System

Abstract

To address such a problem that smartphone charges and service descriptions are unintelligible.SOLUTION: A system includes means for: inputting feature information according to a user's preference; transmitting the input feature information to a server; causing the server to store the received feature information in a database; causing the server to generate a prompt sentence based on the feature information; inputting the prompt sentence into a generative AI model to generate an AI crew member; transmitting data of the generated AI crew member to the user's terminal; enabling conversation with the generated AI crew member; causing the AI crew member to handle smartphone-related consultations and contract procedures; and accumulating and analyzing customer service data of the AI crew member.SELECTED DRAWING: Figure 1

Description

[Technical field]

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

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

[0003] [Patent Document 1] JP 2022-180282 A Summary of the Invention [Problem to be solved by the invention]

[0004] There are issues such as not being able to enjoy the image generation AI and the smartphone charges and service descriptions being difficult to understand. [Means for solving the problem]

[0005] To solve this problem, we will generate AI crew members according to the user's preferences and enable conversation with the generated AI crew members. Furthermore, by having the AI ​​crew members handle smartphone-related consultations and contract procedures, we will provide a service that is easy for users to understand. In addition, by accumulating and analyzing the customer service data of the AI ​​crew members, we will create the strongest AI crew members and provide them with the best sales pitches and faces that the user prefers. [Brief description of the drawings]

[0006] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Diagram 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. FIG. [Diagram 3] FIG. 11 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Diagram 5] FIG. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 13 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 2 is a sequence diagram showing a process flow of the data processing system in the first embodiment of the first form example. [Figure 12] FIG. 11 is a sequence diagram showing a process flow of the data processing system in the application example 1 of the first embodiment. [Figure 13] FIG. 11 is a sequence diagram showing a process flow of the data processing system in the second embodiment of the second embodiment. [Figure 14] FIG. 13 is a sequence diagram showing a process flow of the data processing system in application example 2 of embodiment 2. [Figure 15] FIG. 13 is a sequence diagram showing a process flow of a data processing system in a third embodiment of the present invention. [Figure 16]FIG. 13 is a sequence diagram showing a process flow of the data processing system in the third application example of the third embodiment. [Figure 17] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when combined with an emotion engine. [Figure 19] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system according to the embodiment 2 of the second embodiment in the case where an emotion engine is combined. [Figure 20] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when combined with an emotion engine. [Figure 21] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in the embodiment 3 of the form example 3 in the case where an emotion engine is combined. [Figure 22] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when combined with an emotion engine. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0007] 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.

[0008] First, the terms used in the following description will be explained.

[0009] In the following embodiments, a signed processor (hereinafter simply referred to as a "processor") may be one arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be one type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] In the following embodiments, a signed RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0011] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0012] In the following embodiments, a communication I / F (Interface) with a code is an interface including a communication processor and an antenna. The communication I / F controls communication between multiple computers. An example of a communication standard applied to the communication I / F is a wireless communication standard including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0013] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. In addition, in this specification, the same idea as "A and / or B" is also applied when three or more things are expressed by connecting them with "and / or."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0017] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a wide area network (WAN) and / or a local area network (LAN).

[0018] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0019] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (e.g., a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0020] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (e.g., voice 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 voice according to instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a Complementary Metal-Oxide-Semiconductor (CMOS) image sensor or a Charge Coupled Device (CCD) image sensor.

[0021] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54.

[0022] FIG. 2 shows an example of main functions of the data processing device 12 and the smart device 14.

[0023] As shown in Fig. 2, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32. The specific process program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific process program 56 from the storage 32, and executes the read specific process program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific process program 56 executed on the RAM 30.

[0024] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0025] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores a reception output program 60. The reception output program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads out 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 the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] As one embodiment of the present invention, there is a system in which a user generates an AI crew member according to his / her preferences. Specifically, the user inputs his / her preferred features (e.g., face shape, hair color, tone of voice, etc.), and an AI crew member is generated based on the input. The generated AI crew member can converse with the user and can provide smartphone-related advice and perform contract procedures.

[0029] "Example 2"

[0030] Furthermore, a system for accumulating and analyzing customer service data of AI crew members is also one embodiment of the present invention. Specifically, the system accumulates data that AI crew members obtain through conversations with users and contract procedures, and analyzes that data to create the strongest AI crew members.

[0031] "Example 3"

[0032] The best AI crew members have the face that the user likes and the best sales pitch. Specifically, they are generated by combining the facial features that the user likes the most with the most effective sales pitch. In this way, users can enjoy conversations with their favorite AI crew members while consulting about smartphones or completing contract procedures.

[0033] The process flow of each embodiment will be described below.

[0034] "Example 1"

[0035] Step 1: The user inputs their preferred features (e.g. face shape, hair color, tone of voice, etc.) into the system.

[0036] Step 2: The system generates an AI crew based on the input features.

[0037] Step 3: The generated AI crew can converse with the user and handle smartphone-related inquiries and contract procedures.

[0038] "Example 2"

[0039] Step 1: The AI ​​crew accumulates data obtained through conversations with users and contract procedures.

[0040] Step 2: The system analyzes the accumulated data.

[0041] Step 3: Create the strongest AI crew based on the analysis results.

[0042] "Example 3"

[0043] Step 1: The system generates the strongest AI crew by combining the user's most preferred facial features with the most effective sales pitches.

[0044] Step 2: The generated AI crew can enjoy conversation with the user and assist with smartphone-related issues and contract procedures.

[0045] Example 1

[0046] Next, a description will be given of Example 1 of the embodiment 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal".

[0047] Conventional AI crew generation systems did not adequately customize the system to meet the user's preferences, limiting the user experience. In addition, the quality and performance of the generated AI crews were inconsistent, resulting in a lack of reliability in smartphone-related consultations and contract procedures. Furthermore, the accumulation and analysis of customer service data was insufficient, making it difficult to generate optimal AI crews.

[0048] The specification process by the specification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes a means for inputting feature information according to the user's preferences, a means for transmitting the input feature information to the server, a means for the server to receive the feature information and store it in a database, a means for the server to generate a prompt sentence based on the feature information, a means for inputting a prompt sentence into the generation AI model and generating an AI crew member, a means for transmitting data of the generated AI crew member to the user's terminal, a means for enabling a conversation with the generated AI crew member, a means for the AI ​​crew member to carry out smartphone-related consultations and contract procedures, and a means for accumulating and analyzing customer service data of the AI ​​crew member. This makes it possible to generate a high-quality AI crew member according to the user's preferences, and to realize highly reliable smartphone-related consultations and contract procedures. Furthermore, the accumulation and analysis of customer service data makes it possible to generate an optimal AI crew member.

[0049] The "means for inputting characteristic information according to user preferences" refers to a means for providing an interface for a user to input characteristic information such as face shape, hair color, and tone of voice based on his or her own preferences.

[0050] The "means for transmitting the input characteristic information to the server" refers to a communication means for securely transmitting the characteristic information input by the user to the server.

[0051] The "means for the server to receive the characteristic information and store it in the database" refers to the means for the server to receive the characteristic information sent from the user and store the information in the database.

[0052] "Means for the server to generate a prompt sentence based on feature information" refers to means for the server to generate a prompt sentence to be input into the generative AI model based on feature information stored in the database.

[0053] "Means for inputting a prompt sentence into a generative AI model and generating an AI crew member" refers to means for inputting a prompt sentence into a generative AI model and generating image and voice data of an AI crew member based on the prompt sentence.

[0054] "Means for transmitting data of the generated AI crew to the user's terminal" refers to communications means for transmitting data of the generated AI crew to the user's terminal.

[0055] "Means for enabling conversation with the generated AI crew" refers to means for providing an interface for a user to interact with the generated AI crew.

[0056] "Means for carrying out smartphone-related consultations and contract procedures through an AI crew" refers to a means for users to carry out smartphone-related consultations and contract procedures through an AI crew.

[0057] "Means of accumulating and analyzing customer service data from AI crews" refers to the means by which the AI ​​crews accumulate customer service data obtained through dialogue with users and analyze that data.

[0058] "Means for creating optimal AI crew" refers to a means for analyzing accumulated customer service data and generating optimal AI crew based on the results.

[0059] An "AI crew with the optimal sales pitch" is an AI crew that can deliver the most effective sales pitch to users based on the results of analyzing customer service data.

[0060] This invention relates to a system that allows users to generate AI crew members according to their preferences and interact with the AI ​​crew members. Specifically, it includes a process in which the user inputs characteristic information and generates an AI crew member using a generative AI model based on the information.

[0061] Hardware and Software Used

[0062] Hardware

[0063] Terminal: The device through which the user enters characteristic information (e.g. smartphone, PC).

[0064] Server: A computer system for receiving the feature information, storing it in a database, and generating an AI crew member using a generative AI model.

[0065] software

[0066] Database: A data management system for storing feature information (e.g., MySQL (registered trademark), PostgreSQL).

[0067] Generative AI model: An artificial intelligence model for generating AI crew members based on a prompt sentence (e.g., OpenAI's GPT-4(R), DALL-E).

[0068] Communication Protocol: A protocol for securely transmitting data between the device and the server (e.g. HTTPS).

[0069] Data processing and calculation

[0070] User Actions

[0071] A user uses a terminal to access the system's interface and inputs characteristic information such as face shape, hair color, tone of voice, etc. For example, a user selects "round face, blonde hair, calm, low-pitched voice."

[0072] Device operation

[0073] The device sends the characteristic information entered by the user to the server, where the data is encrypted and transmitted securely using the HTTPS protocol.

[0074] Server Operations

[0075] The server receives the characteristic information sent from the terminal and stores it in a database. When storing the information, it performs validation to maintain the integrity of the data.

[0076] Next, the server generates a prompt sentence to be input to the generative AI model based on the feature information stored in the database. For example, it generates the following prompt sentence:

[0077] "The characteristics of the AI ​​crew that users prefer are as follows: face shape is round, hair color is blonde, and voice tone is calm and low. Please generate an AI crew with these characteristics."

[0078] The server inputs the generated prompt text into the generative AI model to generate image and voice data of the AI ​​crew. The generated data is then sent to the user's device via the server.

[0079] User Actions

[0080] The user interacts with the AI ​​crew member that is displayed on the device, who answers the user's questions and assists with smartphone-related consultations and contract procedures.

[0081] Examples

[0082] For example, if the user selects "round face, blonde hair, soft, deep voice," the following specific actions will occur:

[0083] 1. A user opens an app on their smartphone and selects "round face" as their face shape, "blonde" as their hair color, and "calm, low-pitched" as their voice tone.

[0084] 2. The device sends this information to the server.

[0085] 3. The server receives the information and stores the characteristic information "round face, blonde hair, calm, low voice" in the database.

[0086] 4. The server generates a prompt sentence saying, "The characteristics of the AI ​​crew member that the user prefers are as follows: a round face, blonde hair, and a calm, low voice tone. Please generate an AI crew member with these characteristics."

[0087] 5. The server inputs the prompt text into the generative AI model and generates image and voice data for the AI ​​crew.

[0088] 6. The server sends the generated AI crew data to the user's smartphone.

[0089] 7. The user interacts with the AI ​​crew generated on their smartphone and completes the smartphone contract procedure.

[0090] In this way, users can generate high-quality AI crew members tailored to their preferences and provide reliable smartphone-related consultations and contract procedures. Furthermore, the accumulation and analysis of customer service data will enable the generation of optimal AI crew members.

[0091] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0092] Step 1:

[0093] The user inputs the characteristic information.

[0094] A user uses a terminal to access the system interface and inputs feature information such as face shape, hair color, and voice tone. For example, a user selects "round face, blonde, calm, low-pitched voice." The input data is feature information such as face shape, hair color, and voice tone.

[0095] Step 2:

[0096] The terminal transmits the input characteristic information to the server.

[0097] The terminal transmits the characteristic information input by the user to the server using the HTTPS protocol. The input data is the characteristic information input by the user, and the output data is the characteristic information transmitted to the server.

[0098] Step 3:

[0099] The server receives the characteristic information and stores it in a database.

[0100] The server receives the feature information sent from the terminal and stores it in a database. When storing the data, validation is performed to maintain data consistency. The input data is the feature information sent from the terminal, and the output data is the feature information stored in the database.

[0101] Step 4:

[0102] The server generates a prompt sentence based on the characteristic information.

[0103] The server generates a prompt sentence to be input to the generative AI model based on the feature information stored in the database. For example, it generates a prompt sentence such as "The features of the AI ​​crew member the user prefers are as follows: a round face, blonde hair, and a calm, low voice. Please generate an AI crew member with these features." The input data is the feature information stored in the database, and the output data is the generated prompt sentence.

[0104] Step 5:

[0105] The server inputs a prompt sentence into the generative AI model and generates an AI crew member.

[0106] The server inputs the generated prompt sentence into the generative AI model to generate image and voice data of the AI ​​crew. The generative AI model generates image and voice data of the AI ​​crew based on the prompt sentence. The input data is the generated prompt sentence, and the output data is the generated image and voice data of the AI ​​crew.

[0107] Step 6:

[0108] The server sends the generated AI crew data to the user's device.

[0109] The server transmits the AI ​​crew data obtained from the generative AI model to the user's device. When transmitting, the data is compressed and encrypted to ensure secure transmission. The input data is the image and audio data of the generated AI crew, and the output data is the AI ​​crew data transmitted to the user's device.

[0110] Step 7:

[0111] The user interacts with the generated AI crew.

[0112] The user interacts with the generated AI crew displayed on the device. The AI ​​crew answers the user's questions and supports smartphone-related consultations and contract procedures. The input data is the user's questions and requests, and the output data is the AI ​​crew's responses and support.

[0113] (Application example 1)

[0114] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0115] Traditional shopping experiences often make it difficult for users to find products that suit their tastes, and the purchasing process is often cumbersome. Furthermore, customer service in physical stores is often inconsistent, so there was a need for effective measures to improve user satisfaction.

[0116] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0117] In this invention, the server includes a means for generating an AI crew member according to the user's preferences, a means for enabling a conversation with the generated AI crew member, a means for the AI ​​crew member to handle consultations and contract procedures related to smart devices, a means for accumulating and analyzing customer service data of the AI ​​crew member, a means for recommending products based on the user's preferences, and a means for supporting the user's purchase procedure, thereby enabling the user to easily find products that match their preferences and smoothly complete the purchase procedure.

[0118] "User" means an individual or legal entity that uses the System.

[0119] "Preferences" are personal tastes or preferences that a user has for particular features or attributes.

[0120] "AI Crew" is an artificial intelligence character that is generated based on the user's preferences and will converse with and provide support to the user.

[0121] "Means for generating" means the technical means for generating an AI crew member based on user input.

[0122] "Means enabling conversation" refers to the technical means that allow a natural dialogue between the user and the AI ​​crew.

[0123] A "smart device" is an electronic device with Internet connectivity, such as a smartphone or smart glasses.

[0124] "Means of consultation and contract procedures" refers to the technological means by which users can ask questions about smart devices or complete contract procedures through an AI crew.

[0125] "Customer service data" is information that the AI ​​crew collects through their interactions with users.

[0126] "Means of accumulation and analysis" refers to the technical means for storing and analyzing customer service data.

[0127] "Means for recommending products" means technical means for suggesting appropriate products based on the user's preferences.

[0128] "Means to support the purchase process" are technological means to assist users in the process of purchasing a product.

[0129] The system for implementing the present invention generates an AI crew according to the user's preferences and improves the shopping experience in a physical store. A specific embodiment of the system is described below.

[0130] 1. System Configuration

[0131] The system consists of the following main components:

[0132] User terminal: Smart devices such as smartphones and smart glasses.

[0133] Servers: Servers for running generative AI models (e.g. GPT-4), facial recognition APIs (e.g. Face++), and speech synthesis APIs (e.g. Google® Text-to-Speech).

