system

Abstract

We provide the system. [Solution] A means for selecting from multiple dialogue systems based on user requests and providing the selected dialogue system to the user's device, A means for acquiring information from the above dialogue system from an information processing device and controlling the dialogue with the user based on that information, A means for integrating a dialogue system into a device that performs physical tasks in the user's living space, and for performing dialogue according to the task at hand, A means of providing the user with the option to change the dialogue system based on the interaction with the user, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Existing dialogue agent systems have problems that it is difficult to flexibly respond when a user has different needs according to the situation and mood of the day. In addition, since the agents provided to users are monotonous, they cannot provide individual experiences and cannot meet diverse user needs.

Means for Solving the Problems

[0005] This invention provides a system that allows users to select the most suitable agent from multiple conversational agents according to their situation and mood at the time. Specifically, it includes means for providing an agent to the terminal based on the user's request, means for acquiring data from a server and controlling the conversation, and means for providing the user with options to change agents, thereby realizing a personalized conversational experience that meets the diverse needs of the user.

[0006] A "user" is a person or entity that utilizes a conversational agent system.

[0007] A "conversational agent" is a software program that has the function of providing information and offering advice through conversations with users.

[0008] A "device" refers to equipment used by a user to interface with a conversational agent, such as a smartphone or computer.

[0009] A "server" is a computing system that stores agent data and provides that data to the user's device.

[0010] "Dialogue style" refers to the specific way of speaking and response patterns that a dialogue agent uses in conversations with users.

[0011] "Selection" is the act or process of a user choosing one option from several options provided.

[0012] A "response" is a word or action that a conversational agent returns in response to user input.

[0013] "Function" refers to the ability of a system or device to perform a specific role or function. [Brief explanation of the drawing]

[0014] [Figure 1]It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

MODE FOR CARRYING OUT THE INVENTION

[0015] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0020] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor and 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), or Bluetooth (registered trademark), and the like.

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] As shown in Figure 1, the 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.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0028] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] This invention is a system that provides a personalized conversational experience by allowing the user to select from multiple conversational agents according to their situation and mood at the time. The program processing of the system based on this embodiment is described below in natural language.

[0036] Overall system flow

[0037] 1. User-selected agent

[0038] After the user launches the application on their device, a list of multiple conversational agents is displayed on the screen. This allows the user to select an agent that suits their situation and mood.

[0039] 2. Obtain necessary data and begin interaction

[0040] When a user selects a specific agent, the device retrieves data related to the selected agent from the server. The server then sends data about the selected agent's initial settings and interaction style to the device. This activates the agent on the device, initiating interaction with the user.

[0041] 3. Conducting dialogue and generating responses

[0042] Users can send questions or messages to the agent. The terminal sends this input to the server, which uses an AI engine to generate an appropriate response. This response is then sent to the terminal and displayed to the user.

[0043] 4. Agent changes and adaptations

[0044] If a user wishes to change their conversational agent, they can return to the agent selection screen and select a different agent. This allows them to seamlessly initiate conversations with agents that have different conversational styles and characteristics.

[0045] Specific example

[0046] For example, when a user needs efficient information during work, they can select a work partner agent. This agent can immediately provide detailed information regarding task management and scheduling. On the other hand, when a user wants to relax, they can choose an agent who is willing to engage in casual conversation, allowing for lighthearted dialogue tailored to everyday situations.

[0047] In this way, users can select an agent suitable for different situations on their mobile devices or PCs, and enjoy a highly personalized conversational experience.

[0048] The following describes the processing flow.

[0049] Step 1:

[0050] The user launches the application on their device, and the login screen appears. The user enters their authentication information and attempts to log in. The device sends this authentication information to the server.

[0051] Step 2:

[0052] The server checks the received authentication information against its database, and if the login is successful, it sends a list of authorized conversational agents to the user's device. The device then displays this list on its screen.

[0053] Step 3:

[0054] The user selects a suitable conversational agent from the displayed list. The terminal sends the ID of the selected agent to the server and requests related data.

[0055] Step 4:

[0056] Based on the received agent ID, the server prepares the necessary agent data and profile and sends it to the terminal. The terminal uses this data to activate the selected agent.

[0057] Step 5:

[0058] The user begins interacting with the activated agent. Messages entered by the user are sent to the server via the terminal.

[0059] Step 6:

[0060] The server analyzes the user's message and uses an AI engine to generate an appropriate response. This response is then sent to the terminal and displayed on the screen.

[0061] Step 7:

[0062] If the user wishes to change the conversational agent, they access the agent selection screen again. The terminal provides an interface for selecting a new agent, and once selected, the process from step 3 is repeated.

[0063] (Example 1)

[0064] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0065] Conventional information exchange systems have made it difficult for users to select the optimal agent from multiple information exchange agents due to insufficient information about the agents' characteristics and the user's situation. Furthermore, they lack the ability to generate appropriate responses using AI algorithms and to flexibly change information exchange agents based on user intent, highlighting the need for improved user experience.

[0066] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0067] In this invention, the server includes means for selecting from a plurality of information exchange agents after the user starts up the information processing device and providing the selected information exchange agent to the user's information processing device; means for obtaining information related to the selected information exchange agent from computing resources and controlling information exchange with the user based on that information; and means for generating a corresponding output using a generation AI algorithm based on input from the user. As a result, the user can easily select the optimal information exchange agent and flexible information exchange according to the situation is possible.

[0068] An "information processing device" is a device used by a user to operate an information exchange agent and display data.

[0069] An "information exchange agent" is a program that interacts with users, has a specific information exchange style, and generates responses in response to user input.

[0070] "Computational resources" refer to servers and cloud computing environments used for acquiring and processing data related to information exchange agents.

[0071] A "generative AI algorithm" is an algorithm that utilizes artificial intelligence technology to automatically generate appropriate responses based on user input data.

[0072] A "response" is the output that an information exchange agent generates in response to user input, and it facilitates the interaction with the user.

[0073] To implement this invention, the user first launches an application using an information processing device. At this time, the terminal displays a list of multiple information exchange agents via a user interface. When the user selects an agent according to the situation or mood, the terminal requests information related to the selected information exchange agent from a server, which is a computing resource.

[0074] The server uses a database to retrieve information about the selected agent's initial settings and interaction style. This information is typically sent to the terminal in JSON format. Upon receiving this data, the terminal activates the information exchange agent and prepares to begin interacting with the user.

[0075] When a user wishes to exchange information, the terminal collects the user's message using text input or speech recognition. This input is sent to the server, where an AI algorithm generates an appropriate response. The server uses natural language processing models such as GPT-3 (registered trademark) to analyze the user's intent and generate the most suitable response.

[0076] The generated response is returned to the terminal and displayed to the user. This allows the user to obtain the necessary information while continuing their interaction with the agent.

[0077] For example, if a user wants to relax and enjoy a light conversation, they can enter the prompt, "Tell me which agent can help me relax." The selected agent will then engage in a conversation designed to promote relaxation through everyday interactions. This allows users to select an agent suited to different situations and enjoy an optimized information exchange experience.

[0078] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0079] Step 1:

[0080] When a user launches an application on the information processing device, the terminal displays a list of multiple information exchange agents on the screen. This list is compiled based on data previously received from the server. The input is the user's launch operation, and the output is the display of the agent list. Specifically, the terminal's GUI is activated, and a brief description of each agent and a selection button are displayed.

[0081] Step 2:

[0082] When a user selects a specific agent from a list, the terminal sends the selection information to the server. The server receives this input and retrieves the agent's initial setup information and interaction style data from its database. The input is the user's agent selection, and the output is detailed data about the agent. The server packages this data in JSON format and sends it to the terminal.

[0083] Step 3:

[0084] The terminal analyzes the data received from the server and launches the selected agent. During this process, an agent instance is created based on the initial setup information, and a user interaction screen is prepared. The input is agent data from the server, and the output is an agent ready for user interaction. Specifically, the agent's character icon is displayed, and the interaction input field is activated.

[0085] Step 4:

[0086] When a user enters a message into the agent, the terminal sends that text to the server. The server uses a generative AI model to initiate a process that generates a response based on the user's message. The input is the user message, and the output is the generated response. Specifically, the server executes a natural language processing algorithm to analyze the intent of the message and generate the response.

[0087] Step 5:

[0088] The server's response is sent to the terminal, which then displays it to the user. The input is the response data from the server, and the output is the display on the user's screen. Specifically, the response is displayed in text format on the terminal's display, allowing the user to continue the conversation. This entire process enables effective communication with the conversational agent.

[0089] (Application Example 1)

[0090] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0091] In modern life, users desire to utilize different dialogue systems in diverse situations, but managing them effectively and intuitively presents a challenge. Furthermore, even in devices that assist with physical tasks, further technological advancements are needed to achieve user-optimized dialogue.

[0092] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0093] In this invention, the server includes means for selecting from a plurality of dialogue systems based on the user's request and providing the selected dialogue system to the user's device; means for acquiring information about the dialogue system from an information processing device and controlling the dialogue with the user based on that information; and means for integrating the dialogue system into a device that performs physical tasks in the user's living area and executing dialogue according to the target task. As a result, the user can select the optimal dialogue system according to various situations and enjoy seamless support, including physical tasks.

[0094] A "user" is an entity that utilizes a service or system, primarily referring to a human being, but may include other subjects of exploration as needed.

[0095] A "request" refers to a wish or need expressed by a user to fulfill a specific purpose or need.

[0096] A "dialogue system" refers to a program or process that can engage in conversation with a user, and its purpose is to provide information, entertainment, or task support.

[0097] "Device" refers to a machine or device that performs a specific function or role, and may sometimes include computers or robots.

[0098] An "information processing device" refers to a device or system that receives data, performs calculations and transformations, and outputs the results.

[0099] "Integration" refers to the act or process of connecting multiple elements to make them function as a whole.

[0100] "Physical work" refers to tasks performed through specific actions or means, and is intended to take place within the user's living area.

[0101] "Support" refers to assisting a specific activity or process and enabling its smooth implementation.

[0102] In this invention, a user can use their device to select the most suitable dialogue system from among several dialogue systems. First, the user's request is received via the user interface. Next, the server obtains information corresponding to the selected dialogue system from an information processing device. This information includes the initial settings of the dialogue system, the dialogue format, and related task information.

[0103] The server uses an AI engine running on the cloud to generate appropriate responses to user requests. During this process, data calculations are performed by a generating AI model. The generated response is sent to the user's device and presented to the user via screen or audio. Specifically, it is conceivable to use an AI engine such as OpenAI's GPT-3.

[0104] On the other hand, even in devices that perform physical actions within the user's living space, such as robots, dialogue systems are integrated. This system can initiate actions to assist physical tasks based on user selection and optimize those actions based on dialogueal instructions. Such implementations enable seamless assistance through dialogue.

[0105] For example, you can chat with a robot while relaxing in the living room on a day off, or receive cooking advice from a cooking advisor agent while you're cooking. By using prompts such as "Tell me a new pasta recipe," specific and helpful information will be provided in real time.

[0106] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0107] Step 1:

[0108] From the user's device, the user activates the system through an interface and inputs their current requests and mood. This input is sent to the system as text or voice. Based on this information, the terminal processes the user's requests as digital data and prepares to send them to the server.

[0109] Step 2:

[0110] The server receives request data sent by the user and uses an AI engine to determine which dialogue system is appropriate. In this process, a generative AI model analyzes the user's request data and generates prompt sentences. Prompt sentence generation is data processing to extract the information necessary to present choices.

[0111] Step 3:

[0112] The server retrieves information related to the appropriate dialogue system from the information processing device and transmits that information to the terminal. This information includes the initial settings and dialogue format of the target dialogue system. The server structures the retrieved data and optimizes it into a format that can be immediately responded to by the user.

[0113] Step 4:

[0114] The terminal displays a list of selectable conversational systems on its user interface based on information received from the server. The user selects a conversational system that suits their needs from the list, and the terminal sends the selection information to the server.

[0115] Step 5:

[0116] The server generates a response created by the AI ​​engine based on the selected dialogue system. The input consists of user selection information and data about the dialogue system, and the result of the calculation is an appropriate response constructed by the generating AI model. This response is then sent from the server to the terminal based on the processed data.

