system

Abstract

We provide the system. [Solution] An artificial intelligence method that collects publicly available information and learns human characteristics, A generation means that generates a virtual customer service representative using the artificial intelligence means, A dialogue means for conducting a conversation between a virtual customer representative and a user generated by the generation means, A billing means for measuring and processing usage fees incurred during the aforementioned dialogue, 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 persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Many people desire to interact with famous experts or familiar people. However, in order to actually obtain such opportunities, there are time, economic constraints and psychological barriers. There is also a need to reproduce conversations with important people in the past who were lost due to earthquakes or accidents, and currently, a method to realize these is required. The purpose of this invention is to meet such conversation needs and provide a consultation environment that anyone can easily access.

Means for Solving the Problems

[0005] This invention provides an artificial intelligence means that learns human characteristics based on publicly available information, and a generation means that generates virtual customer service representatives based on the learning results. Users can interact with these virtual customer service representatives, and a billing means that measures and processes usage fees incurred during these interactions to manage their financial burden. This system allows users to virtually interact with celebrities or specific people from the past, making it possible to satisfy their consultation needs while reducing time and psychological barriers.

[0006] "Public information" refers to information, documents, media files, etc., that can be freely accessed on the internet.

[0007] "Artificial intelligence tools" are algorithms or software that can learn human characteristics and behaviors and perform intelligent processing.

[0008] A "virtual customer service representative" is a digital avatar generated by artificial intelligence that possesses the characteristics of a real human being and is capable of interacting with users.

[0009] A "generation method" is a technique or system that can create new content or models based on learned data.

[0010] A "dialogue mechanism" refers to a user interface or algorithm used for information exchange between a user and a virtual customer service representative.

[0011] A "billing method" is a system or method for measuring the cost of using a service and collecting that cost from the user. [Brief explanation of the drawing]

[0012] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential 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.

Embodiments for Carrying Out the Invention

[0013] 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.

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

[0015] In the following embodiments, the numbered 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.

[0016] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0017] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. 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.

[0018] In the following embodiments, the numbered communication I / F (Interface) is an interface that includes a communication processor, an antenna, and the like. 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).

[0019] 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."

[0020] [First Embodiment]

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

[0022] 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.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0027] 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.

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

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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".

[0033] This invention provides a system that generates a virtual customer service representative using artificial intelligence based on publicly available information, and allows users to interact with this representative. This system mainly consists of a server, terminals, and users.

[0034] The server collects publicly available information from the web related to celebrities or historical figures selected by the user. This collected information includes facial features, voice characteristics, and spoken content, which are used by artificial intelligence to learn the characteristics of the target.

[0035] Next, the server uses a generation mechanism to create a virtual customer service representative based on the learned data. The generated customer service representative's appearance and voice are reproduced, and it is possible to simulate a conversation with that person.

[0036] The terminal is equipped with a user interface, which the user uses to select a virtual customer service representative. Interaction with the selected representative takes place through the terminal's display screen and audio output. The terminal transmits user input, i.e., questions and inquiries in text or voice, to the server.

[0037] The server, in response to the inquiry received from the terminal, synthesizes a response generated by artificial intelligence using the voice and style of a virtual customer service representative, and sends it to the terminal. This response is displayed to the user in real time and, in some cases, output as audio from the terminal.

[0038] Users can freely interact with a virtual customer service representative regarding specific inquiries or questions. If the interaction exceeds a certain time limit or if certain features are used, an additional payment process will occur via a billing system. The billing process is displayed to the user through the terminal interface and is designed for easy operation.

[0039] In this way, the embodiment of the present invention is designed to reduce the time and psychological hurdles for users, enabling them to easily engage in dialogue with the person they desire. Furthermore, by even making virtual reunions with people who existed in the past possible, it provides an effective dialogue platform.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The user enters the name of the person they wish to consult using their device.

[0043] Step 2:

[0044] The terminal sends the entered person's name to the server.

[0045] Step 3:

[0046] Based on the name of the person received, the server collects publicly available information related to that person from the internet.

[0047] Step 4:

[0048] The server analyzes the collected information and extracts facial features, voice, and spoken content.

[0049] Step 5:

[0050] The server uses artificial intelligence to train itself on the extracted features.

[0051] Step 6:

[0052] The server uses a generation mechanism to create a virtual customer service representative based on the learned data.

[0053] Step 7:

[0054] The terminal receives information about a virtual customer representative generated from the server and displays it to the user.

[0055] Step 8:

[0056] The user initiates the interaction through the terminal's interface and enters the details of their inquiry.

[0057] Step 9:

[0058] The terminal sends the entered consultation details to the server.

[0059] Step 10:

[0060] The server generates a response using artificial intelligence based on the content of the inquiry, and then synthesizes that response in the style of a virtual customer service representative.

[0061] Step 11:

[0062] The server sends the synthesized response to the terminal.

[0063] Step 12:

[0064] The terminal displays the response to the user and outputs it audibly if necessary.

[0065] Step 13:

[0066] If the user has further questions or concerns, they can continue the conversation.

[0067] Step 14:

[0068] The server measures the interaction time and implements billing measures as needed.

[0069] Step 15:

[0070] When the user ends the interaction, the device notifies the server and displays the final billing information.

[0071] (Example 1)

[0072] 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."

[0073] In recent years, there has been a growing demand from users to interact with specific celebrities or historical figures, but it is naturally impossible to interact with people who do not exist in reality. Furthermore, advanced information processing technology is required for users to interact naturally with virtually recreated figures. In addition, if the procedures for handling fees incurred during the interaction process are complicated, usability may decrease. This invention aims to solve these problems and provide a system that allows a wide range of users to easily enjoy a high-quality conversational experience.

[0074] 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.

[0075] In this invention, the server includes an information processing means for collecting publicly available information and learning human characteristics, a generation means for generating a virtual dialogue subject using the information processing means, and a communication means for the user to interact with the virtual dialogue subject generated by the generation means. This enables users to virtually interact with specific celebrities or historical figures, and the interaction experience is provided in real time, resulting in high-quality interaction. In addition, the measurement and processing of usage fees are simplified, reducing the user's operational burden.

[0076] "Public information" refers to a collection of data that is accessible to the public through the internet or other media, and which includes information about specific individuals.

[0077] "Information processing means" refers to systems or devices that have the function of analyzing and organizing collected data and deriving results that are appropriate for a specific purpose.

[0078] "Generation means" refers to methods and techniques for creating a virtual object based on the results obtained through information processing.

[0079] A "dialogue subject" is a virtual entity designed to interact with users, modeled after a specific person.

[0080] "Communication methods" refer to interfaces and protocols used for exchanging information between users and systems, enabling real-time data transmission.

[0081] "Methods for measuring fees" refer to systems and mechanisms for measuring the costs associated with using a service and for ensuring appropriate billing.

[0082] An "operation screen" refers to an interface that allows users to perform operations visually and tactilely, providing users with information and enabling them to make choices.

[0083] The system implementing this invention mainly consists of a server, a terminal, and a user. The server first collects publicly available information from the internet related to a celebrity or historical figure selected by the user. For this collection, it utilizes web scraping technology and various APIs (e.g., online encyclopedia API, social media API). Through this, the server obtains and stores data such as facial photographs, audio clips, and transcripts of statements of the target person.

[0084] The server preprocesses the acquired data and learns human characteristics using an artificial intelligence model. This process uses facial recognition algorithms and speech analysis technologies (e.g., speech recognition APIs), which are then input into a generative AI model. Specific generative AI models include text generation models widely used in natural language processing and models used for speech synthesis (e.g., general-purpose natural language processing libraries and speech generation engines).

[0085] Next, the server generates a virtual dialogue entity based on the learning results. Using a generative AI model, the text and voice responses of this virtual dialogue entity are realistically reproduced. The virtual dialogue entity is constructed to enable seamless interaction with the user.

[0086] The terminal is equipped with a user interface that the user provides to select a virtual conversational subject through this interface. After selection, the user can ask questions or seek advice via voice or text. The terminal sends the user's input to the server, receives the generated response from the server, and displays or outputs it to the user.

[0087] For example, if a user requests to "interact with a historical scientist," the server collects publicly available information on the relevant individuals and generates a virtual scientist as the conversational subject. The user can then receive an explanation on their desired topic by entering a prompt such as, "I would like a historical scientist to explain my research."

[0088] This system allows the server to provide a customized conversational experience tailored to the user's needs in real time, enabling users to gain new learning and insights. Furthermore, the billing process is simplified through the terminal interface, allowing for smooth processing of usage fees.

[0089] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0090] Step 1:

[0091] The server collects publicly available information from the internet about celebrities or historical figures selected by the user. Specifically, the server uses web scraping techniques and APIs to obtain data such as facial images, audio clips, and transcripts of statements. The input is the name of the person selected by the user and related keywords, and the output is the collected data. This data is temporarily stored in storage for subsequent processing.

[0092] Step 2:

[0093] The server performs preprocessing on the collected data. Specifically, for image data, it extracts features using a facial recognition algorithm, and for audio data, it identifies voice characteristics using speech analysis techniques. For text data, it analyzes the content of the speech using natural language processing techniques. The raw, unprocessed data is used as input, and the output is the data with extracted features.

[0094] Step 3:

[0095] The server generates a virtual dialogue subject using a generative AI model based on preprocessed data. Here, a text generation model is used to create the content of the target person's conversation, and a speech synthesis model is used to reproduce its voice. Feature-extracted data is used as input, and a realistically reproduced virtual dialogue subject is obtained as output.

[0096] Step 4:

[0097] The user selects a virtual conversational subject through the terminal's user interface. The terminal displays available options to the user and transmits the selection to the server. The input includes the user's selection information, and the output generates commands for the server.

[0098] Step 5:

[0099] The user initiates a conversation with a virtual dialogue entity using a terminal. The user can either type prompts or ask questions by voice. The terminal sends the input information to the server, which then uses a generative AI model to return an appropriate response. The input is the user's question, and the output is the answer from the virtual dialogue entity.

[0100] Step 6:

[0101] If the user engages in conversation for a certain period of time or uses a specific function, the terminal initiates the billing process. The terminal presents the user with billing information and payment methods, and completes the process after obtaining user confirmation. Inputs include conversation time and functions used, and output is confirmation that the billing was performed correctly.

[0102] (Application Example 1)

[0103] 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."

[0104] This invention aims to realize an interactive system that utilizes virtual customer service representatives to allow users to receive real-time advice from celebrities and historical figures. In particular, the challenge is to improve the accuracy and satisfaction of fashion and lifestyle-related decision-making by providing more personalized advice that takes into account the user's personal attributes and possessions.

[0105] 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.

[0106] In this invention, the server includes an artificial intelligence means for collecting publicly available information and learning human attributes, a generation means for generating a virtual customer service representative using the artificial intelligence means, and a suggestion means for managing information about the user's possessions and providing attribute-based advice from the virtual advisor. This makes it possible for the user to receive specific and accurate advice tailored to their individual needs from a virtual customer service representative of their choice.

[0107] "Public information" refers to data and documents accessible on the internet that are generally known and relate to a specific person or subject.

[0108] "Human attributes" refer to the characteristics and traits of individual human beings, including information such as appearance, voice, style, and behavioral patterns.

[0109] "Artificial intelligence means" refers to technological means that use computer systems to analyze and learn from data, and then make decisions and predictions based on the results.

[0110] A "virtual customer service representative" is a digital character created using artificial intelligence technology that can simulate a specific person and interact with users.

[0111] "Generation means" refers to technical means for creating new digital objects based on learned data.

[0112] An "action" is the process of information exchange and communication that takes place between the user and a virtual customer service representative.

[0113] "Usage costs" refer to expenses incurred in connection with using the system, and are monetary burdens measured on an hourly basis or according to the functionality used.

[0114] A "billing method" is a technical means for accurately measuring, processing, and billing for the costs incurred when users utilize a system.

[0115] "Possessions information" refers to data related to items and assets owned by the user, including fashion items and other personal items.

[0116] A "suggestion tool" is a technical tool that provides advice indicating the optimal choices and actions based on the user's attributes and possession information.

[0117] The "connection interface" is the interface that users use to select a virtual customer service representative and initiate a conversation.

[0118] The system used to implement this application primarily consists of three elements: a server, a terminal, and a user.

[0119] The server includes artificial intelligence means for collecting and processing publicly available information and learning human attributes. Specifically, it collects publicly accessible data on the web and analyzes information about the appearance, voice, style, and behavioral patterns associated with a particular individual. The learned data is used to generate a virtual customer service role using an AI model (e.g., OpenAI®'s GPT-4®). This virtual role simulates the characteristics of a specific person and enables interaction with the user.

[0120] The terminal acts as an intermediary for the interaction between the user and a virtual customer service representative. The terminal displays a connection screen where the user can select a virtual customer service representative and, if necessary, check the usage costs. Information about the user's possessions (e.g., fashion items) is managed through the terminal and used by the virtual advisor to provide optimal advice based on the user's attributes. This allows the user to receive specific and accurate advice.

[0121] The user uses this system to initiate a conversation with a virtual customer service representative of their choice. For example, by asking a question like, "I'm attending a social event today. What would be appropriate attire?", they can receive style suggestions for the day from a virtual fashion advisor.

[0122] An example of a prompt message is, "Based on the clothing preferences entered by the user, please suggest clothing styles from the selected stylist."

[0123] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0124] Step 1:

[0125] The server collects publicly available information from the internet. This collection process searches data sources related to a specific individual and extracts attribute information such as appearance, voice, and speech content. The input is information about the target individual, and the output is formatted attribute data. This data is stored for the learning phase.

[0126] Step 2:

[0127] The server passes the collected data to an artificial intelligence system to learn human attributes. Using a generative AI model, it analyzes and learns the characteristics of the data, incorporating the person's style and features into the model. The input is formatted attribute data, and the output is the trained model.