[0134] Database: A database for accumulating and analyzing customer service data.

[0135] 2. Program Processing

[0136] The server realizes the system using the following means.

[0137] A way to generate AI crew members to suit user preferences

[0138] The user inputs the user's preferred features (e.g. face shape, hair color, tone of voice, etc.) from the user's device. The server uses a generative AI model to generate an AI crew based on the user's input. It uses a facial recognition API to generate a face that matches the specified features, and a voice synthesis API to generate a voice with the specified tone of voice.

[0139] A means to enable conversation with generated AI crew members

[0140] The server performs natural language processing (NLP) to allow the generated AI crew to have a natural dialogue with the user, allowing the user to enjoy shopping while talking to the AI ​​crew.

[0141] A means of consultation and contract procedures related to smart devices

[0142] The AI ​​Crew supports users when they have questions about their smart devices or when they go through contract procedures. The server provides appropriate answers to the user's questions and guides them through the contract procedures.

[0143] A means of accumulating and analyzing customer service data

[0144] The server collects customer service data from interactions between the AI ​​crew and the user, stores it in a database, and analyzes it, allowing the server to understand the user's preferences and behavioral patterns and provide more personalized services.

[0145] A way to recommend products based on user preferences

[0146] The server analyzes the customer service data and recommends appropriate products based on the user's preferences, allowing users to easily find products that match their tastes.

[0147] Ways to help users complete the purchase

[0148] When a user purchases a product, the AI ​​crew will support the purchase process. The server will confirm the user's purchase intention and guide them through the necessary procedures.

[0149] 3. Specific Examples

[0150] The user puts on the smart glasses and talks to the AI ​​crew while walking around the store. The AI ​​crew recommends products based on the user's preferences, and when the user says, "I would like to purchase this product," the AI ​​crew completes the purchase procedure via smartphone.

[0151] 4. Examples of prompts

[0152] Enter the user's preferred characteristics:

[0153] Face Shape:Round face

[0154] Hair color: Black

[0155] Tone of voice: Calm voice

[0156] Generate your AI crew based on these characteristics.

[0157] In this way, a system can be created that allows users to generate AI crew members based on their preferences, improving their shopping experience in physical stores.

[0158] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0159] Step 1:

[0160] The user terminal inputs the user's preferred features (e.g., face shape, hair color, tone of voice, etc.). The input data is sent to the server. The input data includes specific features such as "round face, black hair, calm voice."

[0161] Step 2:

[0162] The server uses a generative AI model (e.g. GPT-4) based on the received user's preferred features to generate the appearance and voice of the AI ​​crew member. It uses a facial recognition API (e.g. Face++) to generate a face that matches the specified features, and a speech synthesis API (e.g. Google Text-to-Speech) to generate a voice with the specified tone of voice. The appearance data and voice data of the generated AI crew member are output.

[0163] Step 3:

[0164] The server builds a conversational interface using natural language processing (NLP) to enable conversation with the generated AI crew. It receives input from the user's device (e.g., "Tell me about this product"), and the server uses NLP to generate an appropriate response and sends it to the user's device. The user's question and the AI ​​crew's response are treated as input and output.

[0165] Step 4:

[0166] When a user device makes an inquiry or performs a contract procedure related to a smart device, the server supports it through the AI ​​crew. The server receives the user's question (e.g., "What is the contract plan for this smartphone?") and provides the appropriate information. The user's question and the server's answer are treated as input and output.

[0167] Step 5:

[0168] The server accumulates and analyzes the customer service data collected through the interaction between the AI ​​crew and the user in a database. The customer service data includes the content of the user's questions, the AI ​​crew's responses, the user's behavioral patterns, etc. The accumulated data is analyzed to understand the user's preferences and behavioral patterns.

[0169] Step 6:

[0170] The server analyzes the customer service data and recommends appropriate products based on the user's preferences. The server receives input from the user's device (e.g., "What products do you recommend?"), recommends products based on the analysis results, and sends them to the user's device. The user's request and the recommended product information are treated as input and output.

[0171] Step 7:

[0172] When a user purchases a product, the server supports the purchase procedure through the AI ​​crew. The server receives input from the user's device (e.g., "I want to purchase this product") and guides the user through the purchase procedure. The user's purchase intention and the procedure guidance from the server are treated as input and output.

[0173] In this way, a system can be created that allows users to generate AI crew members based on their preferences, improving their shopping experience in physical stores.

[0174] Example 2

[0175] Next, a second embodiment of the second embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0176] In conventional AI crew systems, it was difficult to effectively collect and analyze conversation data with users and generate optimal responses. In addition, there was a lack of means to generate AI crews that matched the user's preferences, or to create the strongest AI crews through the accumulation and analysis of customer service data. This resulted in a decrease in the quality of the user experience and a decrease in the efficiency of contract procedures.

[0177] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0178] In this invention, the server includes a means for generating an AI crew member according to the user's preferences, a means for enabling a conversation with the generated AI crew member, a means for the AI ​​crew member to carry out consultations and contract procedures related to communication devices, a means for collecting customer service data of the AI ​​crew member, a means for storing the collected data in a database, a means for analyzing the stored data using natural language processing technology, a means for feeding back the analysis results to the generation AI model, a means for the generation AI model to generate an optimal response based on a prompt sentence, and a means for providing the generated response to the user. This makes it possible to effectively collect and analyze conversation data with the user and generate an optimal response. In addition, the strongest AI crew member can be created through the accumulation and analysis of customer service data, improving the quality of the user experience and the efficiency of contract procedures.

[0179] "User" refers to any individual or legal entity that uses the System.

[0180] "Artificial Intelligence Crew" refers to an artificial intelligence program designed to converse with users and process contracts.

[0181] "Means for generating" refers to methods and techniques for creating an artificial intelligence crew based on the user's preferences.

[0182] "Conversational enablement" refers to the methods and technologies that allow the user and the AI ​​crew to communicate with each other.

[0183] "Means of consultation and contract procedures related to telecommunications devices" refers to methods and technologies that allow users to ask questions about telecommunications devices or complete contract procedures through an artificial intelligence crew.

[0184] "Customer service data" refers to information collected by the AI ​​crew through conversations with users and contract procedures.

[0185] "Means of collection" refers to the methods and technologies for efficiently collecting customer service data.

[0186] "Means of storing in a database" refers to the methods and technologies for systematically storing collected data.

[0187] "Natural language processing technology" refers to technology for analyzing text data and understanding its meaning.

[0188] "Means for analysis" refers to methods and techniques for analyzing stored data and extracting useful information.

[0189] A "generative AI model" refers to an artificial intelligence model that generates optimal responses based on feedback.

[0190] A "prompt sentence" refers to an instruction sentence input to a generative AI model.

[0191] "Means for generating an optimal response" refers to the methods or techniques that a generative AI model uses to create an optimal reply to a user based on a prompt.

[0192] "Means of providing" refers to the method or technology used to communicate the generated response to the user.

[0193] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0194] This invention is a system that generates an AI crew member according to the user's preferences, and accumulates and analyzes data obtained through conversations with the user and contract procedures. A specific embodiment of this system will be described below.

[0195] System Configuration

[0196] This system mainly consists of three elements: a server, a terminal, and a user.

[0197] 1. Server

[0198] The server has a means for generating an AI crew according to the user's preferences. The generated AI crew can converse with the user.

[0199] The server has a means for handling consultations and contract procedures related to communication devices using an artificial intelligence crew.

[0200] The server has the means to collect customer service data from the AI ​​crew and store it in a database using a database management system such as MySQL or PostgreSQL.

[0201] The server has the means to analyze the stored data using natural language processing techniques (e.g., Python's NLTK or spaCy).

[0202] The server has the means to feed the analysis results back to a generative AI model (e.g., OpenAI's GPT-4).

[0203] The server has the means for the generative AI model to generate an optimal response based on the prompt text.

[0204] 2. Terminal

[0205] The device has the means to collect conversation data with the user, which is converted to text using voice recognition software (e.g., Google Speech-to-Text API).

[0206] The terminal has a means for providing the generated response to the user.

[0207] 3. Users

[0208] The user uses the device to initiate a conversation with the AI ​​crew, for example saying, "I'd like to sign up for a new mobile phone contract."

[0209] Examples

[0210] Consider a case where a user says, "I want to get a new mobile phone contract." The device collects this speech and converts it to text using the Google Speech-to-Text API. The converted text data is sent to the server and stored in a MySQL database. The server tokenizes the stored text data using NLTK and analyzes the user's intent. The analysis results are fed back to the generative AI model, which generates the prompt sentence.

[0211] Examples of prompt statements

[0212] If a user says "I want to get a new mobile phone contract", generate the optimal response, taking into account that the user sentiment is positive.

[0213] Based on this prompt, the generative AI model generates a response: "Let me help you with your new mobile phone contract. What plan would you like?" The device can then provide this response to the user and continue the next conversation.

[0214] In this way, the server can accumulate and analyze the customer service data of the AI ​​crew to create the strongest AI crew, which will improve the quality of the user experience and the efficiency of the contract procedure.

[0215] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0216] Program processing flow

[0217] Step 1: User initiates a conversation with the AI ​​crew member

[0218] The user uses the terminal to start a conversation with the AI ​​crew. For example, the user might say, "I'd like to sign up for a new mobile phone contract."

[0219] Input: User's voice input

[0220] Output: Audio data

[0221] Step 2: The device collects conversation data

[0222] The device collects conversation data with the user in real time. The voice data is converted into text using voice recognition software (e.g., Google Speech-to-Text API).

[0223] Input: Audio data

[0224] Output: Text data

[0225] Step 3: The server stores the collected data in a database

[0226] The terminal sends the collected text data to the server. The server stores this data in a database (e.g., MySQL, PostgreSQL). The stored data includes the content of the conversation, the date and time, the user ID, etc.

[0227] Input: Text data, user ID, date and time

[0228] Output: Data stored in the database

[0229] Step 4: The server analyzes the stored data

[0230] The server analyzes the stored data using natural language processing techniques (e.g., Python's NLTK or spaCy). Specifically, it performs tokenization, part-of-speech tagging, sentiment analysis, etc. on the text data.

[0231] Input: Text data stored in a database

[0232] Output: Analysis results (user intent, emotions, etc.)

[0233] Step 5: The server feeds the analysis results back to the generative AI model

[0234] The server feeds the analysis results back to the generative AI model (e.g., OpenAI's GPT-4), which includes the user's intentions, emotions, and contract tendencies.

[0235] Input: Analysis results

[0236] Output: Feedback to the generative AI model

[0237] Step 6: The generative AI model generates the optimal response based on the prompt.

[0238] The generative AI model generates a prompt sentence based on the feedback and creates an optimal response. For example, if the prompt sentence is "If the user says, 'I want to sign a new mobile phone contract,' generate the optimal response. Please consider that the user's emotion is positive," the generative AI model generates the response "I'll help you with your new mobile phone contract. What kind of plan are you looking for?"

[0239] Input: prompt, feedback

[0240] Output: Best response

[0241] Step 7: The terminal provides the generated response to the user.

[0242] The terminal provides the user with the response generated by the generative AI model. The user can then receive the response from the AI ​​crew through the terminal and continue the next conversation.

[0243] Input: Best response

[0244] Output: Providing a response to the user

[0245] (Application example 2)

[0246] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0247] Conventional AI crew systems had issues with the difficulty of providing services tailored to the user's preferences and the inability to respond to customers in real time. Furthermore, the accumulation and analysis of customer service data was insufficient, making it difficult to propose optimal customer service methods.

[0248] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means. In this invention, the server includes a means for generating an AI crew member according to the user's preferences, a means for enabling a conversation with the generated AI crew member, a means for the AI ​​crew member to handle consultations and contract procedures related to smart devices, a means for accumulating and analyzing customer service data of the AI ​​crew member, a means for collecting conversations with customers in real time using smart glasses and displaying the analysis results, and a means for proposing an optimal customer service method using the generated AI model. This makes it possible to provide optimal customer service in real time according to the user's preferences.

[0249] "User" refers to any individual or legal entity that uses the System.

[0250] "AI Crew" refers to a virtual customer service representative who uses artificial intelligence to converse with users and handle contract procedures.

[0251] "Means for generating" refers to a method or apparatus for creating an AI crew based on user preferences.

[0252] "Means enabling conversation" refers to a method or device that allows the user and the AI ​​crew to communicate through voice or text.

[0253] "Smart devices" refers to electronic devices with Internet connectivity, such as smartphones and smart glasses.

[0254] "Means for consultation and contract procedures" refers to a method or device that allows a user to ask questions or make contracts regarding a smart device through an AI crew.

[0255] "Customer service data" refers to information collected by the AI ​​crew through their interactions with users.

[0256] "Means of storing and analyzing" refers to methods and devices for storing and analyzing collected customer service data.

[0257] "Smart glasses" refers to electronic glasses-type devices equipped with a display, camera, microphone, and Internet connectivity.

[0258] "Means for collecting data in real time and displaying analytical results" refers to a method or device for instantly recording conversations with customers, analyzing the data, and displaying the results.

[0259] A "generative AI model" refers to a model that uses artificial intelligence to suggest the optimal way to serve customers.

[0260] "Means for proposing the optimal customer service method" refers to a method or device for using a generative AI model to present the most appropriate customer service method to a user.

[0261] The system for implementing this invention generates an AI crew member according to the user's preferences and enables conversation with the generated AI crew member. The system also uses the AI ​​crew member to handle smart device-related consultations and contract procedures, and accumulates and analyzes customer service data of the AI ​​crew member. Furthermore, the system uses smart glasses to collect conversations with customers in real time and displays the analysis results. The system can use the generated AI model to suggest optimal customer service methods.

[0262] System Configuration

[0263] The system uses the following hardware and software:

[0264] Hardware: smart glasses, microphone, server

[0265] Software: Python, SpeechRecognition library, OpenAI API

[0266] Processing flow

[0267] 1. Speech Recognition: The microphone on the smart glasses is used to collect the customer's speech as voice data. The collected voice data is converted to text data using the SpeechRecognition library.

[0268] 2. Data Analysis: The converted text data is sent to a server and analyzed using OpenAI's generative AI model. The analysis results suggest the optimal way to serve the customer.

[0269] 3. Display of results: The analysis results are displayed in real time on the smart glasses display, allowing store clerks to provide optimal customer service.

[0270] Examples

[0271] For example, if a customer says, "I'd like to know more about this product," the generative AI model can generate suggestions such as, "This product uses the latest technology and is particularly durable. Plus, it's currently on special discount."

[0272] Examples of prompt statements

[0273] Customer conversation: I want to know more about this product

[0274] Please suggest the best way to serve customers.

[0275] In this way, it is possible to provide optimal customer service in real time according to the user's preferences.

[0276] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0277] Step 1:

[0278] A user puts on the smart glasses and starts a conversation with a customer. A microphone installed in the smart glasses collects what the customer says as voice data. The input is the customer's voice, and the output is voice data.

[0279] Step 2:

[0280] The voice data collected by the device (smart glasses) is converted to text data using the SpeechRecognition library. The input is voice data, and the output is text data. This conversion process allows the voice data to be treated as text information.

[0281] Step 3:

[0282] The terminal sends the converted text data to the server. The input is the text data, and the output is the data sent to the server. The server prepares the received text data for analysis.

[0283] Step 4:

[0284] The server inputs the received text data into OpenAI's generative AI model to generate a prompt that suggests the optimal way to serve the customer. The input is text data, and the output is the generated prompt. The generative AI model analyzes the text data and generates an appropriate response.

[0285] Step 5:

[0286] The server analyzes the generated prompt text and generates a text that suggests the best way to serve the customer. The input is the prompt text, and the output is the suggested text. This suggested text includes a specific way to serve the customer.