[0117] Step 6:

[0118] The terminal presents the user with the response received from the server. This presentation is done as text display or audio output. In parallel with this information presentation, if the user is using a physical device, the dialogue system sends instructions for physical actions to the device, and the actions are executed.

[0119] Step 7:

[0120] If the user wishes to continue the conversation, they can enter additional questions or instructions. The device then sends this back to the server, where the AI ​​engine processes it again to generate a response. The agent can also be seamlessly changed upon user request.

[0121] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0122] This invention is a dialogue agent system that combines an emotion engine to recognize user emotions, and aims to provide an optimal dialogue experience according to the user's situation and mood. Specific embodiments for carrying out this invention are shown below.

[0123] Overall system flow

[0124] First, when a user launches the application on their device, a login screen is displayed. After the user enters their authentication credentials and logs in, the server verifies the credentials. If successful, it sends a list of authorized conversational agents to the device. The device then retrieves this information and displays it to the user.

[0125] Once the user selects an agent, the device retrieves the selected agent's data from the server and begins the conversation. At this point, the emotion engine activates, analyzing the user's emotions from their voice, text messages, or facial expression data collected by the camera. Based on this analysis, the emotion engine either suggests or automatically selects the most suitable agent and conversation style.

[0126] User conversation messages are sent from the device to the server, where an AI engine generates an appropriate response. The generated response is then adjusted based on the user's emotions, as analyzed by an emotion engine, and returned to the device. This allows users to experience natural and appropriate conversations that match their mood and emotions.

[0127] Specific example

[0128] For example, if a user is feeling stressed, the emotion engine detects that emotion and suggests an agent that can calm the user. This agent engages in conversations about relaxation and offers suggestions to soothe the mood. Conversely, if the user is excited, an agent is provided that offers a positive response to support their energy.

[0129] Thus, a dialogue agent system incorporating an emotion engine can achieve highly adaptive dialogue tailored to the user's emotional needs, providing a more personalized user experience.

[0130] The following describes the processing flow.

[0131] Step 1:

[0132] When a user launches the application on their device, a login screen is displayed. The user enters their authentication information and sends an authentication request to the server.

[0133] Step 2:

[0134] The server verifies the authentication credentials, and if authentication is successful, it generates a list of authorized conversational agents for the user and sends it to the terminal. The terminal then displays this information to the user.

[0135] Step 3:

[0136] The user selects a specific agent from the displayed agent list. The terminal sends the ID of the selected agent to the server and requests the agent's profile data.

[0137] Step 4:

[0138] Based on the received agent ID, the server prepares initial data and configuration information related to that agent and sends it to the terminal. This also includes initialization data for the emotion engine.

[0139] Step 5:

[0140] The device activates its emotion engine and prepares sensors or input methods to acquire user voice, text, or facial expression information. The user then transitions to a state where interaction can begin.

[0141] Step 6:

[0142] When a user begins interacting with the agent, the device sends the entered message to the server and simultaneously passes that message and facial expression data to the emotion engine. The emotion engine then analyzes the user's emotional state.

[0143] Step 7:

[0144] The server receives messages from users and generates appropriate responses using an AI engine. These responses are then refined based on the user's emotions, which are analyzed by an emotion engine.

[0145] Step 8:

[0146] A coordinated response is sent from the server to the terminal, which then presents it to the user either visually or audibly.

[0147] Step 9:

[0148] If the user's emotions change, the emotion engine detects the change and either modifies the agent's conversation style accordingly or suggests switching to a different agent.

[0149] Step 10:

[0150] If the user wishes to end the conversation or switch to a different agent, they can repeat the process from step 3 to start a new conversation.

[0151] (Example 2)

[0152] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0153] In recent years, there has been a growing demand for dialogue systems tailored to individual user preferences. However, conventional systems struggle to accurately grasp users' emotional states and provide corresponding dialogue. Therefore, it is necessary to realize personalized dialogue experiences that respond to users' emotions and circumstances.

[0154] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0155] In this invention, the server includes means for selecting from a plurality of dialogue units based on user input information and providing the selected dialogue unit to the user's device; means for acquiring information on the dialogue unit from a data processing device and controlling the dialogue with the user based on that information; means for capturing the user's voice, text, or images, analyzing their emotional state, and automatically suggesting or selecting the optimal dialogue unit based on the analysis results; and means for adjusting the response content to reflect the analyzed emotional state in order to generate an optimized response. This makes it possible to automatically optimize the dialogue according to the user's emotions and situation, and to provide a more natural and personalized dialogue.

[0156] "User input information" refers to data provided by the user through the device, including voice, text, and selected options.

[0157] A "dialogue unit" refers to a basic element used for dialogue, and is a software entity that has a different dialogue format or style.

[0158] A "data processing device" is a device used to process input data and perform necessary calculations and acquire information, and specifically refers to servers and computers.

[0159] "Emotional state" refers to the emotional state exhibited by the user, and is analyzed from data such as voice, text, and facial expressions.

[0160] "Automatic suggestion or selection of optimal dialogue units" means that, based on an analysis of the user's emotional state, the system automatically presents or selects the dialogue style and agent that are most suitable for the user.

[0161] "Optimized responses" refer to conversational approaches and messages that are tailored to the user's emotions and situation, aiming to achieve more effective communication.

[0162] This invention is a dialogue system that recognizes and adapts to the user's emotions, and is implemented through the interaction of a server, a terminal, and the user.

[0163] The user's device has an application installed that provides an interface for the user to initiate interaction. The device acquires user input using hardware such as a voice input device, touch panel, or camera. Software includes the user interface and data capture modules.

[0164] The device captures the user's voice, text, and facial expression data and sends this data to a server. The server is a powerful data processing device connected to a database. Here, the server uses an emotion analysis engine to analyze the user's emotional state from the transmitted data. This engine utilizes machine learning and speech recognition algorithms.

[0165] The server uses a generative AI model to generate optimal dialogue responses based on the user's emotions. These generated responses are then refined through emotion analysis and sent to the terminal. The terminal then presents them to the user in text or audio format.

[0166] For example, if a user is feeling stressed, the emotion engine detects that emotion and automatically selects an agent to provide a relaxing conversation. For instance, if the user provides the prompt, "I'm a little tired. Please tell me how to relax," the system will construct helpful advice and a conversation for the user.

[0167] This system aims to provide users with a more natural and personalized conversational experience by appropriately responding to their emotions.

[0168] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0169] Step 1:

[0170] The user launches a conversational application on their device. When the user enters login information and presses the login button, the device sends this information to the server. The input is the user's authentication information, and the output is the status of the transmission to the server. Specifically, the device encrypts the entered data before sending it to the server.

[0171] Step 2:

[0172] The server compares the authentication information received from the terminal with the database. The input is the authentication information from the user, and the output is whether the authentication was successful or not. The server executes an SQL query on the database to perform the specific action of verifying the user information. If authentication is successful, it generates a list of available interaction units and returns it to the terminal.

[0173] Step 3:

[0174] The terminal displays a list of dialogue units received from the server to the user. The input is the list of dialogue units from the server, and the output is the content displayed to the user. Specifically, the terminal's GUI forms the list and presents it visually to the user.

[0175] Step 4:

[0176] The user selects an interaction unit from a displayed list. The selected data is sent from the terminal to the server as a request. The input is the user's selection, and the output is the request to the server. The terminal captures the selected information and sends it to the server in a structured data format.

[0177] Step 5:

[0178] The server retrieves detailed information about the selected dialogue unit and sends it back to the terminal. The input is the request from the terminal, and the output is the dialogue unit data. The server executes queries to retrieve information from the database.

[0179] Step 6:

[0180] The device acquires user voice, text, camera footage, and other data, and sends this to the sentiment analysis engine. The input is the user's sensor information, and the output is the sentiment analysis result. Specifically, the device processes the acquired data in real time and converts it into an analysis format.

[0181] Step 7:

[0182] The server uses an emotion analysis engine to analyze the user's emotional state from the input data. The input is sensor information, and the output is emotional state data. The emotion analysis engine uses machine learning algorithms to perform the specific actions of inferring emotions from the data.

[0183] Step 8:

[0184] Using a generative AI model, the system generates the optimal response based on the analyzed emotional state. The input is emotional state data, and the output is the adjusted response. The server activates a natural language processing algorithm to generate and adjust the response to suit the user's situation.

[0185] Step 9:

[0186] The terminal receives a response from the server and presents it to the user. The input is the response received from the server, and the output is a presentation to the user via screen or audio. The terminal processes the received data and communicates it to the user through visual or speech synthesis functions.

[0187] (Application Example 2)

[0188] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0189] Modern information systems require personalized dialogue that responds to user emotions. However, conventional dialogue agent systems have struggled to adequately analyze user emotions and provide optimal dialogue accordingly. Furthermore, special consideration for user emotions is necessary when considering use in a home environment.

[0190] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0191] In this invention, the server includes means for analyzing the user's emotions and providing appropriate dialogue based on the analysis results; means for selecting from a plurality of dialogue agents based on the user's request and providing the selected dialogue agent to the user's device; and means for obtaining data of the dialogue agent from the server and controlling the dialogue with the user based on that data. This makes it possible to provide detailed dialogue that responds to the user's emotions.

[0192] "User requirements" refer to the preferences and conditions specified by the user when selecting a conversational agent in the system.

[0193] A "conversational agent" is software designed to engage in conversations with users, generating responses using voice, text, and facial expression data.

[0194] "User's device" refers to electronic devices used to run the conversational agent, including smartphones and tablets.

[0195] A "server" is an information processing system that stores and processes data over a network and provides services to a user's device.

[0196] "Emotional analysis" involves processing a user's voice, text, and facial expression data to estimate their emotional state.

[0197] "Providing appropriate dialogue" is the process of outputting the most suitable response according to the user's emotional state.

[0198] "Household appliances" refer to electronic devices used within the home that are capable of interacting with the user.

[0199] This invention realizes a conversational agent system that recognizes user emotions and provides optimal dialogue. This system consists of a user device, a server, and a home device.

[0200] The server utilizes a generative AI model to analyze the user's emotions. Specifically, it processes voice, text, and facial expression data transmitted from the user's device and analyzes their emotional state. Based on the analyzed emotional data, the server selects an appropriate dialogue agent and provides the generated response to the user's device.

[0201] The user's device consists of home devices such as smartphones and tablets. This device runs a conversational agent selected by the user and interacts with the user based on data received from the server. Through this interaction, the user can receive appropriate responses that match their emotions at the time.

[0202] For example, when a user is feeling tired, the system may recognize this and suggest relaxation-related music or deep breathing exercises. An example of a prompt would be, "How would you respond if the user said they wanted to relax?"

[0203] Thus, with the system of the present invention, users can obtain an emotionally resonant dialogue experience even in a home environment.

[0204] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0205] Step 1:

[0206] The user starts the device and opens the conversational agent application. The user enters authentication information on the login screen. The entered information is sent from the user's device to the server for authentication. If authentication is successful, the server sends a list of authorized conversational agents to the user's device. The device displays this list.

[0207] Step 2:

[0208] The user selects an interactive agent from the displayed list of agents. The user's selection information is sent from the device to the server. The server retrieves data from the selected agent and uses a generated AI model to produce an appropriate response based on that data. This response data is then sent back to the user's device.

[0209] Step 3:

[0210] When a user speaks into the microphone, the device collects audio data. Simultaneously, a camera captures the user's facial expressions. This data is sent from the device to a server for emotion analysis. The server analyzes the audio and facial data to estimate the user's emotional state. Based on this estimation, the response is optimized.

[0211] Step 4:

[0212] The server adjusts the conversational agent's response based on the emotion analysis results and returns the generated response to the user's device. The device outputs the adjusted response to the user as voice or text. This allows the user to receive responses that are adapted to their emotional state.

[0213] Step 5:

[0214] If the user requests yet another conversational agent, the device receives the request and sends another request to the server. Again, the user's emotional state is taken into consideration, and the most appropriate agent is suggested. Once a re-selection is made, this series of steps is repeated.