[0128] Step 3:

[0129] The server generates a virtual customer service representative using a pre-trained model. This generation method constructs a digital character capable of simulating a person's appearance and voice in real time. The input is the pre-trained model data, and the output is the virtual customer service representative.

[0130] Step 4:

[0131] The terminal displays an interface that allows the user to select a virtual customer service role. The user selects their desired role via the screen and completes preparation for the next step. The input is the user's instruction regarding their selection, and the output is the result of that selection.

[0132] Step 5:

[0133] The user initiates a conversation with a virtual customer service representative of their choice. The terminal receives questions from the user and sends them to the server in text or voice format. The input is the user's question, and the output is the data sent to the server.

[0134] Step 6:

[0135] The server uses a generative AI model to generate a response based on the received question. This model analyzes the context of the question and provides a response tailored to the style of a virtual customer service representative. The input is the user's question, and the output is a well-constructed response.

[0136] Step 7:

[0137] The terminal provides the user with a generated response. The response is played back as text or audio and presented in a format that is easy for the user to understand. The input is the generated response data, and the output is the information displayed to the user.

[0138] Step 8:

[0139] The terminal measures the usage costs incurred during the interaction and displays them to the user as needed. This includes calculating charges based on system usage time and the use of special features. Input is usage information related to the interaction, and output is a charge display.

[0140] 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.

[0141] This invention combines a system that generates a virtual customer service representative using artificial intelligence based on publicly available information and interacts with the user with an emotion engine that recognizes the user's emotions. This system consists of a server, a terminal, a user, and an emotion engine.

[0142] When a user enters the name of a specific person they wish to interact with, the server collects publicly available information about that person from the internet. This information includes facial features, voice characteristics, and spoken content, and the artificial intelligence learns the target's characteristics based on this data. Based on the learning results, the server uses a generation mechanism to create a virtual customer service representative and sends that information to the terminal.

[0143] The terminal provides a user interface, which the user uses to select a virtual customer service representative. The terminal also receives input from the user regarding their inquiry and sends it to the server. At this point, the emotion engine operates and analyzes the user's emotional state based on their input. For example, if the user inputs "I've been very tired from work lately," the emotion engine recognizes emotions such as "fatigue" and "stress."

[0144] The server takes into account the emotions recognized by the emotion engine and adjusts the AI-generated response to suit the conditions. It generates dialogue content corresponding to the recognized emotion and synthesizes the response in the style of a virtual customer service representative. For example, if "fatigue" is recognized, the virtual customer service representative might respond with something like, "That must be tough. Do you have time to refresh yourself now?"

[0145] The device displays this response to the user in real time and outputs it audibly as needed. This allows the user to continue the virtual conversation and experience a more empathetic dialogue.

[0146] Furthermore, this system incurs additional charges under certain conditions. These charges are clearly communicated to the user via their device, and the interaction continues only after approval. By incorporating an emotion engine, this invention is able to provide a highly personalized interaction that responds to the user's emotions, going beyond mere information provision.

[0147] The following describes the processing flow.

[0148] Step 1:

[0149] The user uses their device to enter the name of the person they want to consult with and requests the creation of a virtual customer service representative.

[0150] Step 2:

[0151] The terminal sends the entered information to the server.

[0152] Step 3:

[0153] Based on the name of the person who submitted the request, the server automatically collects relevant information that is publicly available on the internet.

[0154] Step 4:

[0155] The server analyzes the collected information and extracts characteristics of the subject, such as their appearance, voice, and personality.

[0156] Step 5:

[0157] The server uses artificial intelligence to learn the extracted features and generate a virtual customer service representative.

[0158] Step 6:

[0159] The server sends the generated virtual customer service representative data to the terminal.

[0160] Step 7:

[0161] The terminal displays a screen for the user to select a virtual customer service representative.

[0162] Step 8:

[0163] The user uses their device to select a virtual customer service representative to begin a consultation with.

[0164] Step 9:

[0165] The user enters their inquiry details as text or voice and sends them to the server via their device.

[0166] Step 10:

[0167] The server analyzes the received consultation content using an emotion engine to recognize the user's emotional state.

[0168] Step 11:

[0169] The server uses artificial intelligence to generate appropriate responses based on recognized emotions, and then synthesizes these responses in the style of a virtual customer service representative.

[0170] Step 12:

[0171] The server sends the synthesized response data to the terminal.

[0172] Step 13:

[0173] The device displays real-time generated responses to the user and provides audio output as needed.

[0174] Step 14:

[0175] If the user wishes to continue the conversation, they will enter additional questions into the terminal and run the process again.

[0176] Step 15:

[0177] The server measures the duration of the interaction and, if it exceeds the time limit for a paid session, activates the billing mechanism and notifies the user via their device.

[0178] Step 16:

[0179] The user can choose to accept the charge and continue the conversation, or end the conversation.

[0180] Step 17:

[0181] The device will end the interaction based on the user's choice and, if necessary, provide the user with final billing information.

[0182] (Example 2)

[0183] 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".

[0184] In recent years, AI-powered dialogue systems have become widespread in many fields. However, conventional systems have struggled to accurately recognize users' emotions and respond accordingly. As a result, users have faced the challenge of receiving uniform dialogue and not being able to receive satisfactory dialogue that reflects their individual emotions and needs. Furthermore, there has been a lack of adequate interfaces that allow users to easily select a specific person they wish to virtually interact with.

[0185] 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.

[0186] In this invention, the server includes artificial intelligence means for collecting publicly available information and learning personal characteristics, generation means for generating a virtual responder, and emotion recognition means for analyzing the emotional state based on the user's input. As a result, the user can interact with a virtual responder that resembles a specific person, and the content of the interaction is adjusted according to the user's emotions, enabling a more personalized experience.

[0187] "Public information" refers to data that is publicly available on the internet or other accessible data sources.

[0188] "Personal characteristics" refer to information used to identify a person, such as their physical appearance, vocal characteristics, and the content of their statements.

[0189] "Artificial intelligence tools" refer to technological means that use machine learning and natural language processing to acquire knowledge from data and perform processing according to specific purposes.

[0190] "Generative means" refers to methods and processes for creating new data-based content using artificial intelligence technology.

[0191] "Emotion recognition means" refers to technical means for analyzing user input data and identifying emotional states based on that analysis.

[0192] "Response generation means" refers to a means for generating an appropriate response based on analyzed emotions and presenting it to the user.

[0193] "Dialogue means" refers to the process for communication between a virtual responder and the user.

[0194] "Billing method" refers to the methods and technologies used to measure and process charges associated with the use of a system.

[0195] The system of this invention consists of a server, a terminal, and a user, and further incorporates an emotion engine for emotion recognition.

[0196] After receiving the name of the person the user wishes to interact with, the server uses web scraping tools to collect relevant publicly available information from the internet. For example, Scrapy can be used. The data collected at this stage includes the person's facial features, voice characteristics, and speech information. Based on this data, artificial intelligence learns the person's characteristics using machine learning algorithms and generates a virtual responder using a generative AI model. Models that can be used as natural language processing techniques in this process include GPT-3®.

[0197] The terminal provides an interface to the user, displaying and allowing them to select a virtual responder. This interface includes fields for the user to input or voice-input their consultation details. Voice input can utilize speech recognition software. The data entered by the user is sent to the server in real time, where an emotion engine analyzes the user's emotions. Through emotion recognition, the system can understand the user's situation, such as if they are experiencing "fatigue" or "stress."

[0198] Based on the analysis results, the server generates a response using a generative AI model and adjusts it to match the user's emotions. This adjusted response is sent to the terminal, which displays the response to the user and, in some cases, also outputs it as audio. In this case, text-to-speech (TTS) technology is used to convert it to speech.

[0199] For example, if a user types "I've been really tired from work lately," a tailored response such as "That must be tough. Do you have time to relax now?" will be generated.

[0200] A concrete example of a prompt message would be: "The user wants a conversation based on information related to a specific person. Based on the emotional information entered by the user, the emotion engine will generate appropriate dialogue content."

[0201] This system allows users to engage in emotionally-driven conversations with virtual characters, which is expected to enhance the personalized experience.

[0202] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0203] Step 1:

[0204] The server receives the name of a specific person from the user. Using this name as input, the server uses web scraping tools to collect publicly available information related to that person from the internet. This data includes facial features, voice characteristics, and statements, and is output as a single database.

[0205] Step 2:

[0206] The server provides the collected information to an artificial intelligence system, which then learns about human characteristics. During this process, machine learning algorithms are applied to extract features from the received data. As a result, a trained model is output.

[0207] Step 3:

[0208] The server generates a virtual responder using a generative AI model. In this process, the artificial intelligence synthesizes content such as text and audio using the trained model as input. This outputs a digital profile of the virtual responder, which is then sent to the terminal.

[0209] Step 4:

[0210] The terminal provides an interface that displays a virtual responder to the user. The user selects a responder they wish to interact with through this interface, and this selection information is sent to the server.

[0211] Step 5:

[0212] The user inputs, either by typing or voice, what they want to communicate with a virtual responder through the device. This user input is sent to an emotion recognition system and processed as data for analysis.

[0213] Step 6:

[0214] The server generates an appropriate response using a response generation mechanism based on the user's emotions analyzed by the emotion recognition mechanism. At this stage, the generation AI model is used again to generate a response that matches the user's emotional state. The adjusted response is output and sent to the terminal.

[0215] Step 7:

[0216] The terminal presents the received response to the user visually and audibly. For audio output, a TTS (text-to-speech) engine is used, and the generated text is played back as natural-sounding speech. The user can then respond or provide further input based on the presented information.

[0217] (Application Example 2)

[0218] 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".

[0219] Traditional systems made it difficult to understand user emotions during customer service, resulting in only simple information being provided. Furthermore, the lack of mechanisms to deliver appropriate dialogue tailored to the user's situation prevented the realization of a deeper customer experience.

[0220] 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.

[0221] In this invention, the server includes artificial intelligence means for collecting publicly available information and learning the attributes of a person; generation means for generating a virtual conversationalist; analysis means including an emotion engine for analyzing the emotional state based on the user's input information; response adjustment means; and billing means. This enables personalized customer service by providing conversational content that corresponds to the user's emotional state.

[0222] "Public information" refers to data and knowledge that is generally accessible on the internet and includes attributes and characteristics related to a specific person.

[0223] "Artificial intelligence means" refers to technologies that function as part of a computer system and have the function of learning and recognizing a person's attributes.

[0224] "Generative means" refers to the process or function of creating a virtual conversational partner based on information learned by artificial intelligence.

[0225] "Dialogue means" refers to a system or function that enables the exchange of information between a virtual interlocutor and the user.

[0226] An "emotion engine" is a technology that analyzes user input information to identify and classify a person's emotional state.

[0227] "Analytical means" refers to the ability or method to process input data and derive specific conclusions or results.

[0228] "Response adjustment means" refers to a system or function that generates and adjusts the optimal response content based on the analyzed emotional state.

[0229] A "billing method" is a system that has the function of measuring and processing usage fees based on the usage of the conversation.

[0230] To realize this invention, a server, terminals, users, and a network to connect them are primarily required. The server should function as a cloud computing environment and can utilize Amazon Web Services (AWS®) or Google® Cloud Platform. For the terminals, smartphones running iOS or Android® are preferable.

[0231] First, the server collects publicly available information from the internet, including a specific person's facial features, voice characteristics, and spoken content. The artificial intelligence system uses this information to learn the person's attributes using a generative AI model. Based on the learning results, the generative system generates a virtual conversational partner, which is then sent to the user's terminal.

[0232] The terminal selects and displays a virtual interlocutor through a user interface. The user inputs their consultation details using the interface, which are then sent to the server. An emotion engine analyzes the user's input and recognizes their emotional state. This analysis result is used by a response adjustment mechanism to generate an appropriate response tailored to the user's emotions.

[0233] For example, if a user inputs "I feel anxious before purchasing a product online," the emotion engine recognizes the emotion of "anxiety." As a result, the virtual dialogue partner will engage in conversation such as, "Purchasing is a big decision, isn't it? It might be helpful to refer to other customers' reviews and usage examples." This allows the user to experience an emotionally empathetic response.

[0234] Example prompt: "The user has expressed concerns about this product. Please explain how they can use this product and how it can improve their daily life, and provide the best way to support them in making a purchase decision with confidence."

[0235] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0236] Step 1:

[0237] The server receives the name of a specific person the user wishes to interact with as input and collects publicly available information related to that person from the internet. This process collects data such as the person's facial features, voice characteristics, and spoken content, and stores this information in a database.

[0238] Step 2:

[0239] The server uses artificial intelligence tools to train a generative AI model based on the collected information, learning the attributes of individuals. During this process, it extracts features from the input data and optimizes the learning model. The output is a digital representation of the learned individuals.

[0240] Step 3:

[0241] The server generates a virtual interlocutor using a generation mechanism based on the learning results. This virtual interlocutor is a digital personality synthesized based on collected information and learned attributes. It is output and becomes available for use when transmitted to the terminal.

[0242] Step 4:

[0243] The terminal displays a virtual interlocutor through a user interface and prompts the user to make a selection. The user provides input through the interface to begin interacting with the selected virtual interlocutor. The selection information is then sent to the server as output.

[0244] Step 5:

[0245] The user inputs their consultation details through an interface, which is then sent to the server. The server activates an emotion engine to analyze the input and recognize the user's emotional state. The input includes text data, and the output is an emotional state (e.g., "anxiety," "joy," etc.).

[0246] Step 6:

[0247] The server uses response adjustment mechanisms, taking emotional states into consideration, to generate optimal dialogue content. In this process, prompt sentences corresponding to emotions are input to the generating AI model, and an appropriate response is output.

[0248] Step 7:

[0249] The terminal displays the generated response to the user and provides audio feedback using an audio output device. The user can confirm the response and continue the conversation. Output is provided in text and audio formats.

[0250] 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.

[0251] 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.

[0252] 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.

[0253] [Second Embodiment]

[0254] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0255] 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.