[0287] Step 6:

[0288] The server sends the generated suggested text to the terminal (smart glasses). The input is the suggested text, and the output is data transmission to the terminal. The terminal prepares the received suggested text for display.

[0289] Step 7:

[0290] The terminal displays the proposed text received on the display of the smart glasses in real time. The input is the proposed text, and the output is the display on the display. This allows the user to provide optimal customer service to the customer.

[0291] Example 3

[0292] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0293] Conventional systems using AI characters had difficulty responding to individual user preferences and were unable to generate effective sales pitches. In addition, there was a lack of means to utilize facial feature data and past reaction data provided by users, making it impossible to provide users with AI characters that were optimal for them. This resulted in a decrease in user satisfaction and a failure to improve the efficiency of contract procedures.

[0294] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0295] In this invention, the server includes a means for generating an AI character according to the user's preferences, a means for enabling a conversation with the generated AI character, a means for carrying out consultations and contract procedures related to communication devices using the AI ​​character, a means for accumulating and analyzing customer service data of the AI ​​character, a means for analyzing facial feature data provided by the user, a means for collecting past reaction data of users, a means for generating the most effective sales pitch, and a means for combining facial features and sales pitches. This makes it possible to provide an AI character that corresponds to the individual preferences of the user and generate effective sales pitches.

[0296] "User" refers to any individual or legal entity that uses the System.

[0297] An "artificial intelligence character" is a virtual being that is generated based on the user's preferences and is used for conversation, consultation, and contract procedures.

[0298] "Communication devices" refers to electronic devices used for communication, such as smartphones, tablets, and personal computers.

[0299] "Customer service data" refers to data generated by an AI character during conversations, consultations, and contract procedures with users.

[0300] "Facial Feature Data" means data about facial features, such as the eyes, nose, and mouth, extracted from an image or information provided by a user.

[0301] "Response Data" means data regarding positive or negative responses a User has previously made.

[0302] "Sales pitch" refers to the way of speaking and the content of a sales pitch used to effectively explain a product or service to a user and encourage them to sign a contract or make a purchase.

[0303] A "generative AI model" refers to an algorithm or system that uses artificial intelligence technology to generate new data or content.

[0304] A "prompt sentence" refers to a sentence of instructions or questions that is input to a generative AI model.

[0305] The present invention is a system for generating an AI character according to the user's preferences and for carrying out consultations and contract procedures related to communication devices. A specific embodiment of this system will be described below.

[0306] First, a user accesses the system and uploads an image with the facial features they prefer. The image provided by the user is sent to the system using a device such as a smartphone or PC.

[0307] The server then receives the uploaded image and uses a facial recognition API (e.g. facial recognition software) to analyze the facial features, specifically extracting features such as eye shape, nose height, mouth size, etc. The results of this analysis are stored as facial feature data.

[0308] The server then collects past reaction data of the user, which is data on positive or negative reactions shown by the user in the past, and is obtained from chat history, survey results, etc.

[0309] Based on the collected response data, the server uses a natural language processing (NLP) model (e.g., a generative AI model) to generate the most effective sales pitch for the user. For example, if the user is price-sensitive, the server generates a pitch that emphasizes price information.

[0310] Next, the server uses a generative AI model (e.g., image generation software) to generate an artificial intelligence character that combines the analyzed facial features with the generated sales pitch. Specifically, the server sets the character with the facial features the user prefers to speak the generated sales pitch.

[0311] Finally, the user can start to interact with the AI ​​character. For example, if the user asks, "Tell me about the new smartphone plan," the AI ​​character will respond, "This plan has a low monthly fee and a large data capacity, so it's a good deal."

[0312] As a concrete example, if a user is considering a new smartphone contract, the following prompt could be used:

[0313] "Generate an AI character with the facial features that the user prefers and pair it with the most effective sales pitch. The user is considering a new smartphone contract."

[0314] In this way, the user can consult about communication devices or carry out contract procedures while enjoying a conversation with the AI ​​character of his / her choice. The flow of the specific process in the third embodiment will be described with reference to FIG.

[0315] Step 1:

[0316] A user provides facial feature data.

[0317] A user uses a smartphone or a PC to access the system's interface and upload an image with facial features that they like. The input is image data provided by the user, and the output is image data sent to the server. A specific operation is when a user says, "I like this celebrity's face," and uploads the image.

[0318] Step 2:

[0319] The server analyzes the facial feature data.

[0320] The server receives the uploaded image and analyzes the facial features using a facial recognition API (e.g., facial recognition software). The input is the image data provided by the user, and the output is the analyzed facial feature data. Specifically, the server extracts features such as "round eyes, high nose, small mouth."

[0321] Step 3:

[0322] The server collects the user's past response data.

[0323] The server collects users' past chat histories and survey results from a database. The input is the users' past reaction data, and the output is the collected reaction data. In concrete terms, the server collects data such as "users responded favorably to information about prices."

[0324] Step 4:

[0325] The server generates the most effective sales pitch.

[0326] The server generates sales pitches using a natural language processing (NLP) model (e.g., a generative AI model) based on the collected response data. The input is the collected response data, and the output is the generated sales pitch. Specifically, the server generates a pitch such as, "This plan is a good deal because it has a low monthly fee and a large data capacity."

[0327] Step 5:

[0328] The server matches the facial features with the sales pitch.

[0329] The server uses a generative AI model (e.g. image generation software) to generate an AI character that combines the analyzed facial features with the generated sales pitch. The input is the facial feature data and the sales pitch, and the output is the generated AI character. As a specific operation, the server sets it so that "a character with round eyes and a high nose speaks a speech that emphasizes the low monthly fee."

[0330] Step 6:

[0331] The user interacts with the generated artificial intelligence character.

[0332] The user starts a dialogue with the generated AI character. The input is the user's question or request, and the output is the AI ​​character's response. In concrete terms, when the user asks, "Tell me about the new smartphone plan," the AI ​​character responds, "This plan has a low monthly fee and a large data capacity, so it's good value."

[0333] (Application example 3)

[0334] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0335] Conventional online shopping systems have problems in that it is difficult for users to find products that suit their tastes and the purchasing process is complicated. Furthermore, the interaction with users is limited, making it difficult to respond to individual needs. For this reason, a new system is required to improve the user experience and realize an efficient purchasing process.

[0336] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0337] In this invention, the server includes means for generating an AI crew member according to the user's preferences, means for enabling a conversation with the generated AI crew member, means for the AI ​​crew member to handle smartphone-related consultations and contract procedures, means for accumulating and analyzing customer service data of the AI ​​crew member, means for proposing products and supporting purchase procedures according to the user's preferences, means for generating a face of the AI ​​crew member based on the user's preferred facial features, means for generating an optimal sales talk based on the sales talk style, and means for converting the generated sales talk into voice. This enables the user to efficiently select products and complete purchase procedures while enjoying a conversation with the AI ​​crew member of their choice.

[0338] "Means for generating an AI crew member based on user preferences" refers to technology that generates an individually customized AI crew member based on the user's input of preferred facial features, tone of voice, and sales talk style.

[0339] "Means for enabling conversation with the generated AI crew" refers to an interface or communication technology that allows a user to have a natural conversation with the generated AI crew.

[0340] "A means for smartphone-related consultations and contract procedures to be carried out by an AI crew" is a function that enables users to ask questions about smartphones and complete contract procedures through an AI crew.

[0341] "Means of accumulating and analyzing customer service data from AI crews" refers to systems and technologies that store and later analyze data obtained by AI crews through their interactions with users.

[0342] "Means of suggesting products tailored to the user's preferences and supporting the purchasing process" refers to a function that suggests optimal products based on the user's preferences and past purchasing history and assists in the purchasing process.

[0343] "Means for generating an AI crew member's face based on a user's preferred facial features" refers to technology for generating an AI crew member's face based on facial features specified by the user.

[0344] The "means for generating an optimal sales talk based on the sales talk style" is a technology for generating an optimal sales talk based on the user's preferences and an effective sales talk style.

[0345] The "means for converting the generated sales talk into speech" refers to a technology for converting the generated sales talk from text to speech.

[0346] The system for implementing this invention generates an AI crew member according to the user's preferences, and supports product suggestions and purchase procedures through conversations with the generated AI crew member. A specific embodiment of this system will be described below.

[0347] Hardware and Software Used

[0348] Hardware: Smartphone

[0349] software:

[0350] Generative AI models (e.g. OpenAI GPT-4)

[0351] Facial feature generation models (e.g. DeepFaceLab)

[0352] A text-to-speech engine (e.g. Google Text-to-Speech)

[0353] A database (e.g. Firebase)

[0354] System Configuration

[0355] 1. COLLECTING USER INFORMATION:

[0356] When a user launches the app for the first time, they input their preferred facial features, tone of voice, and sales pitch style.

[0357] This information is stored in the Firebase database.

[0358] 2. AI Crew Generation:

[0359] DeepFaceLab is used to generate an AI crew member's face based on the user's preferred facial features.

[0360] Based on your sales pitch style, OpenAI GPT-4 is used to generate the optimal sales pitch.

[0361] Use Google Text-to-Speech to convert the generated sales pitch into audio.

[0362] 3. Providing a conversation interface:

[0363] When a user searches for a product using the app, the AI ​​crew will suggest products that match the user's preferences.

[0364] When a user asks a question or asks for advice, the AI ​​crew will provide appropriate answers and suggestions.

[0365] 4. Purchasing assistance:

[0366] Once a user decides to make a purchase, an AI crew member will guide them through the purchase process.

[0367] Enter the necessary information and we will support you until the purchase is complete.

[0368] Examples

[0369] When a user types, "I'm looking for a new smartphone," the AI ​​crew will suggest, "Hello! We've found the perfect smartphone for you. How about this model? It features the latest camera features and a long-lasting battery," and explain the details of the product.

[0370] Examples of prompt statements

[0371] User: I'm looking for a new smartphone.

[0372] AI Crew: Hello! We've found the perfect smartphone for you. How about this model? It features the latest camera features and a long-lasting battery.

[0373] In this way, users can efficiently select products and complete purchase procedures while enjoying conversations with their preferred AI crew members. This system improves the user experience and makes online shopping more comfortable and convenient.

[0374] The flow of the specific process in the application example 3 will be described with reference to FIG.

[0375] Step 1:

[0376] Collection of User Information

[0377] Input: When users first launch the app, they input their preferred facial features, tone of voice, and sales pitch style.

[0378] Processing: The device collects the information entered by the user and stores it in the Firebase database.

[0379] Output: User preferences stored in Firebase database.

[0380] Step 2:

[0381] AI Crew Generation

[0382] Input: User preferences stored in your Firebase database.

[0383] Processing: The server uses DeepFaceLab to generate an AI crew member's face based on the user's preferred facial features, then uses OpenAI GPT-4 to generate the optimal sales pitch based on the sales pitch style, and finally converts the generated sales pitch into audio using Google Text-to-Speech.

[0384] Output: An AI crew member with a face and sales pitch tailored to the user's preferences is generated.

[0385] Step 3:

[0386] Providing a conversational interface

[0387] Input: A user uses the app to search for a product.

[0388] Processing: The device receives the user's search query and sends it to the server, which then uses the generated AI crew to suggest products that match the user's preferences.

[0389] Output: The AI ​​crew will provide product suggestions to the user.

[0390] Step 4:

[0391] Responding to user questions and inquiries

[0392] Input: The user types a question or request into the AI ​​crew.

[0393] Processing: The device receives the user's question or inquiry and sends it to the server, which uses OpenAI GPT-4 to generate appropriate answers or suggestions and converts them into audio using Google Text-to-Speech.

[0394] Output: The AI ​​crew will provide appropriate answers and suggestions to the user.

[0395] Step 5:

[0396] Purchase procedure support

[0397] Input: The user makes a purchase decision.

[0398] Processing: The device receives the user's purchase decision and sends it to the server, which then guides the AI ​​crew through the purchase process and asks them to enter the necessary information.

[0399] Output: The user completes the purchase.

[0400] In this way, users can efficiently select products and complete the purchase process while enjoying a conversation with their preferred AI crew.

[0401] Furthermore, an emotion engine that estimates the emotion of the user may be combined. That is, the identification processing unit 290 may estimate the emotion of the user using the emotion identification model 59, and perform identification processing using the emotion of the user.

[0402] "Example 1"

[0403] As one embodiment of the present invention, there is a system including an emotion engine in which an AI crew recognizes the emotions of a user. In this system, the AI ​​crew reads the emotions of a user through conversation with the user. For example, if the user feels angry, the AI ​​crew sends that information to the emotion engine. The emotion engine analyzes the information and instructs the AI ​​crew to respond to calm the user.

[0404] "Example 2"

[0405] Furthermore, there is also a system including a means for the emotion engine to adjust the response of the AI ​​crew member according to the user's emotions. In this system, the emotion engine grasps changes in the user's emotions in real time and adjusts the response of the AI ​​crew member according to the emotions. For example, if the user feels happy, the emotion engine instructs the AI ​​crew member to respond in a way that will make the user even happier.

[0406] "Example 3"

[0407] There is also a system that includes a means for the emotion engine to accumulate and analyze user emotion data and reflect the results in improving the AI ​​crew. In this system, the emotion engine accumulates user emotion data and analyzes the data. The analysis results are used to improve the AI ​​crew. For example, if information is obtained that a particular user is likely to become angry about a particular topic, the information is used to improve the AI ​​crew's response, so that the AI ​​crew will respond in a way that does not make the user angry.

[0408] The process flow of each embodiment will be described below.

[0409] "Example 1"

[0410] Step 1: A conversation is initiated between the user and the AI ​​crew member.

[0411] Step 2: The AI ​​crew reads the user's emotions through conversation.

[0412] Step 3: The AI ​​Crew sends the user's emotions to the emotion engine.

[0413] Step 4: The emotion engine analyzes the transmitted information.

[0414] Step 5: Based on the analysis results, the emotion engine instructs the AI ​​crew on how to calm the user down.

[0415] "Example 2"

[0416] Step 1: A conversation is initiated between the user and the AI ​​crew member.

[0417] Step 2: The emotion engine listens to the conversation in real time and reads changes in the user's emotions.

[0418] Step 3: The emotion engine adjusts the AI ​​crew's response based on the emotions it reads.

[0419] Step 4: For example, if the user feels happy, the emotion engine will instruct the AI ​​crew on how to make the user even happier.

[0420] "Example 3"

[0421] Step 1: A conversation is initiated between the user and the AI ​​crew member.

[0422] Step 2: The emotion engine reads the user's emotions through conversation and accumulates the data.

[0423] Step 3: The emotion engine analyzes the accumulated emotion data.

[0424] Step 4: The analysis results are used to improve the AI ​​crew.

[0425] Step 5: For example, if information is obtained that a particular user is prone to becoming angry about a particular topic, this information can be used to improve the AI ​​crew's response so that the user does not become angry.

[0426] Example 1

[0427] Next, a description will be given of Example 1 of the embodiment 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal".

[0428] Conventional AI assistant systems have the problem that it is difficult to generate an assistant that matches the individual preferences of the user, and they cannot recognize the user's emotions and respond appropriately. Furthermore, there is a lack of means to create an optimal AI assistant through the accumulation and analysis of customer service data.

[0429] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0430] In this invention, the server includes a means for generating an AI assistant according to the user's preferences, a means for enabling a conversation with the generated AI assistant, a means for carrying out consultations and contract procedures related to communication devices using the AI ​​assistant, a means for accumulating and analyzing customer service data of the AI ​​assistant, a means including an emotion engine for recognizing the user's emotions, and a means for providing an appropriate response to the user based on the analysis results of the emotion engine. This makes it possible to generate an AI assistant according to the individual preferences of the user and to provide an appropriate response according to the user's emotions.