[0215] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0216] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0217] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0218] [Second Embodiment]

[0219] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0220] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0221] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0222] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0223] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0224] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0225] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0226] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0227] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0228] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0229] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0230] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0231] This invention is a system that provides a personalized conversational experience by allowing the user to select from multiple conversational agents according to their situation and mood at the time. The program processing of the system based on this embodiment is described below in natural language.

[0232] Overall system flow

[0233] 1. User-selected agent

[0234] After the user launches the application on their device, a list of multiple conversational agents is displayed on the screen. This allows the user to select an agent that suits their situation and mood.

[0235] 2. Obtain necessary data and begin interaction

[0236] When a user selects a specific agent, the device retrieves data related to the selected agent from the server. The server then sends data about the selected agent's initial settings and interaction style to the device. This activates the agent on the device, initiating interaction with the user.

[0237] 3. Conducting dialogue and generating responses

[0238] Users can send questions or messages to the agent. The terminal sends this input to the server, which uses an AI engine to generate an appropriate response. This response is then sent to the terminal and displayed to the user.

[0239] 4. Agent changes and adaptations

[0240] If a user wishes to change their conversational agent, they can return to the agent selection screen and select a different agent. This allows them to seamlessly initiate conversations with agents that have different conversational styles and characteristics.

[0241] Specific example

[0242] For example, when a user needs efficient information during work, they can select a work partner agent. This agent can immediately provide detailed information regarding task management and scheduling. On the other hand, when a user wants to relax, they can choose an agent who is willing to engage in casual conversation, allowing for lighthearted dialogue tailored to everyday situations.

[0243] In this way, users can select an agent suitable for different situations on their mobile devices or PCs, and enjoy a highly personalized conversational experience.

[0244] The following describes the processing flow.

[0245] Step 1:

[0246] The user launches the application on their device, and the login screen appears. The user enters their authentication information and attempts to log in. The device sends this authentication information to the server.

[0247] Step 2:

[0248] The server checks the received authentication information against its database, and if the login is successful, it sends a list of authorized conversational agents to the user's device. The device then displays this list on its screen.

[0249] Step 3:

[0250] The user selects a suitable conversational agent from the displayed list. The terminal sends the ID of the selected agent to the server and requests related data.

[0251] Step 4:

[0252] Based on the received agent ID, the server prepares the necessary agent data and profile and sends it to the terminal. The terminal uses this data to activate the selected agent.

[0253] Step 5:

[0254] The user begins interacting with the activated agent. Messages entered by the user are sent to the server via the terminal.

[0255] Step 6:

[0256] The server analyzes the user's message and uses an AI engine to generate an appropriate response. This response is then sent to the terminal and displayed on the screen.

[0257] Step 7:

[0258] If the user wishes to change the conversational agent, they access the agent selection screen again. The terminal provides an interface for selecting a new agent, and once selected, the process from step 3 is repeated.

[0259] (Example 1)

[0260] Next, we will describe Example 1. 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."

[0261] Conventional information exchange systems have made it difficult for users to select the optimal agent from multiple information exchange agents due to insufficient information about the agents' characteristics and the user's situation. Furthermore, they lack the ability to generate appropriate responses using AI algorithms and to flexibly change information exchange agents based on user intent, highlighting the need for improved user experience.

[0262] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0263] In this invention, the server includes means for selecting from a plurality of information exchange agents after the user starts up the information processing device and providing the selected information exchange agent to the user's information processing device; means for obtaining information related to the selected information exchange agent from computing resources and controlling information exchange with the user based on that information; and means for generating a corresponding output using a generation AI algorithm based on input from the user. As a result, the user can easily select the optimal information exchange agent and flexible information exchange according to the situation is possible.

[0264] An "information processing device" is a device used by a user to operate an information exchange agent and display data.

[0265] An "information exchange agent" is a program that interacts with users, has a specific information exchange style, and generates responses in response to user input.

[0266] "Computational resources" refer to servers and cloud computing environments used for acquiring and processing data related to information exchange agents.

[0267] A "generative AI algorithm" is an algorithm that utilizes artificial intelligence technology to automatically generate appropriate responses based on user input data.

[0268] A "response" is the output that an information exchange agent generates in response to user input, and it facilitates the interaction with the user.

[0269] To implement this invention, the user first launches an application using an information processing device. At this time, the terminal displays a list of multiple information exchange agents via a user interface. When the user selects an agent according to the situation or mood, the terminal requests information related to the selected information exchange agent from a server, which is a computing resource.

[0270] The server uses a database to retrieve information about the selected agent's initial settings and interaction style. This information is typically sent to the terminal in JSON format. Upon receiving this data, the terminal activates the information exchange agent and prepares to begin interacting with the user.

[0271] When a user wishes to exchange information, the terminal collects the user's message using text input or speech recognition. This input is sent to the server, where an AI algorithm generates an appropriate response. The server uses natural language processing models such as GPT-3 to analyze the user's intent and generate the most suitable response.

[0272] The generated response is returned to the terminal and displayed to the user. This allows the user to obtain the necessary information while continuing their interaction with the agent.

[0273] For example, if a user wants to relax and enjoy a light conversation, they can enter the prompt, "Tell me which agent can help me relax." The selected agent will then engage in a conversation designed to promote relaxation through everyday interactions. This allows users to select an agent suited to different situations and enjoy an optimized information exchange experience.

[0274] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0275] Step 1:

[0276] When a user launches an application on the information processing device, the terminal displays a list of multiple information exchange agents on the screen. This list is compiled based on data previously received from the server. The input is the user's launch operation, and the output is the display of the agent list. Specifically, the terminal's GUI is activated, and a brief description of each agent and a selection button are displayed.

[0277] Step 2:

[0278] When the user selects a specific agent from the list, the terminal sends the selection information to the server. Upon receiving this input, the server retrieves the initial configuration information of the agent and the dialogue style data from the database. The input is the user's agent selection, and the output is the detailed data regarding the agent. The server packages this data in JSON format and sends it to the terminal.

[0279] Step 3:

[0280] The terminal analyzes the data received from the server and activates the selected agent. At this time, an instance of the agent is generated based on the initial configuration information, and a dialogue screen with the user is prepared. The input is the agent data from the server, and the output is the agent in a state where it can communicate with the user. As a specific operation, the character icon of the agent is displayed, and the dialogue input field is activated.

[0281] Step 4:

[0282] When the user inputs a message to the agent, the terminal sends the text to the server. The server activates a process to generate a response based on the user's message using the generative AI model. The input is the user message, and the output is the generated response. Specifically, the server executes a natural language processing algorithm, analyzes the intention of the message, and generates a response.

[0283] Step 5:

[0284] The response from the server is sent to the terminal, and the terminal displays it to the user. The input is the response data from the server, and the output is the display on the user screen. As a specific operation, the response is displayed in text format on the terminal's display, and the user can continue the dialogue. Through this series of processes, effective communication with the dialogue agent is realized.

[0285] (Application Example 1)

[0286] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[0287] In modern life, users desire to utilize different dialogue systems in various situations, but there is a problem that it is difficult to manage them effectively and intuitively. Also, in devices that support physical work, further technical implementation is required to realize a dialogue optimized for the user.

[0288] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0289] In this invention, the server includes means for selecting from a plurality of dialogue systems based on a user's request and providing the selected dialogue system to the user's device, means for obtaining information on the above dialogue system from an information processing device and controlling the dialogue with the user based on that information, and means for integrating a dialogue system into a device that performs physical work in the user's living area and executing a dialogue corresponding to the target work. Thereby, the user can select an optimal dialogue system according to various situations and enjoy seamless support including physical work.

[0290] The "user" is the subject that uses services and systems, mainly referring to humans, but may include different exploration targets as necessary.

[0291] The "request" refers to the wishes and needs expressed by the user to satisfy specific purposes and needs.

[0292] The "dialogue system" refers to a program or process that can conduct conversations with the user, and its purpose is to provide information, entertainment, and support tasks.

[0293] "Device" refers to a machine or device that performs a specific function or role, and may sometimes include computers or robots.

[0294] An "information processing device" refers to a device or system that receives data, performs calculations and transformations, and outputs the results.

[0295] "Integration" refers to the act or process of connecting multiple elements to make them function as a whole.

[0296] "Physical work" refers to tasks performed through specific actions or means, and is intended to take place within the user's living area.

[0297] "Support" refers to assisting a specific activity or process and enabling its smooth implementation.

[0298] In this invention, a user can use their device to select the most suitable dialogue system from among several dialogue systems. First, the user's request is received via the user interface. Next, the server obtains information corresponding to the selected dialogue system from an information processing device. This information includes the initial settings of the dialogue system, the dialogue format, and related task information.

[0299] The server uses an AI engine running on the cloud to generate appropriate responses to user requests. During this process, data calculations are performed by a generating AI model. The generated response is sent to the user's device and presented to the user via screen or audio. Specifically, this could involve using an AI engine such as OpenAI's GPT-3.

[0300] On the other hand, even in devices that perform physical actions within the user's living space, such as robots, dialogue systems are integrated. This system can initiate actions to assist physical tasks based on user selection and optimize those actions based on dialogueal instructions. Such implementations enable seamless assistance through dialogue.

[0301] For example, it is possible to have a casual conversation with a robot while relaxing in the living room on a holiday, or to receive cooking advice from a cooking advisor agent while cooking. By using a prompt sentence such as "Teach me a new pasta recipe", specific and useful information is provided in real time.

[0302] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0303] Step 1:

[0304] From the user's device, the user activates the system through the interface and inputs the current requirements and mood. The input is sent to the system as text or voice. Based on this information, the terminal processes the user's request as digital data and prepares to send it to the server.

[0305] Step 2:

[0306] The server receives the request data sent from the user and determines which dialogue system is suitable using the AI engine. In this process, the generative AI model analyzes the user's request data and generates a prompt sentence. The generation of the prompt sentence is data processing for extracting the information necessary for presenting options.

[0307] Step 3:

[0308] The server obtains information related to the suitable dialogue system from the information processing device and sends that information to the terminal. This information includes the initial settings and dialogue format of the target dialogue system. The server structures the acquired data and optimizes it into a form that can respond immediately to the user.

[0309] Step 4:

[0310] The terminal displays a list of selectable conversational systems on its user interface based on information received from the server. The user selects a conversational system that suits their needs from the list, and the terminal sends the selection information to the server.

[0311] Step 5:

[0312] The server generates a response created by the AI ​​engine based on the selected dialogue system. The input consists of user selection information and data about the dialogue system, and the result of the calculation is an appropriate response constructed by the generating AI model. This response is then sent from the server to the terminal based on the processed data.

[0313] Step 6:

[0314] The terminal presents the user with the response received from the server. This presentation is done as text display or audio output. In parallel with this information presentation, if the user is using a physical device, the dialogue system sends instructions for physical actions to the device, and the actions are executed.

[0315] Step 7:

[0316] If the user wishes to continue the conversation, they can enter additional questions or instructions. The device then sends this back to the server, where the AI ​​engine processes it again to generate a response. The agent can also be seamlessly changed upon user request.

[0317] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0318] This invention is a dialogue agent system that combines an emotion engine to recognize user emotions, and aims to provide an optimal dialogue experience according to the user's situation and mood. Specific embodiments for carrying out this invention are shown below.

[0319] Overall system flow

[0320] First, when a user launches the application on their device, a login screen is displayed. After the user enters their authentication credentials and logs in, the server verifies the credentials. If successful, it sends a list of authorized conversational agents to the device. The device then retrieves this information and displays it to the user.

[0321] Once the user selects an agent, the device retrieves the selected agent's data from the server and begins the conversation. At this point, the emotion engine activates, analyzing the user's emotions from their voice, text messages, or facial expression data collected by the camera. Based on this analysis, the emotion engine either suggests or automatically selects the most suitable agent and conversation style.

[0322] User conversation messages are sent from the device to the server, where an AI engine generates an appropriate response. The generated response is then adjusted based on the user's emotions, as analyzed by an emotion engine, and returned to the device. This allows users to experience natural and appropriate conversations that match their mood and emotions.

