotion is "excited," it generates the response "That's great! Tell me more about that album!"

[1832] Input: Intent = "I want to talk about the album", Entity = "oshi", Emotion = "excited"

[1833] output:initial response="That's great! Tell me more about that album!"

[1834] Step 5: Provide additional information

[1835] The server retrieves the latest information about the target "oshi" from a database to enhance the response. For example, it retrieves the latest album information using an external API and generates a response such as "Tell me more about that album! Your recent reviews have been great."

[1836] Input:initial response="That's great! Tell me more about that album!"

[1837] Output: Enhanced Response = "That's great! Tell me more about that album! I saw some great reviews recently."

[1838] Step 6: View the response

[1839] The server generates a response and sends it to the terminal, where an interactive display module displays the response to the user, who can view the response on their screen.

[1840] Input:Enhanced response="That's great! Tell me more about that album! I saw some great reviews recently."

[1841] Output: The message displayed to the user

[1842] Step 7: Recording Emotional Data

[1843] The emotion engine on the server records the user's emotion data and uses it to improve the user experience during ongoing interactions. This recorded data is used in future interactions.

[1844] Input: emotion = "excited"

[1845] Output: Recorded emotion data

[1846] Step 8: Providing community features

[1847] The server updates the community database and matches users with the same interests. This feature allows users to share information with other users who are interested in the same "oshi."

[1848] Input: User ID, Interest = "Favorite"

[1849] Output: Community database updates, matching user information

[1850] Through the above processing steps, users can receive interactive responses that are in tune with their emotions, obtain the latest content information in real time, and easily share information with other users who share the same interests.

[1851] 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.

[1852] 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.

[1853] 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.

[1854] 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.

[1855] 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.

[1856] 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.

[1857] 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).

[1858] 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.

[1859] 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."

[1860] 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.

[1861] 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).

[1862] 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.

[1863] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1864] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1865] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1866] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1867] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1868] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1869] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1870] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1871] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1872] The following is further disclosed regarding the above embodiment.

[1873] (Claim 1)

[1874] a means of obtaining input from a user;

[1875] a means for parsing the captured user input and extracting intent and entities;

[1876] means for generating an appropriate response based on the extracted intent and entities;

[1877] a means of retrieving relevant information from a database to enhance the response; and

[1878] a means for displaying the generated response to the user;

[1879] A means to provide community features for sharing information with other users who share the same interests;

[1880] A system including:

[1881] (Claim 2)

[1882] 10. The system of claim 1, wherein natural language processing techniques are used to analyze user input.

[1883] (Claim 3)

[1884] 2. The system according to claim 1, wherein information used to generate a response is normally obtained from a database, and new information is periodically obtained using an external API.

[1885] "Example 1"

[1886] (Claim 1)

[1887] a means of obtaining input from a user;

[1888] a means for parsing the captured user input and extracting intent and entities;

[1889] means for generating an appropriate response based on the extracted intent and entities;

[1890] a means of retrieving relevant information from a database to enhance the response; and

[1891] a means for displaying the generated response to the user;

[1892] A means to provide community features for sharing information with other users who share the same interests;

[1893] A means for periodically updating the database by obtaining the latest information using an external interface;

[1894] The means by which the dialogue engine utilizes natural language processing technology;

[1895] A system including:

[1896] (Claim 2)

[1897] 10. The system of claim 1, wherein natural language processing techniques are used to analyze user input.

[1898] (Claim 3)

[1899] 2. The system according to claim 1, wherein information used for generating a response is normally obtained from a database, and new information is periodically obtained using an external interface.

[1900] "Application Example 1"

[1901] (Claim 1)

[1902] a means of obtaining input from a user;

[1903] a means for parsing the captured user input and extracting intent and entities;

[1904] means for generating an appropriate response based on the extracted intent and entities;

[1905] a means of retrieving relevant information from a database to enhance the response; and

[1906] a means for displaying the generated response to the user;

[1907] A means to provide community features for sharing information with other users who share the same interests;

[1908] a means for displaying responses to the user in a virtual space using smart glasses and enabling the user to interact with other users;

[1909] A system including:

[1910] (Claim 2)

[1911] 10. The system of claim 1, wherein natural language processing techniques are used to analyze user input and a generative AI model is used to generate responses.

[1912] (Claim 3)

[1913] 2. The system according to claim 1, wherein information used to generate a response is normally obtained from a database, and new information is periodically obtained using an external API.

[1914] "Example 2: Combining Emotion Engines"

[1915] (Claim 1)

[1916] a means of obtaining input from a user;

[1917] a means for parsing the captured user input and extracting intent and entities;

[1918] a means for recognizing emotions from user input;

[1919] a means for generating an appropriate response based on the extracted intents and entities and the recognized emotions;

[1920] a means of retrieving relevant information from a database to enhance the response; and

[1921] a means for tailoring the response content based on the user's sentiment;

[1922] a means for displaying the generated response to the user;

[1923] a means for recording user emotional data;

[1924] A means to provide community features for sharing information with other users who share the same interests;

[1925] A system including:

[1926] (Claim 2)

[1927] 10. The system of claim 1, wherein natural language processing techniques are used to analyze user input.

[1928] (Claim 3)

[1929] 2. The system according to claim 1, wherein information used for generating a response is normally obtained from a database, and new information is periodically obtained using an external interface.

[1930] "Application example 2 when combining emotion engines"

[1931] (Claim 1)

[1932] a means of obtaining input from a user;

[1933] a means for parsing the captured user input and extracting intent and entities;

[1934] means for generating an appropriate response based on the extracted intent and entities;

[1935] a means of retrieving relevant information from a database to enhance the response; and

[1936] a means for displaying the generated response to the user;

[1937] A means to provide community features for sharing information with other users who share the same interests;

[1938] a means for recognizing emotions from user input and tailoring responses to the user's emotions;

[1939] A means of providing the latest content information in real time;

[1940] A system including:

[1941] (Claim 2)

[1942] 10. The system of claim 1, wherein natural language processing techniques are used to analyze user input.

[1943] (Claim 3)

[1944] 2. The system according to claim 1, wherein information used to generate a response is normally obtained from a database, and new information is periodically obtained using an external API. [Explanation of symbols]

[1945] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means of obtaining input from a user; a means for parsing the captured user input and extracting intent and entities; means for generating an appropriate response based on the extracted intent and entities; a means of retrieving relevant information from a database to enhance the response; and a means for displaying the generated response to the user; A means to provide community features for sharing information with other users who share the same interests; A system including:

2. 10. The system of claim 1, wherein natural language processing techniques are used to analyze user input.

3. 2. The system according to claim 1, wherein information used for generating a response is normally obtained from a database, and new information is periodically obtained using an external API.

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