[0431] "User" refers to any individual or legal entity that uses the System.

[0432] An "artificial intelligence assistant" is a digital agent that is generated based on the user's preferences and can converse with the user and carry out various procedures.

[0433] "Means for generating" refers to a combination of software and hardware for creating an artificial intelligence assistant based on user input.

[0434] "Conversational enablement" refers to technology that allows an artificial intelligence assistant to communicate with the user in natural language.

[0435] "Means for consultations and contract procedures related to telecommunications devices" refers to functions that enable an artificial intelligence assistant to answer users' questions about telecommunications devices and support contract procedures.

[0436] "Means of accumulating and analyzing customer service data" refers to technology that enables an artificial intelligence assistant to record interactions with users and analyze that data.

[0437] "Emotion engine" refers to a combination of software and hardware for recognizing a user's emotions and analyzing that information.

[0438] "Means of taking appropriate action based on the analysis results" refers to the function that enables the artificial intelligence assistant to take appropriate action toward the user based on the analysis results of the emotion engine.

[0439] An "optimal artificial intelligence assistant" refers to an artificial intelligence assistant that is best suited to a user's preferences and needs through the accumulation and analysis of customer service data.

[0440] "Appearance" refers to the visual characteristics and design of the artificial intelligence assistant.

[0441] "Conversational capabilities" refers to the ability of an artificial intelligence assistant to effectively communicate with users in natural language.

[0442] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0443] The present invention is a system that generates an artificial intelligence assistant according to the user's preferences, and that converses with the user, provides advice on communication devices, and handles contract procedures. A specific embodiment of this system will be described below.

[0444] System Configuration

[0445] The system consists of a device used by the user, a server that processes the data, a generative AI model, an emotion engine, and software to link these together.

[0446] Hardware and Software Used

[0447] Device: The device used by the user, such as a smartphone or computer.

[0448] Server: A computer system for processing data and running generative AI models.

[0449] Generative AI models: Models for generating artificial intelligence assistants based on user input (e.g., OpenAI's GPT-4).

[0450] Emotion engine: Software for recognising and analysing user emotions (e.g. Affectiva).

[0451] Natural language processing engine: An engine that allows an artificial intelligence assistant to converse with users (e.g. Google Dialogflow).

[0452] Program Processing

[0453] A user inputs his / her preferred characteristics (e.g., face shape, hair color, tone of voice, etc.) using a dedicated application or web interface on a smartphone or PC. For example, a user inputs "hair color is blue, voice tone is calm."

[0454] The device sends the input data to a server, which uses a generative AI model to generate an artificial intelligence assistant based on the user's input. The generation process creates a digital avatar and voice profile that reflects the user's preferred characteristics.

[0455] The generated AI assistant is equipped with a natural language processing engine to enable conversation with the user. In addition, the AI ​​assistant can recognize the user's emotions using an emotion engine.

[0456] Examples

[0457] As a concrete example, consider a scenario in which a user opens an app on their smartphone and enters the following characteristics:

[0458] Example user input:

[0459] Face Shape: Round Face

[0460] Hair Color: Blue

[0461] Tone of voice: Calm

[0462] The device sends this information to the server, which then uses a generative AI model to generate a prompt like this:

[0463] Example prompt for a generative AI model:

[0464] A user wants to create an artificial intelligence assistant with the following characteristics:

[0465] Face Shape: Round Face

[0466] Hair Color: Blue

[0467] Tone of voice: Calm

[0468] Based on this, generate an artificial intelligence assistant that can hold a conversation with the user.

[0469] The server inputs this prompt into a generative AI model to generate an AI assistant that meets the user's needs. The AI ​​assistant can then consult with the user about telecommunications devices and handle contract procedures through conversations with the user. If the user feels angry, the AI ​​assistant sends that information to an emotion engine, which then uses the analysis results to provide instructions on how to calm the user down.

[0470] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0471] Step 1:

[0472] User enters characteristics

[0473] A user inputs his / her preferred features (e.g., face shape, hair color, tone of voice, etc.) using a dedicated application or web interface on a smartphone or PC. The input data is structured in JSON format. For example, a user inputs "hair color is blue, voice tone is calm."

[0474] Step 2:

[0475] The terminal sends the input data to the server

[0476] The device transmits the user-entered feature data in real time to the server, which receives the data structured in JSON format. The input data includes the user's preference details.

[0477] Step 3:

[0478] The server sends a prompt to the generative AI model.

[0479] The server generates a prompt sentence based on the received feature data. The generated prompt sentence specifically describes the features desired by the user. For example, the following prompt sentence is generated:

[0480] A user wants to create an artificial intelligence assistant with the following characteristics:

[0481] Face Shape: Round Face

[0482] Hair Color: Blue

[0483] Tone of voice: Calm

[0484] Based on this, generate an artificial intelligence assistant that can hold a conversation with the user.

[0485] The server sends this prompt to the generative AI model.

[0486] Step 4:

[0487] A generative AI model generates an AI crew

[0488] The generative AI model generates a personalized AI assistant based on the prompt text. In the process, a digital avatar and voice profile are created. The generated AI assistant has the user's preferred characteristics.

[0489] Step 5:

[0490] The server sends the generated AI crew to the device.

[0491] The server transmits the generated AI assistant data to the terminal. This data includes a 3D model of the AI ​​assistant and audio files. The terminal receives this data.

[0492] Step 6:

[0493] The device displays the AI ​​crew and starts a conversation with the user.

[0494] The device displays the AI ​​assistant on the screen based on the received AI assistant data. The user can start a conversation with the AI ​​assistant. For example, the user asks, "What's the weather like today?"

[0495] Step 7:

[0496] AI Crew uses emotion engine to recognize user emotions

[0497] The AI ​​assistant uses the emotion engine to recognize the user's emotions through conversation with the user. For example, if the user is angry, it sends that information to the emotion engine. The emotion engine analyzes the user's tone of voice and facial expressions.

[0498] Step 8:

[0499] The emotion engine sends the analysis results to the AI ​​crew.

[0500] The emotion engine analyzes the received emotion data and sends the results to the AI ​​assistant. The analysis results contain detailed information about the user's emotional state. For example, the result "The user is angry" may be sent.

[0501] Step 9:

[0502] AI crew responds appropriately to users

[0503] The AI ​​assistant responds appropriately to the user based on the analysis results of the emotion engine. For example, if the user is angry, the AI ​​assistant will say to the user, "Please calm down. Is there anything I can help you with?"

[0504] (Application example 1)

[0505] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0506] Conventional customer service systems have difficulty recognizing customer emotions in real time and responding appropriately. It is also difficult to provide personalized responses that match the customer's preferences. This has made it difficult to improve customer satisfaction.

[0507] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0508] In this invention, the server includes a means for generating an AI crew member according to the user's preferences, a means for enabling a conversation with the generated AI crew member, a means for the AI ​​crew member to handle consultations and contract procedures related to smart devices, a means for accumulating and analyzing customer service data of the AI ​​crew member, a means for recognizing the user's emotions and generating an appropriate response, and a means for displaying the generated response. This makes it possible to recognize the customer's emotions in real time and provide personalized responses.

[0509] "User" means an individual or legal entity that uses the System.

[0510] "Preferences" are personal tastes or preferences that a user has for particular features or attributes.

[0511] "AI Crew" is a virtual assistant generated using artificial intelligence that interacts with users and provides services.

[0512] A "means for generating" is a method or apparatus for creating an AI crew member based on user input.

[0513] A "conversational means" is a method or device that allows the user and the AI ​​crew to communicate through voice or text.

[0514] A "smart device" is an electronic device with Internet connectivity, such as a smartphone or smart glasses.

[0515] "Means for consultation and contract procedures" refers to a method or device that allows a user to ask questions about a smart device or complete contract procedures through an AI crew.

[0516] "Customer service data" refers to information collected by the AI ​​crew through conversations with users.

[0517] "Means of storing and analyzing" refers to methods and devices for storing and analyzing collected customer service data.

[0518] "Means for recognizing emotions" refers to a method or device for determining emotions from a user's facial expressions, tone of voice, etc.

[0519] A "means for generating an appropriate response" is a method or apparatus for determining an optimal response or action for a user based on a recognized emotion.

[0520] A "means for displaying" is a method or device for visually presenting the generated correspondence to a user.

[0521] The system for implementing this invention generates an AI crew member according to the user's preferences, recognizes the user's emotions through conversation with the generated AI crew member, and responds appropriately. A specific embodiment of this system will be described below.

[0522] First, the server receives information about the user's preferences and generates an AI crew member based on this. The user inputs preferences such as face shape, hair color, and tone of voice through a smart device. The server analyzes this information and uses a generative AI model to create an AI crew member that matches the user's preferences.

[0523] Next, the generated AI crew can converse with the user. The user can communicate with the AI ​​crew by voice or text through a smart device. The content of the conversation is analyzed in real time and the user's emotions are recognized. The EmotionRecognition library is used for emotion recognition.

[0524] In addition, the server generates an appropriate response based on the user's emotions. For example, if the user is angry, the AI ​​crew will generate a response such as "Sir, please let us know if there is anything we can help you with." This response is determined using a generative AI model.

[0525] The generated response is displayed on the display of the smart device, allowing the user to receive appropriate responses from the AI ​​crew. Devices such as smart glasses and smartphones are used for display.

[0526] As a concrete example, the following prompt sentence can be input into a generative AI model to generate an appropriate response:

[0527] "If the customer emotion is identified as 'anger', generate an appropriate response."

[0528] This system will be able to recognize user emotions in real time and provide personalized responses, which is expected to improve customer satisfaction.

[0529] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0530] Step 1:

[0531] Users use their smart devices to input preferences such as face shape, hair color, and tone of voice.

[0532] Input: Information about the user's preferences (face shape, hair color, tone of voice, etc.)

[0533] Output: User preference data

[0534] Specific operations: The user inputs preferred features into the application interface via a smartphone or smart glasses.

[0535] Step 2:

[0536] The server receives the user's preference data and generates an AI crew using a generative AI model.

[0537] Input: User preference data

[0538] Output: Generated AI crew

[0539] Specific operation: The server analyzes the received preference data and inputs it into a generative AI model to create an AI crew that matches the user's preferences.

[0540] Step 3:

[0541] The generated AI crew will begin a conversation with the user.

[0542] Input: Conversational data from the user (voice or text)

[0543] Output: Response data from AI crew

[0544] Specific operation: The user communicates with the AI ​​crew via voice or text through a smart device. The AI ​​crew responds.

[0545] Step 4:

[0546] The server analyzes the conversation data in real time and recognizes the user's emotions using the EmotionRecognition library.

[0547] Input: Conversation data from the user

[0548] Output: User emotion data

[0549] Specific operation: The server inputs the conversation data into the EmotionRecognition library and determines the user's emotions.

[0550] Step 5:

[0551] The server uses a generative AI model to generate an appropriate response based on the user's emotional data.

[0552] Input: User emotion data

[0553] Output: Appropriate corresponding data

[0554] Specific operation: The server analyzes the emotion data and inputs a prompt sentence into the generative AI model to generate an appropriate response. For example, a prompt sentence such as "If the customer's emotion is recognized as 'anger,' please generate an appropriate response" can be used.

[0555] Step 6:

[0556] The generated response is displayed on the smart device display.

[0557] Input: Appropriate corresponding data

[0558] Output: The corresponding message that is displayed to the user.

[0559] Specific operation: The server sends the generated response data to the smart device and displays it on the display, allowing the user to visually confirm the appropriate response from the AI ​​crew.

[0560] Example 2

[0561] Next, a second embodiment of the second embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0562] Conventional AI assistant systems had the problem of not responding adequately to the user's emotions, which did not improve the user experience. In addition, the accumulation and analysis of customer service data was insufficient, making it difficult to create an optimal AI assistant.

[0563] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for generating an AI assistant according to the user's preferences, a means for enabling a conversation with the generated AI assistant, a means for carrying out consultations and contract procedures related to communication devices by the AI ​​assistant, a means for accumulating and analyzing customer service data of the AI ​​assistant, and a means for analyzing the user's emotions in real time and adjusting the response of the AI ​​assistant according to the emotions. This enables optimal response according to the user's emotions, improving the user experience and creating an optimal AI assistant.

[0564] "User" refers to any individual or legal entity that uses the System.

[0565] An "artificial intelligence assistant" refers to artificial intelligence generated to interact with users and handle contract procedures.

[0566] "Means for generating" refers to methods or techniques for creating an artificial intelligence assistant based on a user's preferences.

[0567] "Conversational enablement" refers to methods and technologies that allow a user to interact with an artificial intelligence assistant.

[0568] "Consultations and contract procedures related to telecommunications devices" refers to questions and contract procedures related to smartphones and other telecommunications devices.

[0569] "Means of storage" refers to the methods and technologies that an artificial intelligence assistant uses to store the data it obtains from its interactions with users.

[0570] "Means of analysis" refers to the methods and techniques used to analyze accumulated data and extract meaningful information.

[0571] "Means of analyzing emotions in real time" refers to methods and technologies for instantly determining a user's emotions from their statements and facial expressions.

[0572] "Means for tailoring responses" refers to methods or techniques for modifying the responses or behavior of an artificial intelligence assistant based on the analyzed emotions.

[0573] An "optimal artificial intelligence assistant" refers to an artificial intelligence assistant that can respond in a way that is most appropriate to the user's preferences and emotions.

[0574] A "dialogue script" refers to a set of responses and / or questions that an artificial intelligence assistant uses to interact with a user.

[0575] This invention is a system that generates an AI assistant according to the user's preferences, and communicates with the user and handles contract procedures. It also includes a function that analyzes the user's emotions in real time and adjusts the AI ​​assistant's response according to those emotions.

[0576] The server first generates an artificial intelligence assistant based on the user's preferences. A generative AI model is used for this generation. The generated artificial intelligence assistant uses natural language processing (NLP) techniques to enable conversation with the user. Specifically, it uses libraries such as Python's NLTK and spaCy.

[0577] Next, the server collects data obtained by the AI ​​assistant through conversations with the user and through contract procedures, and stores it in a database, including what the user said, the contents of the contract, time, location, etc. The accumulated data will be analyzed later.

[0578] The server uses data analysis tools to analyze the accumulated data. Specifically, it uses Python and R to analyze the data. In particular, it uses natural language processing technology to analyze the content of user comments and perform sentiment analysis.

[0579] The emotion engine analyzes the user's remarks and facial expressions to grasp changes in the user's emotions in real time. The emotion engine adjusts the AI ​​assistant's response according to different emotional states, such as when the user is happy or angry. For example, if the emotion engine determines that the user is happy, it instructs the AI ​​assistant to respond in a way that will make the user even happier. This instruction is executed by dynamically changing the AI ​​assistant's dialogue script.

[0580] Examples

[0581] Example 1: Collecting and storing conversation data with users

[0582] If a user says to an artificial intelligence assistant, "I'm so happy to have found a new job today," the server will collect this statement in real time and store it in a database as follows:

[0583] User ID: 67890

[0584] What he said: I got a new job today and I'm very happy.

[0585] Speaking time: 2023-10-01 11:00:00

[0586] Contract details: None

[0587] Example 2: Emotion engine behavior and corresponding adjustment of artificial intelligence assistant

[0588] If a user says, "I got a new job today and I'm so happy," the emotion engine analyzes the statement and determines that the user is happy. Based on this analysis, the server instructs the AI ​​assistant to respond with something like, "That's great! Tell me more about your new job."

[0589] Examples of prompt statements

[0590] Examples of prompt sentences to be input to a generative AI model include the following:

[0591] If a user says, "Today I got a new job and I'm so happy," explain how the emotion engine would adjust its response.

[0592] By feeding this prompt into the generative AI model, we can get a detailed explanation of the emotion engine's specific behavior and how to respond.