[0323] Specific example

[0324] For example, if a user is feeling stressed, the emotion engine detects that emotion and suggests an agent that can calm the user. This agent engages in conversations about relaxation and offers suggestions to soothe the mood. Conversely, if the user is excited, an agent is provided that offers a positive response to support their energy.

[0325] Thus, a dialogue agent system incorporating an emotion engine can achieve highly adaptive dialogue tailored to the user's emotional needs, providing a more personalized user experience.

[0326] The following describes the processing flow.

[0327] Step 1:

[0328] When a user launches the application on their device, a login screen is displayed. The user enters their authentication information and sends an authentication request to the server.

[0329] Step 2:

[0330] The server verifies the authentication credentials, and if authentication is successful, it generates a list of authorized conversational agents for the user and sends it to the terminal. The terminal then displays this information to the user.

[0331] Step 3:

[0332] The user selects a specific agent from the displayed agent list. The terminal sends the ID of the selected agent to the server and requests the agent's profile data.

[0333] Step 4:

[0334] Based on the received agent ID, the server prepares initial data and configuration information related to that agent and sends it to the terminal. This also includes initialization data for the emotion engine.

[0335] Step 5:

[0336] The device activates its emotion engine and prepares sensors or input methods to acquire user voice, text, or facial expression information. The user then transitions to a state where interaction can begin.

[0337] Step 6:

[0338] When a user begins interacting with the agent, the device sends the entered message to the server and simultaneously passes that message and facial expression data to the emotion engine. The emotion engine then analyzes the user's emotional state.

[0339] Step 7:

[0340] The server receives messages from users and generates appropriate responses using an AI engine. These responses are then refined based on the user's emotions, which are analyzed by an emotion engine.

[0341] Step 8:

[0342] A coordinated response is sent from the server to the terminal, which then presents it to the user either visually or audibly.

[0343] Step 9:

[0344] If the user's emotions change, the emotion engine detects the change and either modifies the agent's conversation style accordingly or suggests switching to a different agent.

[0345] Step 10:

[0346] If the user wishes to end the conversation or switch to a different agent, they can repeat the process from step 3 to start a new conversation.

[0347] (Example 2)

[0348] Next, we will describe Example 2. 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".

[0349] In recent years, there has been a growing demand for dialogue systems tailored to individual user preferences. However, conventional systems struggle to accurately grasp users' emotional states and provide corresponding dialogue. Therefore, it is necessary to realize personalized dialogue experiences that respond to users' emotions and circumstances.

[0350] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0351] In this invention, the server includes means for selecting from a plurality of dialogue units based on user input information and providing the selected dialogue unit to the user's device; means for acquiring information on the dialogue unit from a data processing device and controlling the dialogue with the user based on that information; means for capturing the user's voice, text, or images, analyzing their emotional state, and automatically suggesting or selecting the optimal dialogue unit based on the analysis results; and means for adjusting the response content to reflect the analyzed emotional state in order to generate an optimized response. This makes it possible to automatically optimize the dialogue according to the user's emotions and situation, and to provide a more natural and personalized dialogue.

[0352] "User input information" refers to data provided by the user through the device, including voice, text, and selected options.

[0353] A "dialogue unit" refers to a basic element used for dialogue, and is a software entity that has a different dialogue format or style.

[0354] A "data processing device" is a device used to process input data and perform necessary calculations and acquire information, and specifically refers to servers and computers.

[0355] "Emotional state" refers to the emotional state exhibited by the user, and is analyzed from data such as voice, text, and facial expressions.

[0356] "Automatic suggestion or selection of optimal dialogue units" means that, based on an analysis of the user's emotional state, the system automatically presents or selects the dialogue style and agent that are most suitable for the user.

[0357] "Optimized responses" refer to conversational approaches and messages that are tailored to the user's emotions and situation, aiming to achieve more effective communication.

[0358] This invention is a dialogue system that recognizes and adapts to the user's emotions, and is implemented through the interaction of a server, a terminal, and the user.

[0359] The user's device has an application installed that provides an interface for the user to initiate interaction. The device acquires user input using hardware such as a voice input device, touch panel, or camera. Software includes the user interface and data capture modules.

[0360] The device captures the user's voice, text, and facial expression data and sends this data to a server. The server is a powerful data processing device connected to a database. Here, the server uses an emotion analysis engine to analyze the user's emotional state from the transmitted data. This engine utilizes machine learning and speech recognition algorithms.

[0361] The server uses a generative AI model to generate optimal dialogue responses based on the user's emotions. These generated responses are then refined through emotion analysis and sent to the terminal. The terminal then presents them to the user in text or audio format.

[0362] For example, if a user is feeling stressed, the emotion engine detects that emotion and automatically selects an agent to provide a relaxing conversation. For instance, if the user provides the prompt, "I'm a little tired. Please tell me how to relax," the system will construct helpful advice and a conversation for the user.

[0363] This system aims to provide users with a more natural and personalized conversational experience by appropriately responding to their emotions.

[0364] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0365] Step 1:

[0366] The user launches a conversational application on their device. When the user enters login information and presses the login button, the device sends this information to the server. The input is the user's authentication information, and the output is the status of the transmission to the server. Specifically, the device encrypts the entered data before sending it to the server.

[0367] Step 2:

[0368] The server compares the authentication information received from the terminal with the database. The input is the authentication information from the user, and the output is whether the authentication was successful or not. The server executes an SQL query on the database to perform the specific action of verifying the user information. If authentication is successful, it generates a list of available interaction units and returns it to the terminal.

[0369] Step 3:

[0370] The terminal displays a list of dialogue units received from the server to the user. The input is the list of dialogue units from the server, and the output is the content displayed to the user. Specifically, the terminal's GUI forms the list and presents it visually to the user.

[0371] Step 4:

[0372] The user selects an interaction unit from a displayed list. The selected data is sent from the terminal to the server as a request. The input is the user's selection, and the output is the request to the server. The terminal captures the selected information and sends it to the server in a structured data format.

[0373] Step 5:

[0374] The server retrieves detailed information about the selected dialogue unit and sends it back to the terminal. The input is the request from the terminal, and the output is the dialogue unit data. The server executes queries to retrieve information from the database.

[0375] Step 6:

[0376] The device acquires user voice, text, camera footage, and other data, and sends this to the sentiment analysis engine. The input is the user's sensor information, and the output is the sentiment analysis result. Specifically, the device processes the acquired data in real time and converts it into an analysis format.

[0377] Step 7:

[0378] The server uses an emotion analysis engine to analyze the user's emotional state from the input data. The input is sensor information, and the output is emotional state data. The emotion analysis engine uses machine learning algorithms to perform the specific actions of inferring emotions from the data.

[0379] Step 8:

[0380] Using a generative AI model, the system generates the optimal response based on the analyzed emotional state. The input is emotional state data, and the output is the adjusted response. The server activates a natural language processing algorithm to generate and adjust the response to suit the user's situation.

[0381] Step 9:

[0382] The terminal receives a response from the server and presents it to the user. The input is the response received from the server, and the output is a presentation to the user via screen or audio. The terminal processes the received data and communicates it to the user through visual or speech synthesis functions.

[0383] (Application Example 2)

[0384] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0385] Modern information systems require personalized dialogue that responds to user emotions. However, conventional dialogue agent systems have struggled to adequately analyze user emotions and provide optimal dialogue accordingly. Furthermore, special consideration for user emotions is necessary when considering use in a home environment.

[0386] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0387] In this invention, the server includes means for analyzing the user's emotions and providing appropriate dialogue based on the analysis results; means for selecting from a plurality of dialogue agents based on the user's request and providing the selected dialogue agent to the user's device; and means for obtaining data of the dialogue agent from the server and controlling the dialogue with the user based on that data. This makes it possible to provide detailed dialogue that responds to the user's emotions.

[0388] "User requirements" refer to the preferences and conditions specified by the user when selecting a conversational agent in the system.

[0389] A "conversational agent" is software designed to engage in conversations with users, generating responses using voice, text, and facial expression data.

[0390] "User's device" refers to electronic devices used to run the conversational agent, including smartphones and tablets.

[0391] A "server" is an information processing system that stores and processes data over a network and provides services to a user's device.

[0392] "Emotional analysis" involves processing a user's voice, text, and facial expression data to estimate their emotional state.

[0393] "Providing appropriate dialogue" is the process of outputting the most suitable response according to the user's emotional state.

[0394] "Household appliances" refer to electronic devices used within the home that are capable of interacting with the user.

[0395] This invention realizes a conversational agent system that recognizes user emotions and provides optimal dialogue. This system consists of a user device, a server, and a home device.

[0396] The server utilizes a generative AI model to analyze the user's emotions. Specifically, it processes voice, text, and facial expression data transmitted from the user's device and analyzes their emotional state. Based on the analyzed emotional data, the server selects an appropriate dialogue agent and provides the generated response to the user's device.

[0397] The user's device consists of home devices such as smartphones and tablets. This device runs a conversational agent selected by the user and interacts with the user based on data received from the server. Through this interaction, the user can receive appropriate responses that match their emotions at the time.

[0398] For example, when a user is feeling tired, the system may recognize this and suggest relaxation-related music or deep breathing exercises. An example of a prompt would be, "How would you respond if the user said they wanted to relax?"

[0399] Thus, with the system of the present invention, users can obtain an emotionally resonant dialogue experience even in a home environment.

[0400] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0401] Step 1:

[0402] The user starts the device and opens the conversational agent application. The user enters authentication information on the login screen. The entered information is sent from the user's device to the server for authentication. If authentication is successful, the server sends a list of authorized conversational agents to the user's device. The device displays this list.

[0403] Step 2:

[0404] The user selects an interactive agent from the displayed list of agents. The user's selection information is sent from the device to the server. The server retrieves data from the selected agent and uses a generated AI model to produce an appropriate response based on that data. This response data is then sent back to the user's device.

[0405] Step 3:

[0406] When a user speaks into the microphone, the device collects audio data. Simultaneously, a camera captures the user's facial expressions. This data is sent from the device to a server for emotion analysis. The server analyzes the audio and facial data to estimate the user's emotional state. Based on this estimation, the response is optimized.

[0407] Step 4:

[0408] The server adjusts the conversational agent's response based on the emotion analysis results and returns the generated response to the user's device. The device outputs the adjusted response to the user as voice or text. This allows the user to receive responses that are adapted to their emotional state.

[0409] Step 5:

[0410] If the user requests yet another conversational agent, the device receives the request and sends another request to the server. Again, the user's emotional state is taken into consideration, and the most appropriate agent is suggested. Once a re-selection is made, this series of steps is repeated.

[0411] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0412] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0413] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0414] [Third Embodiment]

[0415] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0416] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0417] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0418] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0419] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0420] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0421] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0422] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0423] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0424] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0425] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0426] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0427] This invention is a system that provides a personalized conversational experience by allowing the user to select from multiple conversational agents according to their situation and mood at the time. The program processing of the system based on this embodiment is described below in natural language.

[0428] Overall system flow

[0429] 1. User-selected agent

[0430] After the user launches the application on their device, a list of multiple conversational agents is displayed on the screen. This allows the user to select an agent that suits their situation and mood.

[0431] 2. Obtain necessary data and begin interaction

[0432] When a user selects a specific agent, the device retrieves data related to the selected agent from the server. The server then sends data about the selected agent's initial settings and interaction style to the device. This activates the agent on the device, initiating interaction with the user.

[0433] 3. Conducting dialogue and generating responses

[0434] Users can send questions or messages to the agent. The terminal sends this input to the server, which uses an AI engine to generate an appropriate response. This response is then sent to the terminal and displayed to the user.

[0435] 4. Agent changes and adaptations

[0436] If a user wishes to change their conversational agent, they can return to the agent selection screen and select a different agent. This allows them to seamlessly initiate conversations with agents that have different conversational styles and characteristics.

[0437] Specific example

[0438] For example, when a user needs efficient information during work, they can select a work partner agent. This agent can immediately provide detailed information regarding task management and scheduling. On the other hand, when a user wants to relax, they can choose an agent who is willing to engage in casual conversation, allowing for lighthearted dialogue tailored to everyday situations.