[0256] 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).

[0257] 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.

[0258] 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.

[0259] 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).

[0260] 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.

[0261] 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.

[0262] 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.

[0263] 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.

[0264] 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.

[0265] 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".

[0266] This invention provides a system that generates a virtual customer service representative using artificial intelligence based on publicly available information, and allows users to interact with this representative. This system mainly consists of a server, terminals, and users.

[0267] The server collects publicly available information from the web related to celebrities or historical figures selected by the user. This collected information includes facial features, voice characteristics, and spoken content, which are used by artificial intelligence to learn the characteristics of the target.

[0268] Next, the server uses a generation mechanism to create a virtual customer service representative based on the learned data. The generated customer service representative's appearance and voice are reproduced, and it is possible to simulate a conversation with that person.

[0269] The terminal is equipped with a user interface, which the user uses to select a virtual customer service representative. Interaction with the selected representative takes place through the terminal's display screen and audio output. The terminal transmits user input, i.e., questions and inquiries in text or voice, to the server.

[0270] The server, in response to the inquiry received from the terminal, synthesizes a response generated by artificial intelligence using the voice and style of a virtual customer service representative, and sends it to the terminal. This response is displayed to the user in real time and, in some cases, output as audio from the terminal.

[0271] Users can freely interact with a virtual customer service representative regarding specific inquiries or questions. If the interaction exceeds a certain time limit or if certain features are used, an additional payment process will occur via a billing system. The billing process is displayed to the user through the terminal interface and is designed for easy operation.

[0272] In this way, the embodiment of the present invention is designed to reduce the time and psychological hurdles for users, enabling them to easily engage in dialogue with the person they desire. Furthermore, by even making virtual reunions with people who existed in the past possible, it provides an effective dialogue platform.

[0273] The following describes the processing flow.

[0274] Step 1:

[0275] The user enters the name of the person they wish to consult using their device.

[0276] Step 2:

[0277] The terminal sends the input person's name to the server.

[0278] Step 3:

[0279] Based on the received person's name, the server collects public information related to that person from the Internet.

[0280] Step 4:

[0281] The server analyzes the collected information and extracts facial features, voice, and speech content.

[0282] Step 5:

[0283] The server uses artificial intelligence means to learn the extracted features.

[0284] Step 6:

[0285] Based on the learned data, the server uses generation means to generate a virtual customer responder.

[0286] Step 7:

[0287] The terminal receives the information of the virtual customer responder generated by the server and displays it to the user.

[0288] Step 8:

[0289] The user starts a conversation through the terminal interface and enters the consultation content.

[0290] Step 9:

[0291] The terminal sends the input consultation content to the server.

[0292] Step 10:

[0293] The server generates a response using artificial intelligence based on the content of the inquiry, and then synthesizes that response in the style of a virtual customer service representative.

[0294] Step 11:

[0295] The server sends the synthesized response to the terminal.

[0296] Step 12:

[0297] The terminal displays the response to the user and outputs it audibly if necessary.

[0298] Step 13:

[0299] If the user has further questions or concerns, they can continue the conversation.

[0300] Step 14:

[0301] The server measures the interaction time and implements billing measures as needed.

[0302] Step 15:

[0303] When the user ends the interaction, the device notifies the server and displays the final billing information.

[0304] (Example 1)

[0305] 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."

[0306] In recent years, the need for users to interact with specific celebrities or historical figures has been on the rise. However, it is naturally impossible to interact with non-existent people. Additionally, in order for users to interact naturally with virtualized figures, advanced information processing technologies are required. Furthermore, if the procedures for handling fees incurred during the interaction process are complicated, the user experience may decline. The purpose of this invention is to solve these problems and provide a system that enables a wide range of users to easily enjoy a high-quality interaction experience.

[0307] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0308] In this invention, the server includes information processing means for collecting public information and learning human characteristics, generation means for generating a virtual interaction subject using the information processing means, and communication means for conducting an interaction between the virtual interaction subject generated by the generation means and the user. As a result, users can interact virtually with specific celebrities or historical figures, and through the real-time provision of experiences via the interaction, high-quality interactions become possible. Also, the measurement and processing of usage fees are performed easily, reducing the operation load on the user. (这里原文中 没有对应翻译内容,保留原文)

[0309] (这里原文中

[0309] 没有对应翻译内容,保留原文) (这里原文中 没有对应翻译内容,保留原文) "Public information" is a collection of data that is generally accessible through the Internet and other media and includes information about specific individuals. (这里原文中 没有对应翻译内容,保留原文)

[0310] (这里原文中

[0310] 没有对应翻译内容,保留原文) (这里原文中 没有对应翻译内容,保留原文) "Information processing means" is a system or device that has the function of analyzing and organizing the collected data and deriving results according to specific purposes. (这里原文中 没有对应翻译内容,保留原文)

[0311] (这里原文中

[0311] 没有对应翻译内容,保留原文) (这里原文中 没有对应翻译内容,保留原文) "Generation means" refers to a method or technology for creating a virtual object based on the results obtained through information processing. (这里原文中 没有对应翻译内容,保留原文)

[0312] (这里原文中

[0312] 没有对应翻译内容,保留原文) (这里原文中 没有对应翻译内容,保留原文) "Interaction subject" is a virtual entity designed to model a specific individual and interact with the user. (这里原文中 没有对应翻译内容,保留原文)

[0313] (这里原文中

[0313] 没有对应翻译内容,保留原文) "Communication methods" refer to interfaces and protocols used for exchanging information between users and systems, enabling real-time data transmission.

[0314] "Methods for measuring fees" refer to systems and mechanisms for measuring the costs associated with using a service and for ensuring appropriate billing.

[0315] An "operation screen" refers to an interface that allows users to perform operations visually and tactilely, providing users with information and enabling them to make choices.

[0316] The system implementing this invention mainly consists of a server, a terminal, and a user. The server first collects publicly available information from the internet related to a celebrity or historical figure selected by the user. For this collection, it utilizes web scraping technology and various APIs (e.g., online encyclopedia API, social media API). Through this, the server obtains and stores data such as facial photographs, audio clips, and transcripts of statements of the target person.

[0317] The server preprocesses the acquired data and learns human characteristics using an artificial intelligence model. This process uses facial recognition algorithms and speech analysis technologies (e.g., speech recognition APIs), which are then input into a generative AI model. Specific generative AI models include text generation models widely used in natural language processing and models used for speech synthesis (e.g., general-purpose natural language processing libraries and speech generation engines).

[0318] Next, the server generates a virtual dialogue entity based on the learning results. Using a generative AI model, the text and voice responses of this virtual dialogue entity are realistically reproduced. The virtual dialogue entity is constructed to enable seamless interaction with the user.

[0319] The terminal is equipped with a user interface that the user provides to select a virtual conversational subject through this interface. After selection, the user can ask questions or seek advice via voice or text. The terminal sends the user's input to the server, receives the generated response from the server, and displays or outputs it to the user.

[0320] For example, if a user requests to "interact with a historical scientist," the server collects publicly available information on the relevant individuals and generates a virtual scientist as the conversational subject. The user can then receive an explanation on their desired topic by entering a prompt such as, "I would like a historical scientist to explain my research."

[0321] This system allows the server to provide a customized conversational experience tailored to the user's needs in real time, enabling users to gain new learning and insights. Furthermore, the billing process is simplified through the terminal interface, allowing for smooth processing of usage fees.

[0322] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0323] Step 1:

[0324] The server collects publicly available information from the internet about celebrities or historical figures selected by the user. Specifically, the server uses web scraping techniques and APIs to obtain data such as facial images, audio clips, and transcripts of statements. The input is the name of the person selected by the user and related keywords, and the output is the collected data. This data is temporarily stored in storage for subsequent processing.

[0325] Step 2:

[0326] The server performs preprocessing on the collected data. Specifically, for image data, it extracts features using a facial recognition algorithm, and for audio data, it identifies voice characteristics using speech analysis techniques. For text data, it analyzes the content of the speech using natural language processing techniques. The raw, unprocessed data is used as input, and the output is the data with extracted features.

[0327] Step 3:

[0328] The server generates a virtual dialogue subject using a generative AI model based on preprocessed data. Here, a text generation model is used to create the content of the target person's conversation, and a speech synthesis model is used to reproduce its voice. Feature-extracted data is used as input, and a realistically reproduced virtual dialogue subject is obtained as output.

[0329] Step 4:

[0330] The user selects a virtual conversational subject through the terminal's user interface. The terminal displays available options to the user and transmits the selection to the server. The input includes the user's selection information, and the output generates commands for the server.

[0331] Step 5:

[0332] The user initiates a conversation with a virtual dialogue entity using a terminal. The user can either type prompts or ask questions by voice. The terminal sends the input information to the server, which then uses a generative AI model to return an appropriate response. The input is the user's question, and the output is the answer from the virtual dialogue entity.

[0333] Step 6:

[0334] If the user engages in conversation for a certain period of time or uses a specific function, the terminal initiates the billing process. The terminal presents the user with billing information and payment methods, and completes the process after obtaining user confirmation. Inputs include conversation time and functions used, and output is confirmation that the billing was performed correctly.

[0335] (Application Example 1)

[0336] 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 glasses 214 will be referred to as the "terminal."

[0337] This invention aims to realize an interactive system that utilizes virtual customer service representatives to allow users to receive real-time advice from celebrities and historical figures. In particular, the challenge is to improve the accuracy and satisfaction of fashion and lifestyle-related decision-making by providing more personalized advice that takes into account the user's personal attributes and possessions.

[0338] 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.

[0339] In this invention, the server includes an artificial intelligence means for collecting publicly available information and learning human attributes, a generation means for generating a virtual customer service representative using the artificial intelligence means, and a suggestion means for managing information about the user's possessions and providing attribute-based advice from the virtual advisor. This makes it possible for the user to receive specific and accurate advice tailored to their individual needs from a virtual customer service representative of their choice.

[0340] "Public information" refers to data and documents accessible on the internet that are generally known and relate to a specific person or subject.

[0341] "Human attributes" refer to the characteristics and traits of individual human beings, including information such as appearance, voice, style, and behavioral patterns.

[0342] "Artificial intelligence means" refers to technological means that use computer systems to analyze and learn from data, and then make decisions and predictions based on the results.

[0343] A "virtual customer service representative" is a digital character created using artificial intelligence technology that can simulate a specific person and interact with users.

[0344] "Generation means" refers to technical means for creating new digital objects based on learned data.

[0345] An "action" is the process of information exchange and communication that takes place between the user and a virtual customer service representative.

[0346] "Usage costs" refer to expenses incurred in connection with using the system, and are monetary burdens measured on an hourly basis or according to the functionality used.

[0347] A "billing method" is a technical means for accurately measuring, processing, and billing for the costs incurred when users utilize a system.

[0348] "Possessions information" refers to data related to items and assets owned by the user, including fashion items and other personal items.

[0349] A "suggestion tool" is a technical tool that provides advice indicating the optimal choices and actions based on the user's attributes and possession information.

[0350] The "connection interface" is the interface that users use to select a virtual customer service representative and initiate a conversation.

[0351] The system used to implement this application primarily consists of three elements: a server, a terminal, and a user.

[0352] The server includes artificial intelligence means for collecting and processing publicly available information and learning human attributes. Specifically, it collects publicly accessible data on the web and analyzes information about the appearance, voice, style, and behavioral patterns associated with a particular individual. The learned data is used to generate a virtual customer service role using an AI model (e.g., OpenAI's GPT-4). This virtual role simulates the characteristics of a specific person and enables interaction with the user.

[0353] The terminal acts as an intermediary for the interaction between the user and a virtual customer service representative. The terminal displays a connection screen where the user can select a virtual customer service representative and, if necessary, check the usage costs. Information about the user's possessions (e.g., fashion items) is managed through the terminal and used by the virtual advisor to provide optimal advice based on the user's attributes. This allows the user to receive specific and accurate advice.

[0354] The user uses this system to initiate a conversation with a virtual customer service representative of their choice. For example, by asking a question like, "I'm attending a social event today. What would be appropriate attire?", they can receive style suggestions for the day from a virtual fashion advisor.

[0355] An example of a prompt message is, "Based on the clothing preferences entered by the user, please suggest clothing styles from the selected stylist."

[0356] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0357] Step 1:

[0358] The server collects publicly available information from the internet. This collection process searches data sources related to a specific individual and extracts attribute information such as appearance, voice, and speech content. The input is information about the target individual, and the output is formatted attribute data. This data is stored for the learning phase.

[0359] Step 2:

[0360] The server passes the collected data to an artificial intelligence system to learn human attributes. Using a generative AI model, it analyzes and learns the characteristics of the data, incorporating the person's style and features into the model. The input is formatted attribute data, and the output is the trained model.

[0361] Step 3:

[0362] The server generates a virtual customer service representative using a pre-trained model. This generation method constructs a digital character capable of simulating a person's appearance and voice in real time. The input is the pre-trained model data, and the output is the virtual customer service representative.

[0363] Step 4:

[0364] The terminal displays an interface that allows the user to select a virtual customer service role. The user selects their desired role via the screen and completes preparation for the next step. The input is the user's instruction regarding their selection, and the output is the result of that selection.

[0365] Step 5:

[0366] The user initiates a conversation with a virtual customer service representative of their choice. The terminal receives questions from the user and sends them to the server in text or voice format. The input is the user's question, and the output is the data sent to the server.

[0367] Step 6:

[0368] The server uses a generative AI model to generate a response based on the received question. This model analyzes the context of the question and provides a response tailored to the style of a virtual customer service representative. The input is the user's question, and the output is a well-constructed response.

[0369] Step 7:

[0370] The terminal provides the user with a generated response. The response is played back as text or audio and presented in a format that is easy for the user to understand. The input is the generated response data, and the output is the information displayed to the user.

[0371] Step 8:

[0372] The terminal measures the usage costs incurred during the interaction and displays them to the user as needed. This includes calculating charges based on system usage time and the use of special features. Input is usage information related to the interaction, and output is a charge display.