[0593] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0594] Step 1: Generate an artificial intelligence assistant based on user preferences

[0595] The server generates an artificial intelligence assistant based on the user's preferences and requests. As input, it receives data on the user's preferences and requests. It uses a generative AI model to create an artificial intelligence assistant that matches the user's preferences. As output, it obtains the generated artificial intelligence assistant. As a specific operation, an artificial intelligence assistant with an appearance and dialogue script that reflects the user's preferences is generated.

[0596] Step 2: Start a conversation with the user

[0597] The user initiates a conversation with the AI ​​assistant through the device. As input, the user's statements and questions are sent to the server through the device. The server uses natural language processing technology to analyze the user's statements and generate an appropriate response. As output, the AI ​​assistant's response is returned to the user. Specifically, Python's NLTK and spaCy libraries are used to analyze the content of the user's statements and generate an appropriate response.

[0598] Step 3: Collect and store conversation data

[0599] The server collects conversation data with the user in real time and stores it in a database. Data such as the content of the user's comments, the time of the comments, and the place where the comments were made are collected as input. The server saves this data in the database. The accumulated conversation data is obtained as output. In concrete terms, the content of the user's comments and the details of the contract are saved in the database in chronological order.

[0600] Step 4: Analyze the data

[0601] The server analyzes the accumulated conversation data. The conversation data stored in the database is used as input. The server analyzes the data using natural language processing technology to extract the user's emotions and tendencies. The analysis results are obtained as output. In concrete terms, data analysis is performed using Python and R to analyze the content of the user's comments and their emotional state.

[0602] Step 5: Sentiment analysis using the emotion engine

[0603] The server uses an emotion engine to analyze the user's emotions in real time. The user's remarks and facial expression data are used as input. The emotion engine analyzes this data and determines the user's emotional state. The user's emotional state is obtained as output. Specifically, analysis is performed to instantly determine emotions from the user's remarks and facial expressions.

[0604] Step 6: Adjusting the AI ​​assistant’s response

[0605] The server adjusts the response of the artificial intelligence assistant based on the analysis results of the emotion engine. The analysis results of the emotion engine are used as input. The server dynamically changes the dialogue script of the artificial intelligence assistant based on the analysis results. The adjusted dialogue script is obtained as output. As a specific operation, the response content of the artificial intelligence assistant is changed so that the optimal response according to the user's emotions is performed.

[0606] Step 7: Creating the perfect artificial intelligence assistant

[0607] The server creates an optimal AI assistant based on the accumulated data and analysis results. Past conversation data and analysis results are used as input. The server analyzes this data and generates an AI assistant that best suits the user's preferences and emotions. The optimal AI assistant is obtained as output. As a specific operation, an AI assistant with an appearance and dialogue script that matches the user's preferences and emotions is generated.

[0608] (Application example 2)

[0609] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0610] With conventional customer service systems, it was difficult to respond to the user's emotions, and customer service data was not sufficiently accumulated and analyzed, making it difficult to provide optimal customer service. Furthermore, customer service support in physical stores was insufficient, making it difficult to improve customer satisfaction.

[0611] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0612] In this invention, the server includes a means for generating an AI crew member according to the user's preferences, a means for enabling a conversation with the generated AI crew member, a means for the AI ​​crew member to handle consultations and contract procedures related to smart devices, a means for accumulating and analyzing customer service data of the AI ​​crew member, a means for adjusting the AI ​​crew member's response according to the user's emotions using an emotion engine, and a means for providing a smart customer service assistant to support customer service in a physical store. This makes it possible to provide optimal customer service according to the user's emotions and improve customer satisfaction in a physical store.

[0613] "Means of generating an AI crew according to the user's preferences" refers to a function that automatically creates an optimal AI crew based on the user's individual preferences and needs.

[0614] "Means for enabling conversation with the generated AI crew" refers to a function that allows a user to have natural conversations with the generated AI crew.

[0615] "A means for AI crew to handle smart device-related consultations and contract procedures" is a function that allows AI crew to handle questions and contract procedures related to devices such as smartphones and tablets.

[0616] "Means of accumulating and analyzing customer service data from AI crews" refers to a function that collects and analyzes data obtained by the AI ​​crews through their interactions with users.

[0617] "A means for adjusting the AI ​​crew's response in accordance with the user's emotions using an emotion engine" is a function that analyzes the user's emotional state in real time and appropriately adjusts the AI ​​crew's responses based on the results.

[0618] "A means of providing a smart customer service assistant to support customer service in physical stores" is a function that enables AI crew members to assist in customer service in physical stores and improve customer satisfaction.

[0619] The following system configuration is used as an embodiment of the present invention. The system includes a means for generating an AI crew member according to the user's preferences, a means for enabling a conversation with the generated AI crew member, a means for the AI ​​crew member to handle consultations and contract procedures related to smart devices, a means for accumulating and analyzing customer service data of the AI ​​crew member, a means for adjusting the response of the AI ​​crew member according to the user's emotions using an emotion engine, and a means for providing a smart customer service assistant to support customer service in physical stores.

[0620] Hardware and Software Configuration

[0621] Hardware:

[0622] Smartphones, smart glasses, head-mounted displays

[0623] software:

[0624] Python

[0625] scikit-learn (for data analysis)

[0626] sentiment_analysis (a custom library for sentiment analysis)

[0627] ai_assistant (custom library of AI crew)

[0628] Data processing and calculation

[0629] server:

[0630] The server collects user interaction data and stores it in a database. The collected data is analyzed using a clustering method (KMeans) with scikit-learn, which clarifies the user's preferences and behavioral patterns.

[0631] Device:

[0632] The device (smartphone, smart glasses, head-mounted display) enables real-time interaction with the user. The emotion engine uses the sentiment_analysis library to analyze the user's emotions and adjust the AI ​​crew's response based on the results.

[0633] User:

[0634] The user interacts with the AI ​​crew through the terminal to ask questions about smart devices and to complete contract procedures. Depending on the user's emotional state, the AI ​​crew will provide appropriate responses.

[0635] Examples

[0636] For example, if a user says, "I'm having so much fun today!", the emotion engine will detect the positive emotion and suggest a way to make the user even happier. In this way, the system can provide optimal customer service according to the user's emotions.

[0637] Examples of prompt statements

[0638] “If a user says, ‘I’m having so much fun today!’ detect that positive emotion and prescribe a response that will make the user even happier.”

[0639] This system will make it possible to improve customer satisfaction in physical stores.

[0640] The flow of the identification process in the application example 2 will be described with reference to FIG.

[0641] Step 1:

[0642] The server collects interaction data with the user. It records the content of the conversation and behavioral data when the user interacts with the AI ​​crew through the terminal in real time and accumulates them in a database. The input is the user's dialogue data, and the output is the accumulated interaction data.

[0643] Step 2:

[0644] The server analyzes the accumulated interaction data. It uses scikit-learn to analyze the data using a clustering method (KMeans) to clarify user preferences and behavioral patterns. The input is the accumulated interaction data, and the output is the clustering results.

[0645] Step 3:

[0646] The terminal enables real-time dialogue with the user. When the user speaks to the terminal, the voice data is converted into text and sent to the AI ​​crew. The input is the user's voice data, and the output is text data.

[0647] Step 4:

[0648] The server analyzes the user's emotions using the emotion engine. It uses the sentiment_analysis library to detect emotions from the user's text data and feeds the results back to the AI ​​crew. The input is the user's text data, and the output is the emotion analysis result.

[0649] Step 5:

[0650] The AI ​​Crew tailors its response based on the sentiment analysis results: if positive sentiment is detected, it responds to make the user more pleased, and if negative sentiment is detected, it responds to comfort. The input is the sentiment analysis results, and the output is the tailored response.

[0651] Step 6:

[0652] The terminal provides the adjusted response to the user, or communicates the response from the AI ​​crew to the user via voice or text. The input is the adjusted response, and the output is the feedback to the user.

[0653] Step 7:

[0654] The server provides a smart customer service assistant to support customer service in brick-and-mortar stores. Based on the AI ​​crew's response data and the results of emotion analysis, the server optimizes the customer service strategy in the brick-and-mortar store. The input is the AI ​​crew's response data and the results of emotion analysis, and the output is the optimized customer service strategy.

[0655] Example 3

[0656] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0657] Conventional AI character systems do not adequately generate characters that match the user's preferences or respond to the user's emotions, resulting in limited user experience. In addition, when consulting about communication devices or going through contract procedures, the system is unable to respond optimally based on the user's emotional data, which may result in reduced user satisfaction. To solve these issues, there is a demand for a system that can generate AI characters that reflect the user's preferences and emotional data and provide optimal sales pitches.

[0658] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0659] In this invention, the server includes means for generating an AI character according to the user's preferences, means for enabling conversation with the generated AI character, means for carrying out consultations and contract procedures related to communication devices using the AI ​​character, means for accumulating and analyzing customer service data of the AI ​​character, means for collecting and analyzing user emotion data, and means for improving the AI ​​character's response based on the analysis results. This makes it possible to generate an optimal AI character according to the user's preferences and emotions, and provide a service that provides high user satisfaction.

[0660] "User" means an individual or legal entity that uses the System.

[0661] An "artificial intelligence character" is a virtual being that is generated based on the user's preferences and is capable of conversation and other actions.

[0662] "Means of generation" refers to methods and technologies for creating an artificial intelligence character based on user preference data.

[0663] "Means for enabling conversation" refers to methods or technologies that allow a user to interact with an artificial intelligence character.

[0664] "Means of consultation and contract procedures related to telecommunications devices" refers to methods and technologies that allow users to ask questions about telecommunications devices or make contracts through artificial intelligence characters.

[0665] "Customer service data" is information that artificial intelligence characters collect through their interactions with users.

[0666] "Means of storage and analysis" refers to the methods and technologies for storing and analyzing collected data.

[0667] "Emotion data" refers to information about emotions obtained from the user's facial expressions, tone of voice, etc.

[0668] "Means of collection and analysis" refers to methods and technologies for obtaining emotion data and analyzing it.

[0669] "Means for improving response" refers to methods and technologies for optimizing the responses and actions of artificial intelligence characters based on the results of analysis.

[0670] An "optimal AI character" is an AI character that reflects the user's preferences and emotional data and delivers the most effective sales pitch.

[0671] "Sales talk" refers to the way of speaking and the content of a sales pitch used to introduce a product or service to a user and encourage them to sign a contract.

[0672] The present invention is a system for generating an AI character according to the user's preferences and for carrying out consultations and contract procedures related to communication devices. A specific embodiment of this system will be described below.

[0673] System Overview

[0674] The system generates an AI character that combines the user's preferred facial features with the most effective sales pitch. Users can enjoy conversations with this character while consulting about telecommunications devices or completing contract procedures. The emotion engine also accumulates and analyzes the user's emotional data, and reflects the results in improving the AI ​​character.

[0675] Hardware and Software Used

[0676] Terminal: A device through which a user accesses the system, such as a smartphone or PC.

[0677] Server: A server for processing data and running generative AI models.

[0678] Generative AI models: Models for generating sales pitches, such as OpenAI's GPT-4.

[0679] Generative models: Models such as StyleGAN that generate facial features that suit the user's preferences.

[0680] Emotion Recognition Software: Software for collecting and analyzing user emotional data, such as Microsoft® Azure® Emotion API.

[0681] Program Processing

[0682] Get the user's preferred facial features

[0683] A user accesses the system using a terminal and inputs the facial features they prefer. Specifically, the user selects eye shape, hairstyle, skin color, etc. on the interface. For example, a user may input "a face with big eyes and a nice smile" as their preference.

[0684] Sales pitch generation

[0685] The server receives the user's input data and uses a generative AI model (e.g., OpenAI's GPT-4) to generate the most effective sales pitch. For example, it generates a "sales pitch for a new smartphone plan."

[0686] AI character generation

[0687] The server generates a facial image using an image generation model (e.g., StyleGAN) based on the user's preferred facial features. Then, it combines the generated sales pitch with the facial image to generate an AI character. For example, an AI character with big eyes and a lovely smile gives a sales pitch about a new smartphone plan.

[0688] Talk to users

[0689] The user uses the device to start a conversation with the generated AI character. The user can ask for advice or complete contract procedures related to telecommunications devices. For example, the user might ask, "What is the plan for my new smartphone?"

[0690] Collecting and analyzing emotion data

[0691] The server uses an emotion engine (e.g., Microsoft Azure's Emotion API) to collect the user's emotion data in real time. Emotion data is obtained from the user's facial expressions, tone of voice, etc. For example, it detects whether the user is smiling or angry.

[0692] Improved AI characters

[0693] The server analyzes the collected emotion data and improves the AI ​​character's response. For example, if the server learns that a certain user is prone to getting angry about a certain topic, it can adjust the AI ​​character's response based on that information. This allows the AI ​​character to respond in a way that does not make the user angry.

[0694] Examples and prompts

[0695] Examples

[0696] A user accesses the system and inputs "a face with big eyes and a nice smile" as their preference. The server uses the generative AI model to generate a "sales pitch for a new smartphone plan." The generated AI character has the facial features the user prefers and delivers an effective sales pitch.

[0697] Examples of prompt statements

[0698] "Users input their preferred facial features, such as eye shape, hairstyle, skin color, etc."

[0699] "Generate a sales pitch for a new smartphone plan."

[0700] In this way, the user can consult about communication devices or carry out contract procedures while enjoying a conversation with the AI ​​character of his / her choice. The flow of the specific process in the third embodiment will be described with reference to FIG.

[0701] Step 1:

[0702] The user inputs preferred facial features.

[0703] A user accesses the system using a terminal and selects preferred facial features such as eye shape, hairstyle, skin color, etc. on the interface. For example, a user may input "big eyes and a nice smile" as their preference. The input data is sent to the server.

[0704] Step 2:

[0705] The server receives the input data and generates a sales pitch using a generative AI model.

[0706] The server receives the preferred facial feature data sent by the user. It then sends prompt sentences to a generative AI model (e.g., OpenAI's GPT-4) to generate the most effective sales pitch. For example, it generates a "sales pitch about a new smartphone plan." The generated sales pitch is stored on the server.

[0707] Step 3:

[0708] The server combines the user's preferred facial features with the generated sales pitch to generate an AI character.

[0709] The server sends a prompt to an image generation model (e.g., StyleGAN) based on the user's preferred facial features to generate a facial image. The server then combines the generated sales pitch with the facial image to generate an AI character. For example, an AI character with big eyes and a lovely smile gives a sales pitch about a new smartphone plan. The generated AI character is stored on the server.

[0710] Step 4:

[0711] The user initiates a conversation with an artificial intelligence character.

[0712] The user uses the terminal to start a conversation with the generated AI character. The user can ask for advice on communication devices or make contracts. For example, the user asks, "Please tell me about the plan for my new smartphone." The user's input is sent to the server, and the AI ​​character responds.

[0713] Step 5:

[0714] The server uses an emotion engine to collect emotion data of the user.

[0715] The server uses an emotion engine (e.g., Microsoft Azure's Emotion API) to collect the user's emotion data in real time. The emotion data is obtained from the user's facial expressions and tone of voice. For example, it detects whether the user is smiling or angry. The collected emotion data is stored on the server.

[0716] Step 6:

[0717] The server analyzes the emotional data and improves the responses of the artificial intelligence characters.

[0718] The server analyzes the collected emotion data and improves the AI ​​character's response. For example, if information is obtained that a particular user is prone to becoming angry about a particular topic, the AI ​​character's response can be adjusted based on that information. This allows the AI ​​character to respond in a way that does not anger the user. The analysis results are stored on the server and reflected in the next conversation.

[0719] (Application example 3)

[0720] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0721] Conventional AI crews had difficulty providing faces and sales pitches that matched the user's preferences, and could not effectively utilize the user's emotional data to improve service. As a result, the user experience did not improve, and improving customer satisfaction was an issue, especially in physical stores.