[0439] In this way, users can select an agent suitable for different situations on their mobile devices or PCs, and enjoy a highly personalized conversational experience.

[0440] The following describes the processing flow.

[0441] Step 1:

[0442] The user launches the application on their device, and the login screen appears. The user enters their authentication information and attempts to log in. The device sends this authentication information to the server.

[0443] Step 2:

[0444] The server checks the received authentication information against its database, and if the login is successful, it sends a list of authorized conversational agents to the user's device. The device then displays this list on its screen.

[0445] Step 3:

[0446] The user selects a suitable conversational agent from the displayed list. The terminal sends the ID of the selected agent to the server and requests related data.

[0447] Step 4:

[0448] Based on the received agent ID, the server prepares the necessary agent data and profile and sends it to the terminal. The terminal uses this data to activate the selected agent.

[0449] Step 5:

[0450] The user begins interacting with the activated agent. Messages entered by the user are sent to the server via the terminal.

[0451] Step 6:

[0452] The server analyzes the user's message and uses an AI engine to generate an appropriate response. This response is then sent to the terminal and displayed on the screen.

[0453] Step 7:

[0454] If the user wishes to change the conversational agent, they access the agent selection screen again. The terminal provides an interface for selecting a new agent, and once selected, the process from step 3 is repeated.

[0455] (Example 1)

[0456] Next, we will describe Example 1. 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."

[0457] Conventional information exchange systems have made it difficult for users to select the optimal agent from multiple information exchange agents due to insufficient information about the agents' characteristics and the user's situation. Furthermore, they lack the ability to generate appropriate responses using AI algorithms and to flexibly change information exchange agents based on user intent, highlighting the need for improved user experience.

[0458] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0459] In this invention, the server includes means for selecting from a plurality of information exchange agents after the user starts up the information processing device and providing the selected information exchange agent to the user's information processing device; means for obtaining information related to the selected information exchange agent from computing resources and controlling information exchange with the user based on that information; and means for generating a corresponding output using a generation AI algorithm based on input from the user. As a result, the user can easily select the optimal information exchange agent and flexible information exchange according to the situation is possible.

[0460] An "information processing device" is a device used by a user to operate an information exchange agent and display data.

[0461] An "information exchange agent" is a program that interacts with users, has a specific information exchange style, and generates responses in response to user input.

[0462] "Computational resources" refer to servers and cloud computing environments used for acquiring and processing data related to information exchange agents.

[0463] A "generative AI algorithm" is an algorithm that utilizes artificial intelligence technology to automatically generate appropriate responses based on user input data.

[0464] A "response" is the output that an information exchange agent generates in response to user input, and it facilitates the interaction with the user.

[0465] To implement this invention, the user first launches an application using an information processing device. At this time, the terminal displays a list of multiple information exchange agents via a user interface. When the user selects an agent according to the situation or mood, the terminal requests information related to the selected information exchange agent from a server, which is a computing resource.

[0466] The server uses a database to retrieve information about the selected agent's initial settings and interaction style. This information is typically sent to the terminal in JSON format. Upon receiving this data, the terminal activates the information exchange agent and prepares to begin interacting with the user.

[0467] When a user wishes to exchange information, the terminal collects the user's message using text input or speech recognition. This input is sent to the server, where an AI algorithm generates an appropriate response. The server uses natural language processing models such as GPT-3 to analyze the user's intent and generate the most suitable response.

[0468] The generated response is returned to the terminal and displayed to the user. This allows the user to obtain the necessary information while continuing their interaction with the agent.

[0469] For example, if a user wants to relax and enjoy a light conversation, they can enter the prompt, "Tell me which agent can help me relax." The selected agent will then engage in a conversation designed to promote relaxation through everyday interactions. This allows users to select an agent suited to different situations and enjoy an optimized information exchange experience.

[0470] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0471] Step 1:

[0472] When a user launches an application on the information processing device, the terminal displays a list of multiple information exchange agents on the screen. This list is compiled based on data previously received from the server. The input is the user's launch operation, and the output is the display of the agent list. Specifically, the terminal's GUI is activated, and a brief description of each agent and a selection button are displayed.

[0473] Step 2:

[0474] When a user selects a specific agent from a list, the terminal sends the selection information to the server. The server receives this input and retrieves the agent's initial setup information and interaction style data from its database. The input is the user's agent selection, and the output is detailed data about the agent. The server packages this data in JSON format and sends it to the terminal.

[0475] Step 3:

[0476] The terminal analyzes the data received from the server and launches the selected agent. During this process, an agent instance is created based on the initial setup information, and a user interaction screen is prepared. The input is agent data from the server, and the output is an agent ready for user interaction. Specifically, the agent's character icon is displayed, and the interaction input field is activated.

[0477] Step 4:

[0478] When a user enters a message into the agent, the terminal sends that text to the server. The server uses a generative AI model to initiate a process that generates a response based on the user's message. The input is the user message, and the output is the generated response. Specifically, the server executes a natural language processing algorithm to analyze the intent of the message and generate the response.

[0479] Step 5:

[0480] The server's response is sent to the terminal, which then displays it to the user. The input is the response data from the server, and the output is the display on the user's screen. Specifically, the response is displayed in text format on the terminal's display, allowing the user to continue the conversation. This entire process enables effective communication with the conversational agent.

[0481] (Application Example 1)

[0482] Next, we will explain Application Example 1. In the following explanation, 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."

[0483] In modern life, users desire to utilize different dialogue systems in diverse situations, but managing them effectively and intuitively presents a challenge. Furthermore, even in devices that assist with physical tasks, further technological advancements are needed to achieve user-optimized dialogue.

[0484] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0485] In this invention, the server includes means for selecting from a plurality of dialogue systems based on the user's request and providing the selected dialogue system to the user's device; means for acquiring information about the dialogue system from an information processing device and controlling the dialogue with the user based on that information; and means for integrating the dialogue system into a device that performs physical tasks in the user's living area and executing dialogue according to the target task. As a result, the user can select the optimal dialogue system according to various situations and enjoy seamless support, including physical tasks.

[0486] A "user" is an entity that utilizes a service or system, primarily referring to a human being, but may include other subjects of exploration as needed.

[0487] A "request" refers to a wish or need expressed by a user to fulfill a specific purpose or need.

[0488] A "dialogue system" refers to a program or process that can engage in conversation with a user, and its purpose is to provide information, entertainment, or task support.

[0489] "Device" refers to a machine or device that performs a specific function or role, and may sometimes include computers or robots.

[0490] An "information processing device" refers to a device or system that receives data, performs calculations and transformations, and outputs the results.

[0491] "Integration" refers to the act or process of connecting multiple elements to make them function as a whole.

[0492] "Physical work" refers to tasks performed through specific actions or means, and is intended to take place within the user's living area.

[0493] "Support" refers to assisting a specific activity or process and enabling its smooth implementation.

[0494] In this invention, a user can use their device to select the most suitable dialogue system from among several dialogue systems. First, the user's request is received via the user interface. Next, the server obtains information corresponding to the selected dialogue system from an information processing device. This information includes the initial settings of the dialogue system, the dialogue format, and related task information.

[0495] The server uses an AI engine running on the cloud to generate appropriate responses to user requests. During this process, data calculations are performed by a generating AI model. The generated response is sent to the user's device and presented to the user via screen or audio. Specifically, this could involve using an AI engine such as OpenAI's GPT-3.

[0496] On the other hand, even in devices that perform physical actions within the user's living space, such as robots, dialogue systems are integrated. This system can initiate actions to assist physical tasks based on user selection and optimize those actions based on dialogueal instructions. Such implementations enable seamless assistance through dialogue.

[0497] For example, you can chat with a robot while relaxing in the living room on a day off, or receive cooking advice from a cooking advisor agent while you're cooking. By using prompts such as "Tell me a new pasta recipe," specific and helpful information will be provided in real time.

[0498] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0499] Step 1:

[0500] From the user's device, the user activates the system through an interface and inputs their current requests and mood. This input is sent to the system as text or voice. Based on this information, the terminal processes the user's requests as digital data and prepares to send them to the server.

[0501] Step 2:

[0502] The server receives request data sent by the user and uses an AI engine to determine which dialogue system is appropriate. In this process, a generative AI model analyzes the user's request data and generates prompt sentences. Prompt sentence generation is data processing to extract the information necessary to present choices.

[0503] Step 3:

[0504] The server retrieves information related to the appropriate dialogue system from the information processing device and transmits that information to the terminal. This information includes the initial settings and dialogue format of the target dialogue system. The server structures the retrieved data and optimizes it into a format that can be immediately responded to by the user.

[0505] Step 4:

[0506] The terminal displays a list of selectable conversational systems on its user interface based on information received from the server. The user selects a conversational system that suits their needs from the list, and the terminal sends the selection information to the server.

[0507] Step 5:

[0508] The server generates a response created by the AI ​​engine based on the selected dialogue system. The input consists of user selection information and data about the dialogue system, and the result of the calculation is an appropriate response constructed by the generating AI model. This response is then sent from the server to the terminal based on the processed data.

[0509] Step 6:

[0510] The terminal presents the user with the response received from the server. This presentation is done as text display or audio output. In parallel with this information presentation, if the user is using a physical device, the dialogue system sends instructions for physical actions to the device, and the actions are executed.

[0511] Step 7:

[0512] If the user wishes to continue the conversation, they can enter additional questions or instructions. The device then sends this back to the server, where the AI ​​engine processes it again to generate a response. The agent can also be seamlessly changed upon user request.

[0513] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0514] This invention is a dialogue agent system that combines an emotion engine to recognize user emotions, and aims to provide an optimal dialogue experience according to the user's situation and mood. Specific embodiments for carrying out this invention are shown below.

[0515] Overall system flow

[0516] First, when a user launches the application on their device, a login screen is displayed. After the user enters their authentication credentials and logs in, the server verifies the credentials. If successful, it sends a list of authorized conversational agents to the device. The device then retrieves this information and displays it to the user.

[0517] Once the user selects an agent, the device retrieves the selected agent's data from the server and begins the conversation. At this point, the emotion engine activates, analyzing the user's emotions from their voice, text messages, or facial expression data collected by the camera. Based on this analysis, the emotion engine either suggests or automatically selects the most suitable agent and conversation style.

[0518] User conversation messages are sent from the device to the server, where an AI engine generates an appropriate response. The generated response is then adjusted based on the user's emotions, as analyzed by an emotion engine, and returned to the device. This allows users to experience natural and appropriate conversations that match their mood and emotions.

[0519] Specific example

[0520] For example, if a user is feeling stressed, the emotion engine detects that emotion and suggests an agent that can calm the user. This agent engages in conversations about relaxation and offers suggestions to soothe the mood. Conversely, if the user is excited, an agent is provided that offers a positive response to support their energy.

[0521] Thus, a dialogue agent system incorporating an emotion engine can achieve highly adaptive dialogue tailored to the user's emotional needs, providing a more personalized user experience.

[0522] The following describes the processing flow.

[0523] Step 1:

[0524] When a user launches the application on their device, a login screen is displayed. The user enters their authentication information and sends an authentication request to the server.

[0525] Step 2:

[0526] The server verifies the authentication credentials, and if authentication is successful, it generates a list of authorized conversational agents for the user and sends it to the terminal. The terminal then displays this information to the user.

[0527] Step 3:

[0528] The user selects a specific agent from the displayed agent list. The terminal sends the ID of the selected agent to the server and requests the agent's profile data.

[0529] Step 4:

[0530] Based on the received agent ID, the server prepares initial data and configuration information related to that agent and sends it to the terminal. This also includes initialization data for the emotion engine.

[0531] Step 5:

[0532] The device activates its emotion engine and prepares sensors or input methods to acquire user voice, text, or facial expression information. The user then transitions to a state where interaction can begin.

[0533] Step 6:

[0534] When a user begins interacting with the agent, the device sends the entered message to the server and simultaneously passes that message and facial expression data to the emotion engine. The emotion engine then analyzes the user's emotional state.

[0535] Step 7:

[0536] The server receives messages from users and generates appropriate responses using an AI engine. These responses are then refined based on the user's emotions, which are analyzed by an emotion engine.