[0373] 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.

[0374] This invention combines a system that generates a virtual customer service representative using artificial intelligence based on publicly available information and interacts with the user with an emotion engine that recognizes the user's emotions. This system consists of a server, a terminal, a user, and an emotion engine.

[0375] When a user enters the name of a specific person they wish to interact with, the server collects publicly available information about that person from the internet. This information includes facial features, voice characteristics, and spoken content, and the artificial intelligence learns the target's characteristics based on this data. Based on the learning results, the server uses a generation mechanism to create a virtual customer service representative and sends that information to the terminal.

[0376] The terminal provides a user interface, which the user uses to select a virtual customer service representative. The terminal also receives input from the user regarding their inquiry and sends it to the server. At this point, the emotion engine operates and analyzes the user's emotional state based on their input. For example, if the user inputs "I've been very tired from work lately," the emotion engine recognizes emotions such as "fatigue" and "stress."

[0377] The server takes into account the emotions recognized by the emotion engine and adjusts the AI-generated response to suit the conditions. It generates dialogue content corresponding to the recognized emotion and synthesizes the response in the style of a virtual customer service representative. For example, if "fatigue" is recognized, the virtual customer service representative might respond with something like, "That must be tough. Do you have time to refresh yourself now?"

[0378] The device displays this response to the user in real time and outputs it audibly as needed. This allows the user to continue the virtual conversation and experience a more empathetic dialogue.

[0379] Furthermore, this system incurs additional charges under certain conditions. These charges are clearly communicated to the user via their device, and the interaction continues only after approval. By incorporating an emotion engine, this invention is able to provide a highly personalized interaction that responds to the user's emotions, going beyond mere information provision.

[0380] The following describes the processing flow.

[0381] Step 1:

[0382] The user uses their device to enter the name of the person they want to consult with and requests the creation of a virtual customer service representative.

[0383] Step 2:

[0384] The terminal sends the entered information to the server.

[0385] Step 3:

[0386] Based on the name of the person who submitted the request, the server automatically collects relevant information that is publicly available on the internet.

[0387] Step 4:

[0388] The server analyzes the collected information and extracts characteristics of the subject, such as their appearance, voice, and personality.

[0389] Step 5:

[0390] The server uses artificial intelligence to learn the extracted features and generate a virtual customer service representative.

[0391] Step 6:

[0392] The server sends the generated virtual customer service representative data to the terminal.

[0393] Step 7:

[0394] The terminal displays a screen for the user to select a virtual customer service representative.

[0395] Step 8:

[0396] The user uses their device to select a virtual customer service representative to begin a consultation with.

[0397] Step 9:

[0398] The user enters their inquiry details as text or voice and sends them to the server via their device.

[0399] Step 10:

[0400] The server analyzes the received consultation content using an emotion engine to recognize the user's emotional state.

[0401] Step 11:

[0402] The server uses artificial intelligence to generate appropriate responses based on recognized emotions, and then synthesizes these responses in the style of a virtual customer service representative.

[0403] Step 12:

[0404] The server sends the synthesized response data to the terminal.

[0405] Step 13:

[0406] The device displays real-time generated responses to the user and provides audio output as needed.

[0407] Step 14:

[0408] If the user wishes to continue the conversation, they will enter additional questions into the terminal and run the process again.

[0409] Step 15:

[0410] The server measures the duration of the interaction and, if it exceeds the time limit for a paid session, activates the billing mechanism and notifies the user via their device.

[0411] Step 16:

[0412] The user can choose to accept the charge and continue the conversation, or end the conversation.

[0413] Step 17:

[0414] The device will end the interaction based on the user's choice and, if necessary, provide the user with final billing information.

[0415] (Example 2)

[0416] 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".

[0417] In recent years, AI-powered dialogue systems have become widespread in many fields. However, conventional systems have struggled to accurately recognize users' emotions and respond accordingly. As a result, users have faced the challenge of receiving uniform dialogue and not being able to receive satisfactory dialogue that reflects their individual emotions and needs. Furthermore, there has been a lack of adequate interfaces that allow users to easily select a specific person they wish to virtually interact with.

[0418] 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.

[0419] In this invention, the server includes artificial intelligence means for collecting publicly available information and learning personal characteristics, generation means for generating a virtual responder, and emotion recognition means for analyzing the emotional state based on the user's input. As a result, the user can interact with a virtual responder that resembles a specific person, and the content of the interaction is adjusted according to the user's emotions, enabling a more personalized experience.

[0420] "Public information" refers to data that is publicly available on the internet or other accessible data sources.

[0421] "Personal characteristics" refer to information used to identify a person, such as their physical appearance, vocal characteristics, and the content of their statements.

[0422] "Artificial intelligence tools" refer to technological means that use machine learning and natural language processing to acquire knowledge from data and perform processing according to specific purposes.

[0423] "Generative means" refers to methods and processes for creating new data-based content using artificial intelligence technology.

[0424] "Emotion recognition means" refers to technical means for analyzing user input data and identifying emotional states based on that analysis.

[0425] "Response generation means" refers to a means for generating an appropriate response based on analyzed emotions and presenting it to the user.

[0426] "Dialogue means" refers to the process for communication between a virtual responder and the user.

[0427] "Billing method" refers to the methods and technologies used to measure and process charges associated with the use of a system.

[0428] The system of this invention consists of a server, a terminal, and a user, and further incorporates an emotion engine for emotion recognition.

[0429] After receiving the name of the person the user wishes to interact with, the server uses web scraping tools to collect relevant publicly available information from the internet. For example, Scrapy can be used. The data collected at this stage includes the person's facial features, voice characteristics, and speech information. Based on this data, artificial intelligence learns the person's characteristics using machine learning algorithms and generates a virtual responder using a generative AI model. Models that can be used as natural language processing techniques in this process include GPT-3.

[0430] The terminal provides an interface to the user, displaying and allowing them to select a virtual responder. This interface includes fields for the user to input or voice-input their consultation details. Voice input can utilize speech recognition software. The data entered by the user is sent to the server in real time, where an emotion engine analyzes the user's emotions. Through emotion recognition, the system can understand the user's situation, such as if they are experiencing "fatigue" or "stress."

[0431] Based on the analysis results, the server generates a response using a generative AI model and adjusts it to match the user's emotions. This adjusted response is sent to the terminal, which displays the response to the user and, in some cases, also outputs it as audio. In this case, text-to-speech (TTS) technology is used to convert it to speech.

[0432] For example, if a user types "I've been really tired from work lately," a tailored response such as "That must be tough. Do you have time to relax now?" will be generated.

[0433] A concrete example of a prompt message would be: "The user wants a conversation based on information related to a specific person. Based on the emotional information entered by the user, the emotion engine will generate appropriate dialogue content."

[0434] This system allows users to engage in emotionally-driven conversations with virtual characters, which is expected to enhance the personalized experience.

[0435] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0436] Step 1:

[0437] The server receives the name of a specific person from the user. Using this name as input, the server uses web scraping tools to collect publicly available information related to that person from the internet. This data includes facial features, voice characteristics, and statements, and is output as a single database.

[0438] Step 2:

[0439] The server provides the collected information to an artificial intelligence system, which then learns about human characteristics. During this process, machine learning algorithms are applied to extract features from the received data. As a result, a trained model is output.

[0440] Step 3:

[0441] The server generates a virtual responder using a generative AI model. In this process, the artificial intelligence synthesizes content such as text and audio using the trained model as input. This outputs a digital profile of the virtual responder, which is then sent to the terminal.

[0442] Step 4:

[0443] The terminal provides an interface that displays a virtual responder to the user. The user selects a responder they wish to interact with through this interface, and this selection information is sent to the server.

[0444] Step 5:

[0445] The user inputs, either by typing or voice, what they want to communicate with a virtual responder through the device. This user input is sent to an emotion recognition system and processed as data for analysis.

[0446] Step 6:

[0447] The server generates an appropriate response using a response generation mechanism based on the user's emotions analyzed by the emotion recognition mechanism. At this stage, the generation AI model is used again to generate a response that matches the user's emotional state. The adjusted response is output and sent to the terminal.

[0448] Step 7:

[0449] The terminal presents the received response to the user visually and audibly. For audio output, a TTS (text-to-speech) engine is used, and the generated text is played back as natural-sounding speech. The user can then respond or provide further input based on the presented information.

[0450] (Application Example 2)

[0451] 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."

[0452] Traditional systems made it difficult to understand user emotions during customer service, resulting in only simple information being provided. Furthermore, the lack of mechanisms to deliver appropriate dialogue tailored to the user's situation prevented the realization of a deeper customer experience.

[0453] 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.

[0454] In this invention, the server includes artificial intelligence means for collecting publicly available information and learning the attributes of a person; generation means for generating a virtual conversationalist; analysis means including an emotion engine for analyzing the emotional state based on the user's input information; response adjustment means; and billing means. This enables personalized customer service by providing conversational content that corresponds to the user's emotional state.

[0455] "Public information" refers to data and knowledge that is generally accessible on the internet and includes attributes and characteristics related to a specific person.

[0456] "Artificial intelligence means" refers to technologies that function as part of a computer system and have the function of learning and recognizing a person's attributes.

[0457] "Generative means" refers to the process or function of creating a virtual conversational partner based on information learned by artificial intelligence.

[0458] "Dialogue means" refers to a system or function that enables the exchange of information between a virtual interlocutor and the user.

[0459] An "emotion engine" is a technology that analyzes user input information to identify and classify a person's emotional state.

[0460] "Analytical means" refers to the ability or method to process input data and derive specific conclusions or results.

[0461] "Response adjustment means" refers to a system or function that generates and adjusts the optimal response content based on the analyzed emotional state.

[0462] A "billing method" is a system that has the function of measuring and processing usage fees based on the usage of the conversation.

[0463] To realize this invention, a server, terminals, users, and a network to connect them are primarily required. The server should function as a cloud computing environment, utilizing Amazon Web Services (AWS) or Google Cloud Platform. For the terminals, smartphones running iOS or Android are preferable.

[0464] First, the server collects publicly available information from the internet, including a specific person's facial features, voice characteristics, and spoken content. The artificial intelligence system uses this information to learn the person's attributes using a generative AI model. Based on the learning results, the generative system generates a virtual conversational partner, which is then sent to the user's terminal.

[0465] The terminal selects and displays a virtual interlocutor through a user interface. The user inputs their consultation details using the interface, which are then sent to the server. An emotion engine analyzes the user's input and recognizes their emotional state. This analysis result is used by a response adjustment mechanism to generate an appropriate response tailored to the user's emotions.

[0466] For example, if a user inputs "I feel anxious before purchasing a product online," the emotion engine recognizes the emotion of "anxiety." As a result, the virtual dialogue partner will engage in conversation such as, "Purchasing is a big decision, isn't it? It might be helpful to refer to other customers' reviews and usage examples." This allows the user to experience an emotionally empathetic response.

[0467] Example prompt: "The user has expressed concerns about this product. Please explain how they can use this product and how it can improve their daily life, and provide the best way to support them in making a purchase decision with confidence."

[0468] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0469] Step 1:

[0470] The server receives the name of a specific person the user wishes to interact with as input and collects publicly available information related to that person from the internet. This process collects data such as the person's facial features, voice characteristics, and spoken content, and stores this information in a database.

[0471] Step 2:

[0472] The server uses artificial intelligence tools to train a generative AI model based on the collected information, learning the attributes of individuals. During this process, it extracts features from the input data and optimizes the learning model. The output is a digital representation of the learned individuals.

[0473] Step 3:

[0474] The server generates a virtual interlocutor using a generation mechanism based on the learning results. This virtual interlocutor is a digital personality synthesized based on collected information and learned attributes. It is output and becomes available for use when transmitted to the terminal.

[0475] Step 4:

[0476] The terminal displays a virtual interlocutor through a user interface and prompts the user to make a selection. The user provides input through the interface to begin interacting with the selected virtual interlocutor. The selection information is then sent to the server as output.

[0477] Step 5:

[0478] The user inputs their consultation details through an interface, which is then sent to the server. The server activates an emotion engine to analyze the input and recognize the user's emotional state. The input includes text data, and the output is an emotional state (e.g., "anxiety," "joy," etc.).

[0479] Step 6:

[0480] The server uses response adjustment mechanisms, taking emotional states into consideration, to generate optimal dialogue content. In this process, prompt sentences corresponding to emotions are input to the generating AI model, and an appropriate response is output.

[0481] Step 7:

[0482] The terminal displays the generated response to the user and provides audio feedback using an audio output device. The user can confirm the response and continue the conversation. Output is provided in text and audio formats.

[0483] 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.

[0484] 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.

[0485] 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.

[0486] [Third Embodiment]

[0487] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0488] 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.

[0489] 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).

[0490] 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.

[0491] 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.

[0492] 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).

[0493] 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.

[0494] 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.

[0495] 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.

[0496] 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.

[0497] 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.

[0498] 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".

[0499] This invention provides a system that generates a virtual customer service representative using artificial intelligence based on publicly available information, and allows users to interact with this representative. This system mainly consists of a server, terminals, and users.

[0500] The server collects publicly available information from the web related to celebrities or historical figures selected by the user. This collected information includes facial features, voice characteristics, and spoken content, which are used by artificial intelligence to learn the characteristics of the target.

[0501] Next, the server uses a generation mechanism to create a virtual customer service representative based on the learned data. The generated customer service representative's appearance and voice are reproduced, and it is possible to simulate a conversation with that person.

[0502] The terminal is equipped with a user interface, which the user uses to select a virtual customer service representative. Interaction with the selected representative takes place through the terminal's display screen and audio output. The terminal transmits user input, i.e., questions and inquiries in text or voice, to the server.

[0503] The server, in response to the inquiry received from the terminal, synthesizes a response generated by artificial intelligence using the voice and style of a virtual customer service representative, and sends it to the terminal. This response is displayed to the user in real time and, in some cases, output as audio from the terminal.