[0722] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0723] In this invention, the server includes a means for generating an AI crew member according to the user's preferences, a means for enabling a conversation with the generated AI crew member, a means for recognizing the user through a smart device, a means for generating a face that the user likes, a means for providing an effective sales pitch, a means for accumulating and analyzing the user's emotional data, a means for improving the AI ​​crew member's response based on the analysis results, a means for the AI ​​crew member to handle smartphone-related consultations and contract procedures, and a means for accumulating and analyzing the customer service data of the AI ​​crew member. This makes it possible to provide an AI crew member with a face and sales pitch that matches the user's preferences, and to improve the response based on the user's emotional data.

[0724] "Means for generating an AI crew based on user preferences" refers to technology that automatically creates an optimal AI crew based on the user's individual preferences and characteristics.

[0725] "Means for enabling conversation with the generated AI crew" refers to technology that provides an interface or algorithm that allows users to engage in natural conversation with the generated AI crew.

[0726] "Means of recognizing a user through a smart device" refers to technology that uses a device such as a smartphone or smart glasses to recognize the user's face or other features.

[0727] "Means for generating a face that suits the user's preferences" refers to technology that generates an AI crew face with optimal facial features based on the user's preferences and requests.

[0728] "Means for providing an effective sales pitch" refers to technology that generates and provides the most effective sales pitch depending on the user's characteristics and situation.

[0729] "Means for accumulating and analyzing user emotional data" refers to technology that collects data on the user's emotions and analyzes it to understand the user's emotional state.

[0730] "Means for improving the AI ​​crew's response based on the analysis results" refers to technology that optimizes and improves the AI ​​crew's response methods based on the results of analysis of users' emotional data.

[0731] "A means for handling smartphone-related inquiries and contract procedures through an AI crew" refers to technology that allows users to ask questions about smartphones and complete contract procedures through an AI crew.

[0732] "Means of accumulating and analyzing customer service data of AI crews" refers to technology that collects data on when the AI ​​crews serve users and analyzes it to evaluate the performance of the AI ​​crews.

[0733] The system for implementing the present invention generates an AI crew member according to the user's preferences and enables conversation with the generated AI crew member. A specific embodiment of this system will be described below.

[0734] 1. System Configuration

[0735] The system consists of the following main components:

[0736] Server: Generates AI crew members based on user preferences, and accumulates and analyzes emotional data.

[0737] Terminal: Includes smart devices such as smartphones and smart glasses. Users are recognized through these devices and can converse with the AI ​​crew.

[0738] User: An individual who uses the system.

[0739] 2. Hardware and Software Used

[0740] Hardware: Smartphones, smart glasses

[0741] Software: OpenCV, DeepFace, GPT-3 (registered trademark)

[0742] 3. Data processing and calculation

[0743] User Awareness

[0744] The terminal captures the user's face through a smart device and uses DeepFace to analyze the user's age, gender, and emotions, thereby obtaining basic information about the user.

[0745] Face Generation

[0746] The server runs an algorithm to generate a face that matches the user's preferences. Based on the user's information, it generates an AI crew member's face with optimal facial features.

[0747] Sales pitch generation

[0748] The server uses GPT-3 to generate effective sales pitches based on user information. The generated sales pitches are optimized according to the user's characteristics and circumstances.

[0749] sentiment analysis

[0750] The server accumulates and analyzes the user's emotional data, which allows the user's emotional state to be understood.

[0751] Response improvement

[0752] The server optimizes and improves the AI ​​crew's response methods based on the analysis results of the emotion data, enabling the AI ​​crew to respond optimally according to the user's emotions.

[0753] 4. Specific Examples

[0754] User Information

[0755] Age: 30

[0756] Gender: Male

[0757] Emotion: Joy

[0758] Generated sales pitch

[0759] "Hello! What products are you looking for today?"

[0760] Examples of prompt statements

[0761] User Age: 30, Gender: Male, Emotion: Joy

[0762] In this way, AI crew members with faces and sales pitches tailored to the user's preferences can be provided, making it possible to improve service based on the user's emotional data.

[0763] The flow of the specific process in the application example 3 will be described with reference to FIG.

[0764] Step 1:

[0765] The terminal captures the user's face using a smart device. The input is the user's face image, and the output is face image data. Specifically, the terminal captures the user's face using a camera on a smartphone or smart glasses.

[0766] Step 2:

[0767] The device inputs the captured facial image into DeepFace to analyze the user's age, gender, and emotions. The input is facial image data, and the output is age, gender, and emotional information. Specifically, the device uses the DeepFace library to analyze the facial image and obtain basic information about the user.

[0768] Step 3:

[0769] The server receives the user's age, gender, and emotional information and generates a face of the user's preference. The input is the user's basic information, and the output is the generated facial image. Specifically, the server runs a face generation algorithm based on the user information to generate an AI crew member's face with optimal facial features.

[0770] Step 4:

[0771] The server generates a prompt sentence based on the user information and inputs it into GPT-3 to generate an effective sales pitch. The input is user information and a prompt sentence, and the output is a sales pitch. The specific operation is to create a prompt sentence and input it into the GPT-3 model to generate a sales pitch.

[0772] Step 5:

[0773] The server accumulates and analyzes the emotional data obtained during the dialogue with the user. The input is the emotional data during the dialogue, and the output is the analysis result. Specifically, the server stores the emotional data in a database and uses an analysis algorithm to grasp the user's emotional state.

[0774] Step 6:

[0775] The server optimizes and improves the AI ​​crew's response methods based on the analysis results of the emotion data. The input is the analysis results of the emotion data, and the output is the improved response method. In concrete terms, the server adjusts the response algorithm based on the analysis results and provides the optimal response according to the user's emotions.

[0776] Step 7:

[0777] The terminal displays the generated face image and sales pitch to the user and starts a dialogue. The input is the generated face image and sales pitch, and the output is a dialogue with the user. In concrete terms, the system displays the face image on the screen of the smart device and provides the sales pitch to the user in voice or text.

[0778] 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 a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0779] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0780] Another example of generative AI is Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0781] In the above embodiment, an example was given in which the specific process was performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0782] [Second embodiment]

[0783] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0784] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0785] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a wide area network (WAN) and / or a local area network (LAN).

[0786] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0787] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs the voice according to instructions from the processor 46.

[0788] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[0789] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[0790] Fig. 4 shows an example of main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0791] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32, and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0792] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0793] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50, and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0794] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0795] "Example 1"

[0796] One embodiment of the present invention is a system that allows a user to generate an AI crew member based on their preferences. Specifically, the user inputs their preferred features (e.g., face shape, hair color, tone of voice, etc.), and an AI crew member is generated based on the input. The generated AI crew member can converse with the user and can provide smartphone-related advice and handle contract procedures. "Example 2"

[0797] Furthermore, a system for accumulating and analyzing customer service data of AI crew members is also one embodiment of the present invention. Specifically, the system accumulates data that AI crew members obtain through conversations with users and contract procedures, and analyzes that data to create the strongest AI crew members.

[0798] "Example 3"

[0799] The best AI crew members have the face that the user likes and the best sales pitch. Specifically, they are generated by combining the facial features that the user likes the most with the most effective sales pitch. In this way, users can enjoy conversations with their favorite AI crew members while consulting about smartphones or completing contract procedures.

[0800] The process flow of each embodiment will be described below.

[0801] "Example 1"

[0802] Step 1: The user inputs their preferred features (e.g. face shape, hair color, tone of voice, etc.) into the system.

[0803] Step 2: The system generates an AI crew based on the input features.

[0804] Step 3: The generated AI crew can converse with the user and handle smartphone-related inquiries and contract procedures.

[0805] "Example 2"

[0806] Step 1: The AI ​​crew accumulates data obtained through conversations with users and contract procedures.

[0807] Step 2: The system analyzes the accumulated data.

[0808] Step 3: Create the strongest AI crew based on the analysis results.

[0809] "Example 3"

[0810] Step 1: The system generates the strongest AI crew by combining the user's most preferred facial features with the most effective sales pitches.

[0811] Step 2: The generated AI crew can enjoy conversation with the user and assist with smartphone-related issues and contract procedures.

[0812] Example 1

[0813] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[0814] Conventional AI crew generation systems did not adequately customize the system to meet the user's preferences, limiting the user experience. In addition, the quality and performance of the generated AI crews were inconsistent, resulting in a lack of reliability in smartphone-related consultations and contract procedures. Furthermore, the accumulation and analysis of customer service data was insufficient, making it difficult to generate optimal AI crews.

[0815] The specification process by the specification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes a means for inputting feature information according to the user's preferences, a means for transmitting the input feature information to the server, a means for the server to receive the feature information and store it in a database, a means for the server to generate a prompt sentence based on the feature information, a means for inputting a prompt sentence into the generation AI model and generating an AI crew member, a means for transmitting data of the generated AI crew member to the user's terminal, a means for enabling a conversation with the generated AI crew member, a means for the AI ​​crew member to carry out smartphone-related consultations and contract procedures, and a means for accumulating and analyzing customer service data of the AI ​​crew member. This makes it possible to generate a high-quality AI crew member according to the user's preferences, and to realize highly reliable smartphone-related consultations and contract procedures. Furthermore, the accumulation and analysis of customer service data makes it possible to generate an optimal AI crew member.

[0816] The "means for inputting characteristic information according to user preferences" refers to a means for providing an interface for a user to input characteristic information such as face shape, hair color, and tone of voice based on his or her own preferences.

[0817] The "means for transmitting the input characteristic information to the server" refers to a communication means for securely transmitting the characteristic information input by the user to the server.

[0818] The "means for the server to receive the characteristic information and store it in the database" refers to the means for the server to receive the characteristic information sent from the user and store the information in the database.

[0819] "Means for the server to generate a prompt sentence based on feature information" refers to means for the server to generate a prompt sentence to be input into the generative AI model based on feature information stored in the database.

[0820] "Means for inputting a prompt sentence into a generative AI model and generating an AI crew member" refers to means for inputting a prompt sentence into a generative AI model and generating image and voice data of an AI crew member based on the prompt sentence.

[0821] "Means for transmitting data of the generated AI crew to the user's terminal" refers to communication means for transmitting data of the generated AI crew to the user's terminal.

[0822] "Means for enabling conversation with the generated AI crew" refers to means for providing an interface for a user to interact with the generated AI crew.

[0823] "A means for users to carry out smartphone-related consultations and contract procedures through an AI crew" refers to a means for users to carry out smartphone-related consultations and contract procedures through an AI crew.

[0824] "Means of accumulating and analyzing customer service data from AI crews" refers to the means by which the AI ​​crews accumulate customer service data obtained through dialogue with users and analyze that data.

[0825] "Means for creating optimal AI crew" refers to a means for analyzing accumulated customer service data and generating optimal AI crew based on the results.

[0826] An "AI crew with the optimal sales pitch" is an AI crew that can deliver the most effective sales pitch to users based on the results of analyzing customer service data.

[0827] This invention relates to a system that allows users to generate AI crew members according to their preferences and interact with the AI ​​crew members. Specifically, it includes a process in which the user inputs characteristic information and generates an AI crew member using a generative AI model based on the information.

[0828] Hardware and Software Used

[0829] Hardware

[0830] Terminal: The device through which the user enters characteristic information (e.g. smartphone, PC).

[0831] Server: A computer system for receiving the feature information, storing it in a database, and generating an AI crew member using a generative AI model.

[0832] software

[0833] Database: A data management system for storing feature information (e.g. MySQL, PostgreSQL).

[0834] Generative AI model: An artificial intelligence model for generating AI crew members based on a prompt sentence (e.g., OpenAI's GPT-4, DALL-E).

[0835] Communication Protocol: A protocol for securely transmitting data between the device and the server (e.g. HTTPS).

[0836] Data processing and calculation

[0837] User Actions

[0838] A user uses a terminal to access the system's interface and inputs characteristic information such as face shape, hair color, tone of voice, etc. For example, a user selects "round face, blonde hair, calm, low-pitched voice."

[0839] Device operation

[0840] The device sends the characteristic information entered by the user to the server, where the data is encrypted and transmitted securely using the HTTPS protocol.

[0841] Server Operations

[0842] The server receives the characteristic information sent from the terminal and stores it in a database. When storing the information, it performs validation to maintain the integrity of the data.

[0843] Next, the server generates a prompt sentence to be input to the generative AI model based on the feature information stored in the database. For example, it generates the following prompt sentence:

[0844] "The characteristics of the AI ​​crew that users prefer are as follows: face shape is round, hair color is blonde, and voice tone is calm and low. Please generate an AI crew with these characteristics."

[0845] The server inputs the generated prompt text into the generative AI model to generate image and voice data of the AI ​​crew. The generated data is then sent to the user's device via the server.

[0846] User Actions

[0847] The user interacts with the AI ​​crew member that is displayed on the device, who answers the user's questions and assists with smartphone-related consultations and contract procedures.

[0848] Examples

[0849] For example, if the user selects "round face, blonde hair, soft, deep voice," the following specific actions will occur:

[0850] 1. A user opens an app on their smartphone and selects "round face" as their face shape, "blonde" as their hair color, and "calm, low-pitched" as their voice tone.

[0851] 2. The device sends this information to the server.

[0852] 3. The server receives the information and stores the characteristic information "round face, blonde hair, calm, low voice" in the database.

[0853] 4. The server generates a prompt sentence saying, "The characteristics of the AI ​​crew member that the user prefers are as follows: a round face, blonde hair, and a calm, low voice tone. Please generate an AI crew member with these characteristics."

[0854] 5. The server inputs the prompt text into the generative AI model and generates image and voice data for the AI ​​crew.

[0855] 6. The server sends the generated AI crew data to the user's smartphone.

[0856] 7. The user interacts with the AI ​​crew generated on their smartphone and completes the smartphone contract procedure.

[0857] In this way, users can generate high-quality AI crew members tailored to their preferences and provide reliable smartphone-related consultations and contract procedures. Furthermore, the accumulation and analysis of customer service data will enable the generation of optimal AI crew members.

[0858] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0859] Step 1:

[0860] The user inputs the characteristic information.

[0861] A user uses a terminal to access the system interface and inputs feature information such as face shape, hair color, and voice tone. For example, a user selects "round face, blonde, calm, low-pitched voice." The input data is feature information such as face shape, hair color, and voice tone.

[0862] Step 2:

[0863] The terminal transmits the input characteristic information to the server.

[0864] The terminal transmits the characteristic information input by the user to the server using the HTTPS protocol. The input data is the characteristic information input by the user, and the output data is the characteristic information transmitted to the server.

[0865] Step 3:

[0866] The server receives the characteristic information and stores it in a database.

[0867] The server receives the feature information sent from the terminal and stores it in a database. When storing the data, validation is performed to maintain data consistency. The input data is the feature information sent from the terminal, and the output data is the feature information stored in the database.

[0868] Step 4:

[0869] The server generates a prompt sentence based on the characteristic information.

[0870] The server generates a prompt sentence to be input to the generative AI model based on the feature information stored in the database. For example, it generates a prompt sentence such as "The features of the AI ​​crew member the user prefers are as follows: a round face, blonde hair, and a calm, low voice. Please generate an AI crew member with these features." The input data is the feature information stored in the database, and the output data is the generated prompt sentence.

[0871] Step 5:

[0872] The server inputs a prompt sentence into the generative AI model and generates an AI crew member.

[0873] The server inputs the generated prompt sentence into the generative AI model to generate image and voice data of the AI ​​crew. The generative AI model generates image and voice data of the AI ​​crew based on the prompt sentence. The input data is the generated prompt sentence, and the output data is the generated image and voice data of the AI ​​crew.

[0874] Step 6:

[0875] The server sends the generated AI crew data to the user's device.