[0537] Step 8:

[0538] A coordinated response is sent from the server to the terminal, which then presents it to the user either visually or audibly.

[0539] Step 9:

[0540] If the user's emotions change, the emotion engine detects the change and either modifies the agent's conversation style accordingly or suggests switching to a different agent.

[0541] Step 10:

[0542] If the user wishes to end the conversation or switch to a different agent, they can repeat the process from step 3 to start a new conversation.

[0543] (Example 2)

[0544] Next, we will describe Example 2. 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."

[0545] In recent years, there has been a growing demand for dialogue systems tailored to individual user preferences. However, conventional systems struggle to accurately grasp users' emotional states and provide corresponding dialogue. Therefore, it is necessary to realize personalized dialogue experiences that respond to users' emotions and circumstances.

[0546] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0547] In this invention, the server includes means for selecting from a plurality of dialogue units based on user input information and providing the selected dialogue unit to the user's device; means for acquiring information on the dialogue unit from a data processing device and controlling the dialogue with the user based on that information; means for capturing the user's voice, text, or images, analyzing their emotional state, and automatically suggesting or selecting the optimal dialogue unit based on the analysis results; and means for adjusting the response content to reflect the analyzed emotional state in order to generate an optimized response. This makes it possible to automatically optimize the dialogue according to the user's emotions and situation, and to provide a more natural and personalized dialogue.

[0548] "User input information" refers to data provided by the user through the device, including voice, text, and selected options.

[0549] A "dialogue unit" refers to a basic element used for dialogue, and is a software entity that has a different dialogue format or style.

[0550] A "data processing device" is a device used to process input data and perform necessary calculations and acquire information, and specifically refers to servers and computers.

[0551] "Emotional state" refers to the emotional state exhibited by the user, and is analyzed from data such as voice, text, and facial expressions.

[0552] "Automatic suggestion or selection of optimal dialogue units" means that, based on an analysis of the user's emotional state, the system automatically presents or selects the dialogue style and agent that are most suitable for the user.

[0553] "Optimized responses" refer to conversational approaches and messages that are tailored to the user's emotions and situation, aiming to achieve more effective communication.

[0554] This invention is a dialogue system that recognizes and adapts to the user's emotions, and is implemented through the interaction of a server, a terminal, and the user.

[0555] The user's device has an application installed that provides an interface for the user to initiate interaction. The device acquires user input using hardware such as a voice input device, touch panel, or camera. Software includes the user interface and data capture modules.

[0556] The device captures the user's voice, text, and facial expression data and sends this data to a server. The server is a powerful data processing device connected to a database. Here, the server uses an emotion analysis engine to analyze the user's emotional state from the transmitted data. This engine utilizes machine learning and speech recognition algorithms.

[0557] The server uses a generative AI model to generate optimal dialogue responses based on the user's emotions. These generated responses are then refined through emotion analysis and sent to the terminal. The terminal then presents them to the user in text or audio format.

[0558] For example, if a user is feeling stressed, the emotion engine detects that emotion and automatically selects an agent to provide a relaxing conversation. For instance, if the user provides the prompt, "I'm a little tired. Please tell me how to relax," the system will construct helpful advice and a conversation for the user.

[0559] This system aims to provide users with a more natural and personalized conversational experience by appropriately responding to their emotions.

[0560] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0561] Step 1:

[0562] The user launches a conversational application on their device. When the user enters login information and presses the login button, the device sends this information to the server. The input is the user's authentication information, and the output is the status of the transmission to the server. Specifically, the device encrypts the entered data before sending it to the server.

[0563] Step 2:

[0564] The server compares the authentication information received from the terminal with the database. The input is the authentication information from the user, and the output is whether the authentication was successful or not. The server executes an SQL query on the database to perform the specific action of verifying the user information. If authentication is successful, it generates a list of available interaction units and returns it to the terminal.

[0565] Step 3:

[0566] The terminal displays a list of dialogue units received from the server to the user. The input is the list of dialogue units from the server, and the output is the content displayed to the user. Specifically, the terminal's GUI forms the list and presents it visually to the user.

[0567] Step 4:

[0568] The user selects an interaction unit from a displayed list. The selected data is sent from the terminal to the server as a request. The input is the user's selection, and the output is the request to the server. The terminal captures the selected information and sends it to the server in a structured data format.

[0569] Step 5:

[0570] The server retrieves detailed information about the selected dialogue unit and sends it back to the terminal. The input is the request from the terminal, and the output is the dialogue unit data. The server executes queries to retrieve information from the database.

[0571] Step 6:

[0572] The device acquires user voice, text, camera footage, and other data, and sends this to the sentiment analysis engine. The input is the user's sensor information, and the output is the sentiment analysis result. Specifically, the device processes the acquired data in real time and converts it into an analysis format.

[0573] Step 7:

[0574] The server uses an emotion analysis engine to analyze the user's emotional state from the input data. The input is sensor information, and the output is emotional state data. The emotion analysis engine uses machine learning algorithms to perform the specific actions of inferring emotions from the data.

[0575] Step 8:

[0576] Using a generative AI model, the system generates the optimal response based on the analyzed emotional state. The input is emotional state data, and the output is the adjusted response. The server activates a natural language processing algorithm to generate and adjust the response to suit the user's situation.

[0577] Step 9:

[0578] The terminal receives a response from the server and presents it to the user. The input is the response received from the server, and the output is a presentation to the user via screen or audio. The terminal processes the received data and communicates it to the user through visual or speech synthesis functions.

[0579] (Application Example 2)

[0580] Next, we will explain application example 2. In the following explanation, 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."

[0581] Modern information systems require personalized dialogue that responds to user emotions. However, conventional dialogue agent systems have struggled to adequately analyze user emotions and provide optimal dialogue accordingly. Furthermore, special consideration for user emotions is necessary when considering use in a home environment.

[0582] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0583] In this invention, the server includes means for analyzing the user's emotions and providing appropriate dialogue based on the analysis results; means for selecting from a plurality of dialogue agents based on the user's request and providing the selected dialogue agent to the user's device; and means for obtaining data of the dialogue agent from the server and controlling the dialogue with the user based on that data. This makes it possible to provide detailed dialogue that responds to the user's emotions.

[0584] "User requirements" refer to the preferences and conditions specified by the user when selecting a conversational agent in the system.

[0585] A "conversational agent" is software designed to engage in conversations with users, generating responses using voice, text, and facial expression data.

[0586] "User's device" refers to electronic devices used to run the conversational agent, including smartphones and tablets.

[0587] A "server" is an information processing system that stores and processes data over a network and provides services to a user's device.

[0588] "Emotional analysis" involves processing a user's voice, text, and facial expression data to estimate their emotional state.

[0589] "Providing appropriate dialogue" is the process of outputting the most suitable response according to the user's emotional state.

[0590] "Household appliances" refer to electronic devices used within the home that are capable of interacting with the user.

[0591] This invention realizes a conversational agent system that recognizes user emotions and provides optimal dialogue. This system consists of a user device, a server, and a home device.

[0592] The server utilizes a generative AI model to analyze the user's emotions. Specifically, it processes voice, text, and facial expression data transmitted from the user's device and analyzes their emotional state. Based on the analyzed emotional data, the server selects an appropriate dialogue agent and provides the generated response to the user's device.

[0593] The user's device consists of home devices such as smartphones and tablets. This device runs a conversational agent selected by the user and interacts with the user based on data received from the server. Through this interaction, the user can receive appropriate responses that match their emotions at the time.

[0594] For example, when a user is feeling tired, the system may recognize this and suggest relaxation-related music or deep breathing exercises. An example of a prompt would be, "How would you respond if the user said they wanted to relax?"

[0595] Thus, with the system of the present invention, users can obtain an emotionally resonant dialogue experience even in a home environment.

[0596] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0597] Step 1:

[0598] The user starts the device and opens the conversational agent application. The user enters authentication information on the login screen. The entered information is sent from the user's device to the server for authentication. If authentication is successful, the server sends a list of authorized conversational agents to the user's device. The device displays this list.

[0599] Step 2:

[0600] The user selects an interactive agent from the displayed list of agents. The user's selection information is sent from the device to the server. The server retrieves data from the selected agent and uses a generated AI model to produce an appropriate response based on that data. This response data is then sent back to the user's device.

[0601] Step 3:

[0602] When a user speaks into the microphone, the device collects audio data. Simultaneously, a camera captures the user's facial expressions. This data is sent from the device to a server for emotion analysis. The server analyzes the audio and facial data to estimate the user's emotional state. Based on this estimation, the response is optimized.

[0603] Step 4:

[0604] The server adjusts the conversational agent's response based on the emotion analysis results and returns the generated response to the user's device. The device outputs the adjusted response to the user as voice or text. This allows the user to receive responses that are adapted to their emotional state.

[0605] Step 5:

[0606] If the user requests yet another conversational agent, the device receives the request and sends another request to the server. Again, the user's emotional state is taken into consideration, and the most appropriate agent is suggested. Once a re-selection is made, this series of steps is repeated.

[0607] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0608] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0609] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0610] [Fourth Embodiment]

[0611] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0612] As shown in Figure 7, the 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.

[0613] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0614] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0615] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0616] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0617] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0618] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0619] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0620] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0621] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0622] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0623] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0624] This invention is a system that provides a personalized conversational experience by allowing the user to select from multiple conversational agents according to their situation and mood at the time. The program processing of the system based on this embodiment is described below in natural language.

[0625] Overall system flow

[0626] 1. User-selected agent

[0627] After the user launches the application on their device, a list of multiple conversational agents is displayed on the screen. This allows the user to select an agent that suits their situation and mood.

[0628] 2. Obtain necessary data and begin interaction

[0629] When a user selects a specific agent, the device retrieves data related to the selected agent from the server. The server then sends data about the selected agent's initial settings and interaction style to the device. This activates the agent on the device, initiating interaction with the user.

[0630] 3. Conducting dialogue and generating responses

[0631] Users can send questions or messages to the agent. The terminal sends this input to the server, which uses an AI engine to generate an appropriate response. This response is then sent to the terminal and displayed to the user.

[0632] 4. Agent changes and adaptations

[0633] If a user wishes to change their conversational agent, they can return to the agent selection screen and select a different agent. This allows them to seamlessly initiate conversations with agents that have different conversational styles and characteristics.

[0634] Specific example

[0635] For example, when a user needs efficient information during work, they can select a work partner agent. This agent can immediately provide detailed information regarding task management and scheduling. On the other hand, when a user wants to relax, they can choose an agent who is willing to engage in casual conversation, allowing for lighthearted dialogue tailored to everyday situations.

[0636] In this way, users can select an agent suitable for different situations on their mobile devices or PCs, and enjoy a highly personalized conversational experience.

[0637] The following describes the processing flow.

[0638] Step 1:

[0639] The user launches the application on their device, and the login screen appears. The user enters their authentication information and attempts to log in. The device sends this authentication information to the server.

[0640] Step 2:

[0641] The server checks the received authentication information against its database, and if the login is successful, it sends a list of authorized conversational agents to the user's device. The device then displays this list on its screen.

[0642] Step 3:

[0643] The user selects a suitable conversational agent from the displayed list. The terminal sends the ID of the selected agent to the server and requests related data.

[0644] Step 4:

[0645] Based on the received agent ID, the server prepares the necessary agent data and profile and sends it to the terminal. The terminal uses this data to activate the selected agent.

[0646] Step 5:

[0647] The user begins interacting with the activated agent. Messages entered by the user are sent to the server via the terminal.

[0648] Step 6:

[0649] The server analyzes the user's message and uses an AI engine to generate an appropriate response. This response is then sent to the terminal and displayed on the screen.

[0650] Step 7:

[0651] If the user wishes to change the conversational agent, they access the agent selection screen again. The terminal provides an interface for selecting a new agent, and once selected, the process from step 3 is repeated.

[0652] (Example 1)

[0653] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0654] Conventional information exchange systems have made it difficult for users to select the optimal agent from multiple information exchange agents due to insufficient information about the agents' characteristics and the user's situation. Furthermore, they lack the ability to generate appropriate responses using AI algorithms and to flexibly change information exchange agents based on user intent, highlighting the need for improved user experience.