[0504] Users can freely interact with a virtual customer service representative regarding specific inquiries or questions. If the interaction exceeds a certain time limit or if certain features are used, an additional payment process will occur via a billing system. The billing process is displayed to the user through the terminal interface and is designed for easy operation.

[0505] In this way, the embodiment of the present invention is designed to reduce the time and psychological hurdles for users, enabling them to easily engage in dialogue with the person they desire. Furthermore, by even making virtual reunions with people who existed in the past possible, it provides an effective dialogue platform.

[0506] The following describes the processing flow.

[0507] Step 1:

[0508] The user enters the name of the person they wish to consult using their device.

[0509] Step 2:

[0510] The terminal sends the entered person's name to the server.

[0511] Step 3:

[0512] Based on the name of the person received, the server collects publicly available information related to that person from the internet.

[0513] Step 4:

[0514] The server analyzes the collected information and extracts facial features, voice, and spoken content.

[0515] Step 5:

[0516] The server uses artificial intelligence to train itself on the extracted features.

[0517] Step 6:

[0518] The server uses a generation mechanism to create a virtual customer service representative based on the learned data.

[0519] Step 7:

[0520] The terminal receives information about a virtual customer representative generated from the server and displays it to the user.

[0521] Step 8:

[0522] The user initiates the interaction through the terminal's interface and enters the details of their inquiry.

[0523] Step 9:

[0524] The terminal sends the entered consultation details to the server.

[0525] Step 10:

[0526] The server generates a response using artificial intelligence based on the content of the inquiry, and then synthesizes that response in the style of a virtual customer service representative.

[0527] Step 11:

[0528] The server sends the synthesized response to the terminal.

[0529] Step 12:

[0530] The terminal displays the response to the user and outputs it audibly if necessary.

[0531] Step 13:

[0532] If the user has further questions or concerns, they can continue the conversation.

[0533] Step 14:

[0534] The server measures the interaction time and implements billing measures as needed.

[0535] Step 15:

[0536] When the user ends the interaction, the device notifies the server and displays the final billing information.

[0537] (Example 1)

[0538] 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."

[0539] In recent years, there has been a growing demand from users to interact with specific celebrities or historical figures, but it is naturally impossible to interact with people who do not exist in reality. Furthermore, advanced information processing technology is required for users to interact naturally with virtually recreated figures. In addition, if the procedures for handling fees incurred during the interaction process are complicated, usability may decrease. This invention aims to solve these problems and provide a system that allows a wide range of users to easily enjoy a high-quality conversational experience.

[0540] 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.

[0541] In this invention, the server includes an information processing means for collecting publicly available information and learning human characteristics, a generation means for generating a virtual dialogue subject using the information processing means, and a communication means for the user to interact with the virtual dialogue subject generated by the generation means. This enables users to virtually interact with specific celebrities or historical figures, and the interaction experience is provided in real time, resulting in high-quality interaction. In addition, the measurement and processing of usage fees are simplified, reducing the user's operational burden.

[0542] "Public information" refers to a collection of data that is accessible to the public through the internet or other media, and which includes information about specific individuals.

[0543] "Information processing means" refers to systems or devices that have the function of analyzing and organizing collected data and deriving results that are appropriate for a specific purpose.

[0544] "Generation means" refers to methods and techniques for creating a virtual object based on the results obtained through information processing.

[0545] A "dialogue subject" is a virtual entity designed to interact with users, modeled after a specific person.

[0546] "Communication methods" refer to interfaces and protocols used for exchanging information between users and systems, enabling real-time data transmission.

[0547] "Methods for measuring fees" refer to systems and mechanisms for measuring the costs associated with using a service and for ensuring appropriate billing.

[0548] An "operation screen" refers to an interface that allows users to perform operations visually and tactilely, providing users with information and enabling them to make choices.

[0549] The system implementing this invention mainly consists of a server, a terminal, and a user. The server first collects publicly available information from the internet related to a celebrity or historical figure selected by the user. For this collection, it utilizes web scraping technology and various APIs (e.g., online encyclopedia API, social media API). Through this, the server obtains and stores data such as facial photographs, audio clips, and transcripts of statements of the target person.

[0550] The server preprocesses the acquired data and learns human characteristics using an artificial intelligence model. This process uses facial recognition algorithms and speech analysis technologies (e.g., speech recognition APIs), which are then input into a generative AI model. Specific generative AI models include text generation models widely used in natural language processing and models used for speech synthesis (e.g., general-purpose natural language processing libraries and speech generation engines).

[0551] Next, the server generates a virtual dialogue entity based on the learning results. Using a generative AI model, the text and voice responses of this virtual dialogue entity are realistically reproduced. The virtual dialogue entity is constructed to enable seamless interaction with the user.

[0552] The terminal is equipped with a user interface that the user provides to select a virtual conversational subject through this interface. After selection, the user can ask questions or seek advice via voice or text. The terminal sends the user's input to the server, receives the generated response from the server, and displays or outputs it to the user.

[0553] For example, if a user requests to "interact with a historical scientist," the server collects publicly available information on the relevant individuals and generates a virtual scientist as the conversational subject. The user can then receive an explanation on their desired topic by entering a prompt such as, "I would like a historical scientist to explain my research."

[0554] This system allows the server to provide a customized conversational experience tailored to the user's needs in real time, enabling users to gain new learning and insights. Furthermore, the billing process is simplified through the terminal interface, allowing for smooth processing of usage fees.

[0555] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0556] Step 1:

[0557] The server collects publicly available information from the internet about celebrities or historical figures selected by the user. Specifically, the server uses web scraping techniques and APIs to obtain data such as facial images, audio clips, and transcripts of statements. The input is the name of the person selected by the user and related keywords, and the output is the collected data. This data is temporarily stored in storage for subsequent processing.

[0558] Step 2:

[0559] The server performs preprocessing on the collected data. Specifically, for image data, it extracts features using a facial recognition algorithm, and for audio data, it identifies voice characteristics using speech analysis techniques. For text data, it analyzes the content of the speech using natural language processing techniques. The raw, unprocessed data is used as input, and the output is the data with extracted features.

[0560] Step 3:

[0561] The server generates a virtual dialogue subject using a generative AI model based on preprocessed data. Here, a text generation model is used to create the content of the target person's conversation, and a speech synthesis model is used to reproduce its voice. Feature-extracted data is used as input, and a realistically reproduced virtual dialogue subject is obtained as output.

[0562] Step 4:

[0563] The user selects a virtual conversational subject through the terminal's user interface. The terminal displays available options to the user and transmits the selection to the server. The input includes the user's selection information, and the output generates commands for the server.

[0564] Step 5:

[0565] The user initiates a conversation with a virtual dialogue entity using a terminal. The user can either type prompts or ask questions by voice. The terminal sends the input information to the server, which then uses a generative AI model to return an appropriate response. The input is the user's question, and the output is the answer from the virtual dialogue entity.

[0566] Step 6:

[0567] If the user engages in conversation for a certain period of time or uses a specific function, the terminal initiates the billing process. The terminal presents the user with billing information and payment methods, and completes the process after obtaining user confirmation. Inputs include conversation time and functions used, and output is confirmation that the billing was performed correctly.

[0568] (Application Example 1)

[0569] 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."

[0570] This invention aims to realize an interactive system that utilizes virtual customer service representatives to allow users to receive real-time advice from celebrities and historical figures. In particular, the challenge is to improve the accuracy and satisfaction of fashion and lifestyle-related decision-making by providing more personalized advice that takes into account the user's personal attributes and possessions.

[0571] 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.

[0572] In this invention, the server includes an artificial intelligence means for collecting publicly available information and learning human attributes, a generation means for generating a virtual customer service representative using the artificial intelligence means, and a suggestion means for managing information about the user's possessions and providing attribute-based advice from the virtual advisor. This makes it possible for the user to receive specific and accurate advice tailored to their individual needs from a virtual customer service representative of their choice.

[0573] "Public information" refers to data and documents accessible on the internet that are generally known and relate to a specific person or subject.

[0574] "Human attributes" refer to the characteristics and traits of individual human beings, including information such as appearance, voice, style, and behavioral patterns.

[0575] "Artificial intelligence means" refers to technological means that use computer systems to analyze and learn from data, and then make decisions and predictions based on the results.

[0576] A "virtual customer service representative" is a digital character created using artificial intelligence technology that can simulate a specific person and interact with users.

[0577] "Generation means" refers to technical means for creating new digital objects based on learned data.

[0578] An "action" is the process of information exchange and communication that takes place between the user and a virtual customer service representative.

[0579] "Usage costs" refer to expenses incurred in connection with using the system, and are monetary burdens measured on an hourly basis or according to the functionality used.

[0580] A "billing method" is a technical means for accurately measuring, processing, and billing for the costs incurred when users utilize a system.

[0581] "Possessions information" refers to data related to items and assets owned by the user, including fashion items and other personal items.

[0582] A "suggestion tool" is a technical tool that provides advice indicating the optimal choices and actions based on the user's attributes and possession information.

[0583] The "connection interface" is the interface that users use to select a virtual customer service representative and initiate a conversation.

[0584] The system used to implement this application primarily consists of three elements: a server, a terminal, and a user.

[0585] The server includes artificial intelligence means for collecting and processing publicly available information and learning human attributes. Specifically, it collects publicly accessible data on the web and analyzes information about the appearance, voice, style, and behavioral patterns associated with a particular individual. The learned data is used to generate a virtual customer service role using an AI model (e.g., OpenAI's GPT-4). This virtual role simulates the characteristics of a specific person and enables interaction with the user.

[0586] The terminal acts as an intermediary for the interaction between the user and a virtual customer service representative. The terminal displays a connection screen where the user can select a virtual customer service representative and, if necessary, check the usage costs. Information about the user's possessions (e.g., fashion items) is managed through the terminal and used by the virtual advisor to provide optimal advice based on the user's attributes. This allows the user to receive specific and accurate advice.

[0587] The user uses this system to initiate a conversation with a virtual customer service representative of their choice. For example, by asking a question like, "I'm attending a social event today. What would be appropriate attire?", they can receive style suggestions for the day from a virtual fashion advisor.

[0588] An example of a prompt message is, "Based on the clothing preferences entered by the user, please suggest clothing styles from the selected stylist."

[0589] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0590] Step 1:

[0591] The server collects publicly available information from the internet. This collection process searches data sources related to a specific individual and extracts attribute information such as appearance, voice, and speech content. The input is information about the target individual, and the output is formatted attribute data. This data is stored for the learning phase.

[0592] Step 2:

[0593] The server passes the collected data to an artificial intelligence system to learn human attributes. Using a generative AI model, it analyzes and learns the characteristics of the data, incorporating the person's style and features into the model. The input is formatted attribute data, and the output is the trained model.

[0594] Step 3:

[0595] The server generates a virtual customer service representative using a pre-trained model. This generation method constructs a digital character capable of simulating a person's appearance and voice in real time. The input is the pre-trained model data, and the output is the virtual customer service representative.

[0596] Step 4:

[0597] The terminal displays an interface that allows the user to select a virtual customer service role. The user selects their desired role via the screen and completes preparation for the next step. The input is the user's instruction regarding their selection, and the output is the result of that selection.

[0598] Step 5:

[0599] The user initiates a conversation with a virtual customer service representative of their choice. The terminal receives questions from the user and sends them to the server in text or voice format. The input is the user's question, and the output is the data sent to the server.

[0600] Step 6:

[0601] The server uses a generative AI model to generate a response based on the received question. This model analyzes the context of the question and provides a response tailored to the style of a virtual customer service representative. The input is the user's question, and the output is a well-constructed response.

[0602] Step 7:

[0603] The terminal provides the user with a generated response. The response is played back as text or audio and presented in a format that is easy for the user to understand. The input is the generated response data, and the output is the information displayed to the user.

[0604] Step 8:

[0605] The terminal measures the usage costs incurred during the interaction and displays them to the user as needed. This includes calculating charges based on system usage time and the use of special features. Input is usage information related to the interaction, and output is a charge display.

[0606] 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.

[0607] This invention combines a system that generates a virtual customer service representative using artificial intelligence based on publicly available information and interacts with the user with an emotion engine that recognizes the user's emotions. This system consists of a server, a terminal, a user, and an emotion engine.

[0608] When a user enters the name of a specific person they wish to interact with, the server collects publicly available information about that person from the internet. This information includes facial features, voice characteristics, and spoken content, and the artificial intelligence learns the target's characteristics based on this data. Based on the learning results, the server uses a generation mechanism to create a virtual customer service representative and sends that information to the terminal.

[0609] The terminal provides a user interface, which the user uses to select a virtual customer service representative. The terminal also receives input from the user regarding their inquiry and sends it to the server. At this point, the emotion engine operates and analyzes the user's emotional state based on their input. For example, if the user inputs "I've been very tired from work lately," the emotion engine recognizes emotions such as "fatigue" and "stress."

[0610] The server takes into account the emotions recognized by the emotion engine and adjusts the AI-generated response to suit the conditions. It generates dialogue content corresponding to the recognized emotion and synthesizes the response in the style of a virtual customer service representative. For example, if "fatigue" is recognized, the virtual customer service representative might respond with something like, "That must be tough. Do you have time to refresh yourself now?"

[0611] The device displays this response to the user in real time and outputs it audibly as needed. This allows the user to continue the virtual conversation and experience a more empathetic dialogue.

[0612] Furthermore, this system incurs additional charges under certain conditions. These charges are clearly communicated to the user via their device, and the interaction continues only after approval. By incorporating an emotion engine, this invention is able to provide a highly personalized interaction that responds to the user's emotions, going beyond mere information provision.

[0613] The following describes the processing flow.

[0614] Step 1:

[0615] The user uses their device to enter the name of the person they want to consult with and requests the creation of a virtual customer service representative.

[0616] Step 2:

[0617] The terminal sends the entered information to the server.