[0876] The server transmits the AI ​​crew data obtained from the generative AI model to the user's device. When transmitting, the data is compressed and encrypted to ensure secure transmission. The input data is the image and audio data of the generated AI crew, and the output data is the AI ​​crew data transmitted to the user's device.

[0877] Step 7:

[0878] The user interacts with the generated AI crew.

[0879] The user interacts with the generated AI crew displayed on the device. The AI ​​crew answers the user's questions and supports smartphone-related consultations and contract procedures. The input data is the user's questions and requests, and the output data is the AI ​​crew's responses and support.

[0880] (Application example 1)

[0881] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[0882] Traditional shopping experiences often make it difficult for users to find products that match their tastes, and the purchasing process is often cumbersome. Furthermore, customer service in physical stores is often inconsistent, so there was a need for effective measures to improve user satisfaction.

[0883] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0884] In this invention, the server includes a means for generating an AI crew member according to the user's preferences, a means for enabling a conversation with the generated AI crew member, a means for the AI ​​crew member to handle consultations and contract procedures related to smart devices, a means for accumulating and analyzing customer service data of the AI ​​crew member, a means for recommending products based on the user's preferences, and a means for supporting the user's purchase procedure, thereby enabling the user to easily find products that match their preferences and smoothly complete the purchase procedure.

[0885] "User" means an individual or legal entity that uses the System.

[0886] "Preferences" are personal tastes or preferences that a user has for particular features or attributes.

[0887] "AI Crew" is an artificial intelligence character that is generated based on the user's preferences and will converse with and provide support to the user.

[0888] "Means for generating" means the technical means for generating an AI crew member based on user input.

[0889] "Means enabling conversation" refers to the technical means that allow a natural dialogue between the user and the AI ​​crew.

[0890] A "smart device" is an electronic device with Internet connectivity, such as a smartphone or smart glasses.

[0891] "Means of consultation and contract procedures" refers to the technological means by which users can ask questions about smart devices or complete contract procedures through an AI crew.

[0892] "Customer service data" is information that the AI ​​crew collects through their interactions with users.

[0893] "Means of accumulation and analysis" refers to the technical means for storing and analyzing customer service data.

[0894] "Means for recommending products" means technical means for suggesting appropriate products based on the user's preferences.

[0895] "Means to support the purchase process" are technological means to assist users in the process of purchasing a product.

[0896] The system for implementing the present invention generates an AI crew according to the user's preferences and improves the shopping experience in a physical store. A specific embodiment of the system is described below.

[0897] 1. System Configuration

[0898] The system consists of the following main components:

[0899] User terminal: Smart devices such as smartphones and smart glasses.

[0900] Servers: Servers for running generative AI models (e.g. GPT-4), facial recognition APIs (e.g. Face++), and speech synthesis APIs (e.g. Google Text-to-Speech).

[0901] Database: A database for accumulating and analyzing customer service data.

[0902] 2. Program Processing

[0903] The server realizes the system using the following means.

[0904] A way to generate AI crew members to suit user preferences

[0905] The user inputs the user's preferred features (e.g. face shape, hair color, tone of voice, etc.) from the user's device. The server uses a generative AI model to generate an AI crew based on the user's input. It uses a facial recognition API to generate a face that matches the specified features, and a voice synthesis API to generate a voice with the specified tone of voice.

[0906] A means to enable conversation with generated AI crew members

[0907] The server performs natural language processing (NLP) to allow the generated AI crew to have a natural dialogue with the user, allowing the user to enjoy shopping while talking to the AI ​​crew.

[0908] A means of consultation and contract procedures related to smart devices

[0909] The AI ​​Crew supports users when they have questions about their smart devices or when they go through contract procedures. The server provides appropriate answers to the user's questions and guides them through the contract procedures.

[0910] A means of accumulating and analyzing customer service data

[0911] The server collects customer service data from interactions between the AI ​​crew and the user, stores it in a database, and analyzes it, allowing the server to understand the user's preferences and behavioral patterns and provide more personalized services.

[0912] A way to recommend products based on user preferences

[0913] The server analyzes the customer service data and recommends appropriate products based on the user's preferences, allowing users to easily find products that match their tastes.

[0914] Ways to help users complete the purchase

[0915] When a user purchases a product, the AI ​​crew will support the purchase process. The server will confirm the user's purchase intention and guide them through the necessary procedures.

[0916] 3. Specific Examples

[0917] The user puts on the smart glasses and talks to the AI ​​crew while walking around the store. The AI ​​crew recommends products based on the user's preferences, and when the user says, "I would like to purchase this product," the AI ​​crew completes the purchase procedure via smartphone.

[0918] 4. Examples of prompts

[0919] Enter the user's preferred characteristics:

[0920] Face Shape:Round face

[0921] Hair color: Black

[0922] Tone of voice: Calm voice

[0923] Generate your AI crew based on these characteristics.

[0924] In this way, a system can be created that allows users to generate AI crew members based on their preferences, improving their shopping experience in physical stores.

[0925] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0926] Step 1:

[0927] The user terminal inputs the user's preferred features (e.g., face shape, hair color, tone of voice, etc.). The input data is sent to the server. The input data includes specific features such as "round face, black hair, calm voice."

[0928] Step 2:

[0929] The server uses a generative AI model (e.g. GPT-4) based on the received user's preferred features to generate the appearance and voice of the AI ​​crew member. It uses a facial recognition API (e.g. Face++) to generate a face that matches the specified features, and a speech synthesis API (e.g. Google Text-to-Speech) to generate a voice with the specified tone of voice. The appearance data and voice data of the generated AI crew member are output.

[0930] Step 3:

[0931] The server builds a conversational interface using natural language processing (NLP) to enable conversation with the generated AI crew. It receives input from the user's device (e.g., "Tell me about this product"), and the server uses NLP to generate an appropriate response and sends it to the user's device. The user's question and the AI ​​crew's response are treated as input and output.

[0932] Step 4:

[0933] When a user device makes an inquiry or performs a contract procedure related to a smart device, the server supports it through the AI ​​crew. The server receives the user's question (e.g., "What is the contract plan for this smartphone?") and provides the appropriate information. The user's question and the server's answer are treated as input and output.

[0934] Step 5:

[0935] The server accumulates and analyzes the customer service data collected through the interaction between the AI ​​crew and the user in a database. The customer service data includes the content of the user's questions, the AI ​​crew's responses, the user's behavioral patterns, etc. The accumulated data is analyzed to understand the user's preferences and behavioral patterns.

[0936] Step 6:

[0937] The server analyzes the customer service data and recommends appropriate products based on the user's preferences. The server receives input from the user's device (e.g., "What products do you recommend?"), recommends products based on the analysis results, and sends them to the user's device. The user's request and the recommended product information are treated as input and output.

[0938] Step 7:

[0939] When a user purchases a product, the server supports the purchase procedure through the AI ​​crew. The server receives input from the user's device (e.g., "I want to purchase this product") and guides the user through the purchase procedure. The user's purchase intention and the procedure guidance from the server are treated as input and output.

[0940] In this way, a system can be created that allows users to generate AI crew members based on their preferences, improving their shopping experience in physical stores.

[0941] Example 2

[0942] Next, a description will be given of Example 2 of the embodiment 2. In the following description, the data processing device 12 is referred to as a "server" and the smart glasses 214 are referred to as a "terminal".

[0943] In conventional AI crew systems, it was difficult to effectively collect and analyze conversation data with users and generate optimal responses. In addition, there was a lack of means to generate AI crews that matched the user's preferences, or to create the strongest AI crews through the accumulation and analysis of customer service data. This resulted in a decrease in the quality of the user experience and a decrease in the efficiency of contract procedures.

[0944] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0945] In this invention, the server includes a means for generating an AI crew member according to the user's preferences, a means for enabling a conversation with the generated AI crew member, a means for the AI ​​crew member to carry out consultations and contract procedures related to communication devices, a means for collecting customer service data of the AI ​​crew member, a means for storing the collected data in a database, a means for analyzing the stored data using natural language processing technology, a means for feeding back the analysis results to the generation AI model, a means for the generation AI model to generate an optimal response based on a prompt sentence, and a means for providing the generated response to the user. This makes it possible to effectively collect and analyze conversation data with the user and generate an optimal response. In addition, the strongest AI crew member can be created through the accumulation and analysis of customer service data, improving the quality of the user experience and the efficiency of contract procedures.

[0946] "User" refers to any individual or legal entity that uses the System.

[0947] "Artificial Intelligence Crew" refers to an artificial intelligence program designed to converse with users and process contracts.

[0948] "Means for generating" refers to methods and techniques for creating an artificial intelligence crew based on the user's preferences.

[0949] "Conversational enablement" refers to the methods and technologies that allow the user and the AI ​​crew to communicate with each other.

[0950] "Means of consultation and contract procedures related to telecommunications devices" refers to methods and technologies that allow users to ask questions about telecommunications devices or complete contract procedures through an artificial intelligence crew.

[0951] "Customer service data" refers to information collected by the AI ​​crew through conversations with users and contract procedures.

[0952] "Means of collection" refers to the methods and technologies for efficiently collecting customer service data.

[0953] "Means of storing in a database" refers to the methods and technologies for systematically storing collected data.

[0954] "Natural language processing technology" refers to technology for analyzing text data and understanding its meaning.

[0955] "Means for analysis" refers to methods and techniques for analyzing stored data and extracting useful information.

[0956] A "generative AI model" refers to an artificial intelligence model that generates optimal responses based on feedback.

[0957] A "prompt sentence" refers to an instruction sentence input to a generative AI model.

[0958] "Means for generating an optimal response" refers to the methods or techniques that a generative AI model uses to create an optimal reply to a user based on a prompt.

[0959] "Means of providing" refers to the method or technology used to communicate the generated response to the user.

[0960] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0961] This invention is a system that generates an AI crew member according to the user's preferences, and accumulates and analyzes data obtained through conversations with the user and contract procedures. A specific embodiment of this system will be described below.

[0962] System Configuration

[0963] This system mainly consists of three elements: a server, a terminal, and a user.

[0964] 1. Server

[0965] The server has a means for generating an AI crew according to the user's preferences. The generated AI crew can converse with the user.

[0966] The server has a means for handling consultations and contract procedures related to communication devices using an artificial intelligence crew.

[0967] The server has the means to collect customer service data from the AI ​​crew and store it in a database using a database management system such as MySQL or PostgreSQL.

[0968] The server has the means to analyze the stored data using natural language processing techniques (e.g., Python's NLTK or spaCy).

[0969] The server has the means to feed the analysis results back to a generative AI model (e.g., OpenAI's GPT-4).

[0970] The server has the means for the generative AI model to generate an optimal response based on the prompt text.

[0971] 2. Terminal

[0972] The device has the means to collect data about the user's conversation, which is converted to text using voice recognition software (e.g., Google Speech-to-Text API).

[0973] The terminal has a means for providing the generated response to the user.

[0974] 3. Users

[0975] The user uses the device to initiate a conversation with the AI ​​crew, for example saying, "I'd like to sign up for a new mobile phone contract."

[0976] Examples

[0977] Consider a case where a user says, "I want to get a new mobile phone contract." The device collects this speech and converts it to text using the Google Speech-to-Text API. The converted text data is sent to the server and stored in a MySQL database. The server tokenizes the stored text data using NLTK and analyzes the user's intent. The analysis results are fed back to the generative AI model, which generates the prompt sentence.

[0978] Examples of prompt statements

[0979] If a user says "I want to get a new mobile phone contract", generate the optimal response, taking into account that the user sentiment is positive.

[0980] Based on this prompt, the generative AI model generates a response: "Let me help you with your new mobile phone contract. What plan would you like?" The device can then provide this response to the user and continue the next conversation.

[0981] In this way, the server can accumulate and analyze the customer service data of the AI ​​crew to create the strongest AI crew, which will improve the quality of the user experience and the efficiency of the contract procedure.

[0982] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0983] Program processing flow

[0984] Step 1: User initiates a conversation with the AI ​​crew member

[0985] The user uses the terminal to start a conversation with the AI ​​crew. For example, the user might say, "I'd like to sign up for a new mobile phone contract."

[0986] Input: User's voice input

[0987] Output: Audio data

[0988] Step 2: The device collects conversation data

[0989] The device collects conversation data with the user in real time. The voice data is converted into text using voice recognition software (e.g., Google Speech-to-Text API).

[0990] Input: Audio data

[0991] Output: Text data

[0992] Step 3: The server stores the collected data in a database

[0993] The terminal sends the collected text data to the server. The server stores this data in a database (e.g., MySQL, PostgreSQL). The stored data includes the content of the conversation, the date and time, the user ID, etc.

[0994] Input: Text data, user ID, date and time

[0995] Output: Data stored in the database

[0996] Step 4: The server analyzes the stored data

[0997] The server analyzes the stored data using natural language processing techniques (e.g., Python's NLTK or spaCy). Specifically, it performs tokenization, part-of-speech tagging, sentiment analysis, etc. on the text data.

[0998] Input: Text data stored in a database

[0999] Output: Analysis results (user intent, emotions, etc.)

[1000] Step 5: The server feeds the analysis results back to the generative AI model

[1001] The server feeds the analysis results back to the generative AI model (e.g., OpenAI's GPT-4), which includes the user's intentions, emotions, and contract tendencies.

[1002] Input: Analysis results

[1003] Output: Feedback to the generative AI model

[1004] Step 6: The generative AI model generates the optimal response based on the prompt.

[1005] The generative AI model generates a prompt sentence based on the feedback and creates an optimal response. For example, if the prompt sentence is "If the user says, 'I want to sign a new mobile phone contract,' generate the optimal response. Please consider that the user's emotion is positive," the generative AI model generates the response "I'll help you with your new mobile phone contract. What kind of plan are you looking for?"

[1006] Input: prompt, feedback

[1007] Output: Best response

[1008] Step 7: The terminal provides the generated response to the user.

[1009] The terminal provides the user with the response generated by the generative AI model. The user can then receive the response from the AI ​​crew through the terminal and continue the next conversation.

[1010] Input: Best response

[1011] Output: Providing a response to the user

[1012] (Application example 2)

[1013] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server", and the smart glasses 214 will be referred to as a "terminal".

[1014] Conventional AI crew systems had issues with the difficulty of providing services tailored to the user's preferences and the inability to respond to customers in real time. Furthermore, the accumulation and analysis of customer service data was insufficient, making it difficult to propose optimal customer service methods.

[1015] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means. In this invention, the server includes a means for generating an AI crew member according to the user's preferences, a means for enabling a conversation with the generated AI crew member, a means for the AI ​​crew member to handle consultations and contract procedures related to smart devices, a means for accumulating and analyzing customer service data of the AI ​​crew member, a means for collecting conversations with customers in real time using smart glasses and displaying the analysis results, and a means for proposing an optimal customer service method using the generated AI model. This makes it possible to provide optimal customer service in real time according to the user's preferences.

[1016] "User" refers to any individual or legal entity that uses the System.

[1017] "AI Crew" refers to a virtual customer service representative who uses artificial intelligence to converse with users and handle contract procedures.

[1018] "Means for generating" refers to a method or apparatus for creating an AI crew based on user preferences.

[1019] "Means enabling conversation" refers to a method or device that allows the user and the AI ​​crew to communicate through voice or text.

[1020] "Smart devices" refers to electronic devices with Internet connectivity, such as smartphones and smart glasses.

[1021] "Means for consultation and contract procedures" refers to a method or device that allows a user to ask questions or make contracts regarding a smart device through an AI crew.

[1022] "Customer service data" refers to information collected by the AI ​​crew through their interactions with users.

[1023] "Means of storing and analyzing" refers to methods and devices for storing and analyzing collected customer service data.