[0655] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0656] In this invention, the server includes means for selecting from a plurality of information exchange agents after the user starts up the information processing device and providing the selected information exchange agent to the user's information processing device; means for obtaining information related to the selected information exchange agent from computing resources and controlling information exchange with the user based on that information; and means for generating a corresponding output using a generation AI algorithm based on input from the user. As a result, the user can easily select the optimal information exchange agent and flexible information exchange according to the situation is possible.

[0657] An "information processing device" is a device used by a user to operate an information exchange agent and display data.

[0658] An "information exchange agent" is a program that interacts with users, has a specific information exchange style, and generates responses in response to user input.

[0659] "Computational resources" refer to servers and cloud computing environments used for acquiring and processing data related to information exchange agents.

[0660] A "generative AI algorithm" is an algorithm that utilizes artificial intelligence technology to automatically generate appropriate responses based on user input data.

[0661] A "response" is the output that an information exchange agent generates in response to user input, and it facilitates the interaction with the user.

[0662] To implement this invention, the user first launches an application using an information processing device. At this time, the terminal displays a list of multiple information exchange agents via a user interface. When the user selects an agent according to the situation or mood, the terminal requests information related to the selected information exchange agent from a server, which is a computing resource.

[0663] The server uses a database to retrieve information about the selected agent's initial settings and interaction style. This information is typically sent to the terminal in JSON format. Upon receiving this data, the terminal activates the information exchange agent and prepares to begin interacting with the user.

[0664] When a user wishes to exchange information, the terminal collects the user's message using text input or speech recognition. This input is sent to the server, where an AI algorithm generates an appropriate response. The server uses natural language processing models such as GPT-3 to analyze the user's intent and generate the most suitable response.

[0665] The generated response is returned to the terminal and displayed to the user. This allows the user to obtain the necessary information while continuing their interaction with the agent.

[0666] For example, if a user wants to relax and enjoy a light conversation, they can enter the prompt, "Tell me which agent can help me relax." The selected agent will then engage in a conversation designed to promote relaxation through everyday interactions. This allows users to select an agent suited to different situations and enjoy an optimized information exchange experience.

[0667] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0668] Step 1:

[0669] When a user launches an application on the information processing device, the terminal displays a list of multiple information exchange agents on the screen. This list is compiled based on data previously received from the server. The input is the user's launch operation, and the output is the display of the agent list. Specifically, the terminal's GUI is activated, and a brief description of each agent and a selection button are displayed.

[0670] Step 2:

[0671] When a user selects a specific agent from a list, the terminal sends the selection information to the server. The server receives this input and retrieves the agent's initial setup information and interaction style data from its database. The input is the user's agent selection, and the output is detailed data about the agent. The server packages this data in JSON format and sends it to the terminal.

[0672] Step 3:

[0673] The terminal analyzes the data received from the server and launches the selected agent. During this process, an agent instance is created based on the initial setup information, and a user interaction screen is prepared. The input is agent data from the server, and the output is an agent ready for user interaction. Specifically, the agent's character icon is displayed, and the interaction input field is activated.

[0674] Step 4:

[0675] When a user enters a message into the agent, the terminal sends that text to the server. The server uses a generative AI model to initiate a process that generates a response based on the user's message. The input is the user message, and the output is the generated response. Specifically, the server executes a natural language processing algorithm to analyze the intent of the message and generate the response.

[0676] Step 5:

[0677] The server's response is sent to the terminal, which then displays it to the user. The input is the response data from the server, and the output is the display on the user's screen. Specifically, the response is displayed in text format on the terminal's display, allowing the user to continue the conversation. This entire process enables effective communication with the conversational agent.

[0678] (Application Example 1)

[0679] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0680] In modern life, users desire to utilize different dialogue systems in diverse situations, but managing them effectively and intuitively presents a challenge. Furthermore, even in devices that assist with physical tasks, further technological advancements are needed to achieve user-optimized dialogue.

[0681] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0682] In this invention, the server includes means for selecting from a plurality of dialogue systems based on the user's request and providing the selected dialogue system to the user's device; means for acquiring information about the dialogue system from an information processing device and controlling the dialogue with the user based on that information; and means for integrating the dialogue system into a device that performs physical tasks in the user's living area and executing dialogue according to the target task. As a result, the user can select the optimal dialogue system according to various situations and enjoy seamless support, including physical tasks.

[0683] A "user" is an entity that utilizes a service or system, primarily referring to a human being, but may include other subjects of exploration as needed.

[0684] A "request" refers to a wish or need expressed by a user to fulfill a specific purpose or need.

[0685] A "dialogue system" refers to a program or process that can engage in conversation with a user, and its purpose is to provide information, entertainment, or task support.

[0686] "Device" refers to a machine or device that performs a specific function or role, and may sometimes include computers or robots.

[0687] An "information processing device" refers to a device or system that receives data, performs calculations and transformations, and outputs the results.

[0688] "Integration" refers to the act or process of connecting multiple elements to make them function as a whole.

[0689] "Physical work" refers to tasks performed through specific actions or means, and is intended to take place within the user's living area.

[0690] "Support" refers to assisting a specific activity or process and enabling its smooth implementation.

[0691] In this invention, a user can use their device to select the most suitable dialogue system from among several dialogue systems. First, the user's request is received via the user interface. Next, the server obtains information corresponding to the selected dialogue system from an information processing device. This information includes the initial settings of the dialogue system, the dialogue format, and related task information.

[0692] The server uses an AI engine running on the cloud to generate appropriate responses to user requests. During this process, data calculations are performed by a generating AI model. The generated response is sent to the user's device and presented to the user via screen or audio. Specifically, this could involve using an AI engine such as OpenAI's GPT-3.

[0693] On the other hand, even in devices that perform physical actions within the user's living space, such as robots, dialogue systems are integrated. This system can initiate actions to assist physical tasks based on user selection and optimize those actions based on dialogueal instructions. Such implementations enable seamless assistance through dialogue.

[0694] For example, you can chat with a robot while relaxing in the living room on a day off, or receive cooking advice from a cooking advisor agent while you're cooking. By using prompts such as "Tell me a new pasta recipe," specific and helpful information will be provided in real time.

[0695] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0696] Step 1:

[0697] From the user's device, the user activates the system through an interface and inputs their current requests and mood. This input is sent to the system as text or voice. Based on this information, the terminal processes the user's requests as digital data and prepares to send them to the server.

[0698] Step 2:

[0699] The server receives request data sent by the user and uses an AI engine to determine which dialogue system is appropriate. In this process, a generative AI model analyzes the user's request data and generates prompt sentences. Prompt sentence generation is data processing to extract the information necessary to present choices.

[0700] Step 3:

[0701] The server retrieves information related to the appropriate dialogue system from the information processing device and transmits that information to the terminal. This information includes the initial settings and dialogue format of the target dialogue system. The server structures the retrieved data and optimizes it into a format that can be immediately responded to by the user.

[0702] Step 4:

[0703] The terminal displays a list of selectable conversational systems on its user interface based on information received from the server. The user selects a conversational system that suits their needs from the list, and the terminal sends the selection information to the server.

[0704] Step 5:

[0705] The server generates a response created by the AI ​​engine based on the selected dialogue system. The input consists of user selection information and data about the dialogue system, and the result of the calculation is an appropriate response constructed by the generating AI model. This response is then sent from the server to the terminal based on the processed data.

[0706] Step 6:

[0707] The terminal presents the user with the response received from the server. This presentation is done as text display or audio output. In parallel with this information presentation, if the user is using a physical device, the dialogue system sends instructions for physical actions to the device, and the actions are executed.

[0708] Step 7:

[0709] If the user wishes to continue the conversation, they can enter additional questions or instructions. The device then sends this back to the server, where the AI ​​engine processes it again to generate a response. The agent can also be seamlessly changed upon user request.

[0710] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0711] This invention is a dialogue agent system that combines an emotion engine to recognize user emotions, and aims to provide an optimal dialogue experience according to the user's situation and mood. Specific embodiments for carrying out this invention are shown below.

[0712] Overall system flow

[0713] First, when a user launches the application on their device, a login screen is displayed. After the user enters their authentication credentials and logs in, the server verifies the credentials. If successful, it sends a list of authorized conversational agents to the device. The device then retrieves this information and displays it to the user.

[0714] Once the user selects an agent, the device retrieves the selected agent's data from the server and begins the conversation. At this point, the emotion engine activates, analyzing the user's emotions from their voice, text messages, or facial expression data collected by the camera. Based on this analysis, the emotion engine either suggests or automatically selects the most suitable agent and conversation style.

[0715] User conversation messages are sent from the device to the server, where an AI engine generates an appropriate response. The generated response is then adjusted based on the user's emotions, as analyzed by an emotion engine, and returned to the device. This allows users to experience natural and appropriate conversations that match their mood and emotions.

[0716] Specific example

[0717] For example, if a user is feeling stressed, the emotion engine detects that emotion and suggests an agent that can calm the user. This agent engages in conversations about relaxation and offers suggestions to soothe the mood. Conversely, if the user is excited, an agent is provided that offers a positive response to support their energy.

[0718] Thus, a dialogue agent system incorporating an emotion engine can achieve highly adaptive dialogue tailored to the user's emotional needs, providing a more personalized user experience.

[0719] The following describes the processing flow.

[0720] Step 1:

[0721] When a user launches the application on their device, a login screen is displayed. The user enters their authentication information and sends an authentication request to the server.

[0722] Step 2:

[0723] The server verifies the authentication credentials, and if authentication is successful, it generates a list of authorized conversational agents for the user and sends it to the terminal. The terminal then displays this information to the user.

[0724] Step 3:

[0725] The user selects a specific agent from the displayed agent list. The terminal sends the ID of the selected agent to the server and requests the agent's profile data.

[0726] Step 4:

[0727] Based on the received agent ID, the server prepares initial data and configuration information related to that agent and sends it to the terminal. This also includes initialization data for the emotion engine.

[0728] Step 5:

[0729] The device activates its emotion engine and prepares sensors or input methods to acquire user voice, text, or facial expression information. The user then transitions to a state where interaction can begin.

[0730] Step 6:

[0731] When a user begins interacting with the agent, the device sends the entered message to the server and simultaneously passes that message and facial expression data to the emotion engine. The emotion engine then analyzes the user's emotional state.

[0732] Step 7:

[0733] The server receives messages from users and generates appropriate responses using an AI engine. These responses are then refined based on the user's emotions, which are analyzed by an emotion engine.

[0734] Step 8:

[0735] A coordinated response is sent from the server to the terminal, which then presents it to the user either visually or audibly.

[0736] Step 9:

[0737] If the user's emotions change, the emotion engine detects the change and either modifies the agent's conversation style accordingly or suggests switching to a different agent.

[0738] Step 10:

[0739] If the user wishes to end the conversation or switch to a different agent, they can repeat the process from step 3 to start a new conversation.

[0740] (Example 2)

[0741] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0742] In recent years, there has been a growing demand for dialogue systems tailored to individual user preferences. However, conventional systems struggle to accurately grasp users' emotional states and provide corresponding dialogue. Therefore, it is necessary to realize personalized dialogue experiences that respond to users' emotions and circumstances.

[0743] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0744] In this invention, the server includes means for selecting from a plurality of dialogue units based on user input information and providing the selected dialogue unit to the user's device; means for acquiring information on the dialogue unit from a data processing device and controlling the dialogue with the user based on that information; means for capturing the user's voice, text, or images, analyzing their emotional state, and automatically suggesting or selecting the optimal dialogue unit based on the analysis results; and means for adjusting the response content to reflect the analyzed emotional state in order to generate an optimized response. This makes it possible to automatically optimize the dialogue according to the user's emotions and situation, and to provide a more natural and personalized dialogue.

[0745] "User input information" refers to data provided by the user through the device, including voice, text, and selected options.

[0746] A "dialogue unit" refers to a basic element used for dialogue, and is a software entity that has a different dialogue format or style.

[0747] A "data processing device" is a device used to process input data and perform necessary calculations and acquire information, and specifically refers to servers and computers.