[0618] Step 3:

[0619] Based on the name of the person who submitted the request, the server automatically collects relevant information that is publicly available on the internet.

[0620] Step 4:

[0621] The server analyzes the collected information and extracts characteristics of the subject, such as their appearance, voice, and personality.

[0622] Step 5:

[0623] The server uses artificial intelligence to learn the extracted features and generate a virtual customer service representative.

[0624] Step 6:

[0625] The server sends the generated virtual customer service representative data to the terminal.

[0626] Step 7:

[0627] The terminal displays a screen for the user to select a virtual customer service representative.

[0628] Step 8:

[0629] The user uses their device to select a virtual customer service representative to begin a consultation with.

[0630] Step 9:

[0631] The user enters their inquiry details as text or voice and sends them to the server via their device.

[0632] Step 10:

[0633] The server analyzes the received consultation content using an emotion engine to recognize the user's emotional state.

[0634] Step 11:

[0635] The server uses artificial intelligence to generate appropriate responses based on recognized emotions, and then synthesizes these responses in the style of a virtual customer service representative.

[0636] Step 12:

[0637] The server sends the synthesized response data to the terminal.

[0638] Step 13:

[0639] The device displays real-time generated responses to the user and provides audio output as needed.

[0640] Step 14:

[0641] If the user wishes to continue the conversation, they will enter additional questions into the terminal and run the process again.

[0642] Step 15:

[0643] The server measures the duration of the interaction and, if it exceeds the time limit for a paid session, activates the billing mechanism and notifies the user via their device.

[0644] Step 16:

[0645] The user can choose to accept the charge and continue the conversation, or end the conversation.

[0646] Step 17:

[0647] The device will end the interaction based on the user's choice and, if necessary, provide the user with final billing information.

[0648] (Example 2)

[0649] 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."

[0650] In recent years, AI-powered dialogue systems have become widespread in many fields. However, conventional systems have struggled to accurately recognize users' emotions and respond accordingly. As a result, users have faced the challenge of receiving uniform dialogue and not being able to receive satisfactory dialogue that reflects their individual emotions and needs. Furthermore, there has been a lack of adequate interfaces that allow users to easily select a specific person they wish to virtually interact with.

[0651] 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.

[0652] In this invention, the server includes artificial intelligence means for collecting publicly available information and learning personal characteristics, generation means for generating a virtual responder, and emotion recognition means for analyzing the emotional state based on the user's input. As a result, the user can interact with a virtual responder that resembles a specific person, and the content of the interaction is adjusted according to the user's emotions, enabling a more personalized experience.

[0653] "Public information" refers to data that is publicly available on the internet or other accessible data sources.

[0654] "Personal characteristics" refer to information used to identify a person, such as their physical appearance, vocal characteristics, and the content of their statements.

[0655] "Artificial intelligence tools" refer to technological means that use machine learning and natural language processing to acquire knowledge from data and perform processing according to specific purposes.

[0656] "Generative means" refers to methods and processes for creating new data-based content using artificial intelligence technology.

[0657] "Emotion recognition means" refers to technical means for analyzing user input data and identifying emotional states based on that analysis.

[0658] "Response generation means" refers to a means for generating an appropriate response based on analyzed emotions and presenting it to the user.

[0659] "Dialogue means" refers to the process for communication between a virtual responder and the user.

[0660] "Billing method" refers to the methods and technologies used to measure and process charges associated with the use of a system.

[0661] The system of this invention consists of a server, a terminal, and a user, and further incorporates an emotion engine for emotion recognition.

[0662] After receiving the name of the person the user wishes to interact with, the server uses web scraping tools to collect relevant publicly available information from the internet. For example, Scrapy can be used. The data collected at this stage includes the person's facial features, voice characteristics, and speech information. Based on this data, artificial intelligence learns the person's characteristics using machine learning algorithms and generates a virtual responder using a generative AI model. Models that can be used as natural language processing techniques in this process include GPT-3.

[0663] The terminal provides an interface to the user, displaying and allowing them to select a virtual responder. This interface includes fields for the user to input or voice-input their consultation details. Voice input can utilize speech recognition software. The data entered by the user is sent to the server in real time, where an emotion engine analyzes the user's emotions. Through emotion recognition, the system can understand the user's situation, such as if they are experiencing "fatigue" or "stress."

[0664] Based on the analysis results, the server generates a response using a generative AI model and adjusts it to match the user's emotions. This adjusted response is sent to the terminal, which displays the response to the user and, in some cases, also outputs it as audio. In this case, text-to-speech (TTS) technology is used to convert it to speech.

[0665] For example, if a user types "I've been really tired from work lately," a tailored response such as "That must be tough. Do you have time to relax now?" will be generated.

[0666] A concrete example of a prompt message would be: "The user wants a conversation based on information related to a specific person. Based on the emotional information entered by the user, the emotion engine will generate appropriate dialogue content."

[0667] This system allows users to engage in emotionally-driven conversations with virtual characters, which is expected to enhance the personalized experience.

[0668] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0669] Step 1:

[0670] The server receives the name of a specific person from the user. Using this name as input, the server uses web scraping tools to collect publicly available information related to that person from the internet. This data includes facial features, voice characteristics, and statements, and is output as a single database.

[0671] Step 2:

[0672] The server provides the collected information to an artificial intelligence system, which then learns about human characteristics. During this process, machine learning algorithms are applied to extract features from the received data. As a result, a trained model is output.

[0673] Step 3:

[0674] The server generates a virtual responder using a generative AI model. In this process, the artificial intelligence synthesizes content such as text and audio using the trained model as input. This outputs a digital profile of the virtual responder, which is then sent to the terminal.

[0675] Step 4:

[0676] The terminal provides an interface that displays a virtual responder to the user. The user selects a responder they wish to interact with through this interface, and this selection information is sent to the server.

[0677] Step 5:

[0678] The user inputs, either by typing or voice, what they want to communicate with a virtual responder through the device. This user input is sent to an emotion recognition system and processed as data for analysis.

[0679] Step 6:

[0680] The server generates an appropriate response using a response generation mechanism based on the user's emotions analyzed by the emotion recognition mechanism. At this stage, the generation AI model is used again to generate a response that matches the user's emotional state. The adjusted response is output and sent to the terminal.

[0681] Step 7:

[0682] The terminal presents the received response to the user visually and audibly. For audio output, a TTS (text-to-speech) engine is used, and the generated text is played back as natural-sounding speech. The user can then respond or provide further input based on the presented information.

[0683] (Application Example 2)

[0684] 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."

[0685] Traditional systems made it difficult to understand user emotions during customer service, resulting in only simple information being provided. Furthermore, the lack of mechanisms to deliver appropriate dialogue tailored to the user's situation prevented the realization of a deeper customer experience.

[0686] 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.

[0687] In this invention, the server includes artificial intelligence means for collecting publicly available information and learning the attributes of a person; generation means for generating a virtual conversationalist; analysis means including an emotion engine for analyzing the emotional state based on the user's input information; response adjustment means; and billing means. This enables personalized customer service by providing conversational content that corresponds to the user's emotional state.

[0688] "Public information" refers to data and knowledge that is generally accessible on the internet and includes attributes and characteristics related to a specific person.

[0689] "Artificial intelligence means" refers to technologies that function as part of a computer system and have the function of learning and recognizing a person's attributes.

[0690] "Generative means" refers to the process or function of creating a virtual conversational partner based on information learned by artificial intelligence.

[0691] "Dialogue means" refers to a system or function that enables the exchange of information between a virtual interlocutor and the user.

[0692] An "emotion engine" is a technology that analyzes user input information to identify and classify a person's emotional state.

[0693] "Analytical means" refers to the ability or method to process input data and derive specific conclusions or results.

[0694] "Response adjustment means" refers to a system or function that generates and adjusts the optimal response content based on the analyzed emotional state.

[0695] A "billing method" is a system that has the function of measuring and processing usage fees based on the usage of the conversation.

[0696] To realize this invention, a server, terminals, users, and a network to connect them are primarily required. The server should function as a cloud computing environment, utilizing Amazon Web Services (AWS) or Google Cloud Platform. For the terminals, smartphones running iOS or Android are preferable.

[0697] First, the server collects publicly available information from the internet, including a specific person's facial features, voice characteristics, and spoken content. The artificial intelligence system uses this information to learn the person's attributes using a generative AI model. Based on the learning results, the generative system generates a virtual conversational partner, which is then sent to the user's terminal.

[0698] The terminal selects and displays a virtual interlocutor through a user interface. The user inputs their consultation details using the interface, which are then sent to the server. An emotion engine analyzes the user's input and recognizes their emotional state. This analysis result is used by a response adjustment mechanism to generate an appropriate response tailored to the user's emotions.

[0699] For example, if a user inputs "I feel anxious before purchasing a product online," the emotion engine recognizes the emotion of "anxiety." As a result, the virtual dialogue partner will engage in conversation such as, "Purchasing is a big decision, isn't it? It might be helpful to refer to other customers' reviews and usage examples." This allows the user to experience an emotionally empathetic response.

[0700] Example prompt: "The user has expressed concerns about this product. Please explain how they can use this product and how it can improve their daily life, and provide the best way to support them in making a purchase decision with confidence."

[0701] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0702] Step 1:

[0703] The server receives the name of a specific person the user wishes to interact with as input and collects publicly available information related to that person from the internet. This process collects data such as the person's facial features, voice characteristics, and spoken content, and stores this information in a database.

[0704] Step 2:

[0705] The server uses artificial intelligence tools to train a generative AI model based on the collected information, learning the attributes of individuals. During this process, it extracts features from the input data and optimizes the learning model. The output is a digital representation of the learned individuals.

[0706] Step 3:

[0707] The server generates a virtual interlocutor using a generation mechanism based on the learning results. This virtual interlocutor is a digital personality synthesized based on collected information and learned attributes. It is output and becomes available for use when transmitted to the terminal.

[0708] Step 4:

[0709] The terminal displays a virtual interlocutor through a user interface and prompts the user to make a selection. The user provides input through the interface to begin interacting with the selected virtual interlocutor. The selection information is then sent to the server as output.

[0710] Step 5:

[0711] The user inputs their consultation details through an interface, which is then sent to the server. The server activates an emotion engine to analyze the input and recognize the user's emotional state. The input includes text data, and the output is an emotional state (e.g., "anxiety," "joy," etc.).

[0712] Step 6:

[0713] The server uses response adjustment mechanisms, taking emotional states into consideration, to generate optimal dialogue content. In this process, prompt sentences corresponding to emotions are input to the generating AI model, and an appropriate response is output.

[0714] Step 7:

[0715] The terminal displays the generated response to the user and provides audio feedback using an audio output device. The user can confirm the response and continue the conversation. Output is provided in text and audio formats.

[0716] 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.

[0717] 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.

[0718] 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.

[0719] [Fourth Embodiment]

[0720] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0721] 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.

[0722] 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).

[0723] 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.

[0724] 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.

[0725] 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).

[0726] 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.

[0727] 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.

[0728] 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.

[0729] 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.

[0730] 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.

[0731] 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.

[0732] 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".

[0733] This invention provides a system that generates a virtual customer service representative using artificial intelligence based on publicly available information, and allows users to interact with this representative. This system mainly consists of a server, terminals, and users.

[0734] The server collects publicly available information from the web related to celebrities or historical figures selected by the user. This collected information includes facial features, voice characteristics, and spoken content, which are used by artificial intelligence to learn the characteristics of the target.

[0735] Next, the server uses a generation mechanism to create a virtual customer service representative based on the learned data. The generated customer service representative's appearance and voice are reproduced, and it is possible to simulate a conversation with that person.

[0736] The terminal is equipped with a user interface, which the user uses to select a virtual customer service representative. Interaction with the selected representative takes place through the terminal's display screen and audio output. The terminal transmits user input, i.e., questions and inquiries in text or voice, to the server.

[0737] The server, in response to the inquiry received from the terminal, synthesizes a response generated by artificial intelligence using the voice and style of a virtual customer service representative, and sends it to the terminal. This response is displayed to the user in real time and, in some cases, output as audio from the terminal.

[0738] Users can freely interact with a virtual customer service representative regarding specific inquiries or questions. If the interaction exceeds a certain time limit or if certain features are used, an additional payment process will occur via a billing system. The billing process is displayed to the user through the terminal interface and is designed for easy operation.

[0739] In this way, the embodiment of the present invention is designed to reduce the time and psychological hurdles for users, enabling them to easily engage in dialogue with the person they desire. Furthermore, by even making virtual reunions with people who existed in the past possible, it provides an effective dialogue platform.

[0740] The following describes the processing flow.

[0741] Step 1:

[0742] The user enters the name of the person they wish to consult using their device.

[0743] Step 2:

[0744] The terminal sends the entered person's name to the server.

[0745] Step 3:

[0746] Based on the name of the person received, the server collects publicly available information related to that person from the internet.

[0747] Step 4:

[0748] The server analyzes the collected information and extracts facial features, voice, and spoken content.

[0749] Step 5:

[0750] The server uses artificial intelligence to train itself on the extracted features.

[0751] Step 6:

[0752] The server uses a generation mechanism to create a virtual customer service representative based on the learned data.

[0753] Step 7:

[0754] The terminal receives information about a virtual customer representative generated from the server and displays it to the user.

[0755] Step 8:

[0756] The user initiates the interaction through the terminal's interface and enters the details of their inquiry.

[0757] Step 9:

[0758] The terminal sends the entered consultation details to the server.

[0759] Step 10:

[0760] The server generates a response using artificial intelligence based on the content of the inquiry, and then synthesizes that response in the style of a virtual customer service representative.

[0761] Step 11:

[0762] The server sends the synthesized response to the terminal.

[0763] Step 12:

[0764] The terminal displays the response to the user and outputs it audibly if necessary.

[0765] Step 13:

[0766] If the user has further questions or concerns, they can continue the conversation.