[0748] "Emotional state" refers to the emotional state exhibited by the user, and is analyzed from data such as voice, text, and facial expressions.

[0749] "Automatic suggestion or selection of optimal dialogue units" means that, based on an analysis of the user's emotional state, the system automatically presents or selects the dialogue style and agent that are most suitable for the user.

[0750] "Optimized responses" refer to conversational approaches and messages that are tailored to the user's emotions and situation, aiming to achieve more effective communication.

[0751] This invention is a dialogue system that recognizes and adapts to the user's emotions, and is implemented through the interaction of a server, a terminal, and the user.

[0752] The user's device has an application installed that provides an interface for the user to initiate interaction. The device acquires user input using hardware such as a voice input device, touch panel, or camera. Software includes the user interface and data capture modules.

[0753] The device captures the user's voice, text, and facial expression data and sends this data to a server. The server is a powerful data processing device connected to a database. Here, the server uses an emotion analysis engine to analyze the user's emotional state from the transmitted data. This engine utilizes machine learning and speech recognition algorithms.

[0754] The server uses a generative AI model to generate optimal dialogue responses based on the user's emotions. These generated responses are then refined through emotion analysis and sent to the terminal. The terminal then presents them to the user in text or audio format.

[0755] For example, if a user is feeling stressed, the emotion engine detects that emotion and automatically selects an agent to provide a relaxing conversation. For instance, if the user provides the prompt, "I'm a little tired. Please tell me how to relax," the system will construct helpful advice and a conversation for the user.

[0756] This system aims to provide users with a more natural and personalized conversational experience by appropriately responding to their emotions.

[0757] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0758] Step 1:

[0759] The user launches a conversational application on their device. When the user enters login information and presses the login button, the device sends this information to the server. The input is the user's authentication information, and the output is the status of the transmission to the server. Specifically, the device encrypts the entered data before sending it to the server.

[0760] Step 2:

[0761] The server compares the authentication information received from the terminal with the database. The input is the authentication information from the user, and the output is whether the authentication was successful or not. The server executes an SQL query on the database to perform the specific action of verifying the user information. If authentication is successful, it generates a list of available interaction units and returns it to the terminal.

[0762] Step 3:

[0763] The terminal displays a list of dialogue units received from the server to the user. The input is the list of dialogue units from the server, and the output is the content displayed to the user. Specifically, the terminal's GUI forms the list and presents it visually to the user.

[0764] Step 4:

[0765] The user selects an interaction unit from a displayed list. The selected data is sent from the terminal to the server as a request. The input is the user's selection, and the output is the request to the server. The terminal captures the selected information and sends it to the server in a structured data format.

[0766] Step 5:

[0767] The server retrieves detailed information about the selected dialogue unit and sends it back to the terminal. The input is the request from the terminal, and the output is the dialogue unit data. The server executes queries to retrieve information from the database.

[0768] Step 6:

[0769] The device acquires user voice, text, camera footage, and other data, and sends this to the sentiment analysis engine. The input is the user's sensor information, and the output is the sentiment analysis result. Specifically, the device processes the acquired data in real time and converts it into an analysis format.

[0770] Step 7:

[0771] The server uses an emotion analysis engine to analyze the user's emotional state from the input data. The input is sensor information, and the output is emotional state data. The emotion analysis engine uses machine learning algorithms to perform the specific actions of inferring emotions from the data.

[0772] Step 8:

[0773] Using a generative AI model, the system generates the optimal response based on the analyzed emotional state. The input is emotional state data, and the output is the adjusted response. The server activates a natural language processing algorithm to generate and adjust the response to suit the user's situation.

[0774] Step 9:

[0775] The terminal receives a response from the server and presents it to the user. The input is the response received from the server, and the output is a presentation to the user via screen or audio. The terminal processes the received data and communicates it to the user through visual or speech synthesis functions.

[0776] (Application Example 2)

[0777] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0778] Modern information systems require personalized dialogue that responds to user emotions. However, conventional dialogue agent systems have struggled to adequately analyze user emotions and provide optimal dialogue accordingly. Furthermore, special consideration for user emotions is necessary when considering use in a home environment.

[0779] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0780] In this invention, the server includes means for analyzing the user's emotions and providing appropriate dialogue based on the analysis results; means for selecting from a plurality of dialogue agents based on the user's request and providing the selected dialogue agent to the user's device; and means for obtaining data of the dialogue agent from the server and controlling the dialogue with the user based on that data. This makes it possible to provide detailed dialogue that responds to the user's emotions.

[0781] "User requirements" refer to the preferences and conditions specified by the user when selecting a conversational agent in the system.

[0782] A "conversational agent" is software designed to engage in conversations with users, generating responses using voice, text, and facial expression data.

[0783] "User's device" refers to electronic devices used to run the conversational agent, including smartphones and tablets.

[0784] A "server" is an information processing system that stores and processes data over a network and provides services to a user's device.

[0785] "Emotional analysis" involves processing a user's voice, text, and facial expression data to estimate their emotional state.

[0786] "Providing appropriate dialogue" is the process of outputting the most suitable response according to the user's emotional state.

[0787] "Household appliances" refer to electronic devices used within the home that are capable of interacting with the user.

[0788] This invention realizes a conversational agent system that recognizes user emotions and provides optimal dialogue. This system consists of a user device, a server, and a home device.

[0789] The server utilizes a generative AI model to analyze the user's emotions. Specifically, it processes voice, text, and facial expression data transmitted from the user's device and analyzes their emotional state. Based on the analyzed emotional data, the server selects an appropriate dialogue agent and provides the generated response to the user's device.

[0790] The user's device consists of home devices such as smartphones and tablets. This device runs a conversational agent selected by the user and interacts with the user based on data received from the server. Through this interaction, the user can receive appropriate responses that match their emotions at the time.

[0791] For example, when a user is feeling tired, the system may recognize this and suggest relaxation-related music or deep breathing exercises. An example of a prompt would be, "How would you respond if the user said they wanted to relax?"

[0792] Thus, with the system of the present invention, users can obtain an emotionally resonant dialogue experience even in a home environment.

[0793] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0794] Step 1:

[0795] The user starts the device and opens the conversational agent application. The user enters authentication information on the login screen. The entered information is sent from the user's device to the server for authentication. If authentication is successful, the server sends a list of authorized conversational agents to the user's device. The device displays this list.

[0796] Step 2:

[0797] The user selects an interactive agent from the displayed list of agents. The user's selection information is sent from the device to the server. The server retrieves data from the selected agent and uses a generated AI model to produce an appropriate response based on that data. This response data is then sent back to the user's device.

[0798] Step 3:

[0799] When a user speaks into the microphone, the device collects audio data. Simultaneously, a camera captures the user's facial expressions. This data is sent from the device to a server for emotion analysis. The server analyzes the audio and facial data to estimate the user's emotional state. Based on this estimation, the response is optimized.

[0800] Step 4:

[0801] The server adjusts the conversational agent's response based on the emotion analysis results and returns the generated response to the user's device. The device outputs the adjusted response to the user as voice or text. This allows the user to receive responses that are adapted to their emotional state.

[0802] Step 5:

[0803] If the user requests yet another conversational agent, the device receives the request and sends another request to the server. Again, the user's emotional state is taken into consideration, and the most appropriate agent is suggested. Once a re-selection is made, this series of steps is repeated.

[0804] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0805] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0806] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0807] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0808] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0809] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0810] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0811] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0812] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0813] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0814] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0815] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0816] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0817] 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.

[0818] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0819] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0820] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0821] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0822] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0823] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0824] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0825] The following is further disclosed regarding the embodiments described above.

[0826] (Claim 1)

[0827] A means for selecting from multiple conversational agents based on user requests and providing the selected conversational agent to the user's device,

[0828] A means of obtaining data from the above-mentioned dialogue agent from the server and controlling the interaction with the user based on that data,

[0829] A means of providing the user with the option to change the conversational agent based on the interaction with the user,

[0830] A system that includes this.

[0831] (Claim 2)

[0832] The system according to claim 1, wherein each dialogue agent has a different dialogue style and generates different responses depending on the user's selection.

[0833] (Claim 3)

[0834] The system according to claim 1, further comprising a function to automatically suggest the most suitable conversational agent based on the user's situation and mood.

[0835] "Example 1"

[0836] (Claim 1)

[0837] A means for selecting from multiple information exchange agents after the user starts up the information processing device and providing the selected information exchange agent to the user's information processing device,

[0838] A means for obtaining information related to the selected information exchange agent from computing resources and controlling information exchange with the user based on that information,

[0839] A means of generating a corresponding output using a generative AI algorithm based on user input,

[0840] A means of providing users with the option to select an information exchange agent based on information exchange with the user,

[0841] A system that includes this.

[0842] (Claim 2)

[0843] The system according to claim 1, in which each information exchange agent has a different information exchange style and produces different responses depending on the user's selection.

[0844] (Claim 3)

[0845] The system according to claim 1, comprising a function that automatically recommends the most suitable information exchange agent based on the user's situation and emotional state.

[0846] "Application Example 1"

[0847] (Claim 1)

[0848] A means for selecting from multiple dialogue systems based on user requests and providing the selected dialogue system to the user's device,

[0849] A means for acquiring information from the above dialogue system from an information processing device and controlling the dialogue with the user based on that information,

[0850] A means for integrating a dialogue system into a device that performs physical tasks in the user's living space, and for performing dialogue according to the task at hand,

[0851] A means of providing the user with the option to change the dialogue system based on the interaction with the user,

[0852] A system that includes this.

[0853] (Claim 2)

[0854] The system according to claim 1, wherein each dialogue system has a different dialogue format and generates different responses depending on the user's selection.

[0855] (Claim 3)

[0856] The system according to claim 1, comprising a function to automatically suggest an optimal dialogue system based on the user's situation and mood, and to support physical actions related to the system.

[0857] "Example 2 of combining an emotion engine"

[0858] (Claim 1)

[0859] A means for selecting from multiple interaction units based on user input information and providing the selected interaction unit to the user's device,

[0860] A means for obtaining the above-mentioned dialogue unit information from a data processing device and controlling the dialogue with the user based on that information,

[0861] A means for capturing user voice, text, or images, analyzing their emotional state, and automatically suggesting or selecting the optimal dialogue unit based on the analysis results,

[0862] In order to generate an optimized response, means are provided to adjust the response content to reflect the analyzed emotional state,

[0863] A system that includes this.

[0864] (Claim 2)

[0865] The system according to claim 1, wherein each dialogue unit has a different dialogue format and generates different responses depending on the user's selection.

[0866] (Claim 3)

[0867] The system according to claim 1, further comprising a function that automatically suggests the optimal dialogue unit based on changes in the user's emotions.

[0868] "Application example 2 when combining with an emotional engine"

[0869] (Claim 1)

[0870] A means for selecting from multiple conversational agents based on user requests and providing the selected conversational agent to the user's device,

[0871] A means of obtaining data from the above-mentioned dialogue agent from the server and controlling the interaction with the user based on that data,

[0872] A means of providing the user with the option to change the conversational agent based on the interaction with the user,

[0873] A means of analyzing user emotions and providing appropriate dialogue based on the analysis results,

[0874] A system that includes this.

[0875] (Claim 2)

[0876] The system according to claim 1, wherein each dialogue agent has a different dialogue style and generates different responses according to the user's emotions.

[0877] (Claim 3)

[0878] The system according to claim 1, which automatically suggests the most suitable conversational agent based on the user's situation and mood, and operates on a home device. [Explanation of Symbols]

[0879] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for selecting from multiple dialogue systems based on user requests and providing the selected dialogue system to the user's device, A means for acquiring information from the above dialogue system from an information processing device and controlling the dialogue with the user based on that information, A means for integrating a dialogue system into a device that performs physical tasks in the user's living space, and for performing dialogue according to the task at hand, A means of providing the user with the option to change the dialogue system based on the interaction with the user, A system that includes this.

2. The system according to claim 1, wherein each dialogue system has a different dialogue format and generates different responses according to the user's selection.

3. The system according to claim 1, comprising a function to automatically propose an optimal dialogue system based on the user's situation and mood, and to support physical actions related to the system.

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