[0767] Step 14:

[0768] The server measures the interaction time and implements billing measures as needed.

[0769] Step 15:

[0770] When the user ends the interaction, the device notifies the server and displays the final billing information.

[0771] (Example 1)

[0772] 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".

[0773] In recent years, there has been a growing demand from users to interact with specific celebrities or historical figures, but it is naturally impossible to interact with people who do not exist in reality. Furthermore, advanced information processing technology is required for users to interact naturally with virtually recreated figures. In addition, if the procedures for handling fees incurred during the interaction process are complicated, usability may decrease. This invention aims to solve these problems and provide a system that allows a wide range of users to easily enjoy a high-quality conversational experience.

[0774] 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.

[0775] In this invention, the server includes an information processing means for collecting publicly available information and learning human characteristics, a generation means for generating a virtual dialogue subject using the information processing means, and a communication means for the user to interact with the virtual dialogue subject generated by the generation means. This enables users to virtually interact with specific celebrities or historical figures, and the interaction experience is provided in real time, resulting in high-quality interaction. In addition, the measurement and processing of usage fees are simplified, reducing the user's operational burden.

[0776] "Public information" refers to a collection of data that is accessible to the public through the internet or other media, and which includes information about specific individuals.

[0777] "Information processing means" refers to systems or devices that have the function of analyzing and organizing collected data and deriving results that are appropriate for a specific purpose.

[0778] "Generation means" refers to methods and techniques for creating a virtual object based on the results obtained through information processing.

[0779] A "dialogue subject" is a virtual entity designed to interact with users, modeled after a specific person.

[0780] "Communication methods" refer to interfaces and protocols used for exchanging information between users and systems, enabling real-time data transmission.

[0781] "Methods for measuring fees" refer to systems and mechanisms for measuring the costs associated with using a service and for ensuring appropriate billing.

[0782] An "operation screen" refers to an interface that allows users to perform operations visually and tactilely, providing users with information and enabling them to make choices.

[0783] The system implementing this invention mainly consists of a server, a terminal, and a user. The server first collects publicly available information from the internet related to a celebrity or historical figure selected by the user. For this collection, it utilizes web scraping technology and various APIs (e.g., online encyclopedia API, social media API). Through this, the server obtains and stores data such as facial photographs, audio clips, and transcripts of statements of the target person.

[0784] The server preprocesses the acquired data and learns human characteristics using an artificial intelligence model. This process uses facial recognition algorithms and speech analysis technologies (e.g., speech recognition APIs), which are then input into a generative AI model. Specific generative AI models include text generation models widely used in natural language processing and models used for speech synthesis (e.g., general-purpose natural language processing libraries and speech generation engines).

[0785] Next, the server generates a virtual dialogue entity based on the learning results. Using a generative AI model, the text and voice responses of this virtual dialogue entity are realistically reproduced. The virtual dialogue entity is constructed to enable seamless interaction with the user.

[0786] The terminal is equipped with a user interface that the user provides to select a virtual conversational subject through this interface. After selection, the user can ask questions or seek advice via voice or text. The terminal sends the user's input to the server, receives the generated response from the server, and displays or outputs it to the user.

[0787] For example, if a user requests to "interact with a historical scientist," the server collects publicly available information on the relevant individuals and generates a virtual scientist as the conversational subject. The user can then receive an explanation on their desired topic by entering a prompt such as, "I would like a historical scientist to explain my research."

[0788] This system allows the server to provide a customized conversational experience tailored to the user's needs in real time, enabling users to gain new learning and insights. Furthermore, the billing process is simplified through the terminal interface, allowing for smooth processing of usage fees.

[0789] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0790] Step 1:

[0791] The server collects publicly available information from the internet about celebrities or historical figures selected by the user. Specifically, the server uses web scraping techniques and APIs to obtain data such as facial images, audio clips, and transcripts of statements. The input is the name of the person selected by the user and related keywords, and the output is the collected data. This data is temporarily stored in storage for subsequent processing.

[0792] Step 2:

[0793] The server performs preprocessing on the collected data. Specifically, for image data, it extracts features using a facial recognition algorithm, and for audio data, it identifies voice characteristics using speech analysis techniques. For text data, it analyzes the content of the speech using natural language processing techniques. The raw, unprocessed data is used as input, and the output is the data with extracted features.

[0794] Step 3:

[0795] The server generates a virtual dialogue subject using a generative AI model based on preprocessed data. Here, a text generation model is used to create the content of the target person's conversation, and a speech synthesis model is used to reproduce its voice. Feature-extracted data is used as input, and a realistically reproduced virtual dialogue subject is obtained as output.

[0796] Step 4:

[0797] The user selects a virtual conversational subject through the terminal's user interface. The terminal displays available options to the user and transmits the selection to the server. The input includes the user's selection information, and the output generates commands for the server.

[0798] Step 5:

[0799] The user initiates a conversation with a virtual dialogue entity using a terminal. The user can either type prompts or ask questions by voice. The terminal sends the input information to the server, which then uses a generative AI model to return an appropriate response. The input is the user's question, and the output is the answer from the virtual dialogue entity.

[0800] Step 6:

[0801] If the user engages in conversation for a certain period of time or uses a specific function, the terminal initiates the billing process. The terminal presents the user with billing information and payment methods, and completes the process after obtaining user confirmation. Inputs include conversation time and functions used, and output is confirmation that the billing was performed correctly.

[0802] (Application Example 1)

[0803] 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".

[0804] This invention aims to realize an interactive system that utilizes virtual customer service representatives to allow users to receive real-time advice from celebrities and historical figures. In particular, the challenge is to improve the accuracy and satisfaction of fashion and lifestyle-related decision-making by providing more personalized advice that takes into account the user's personal attributes and possessions.

[0805] 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.

[0806] In this invention, the server includes an artificial intelligence means for collecting publicly available information and learning human attributes, a generation means for generating a virtual customer service representative using the artificial intelligence means, and a suggestion means for managing information about the user's possessions and providing attribute-based advice from the virtual advisor. This makes it possible for the user to receive specific and accurate advice tailored to their individual needs from a virtual customer service representative of their choice.

[0807] "Public information" refers to data and documents accessible on the internet that are generally known and relate to a specific person or subject.

[0808] "Human attributes" refer to the characteristics and traits of individual human beings, including information such as appearance, voice, style, and behavioral patterns.

[0809] "Artificial intelligence means" refers to technological means that use computer systems to analyze and learn from data, and then make decisions and predictions based on the results.

[0810] A "virtual customer service representative" is a digital character created using artificial intelligence technology that can simulate a specific person and interact with users.

[0811] "Generation means" refers to technical means for creating new digital objects based on learned data.

[0812] An "action" is the process of information exchange and communication that takes place between the user and a virtual customer service representative.

[0813] "Usage costs" refer to expenses incurred in connection with using the system, and are monetary burdens measured on an hourly basis or according to the functionality used.

[0814] A "billing method" is a technical means for accurately measuring, processing, and billing for the costs incurred when users utilize a system.

[0815] "Possessions information" refers to data related to items and assets owned by the user, including fashion items and other personal items.

[0816] A "suggestion tool" is a technical tool that provides advice indicating the optimal choices and actions based on the user's attributes and possession information.

[0817] The "connection interface" is the interface that users use to select a virtual customer service representative and initiate a conversation.

[0818] The system used to implement this application primarily consists of three elements: a server, a terminal, and a user.

[0819] The server includes artificial intelligence means for collecting and processing publicly available information and learning human attributes. Specifically, it collects publicly accessible data on the web and analyzes information about the appearance, voice, style, and behavioral patterns associated with a particular individual. The learned data is used to generate a virtual customer service role using an AI model (e.g., OpenAI's GPT-4). This virtual role simulates the characteristics of a specific person and enables interaction with the user.

[0820] The terminal acts as an intermediary for the interaction between the user and a virtual customer service representative. The terminal displays a connection screen where the user can select a virtual customer service representative and, if necessary, check the usage costs. Information about the user's possessions (e.g., fashion items) is managed through the terminal and used by the virtual advisor to provide optimal advice based on the user's attributes. This allows the user to receive specific and accurate advice.

[0821] The user uses this system to initiate a conversation with a virtual customer service representative of their choice. For example, by asking a question like, "I'm attending a social event today. What would be appropriate attire?", they can receive style suggestions for the day from a virtual fashion advisor.

[0822] An example of a prompt message is, "Based on the clothing preferences entered by the user, please suggest clothing styles from the selected stylist."

[0823] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0824] Step 1:

[0825] The server collects publicly available information from the internet. This collection process searches data sources related to a specific individual and extracts attribute information such as appearance, voice, and speech content. The input is information about the target individual, and the output is formatted attribute data. This data is stored for the learning phase.

[0826] Step 2:

[0827] The server passes the collected data to an artificial intelligence system to learn human attributes. Using a generative AI model, it analyzes and learns the characteristics of the data, incorporating the person's style and features into the model. The input is formatted attribute data, and the output is the trained model.

[0828] Step 3:

[0829] The server generates a virtual customer service representative using a pre-trained model. This generation method constructs a digital character capable of simulating a person's appearance and voice in real time. The input is the pre-trained model data, and the output is the virtual customer service representative.

[0830] Step 4:

[0831] The terminal displays an interface that allows the user to select a virtual customer service role. The user selects their desired role via the screen and completes preparation for the next step. The input is the user's instruction regarding their selection, and the output is the result of that selection.

[0832] Step 5:

[0833] The user initiates a conversation with a virtual customer service representative of their choice. The terminal receives questions from the user and sends them to the server in text or voice format. The input is the user's question, and the output is the data sent to the server.

[0834] Step 6:

[0835] The server uses a generative AI model to generate a response based on the received question. This model analyzes the context of the question and provides a response tailored to the style of a virtual customer service representative. The input is the user's question, and the output is a well-constructed response.

[0836] Step 7:

[0837] The terminal provides the user with a generated response. The response is played back as text or audio and presented in a format that is easy for the user to understand. The input is the generated response data, and the output is the information displayed to the user.

[0838] Step 8:

[0839] The terminal measures the usage costs incurred during the interaction and displays them to the user as needed. This includes calculating charges based on system usage time and the use of special features. Input is usage information related to the interaction, and output is a charge display.

[0840] 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.

[0841] This invention combines a system that generates a virtual customer service representative using artificial intelligence based on publicly available information and interacts with the user with an emotion engine that recognizes the user's emotions. This system consists of a server, a terminal, a user, and an emotion engine.

[0842] When a user enters the name of a specific person they wish to interact with, the server collects publicly available information about that person from the internet. This information includes facial features, voice characteristics, and spoken content, and the artificial intelligence learns the target's characteristics based on this data. Based on the learning results, the server uses a generation mechanism to create a virtual customer service representative and sends that information to the terminal.

[0843] The terminal provides a user interface, which the user uses to select a virtual customer service representative. The terminal also receives input from the user regarding their inquiry and sends it to the server. At this point, the emotion engine operates and analyzes the user's emotional state based on their input. For example, if the user inputs "I've been very tired from work lately," the emotion engine recognizes emotions such as "fatigue" and "stress."

[0844] The server takes into account the emotions recognized by the emotion engine and adjusts the AI-generated response to suit the conditions. It generates dialogue content corresponding to the recognized emotion and synthesizes the response in the style of a virtual customer service representative. For example, if "fatigue" is recognized, the virtual customer service representative might respond with something like, "That must be tough. Do you have time to refresh yourself now?"

[0845] The device displays this response to the user in real time and outputs it audibly as needed. This allows the user to continue the virtual conversation and experience a more empathetic dialogue.

[0846] Furthermore, this system incurs additional charges under certain conditions. These charges are clearly communicated to the user via their device, and the interaction continues only after approval. By incorporating an emotion engine, this invention is able to provide a highly personalized interaction that responds to the user's emotions, going beyond mere information provision.

[0847] The following describes the processing flow.

[0848] Step 1:

[0849] The user uses their device to enter the name of the person they want to consult with and requests the creation of a virtual customer service representative.

[0850] Step 2:

[0851] The terminal sends the entered information to the server.

[0852] Step 3:

[0853] Based on the name of the person who submitted the request, the server automatically collects relevant information that is publicly available on the internet.

[0854] Step 4:

[0855] The server analyzes the collected information and extracts characteristics of the subject, such as their appearance, voice, and personality.

[0856] Step 5:

[0857] The server uses artificial intelligence to learn the extracted features and generate a virtual customer service representative.

[0858] Step 6:

[0859] The server sends the generated virtual customer service representative data to the terminal.

[0860] Step 7:

[0861] The terminal displays a screen for the user to select a virtual customer service representative.

[0862] Step 8:

[0863] The user uses their device to select a virtual customer service representative to begin a consultation with.

[0864] Step 9:

[0865] The user enters their inquiry details as text or voice and sends them to the server via their device.

[0866] Step 10:

[0867] The server analyzes the received consultation content using an emotion engine to recognize the user's emotional state.

[0868] Step 11:

[0869] The server uses artificial intelligence to generate appropriate responses based on recognized emotions, and then synthesizes these responses in the style of a virtual customer service representative.

[0870] Step 12:

[0871] The server sends the synthesized response data to the terminal.

[0872] Step 13:

[0873] The device displays real-time generated responses to the user and provides audio output as needed.

[0874] Step 14:

[0875] If the user wishes to continue the conversation, they will enter additional questions into the terminal and run the process again.

[0876] Step 15:

[0877] The server measures the duration of the interaction and, if it exceeds the time limit for a paid session, activates the billing mechanism and notifies the user via their device.

[0878] Step 16:

[0879] The user can choose to accept the charge and continue the conversation, or end the conversation.

[0880] Step 17:

[0881] The device will end the interaction based on the user's choice and, if necessary, provide the user with final billing information.

[0882] (Example 2)

[0883] 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".

[0884] In recent years, AI-powered dialogue systems have become widespread in many fields. However, conventional systems have struggled to accurately recognize users' emotions and respond accordingly. As a result, users have faced the challenge of receiving uniform dialogue and not being able to receive satisfactory dialogue that reflects their individual emotions and needs. Furthermore, there has been a lack of adequate interfaces that allow users to easily select a specific person they wish to virtually interact with.

[0885] 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.

[0886] In this invention, the server includes artificial intelligence means for collecting publicly available information and learning personal characteristics, generation means for generating a virtual responder, and emotion recognition means for analyzing the emotional state based on the user's input. As a result, the user can interact with a virtual responder that resembles a specific person, and the content of the interaction is adjusted according to the user's emotions, enabling a more personalized experience.

[0887] "Public information" refers to data that is publicly available on the internet or other accessible data sources.

[0888] "Personal characteristics" refer to information used to identify a person, such as their physical appearance, vocal characteristics, and the content of their statements.

[0889] "Artificial intelligence tools" refer to technological means that use machine learning and natural language processing to acquire knowledge from data and perform processing according to specific purposes.

[0890] "Generative means" refers to methods and processes for creating new data-based content using artificial intelligence technology.

[0891] "Emotion recognition means" refers to technical means for analyzing user input data and identifying emotional states based on that analysis.

[0892] "Response generation means" refers to a means for generating an appropriate response based on analyzed emotions and presenting it to the user.

[0893] "Dialogue means" refers to the process for communication between a virtual responder and the user.

[0894] "Billing method" refers to the methods and technologies used to measure and process charges associated with the use of a system.

[0895] The system of this invention consists of a server, a terminal, and a user, and further incorporates an emotion engine for emotion recognition.

[0896] After receiving the name of the person the user wishes to interact with, the server uses web scraping tools to collect relevant publicly available information from the internet. For example, Scrapy can be used. The data collected at this stage includes the person's facial features, voice characteristics, and speech information. Based on this data, artificial intelligence learns the person's characteristics using machine learning algorithms and generates a virtual responder using a generative AI model. Models that can be used as natural language processing techniques in this process include GPT-3.

[0897] The terminal provides an interface to the user, displaying and allowing them to select a virtual responder. This interface includes fields for the user to input or voice-input their consultation details. Voice input can utilize speech recognition software. The data entered by the user is sent to the server in real time, where an emotion engine analyzes the user's emotions. Through emotion recognition, the system can understand the user's situation, such as if they are experiencing "fatigue" or "stress."

[0898] Based on the analysis results, the server generates a response using a generative AI model and adjusts it to match the user's emotions. This adjusted response is sent to the terminal, which displays the response to the user and, in some cases, also outputs it as audio. In this case, text-to-speech (TTS) technology is used to convert it to speech.

[0899] For example, if a user types "I've been really tired from work lately," a tailored response such as "That must be tough. Do you have time to relax now?" will be generated.

[0900] A concrete example of a prompt message would be: "The user wants a conversation based on information related to a specific person. Based on the emotional information entered by the user, the emotion engine will generate appropriate dialogue content."

[0901] This system allows users to engage in emotionally-driven conversations with virtual characters, which is expected to enhance the personalized experience.

[0902] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0903] Step 1:

[0904] The server receives the name of a specific person from the user. Using this name as input, the server uses web scraping tools to collect publicly available information related to that person from the internet. This data includes facial features, voice characteristics, and statements, and is output as a single database.

[0905] Step 2:

[0906] The server provides the collected information to an artificial intelligence system, which then learns about human characteristics. During this process, machine learning algorithms are applied to extract features from the received data. As a result, a trained model is output.

[0907] Step 3:

[0908] The server generates a virtual responder using a generative AI model. In this process, the artificial intelligence synthesizes content such as text and audio using the trained model as input. This outputs a digital profile of the virtual responder, which is then sent to the terminal.

[0909] Step 4:

[0910] The terminal provides an interface that displays a virtual responder to the user. The user selects a responder they wish to interact with through this interface, and this selection information is sent to the server.

[0911] Step 5:

[0912] The user inputs, either by typing or voice, what they want to communicate with a virtual responder through the device. This user input is sent to an emotion recognition system and processed as data for analysis.

[0913] Step 6:

[0914] The server generates an appropriate response using a response generation mechanism based on the user's emotions analyzed by the emotion recognition mechanism. At this stage, the generation AI model is used again to generate a response that matches the user's emotional state. The adjusted response is output and sent to the terminal.

[0915] Step 7:

[0916] The terminal presents the received response to the user visually and audibly. For audio output, a TTS (text-to-speech) engine is used, and the generated text is played back as natural-sounding speech. The user can then respond or provide further input based on the presented information.

[0917] (Application Example 2)

[0918] 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".

[0919] Traditional systems made it difficult to understand user emotions during customer service, resulting in only simple information being provided. Furthermore, the lack of mechanisms to deliver appropriate dialogue tailored to the user's situation prevented the realization of a deeper customer experience.

[0920] 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.

[0921] In this invention, the server includes artificial intelligence means for collecting publicly available information and learning the attributes of a person; generation means for generating a virtual conversationalist; analysis means including an emotion engine for analyzing the emotional state based on the user's input information; response adjustment means; and billing means. This enables personalized customer service by providing conversational content that corresponds to the user's emotional state.

[0922] "Public information" refers to data and knowledge that is generally accessible on the internet and includes attributes and characteristics related to a specific person.

[0923] "Artificial intelligence means" refers to technologies that function as part of a computer system and have the function of learning and recognizing a person's attributes.

[0924] "Generative means" refers to the process or function of creating a virtual conversational partner based on information learned by artificial intelligence.

[0925] "Dialogue means" refers to a system or function that enables the exchange of information between a virtual interlocutor and the user.

[0926] An "emotion engine" is a technology that analyzes user input information to identify and classify a person's emotional state.

[0927] "Analytical means" refers to the ability or method to process input data and derive specific conclusions or results.

[0928] "Response adjustment means" refers to a system or function that generates and adjusts the optimal response content based on the analyzed emotional state.

[0929] A "billing method" is a system that has the function of measuring and processing usage fees based on the usage of the conversation.

[0930] To realize this invention, a server, terminals, users, and a network to connect them are primarily required. The server should function as a cloud computing environment, utilizing Amazon Web Services (AWS) or Google Cloud Platform. For the terminals, smartphones running iOS or Android are preferable.

[0931] First, the server collects publicly available information from the internet, including a specific person's facial features, voice characteristics, and spoken content. The artificial intelligence system uses this information to learn the person's attributes using a generative AI model. Based on the learning results, the generative system generates a virtual conversational partner, which is then sent to the user's terminal.

[0932] The terminal selects and displays a virtual interlocutor through a user interface. The user inputs their consultation details using the interface, which are then sent to the server. An emotion engine analyzes the user's input and recognizes their emotional state. This analysis result is used by a response adjustment mechanism to generate an appropriate response tailored to the user's emotions.

[0933] For example, if a user inputs "I feel anxious before purchasing a product online," the emotion engine recognizes the emotion of "anxiety." As a result, the virtual dialogue partner will engage in conversation such as, "Purchasing is a big decision, isn't it? It might be helpful to refer to other customers' reviews and usage examples." This allows the user to experience an emotionally empathetic response.

[0934] Example prompt: "The user has expressed concerns about this product. Please explain how they can use this product and how it can improve their daily life, and provide the best way to support them in making a purchase decision with confidence."

[0935] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0936] Step 1:

[0937] The server receives the name of a specific person the user wishes to interact with as input and collects publicly available information related to that person from the internet. This process collects data such as the person's facial features, voice characteristics, and spoken content, and stores this information in a database.

[0938] Step 2:

[0939] The server uses artificial intelligence tools to train a generative AI model based on the collected information, learning the attributes of individuals. During this process, it extracts features from the input data and optimizes the learning model. The output is a digital representation of the learned individuals.

[0940] Step 3:

[0941] The server generates a virtual interlocutor using a generation mechanism based on the learning results. This virtual interlocutor is a digital personality synthesized based on collected information and learned attributes. It is output and becomes available for use when transmitted to the terminal.

[0942] Step 4:

[0943] The terminal displays a virtual interlocutor through a user interface and prompts the user to make a selection. The user provides input through the interface to begin interacting with the selected virtual interlocutor. The selection information is then sent to the server as output.

[0944] Step 5:

[0945] The user inputs their consultation details through an interface, which is then sent to the server. The server activates an emotion engine to analyze the input and recognize the user's emotional state. The input includes text data, and the output is an emotional state (e.g., "anxiety," "joy," etc.).

[0946] Step 6:

[0947] The server uses response adjustment mechanisms, taking emotional states into consideration, to generate optimal dialogue content. In this process, prompt sentences corresponding to emotions are input to the generating AI model, and an appropriate response is output.

[0948] Step 7:

[0949] The terminal displays the generated response to the user and provides audio feedback using an audio output device. The user can confirm the response and continue the conversation. Output is provided in text and audio formats.

[0950] 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.

[0951] 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.

[0952] 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 robot 414.

[0953] 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.

[0954] 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.

[0955] 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.

[0956] 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.

[0957] 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.

[0958] 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."

[0959] 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.

[0960] 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.

[0961] 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.

[0962] 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.

[0963] 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.

[0964] 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.

[0965] 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.

[0966] 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.

[0967] 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.

[0968] 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.

[0969] 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.

[0970] 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.

[0971] The following is further disclosed regarding the embodiments described above.

[0972] (Claim 1)

[0973] An artificial intelligence method that collects publicly available information and learns human characteristics,

[0974] A generation means that generates a virtual customer service representative using the artificial intelligence means,

[0975] A dialogue means for conducting a conversation between a virtual customer representative and a user generated by the generation means,

[0976] A billing means for measuring and processing usage fees incurred during the aforementioned dialogue,

[0977] A system that includes this.

[0978] (Claim 2)

[0979] The system according to claim 1, characterized in that it includes an interface for a user to select the virtual customer service representative.

[0980] (Claim 3)

[0981] The system according to claim 1, characterized by having a means for a user to virtually interact with a specific person who existed in the past.

[0982] "Example 1"

[0983] (Claim 1)

[0984] Information processing means that collects publicly available information and learns human characteristics,

[0985] A generation means that generates a virtual dialogue subject using the aforementioned information processing means,

[0986] A communication means for conducting a dialogue between a virtual dialogue subject generated by the generation means and a user,

[0987] A fee measurement means for measuring and processing usage fees incurred during the aforementioned dialogue process,

[0988] An interface means having an operation screen for the user to select the virtual dialogue subject,

[0989] A functional means that provides a way for a user to virtually interact with a specific person from the past,

[0990] Information technology systems including

[0991] (Claim 2)

[0992] The system according to claim 1, characterized in that the user selects the virtual dialogue subject using an operation screen.

[0993] (Claim 3)

[0994] The system according to claim 1, comprising means for realizing real-time dialogue with a virtual dialogue subject based on a specific person who existed in the past.

[0995] "Application Example 1"

[0996] (Claim 1)

[0997] An artificial intelligence method that collects publicly available information and learns human attributes,

[0998] A generation means that generates a virtual customer service representative using the artificial intelligence means,

[0999] A dialogue means that performs actions between a virtual customer service representative generated by the generation means and a user,

[1000] A billing mechanism for measuring and processing the usage costs incurred during the aforementioned dialogue process,

[1001] A means of managing information about the user's possessions and providing advice based on attributes from a virtual advisor,

[1002] A system that includes this.

[1003] (Claim 2)

[1004] The system according to claim 1, characterized in that it includes a connection surface for a user to select the virtual customer service representative.

[1005] (Claim 3)

[1006] The system according to claim 1, characterized by comprising means for a user to virtually interact with a specific person who existed in the past.

[1007] "Example 2 of combining an emotion engine"

[1008] (Claim 1)

[1009] An artificial intelligence method that collects publicly available information and learns personal characteristics,

[1010] A generation means that generates a virtual responder using the artificial intelligence means,

[1011] An emotion recognition means that analyzes the emotional state based on the user's input,

[1012] A response generation means for generating and adjusting responses according to the aforementioned emotional state,

[1013] A dialogue means for conducting a dialogue between a virtual responder generated by the generation means and the user,

[1014] A billing means for measuring and processing usage fees incurred during the aforementioned dialogue,

[1015] A system that includes this.

[1016] (Claim 2)

[1017] The system according to claim 1, characterized by comprising an interface for a user to select the virtual responder.

[1018] (Claim 3)

[1019] The system according to claim 1, characterized by comprising means for a user to virtually interact with a specific person who existed in the past.

[1020] "Application example 2 when combining with an emotional engine"

[1021] (Claim 1)

[1022] An artificial intelligence method that collects publicly available information and learns the attributes of individuals,

[1023] A generation means that generates a virtual interlocutor using the artificial intelligence means,

[1024] A dialogue means for conducting a dialogue between a virtual interlocutor and a user generated by the generation means,

[1025] Analysis means including an emotion engine that analyzes the emotional state based on the user's input information,

[1026] A response adjustment means that provides dialogue content corresponding to the emotional state analyzed by the aforementioned analysis means,

[1027] A billing means for measuring and processing usage fees incurred during the aforementioned dialogue,

[1028] A system that includes this.

[1029] (Claim 2)

[1030] The system according to claim 1, characterized in that it includes information display means for the user to select the virtual interlocutor.

[1031] (Claim 3)

[1032] The system according to claim 1, characterized by having a means for the user to virtually interact with a specific person who existed in the past. [Explanation of symbols]

[1033] 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. An artificial intelligence method that collects publicly available information and learns human characteristics, A generation means that generates a virtual customer service representative using the artificial intelligence means, A dialogue means for conducting a conversation between a virtual customer representative and a user generated by the generation means, A billing means for measuring and processing usage fees incurred during the aforementioned dialogue, A system that includes this.

2. The system according to claim 1, characterized in that it includes an interface for a user to select the virtual customer service representative.

3. The system according to claim 1, characterized by having a means for a user to virtually interact with a specific person who existed in the past.

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