[1024] "Smart glasses" refers to electronic glasses-type devices equipped with a display, camera, microphone, and Internet connectivity.

[1025] "Means for collecting data in real time and displaying analytical results" refers to a method or device for instantly recording conversations with customers, analyzing the data, and displaying the results.

[1026] A "generative AI model" refers to a model that uses artificial intelligence to suggest the optimal way to serve customers.

[1027] "Means for proposing the optimal customer service method" refers to a method or device for using a generative AI model to present the most appropriate customer service method to a user.

[1028] The system for implementing this invention generates an AI crew member according to the user's preferences and enables conversation with the generated AI crew member. The system also uses the AI ​​crew member to handle smart device-related consultations and contract procedures, and accumulates and analyzes customer service data of the AI ​​crew member. Furthermore, the system uses smart glasses to collect conversations with customers in real time and displays the analysis results. The system can use the generated AI model to suggest optimal customer service methods.

[1029] System Configuration

[1030] The system uses the following hardware and software:

[1031] Hardware: smart glasses, microphone, server

[1032] Software: Python, SpeechRecognition library, OpenAI API

[1033] Processing flow

[1034] 1. Speech Recognition: The microphone on the smart glasses is used to collect the customer's speech as voice data. The collected voice data is converted to text data using the SpeechRecognition library.

[1035] 2. Data Analysis: The converted text data is sent to a server and analyzed using OpenAI's generative AI model. The analysis results suggest the optimal way to serve the customer.

[1036] 3. Display of results: The analysis results are displayed in real time on the smart glasses display, allowing store clerks to provide optimal customer service.

[1037] Examples

[1038] For example, if a customer says, "I'd like to know more about this product," the generative AI model can generate suggestions such as, "This product uses the latest technology and is particularly durable. Plus, it's currently on special discount."

[1039] Examples of prompt statements

[1040] Customer conversation: I want to know more about this product

[1041] Please suggest the best way to serve customers.

[1042] In this way, it is possible to provide optimal customer service in real time according to the user's preferences.

[1043] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1044] Step 1:

[1045] A user puts on the smart glasses and starts a conversation with a customer. A microphone installed in the smart glasses collects what the customer says as voice data. The input is the customer's voice, and the output is voice data.

[1046] Step 2:

[1047] The voice data collected by the device (smart glasses) is converted to text data using the SpeechRecognition library. The input is voice data, and the output is text data. This conversion process allows the voice data to be treated as text information.

[1048] Step 3:

[1049] The terminal sends the converted text data to the server. The input is the text data, and the output is the data sent to the server. The server prepares the received text data for analysis.

[1050] Step 4:

[1051] The server inputs the received text data into OpenAI's generative AI model to generate a prompt that suggests the optimal way to serve the customer. The input is text data, and the output is the generated prompt. The generative AI model analyzes the text data and generates an appropriate response.

[1052] Step 5:

[1053] The server analyzes the generated prompt text and generates a text that suggests the best way to serve the customer. The input is the prompt text, and the output is the suggested text. This suggested text includes a specific way to serve the customer.

[1054] Step 6:

[1055] The server sends the generated suggested text to the terminal (smart glasses). The input is the suggested text, and the output is data transmission to the terminal. The terminal prepares the received suggested text for display.

[1056] Step 7:

[1057] The terminal displays the proposed text received on the display of the smart glasses in real time. The input is the proposed text, and the output is the display on the display. This allows the user to provide optimal customer service to the customer.

[1058] Example 3

[1059] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[1060] Conventional systems using AI characters had difficulty responding to individual user preferences and were unable to generate effective sales pitches. In addition, there was a lack of means to utilize facial feature data and past reaction data provided by users, making it impossible to provide users with AI characters that were optimal for them. This resulted in a decrease in user satisfaction and a failure to improve the efficiency of contract procedures.

[1061] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1062] In this invention, the server includes a means for generating an AI character according to the user's preferences, a means for enabling a conversation with the generated AI character, a means for carrying out consultations and contract procedures related to communication devices using the AI ​​character, a means for accumulating and analyzing customer service data of the AI ​​character, a means for analyzing facial feature data provided by the user, a means for collecting past reaction data of users, a means for generating the most effective sales pitch, and a means for combining facial features and sales pitches. This makes it possible to provide an AI character that corresponds to the individual preferences of the user and generate effective sales pitches.

[1063] "User" refers to any individual or legal entity that uses the System.

[1064] An "artificial intelligence character" is a virtual being that is generated based on the user's preferences and is used for conversation, consultation, and contract procedures.

[1065] "Communication devices" refers to electronic devices used for communication, such as smartphones, tablets, and personal computers.

[1066] "Customer service data" refers to data generated by an AI character during conversations, consultations, and contract procedures with users.

[1067] "Facial Feature Data" means data about facial features, such as the eyes, nose, and mouth, extracted from an image or information provided by a user.

[1068] "Response Data" means data regarding positive or negative responses a User has previously made.

[1069] "Sales pitch" refers to the way of speaking and the content of a sales pitch used to effectively explain a product or service to a user and encourage them to sign a contract or make a purchase.

[1070] A "generative AI model" refers to an algorithm or system that uses artificial intelligence technology to generate new data or content.

[1071] A "prompt sentence" refers to a sentence of instructions or questions that is input to a generative AI model.

[1072] The present invention is a system for generating an AI character according to the user's preferences and for carrying out consultations and contract procedures related to communication devices. A specific embodiment of this system will be described below.

[1073] First, a user accesses the system and uploads an image with the facial features they prefer. The image provided by the user is sent to the system using a device such as a smartphone or PC.

[1074] The server then receives the uploaded image and uses a facial recognition API (e.g. facial recognition software) to analyze the facial features, specifically extracting features such as eye shape, nose height, mouth size, etc. The results of this analysis are stored as facial feature data.

[1075] The server then collects past reaction data of the user, which is data on positive or negative reactions shown by the user in the past, and is obtained from chat history, survey results, etc.

[1076] Based on the collected response data, the server uses a natural language processing (NLP) model (e.g., a generative AI model) to generate the most effective sales pitch for the user. For example, if the user is price-sensitive, the server generates a pitch that emphasizes price information.

[1077] Next, the server uses a generative AI model (e.g., image generation software) to generate an artificial intelligence character that combines the analyzed facial features with the generated sales pitch. Specifically, the server sets the character with the facial features the user prefers to speak the generated sales pitch.

[1078] Finally, the user can start to interact with the AI ​​character. For example, if the user asks, "Tell me about the new smartphone plan," the AI ​​character will respond, "This plan has a low monthly fee and a large data capacity, so it's a good deal."

[1079] As a concrete example, if a user is considering a new smartphone contract, the following prompt could be used:

[1080] "Generate an AI character with the facial features that the user prefers and pair it with the most effective sales pitch. The user is considering a new smartphone contract."

[1081] In this way, the user can consult about communication devices or carry out contract procedures while enjoying a conversation with the AI ​​character of his / her choice. The flow of the specific process in the third embodiment will be described with reference to FIG.

[1082] Step 1:

[1083] A user provides facial feature data.

[1084] A user uses a smartphone or a PC to access the system's interface and upload an image with facial features that they like. The input is image data provided by the user, and the output is image data sent to the server. A specific operation is when a user says, "I like this celebrity's face," and uploads the image.

[1085] Step 2:

[1086] The server analyzes the facial feature data.

[1087] The server receives the uploaded image and analyzes the facial features using a facial recognition API (e.g., facial recognition software). The input is the image data provided by the user, and the output is the analyzed facial feature data. Specifically, the server extracts features such as "round eyes, high nose, small mouth."

[1088] Step 3:

[1089] The server collects the user's past response data.

[1090] The server collects users' past chat histories and survey results from a database. The input is the users' past reaction data, and the output is the collected reaction data. In concrete terms, the server collects data such as "users responded favorably to information about prices."

[1091] Step 4:

[1092] The server generates the most effective sales pitch.

[1093] The server generates sales pitches using a natural language processing (NLP) model (e.g., a generative AI model) based on the collected response data. The input is the collected response data, and the output is the generated sales pitch. Specifically, the server generates a pitch such as, "This plan is a good deal because it has a low monthly fee and a large data capacity."

[1094] Step 5:

[1095] The server matches the facial features with the sales pitch.

[1096] The server uses a generative AI model (e.g. image generation software) to generate an AI character that combines the analyzed facial features with the generated sales pitch. The input is the facial feature data and the sales pitch, and the output is the generated AI character. As a specific operation, the server sets it so that "a character with round eyes and a high nose speaks a speech that emphasizes the low monthly fee."

[1097] Step 6:

[1098] The user interacts with the generated artificial intelligence character.

[1099] The user starts a dialogue with the generated AI character. The input is the user's question or request, and the output is the AI ​​character's response. In concrete terms, when the user asks, "Tell me about the new smartphone plan," the AI ​​character responds, "This plan has a low monthly fee and a large data capacity, so it's good value."

[1100] (Application example 3)

[1101] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server", and the smart glasses 214 will be referred to as a "terminal".

[1102] Conventional online shopping systems have problems in that it is difficult for users to find products that suit their tastes and the purchasing process is complicated. Furthermore, the interaction with users is limited, making it difficult to respond to individual needs. For this reason, a new system is required to improve the user experience and realize an efficient purchasing process.

[1103] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1104] In this invention, the server includes means for generating an AI crew member according to the user's preferences, means for enabling a conversation with the generated AI crew member, means for the AI ​​crew member to handle smartphone-related consultations and contract procedures, means for accumulating and analyzing customer service data of the AI ​​crew member, means for proposing products and supporting purchase procedures according to the user's preferences, means for generating a face of the AI ​​crew member based on the user's preferred facial features, means for generating an optimal sales talk based on the sales talk style, and means for converting the generated sales talk into voice. This enables the user to efficiently select products and complete purchase procedures while enjoying a conversation with the AI ​​crew member of their choice.

[1105] "Means for generating an AI crew member based on user preferences" refers to technology that generates an individually customized AI crew member based on the user's input of preferred facial features, tone of voice, and sales talk style.

[1106] "Means for enabling conversation with the generated AI crew" refers to an interface or communication technology that allows a user to have a natural conversation with the generated AI crew.

[1107] "A means for smartphone-related consultations and contract procedures to be carried out by an AI crew" is a function that enables users to ask questions about smartphones and complete contract procedures through an AI crew.

[1108] "Means of accumulating and analyzing customer service data from AI crews" refers to systems and technologies that store and later analyze data obtained by AI crews through their interactions with users.

[1109] "Means of suggesting products tailored to the user's preferences and supporting the purchasing process" refers to a function that suggests optimal products based on the user's preferences and past purchasing history and assists in the purchasing process.

[1110] "Means for generating an AI crew member's face based on a user's preferred facial features" refers to technology for generating an AI crew member's face based on facial features specified by the user.

[1111] The "means for generating an optimal sales talk based on the sales talk style" is a technology for generating an optimal sales talk based on the user's preferences and an effective sales talk style.

[1112] The "means for converting the generated sales talk into speech" refers to a technology for converting the generated sales talk from text to speech.

[1113] The system for implementing this invention generates an AI crew member according to the user's preferences, and supports product suggestions and purchase procedures through conversations with the generated AI crew member. A specific embodiment of this system will be described below.

[1114] Hardware and Software Used

[1115] Hardware: Smartphone

[1116] software:

[1117] Generative AI models (e.g. OpenAI GPT-4)

[1118] Facial feature generation models (e.g. DeepFaceLab)

[1119] A text-to-speech engine (e.g. Google Text-to-Speech)

[1120] A database (e.g. Firebase)

[1121] System Configuration

[1122] 1. COLLECTING USER INFORMATION:

[1123] When a user launches the app for the first time, they input their preferred facial features, tone of voice, and sales pitch style.

[1124] This information is stored in the Firebase database.

[1125] 2. AI Crew Generation:

[1126] DeepFaceLab is used to generate an AI crew member's face based on the user's preferred facial features.

[1127] Based on your sales pitch style, OpenAI GPT-4 is used to generate the optimal sales pitch.

[1128] Use Google Text-to-Speech to convert the generated sales pitch into audio.

[1129] 3. Providing a conversation interface:

[1130] When a user searches for a product using the app, the AI ​​crew will suggest products that match the user's preferences.

[1131] When a user asks a question or asks for advice, the AI ​​crew will provide appropriate answers and suggestions.

[1132] 4. Purchasing assistance:

[1133] Once a user decides to make a purchase, an AI crew member will guide them through the purchase process.

[1134] Enter the necessary information and we will support you until the purchase is complete.

[1135] Examples

[1136] When a user types, "I'm looking for a new smartphone," the AI ​​crew will suggest, "Hello! We've found the perfect smartphone for you. How about this model? It features the latest camera features and a long-lasting battery," and explain the details of the product.

[1137] Examples of prompt statements

[1138] User: I'm looking for a new smartphone.

[1139] AI Crew: Hello! We've found the perfect smartphone for you. How about this model? It features the latest camera features and a long-lasting battery.

[1140] In this way, users can efficiently select products and complete purchase procedures while enjoying conversations with their preferred AI crew members. This system improves the user experience and makes online shopping more comfortable and convenient.

[1141] The flow of the specific process in the application example 3 will be described with reference to FIG.

[1142] Step 1:

[1143] Collection of User Information

[1144] Input: When users first launch the app, they input their preferred facial features, tone of voice, and sales pitch style.

[1145] Processing: The device collects the information entered by the user and stores it in the Firebase database.

[1146] Output: User preferences stored in Firebase database.

[1147] Step 2:

[1148] AI Crew Generation

[1149] Input: User preferences stored in your Firebase database.

[1150] Processing: The server uses DeepFaceLab to generate an AI crew member's face based on the user's preferred facial features, then uses OpenAI GPT-4 to generate the optimal sales pitch based on the sales pitch style, and finally converts the generated sales pitch into audio using Google Text-to-Speech.

[1151] Output: An AI crew member with a face and sales pitch tailored to the user's preferences is generated.

[1152] Step 3:

[1153] Providing a conversational interface

[1154] Input: A user uses the app to search for a product.

[1155] Processing: The device receives the user's search query and sends it to the server, which then uses the generated AI crew to suggest products that match the user's preferences.

[1156] Output: The AI ​​crew will provide product suggestions to the user.

[1157] Step 4:

[1158] Responding to user questions and inquiries

[1159] Input: The user types a question or request into the AI ​​crew.

[1160] Processing: The device receives the user's question or inquiry and sends it to the server, which uses OpenAI GPT-4 to generate appropriate answers or suggestions and converts them into audio using Google Text-to-Speech.

[1161] Output: The AI ​​crew will provide appropriate answers and suggestions to the user.

[1162] Step 5:

[1163] Purchase procedure support

[1164] Input: The user makes a purchase decision.

[1165] Processing: The device receives the user's purchase decision and sends it to the server, which then guides the AI ​​crew through the purchase process and asks them to enter the necessary information.

[1166] Output: The user completes the purchase.

[1167] In this way, users can efficiently select products and complete the purchase process while enjoying a conversation with their preferred AI crew.

[1168] In addition, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1169] "Example 1"

[1170] As one embodiment of the present invention, there is a system including an emotion engine in which an AI crew recognizes the emotions of a user. In this system, the AI ​​crew reads the emotions of a user through conversation with the user. For example, if the user feels angry, the AI ​​crew sends that information to the emotion engine. The emotion engine analyzes the information and instructs the AI ​​crew to respond to calm the user.

[1171] "Example 2"

[1172] Furthermore, there is also a system including a means for the emotion engine to adjust the response of the AI ​​crew member according to the user's emotions. In this system, the emotion engine grasps changes in the user's emotions in real time and adjusts the response of the AI ​​crew member according to the emotions. For example, if the user feels happy, the emotion engine instructs the AI ​​crew member to respond in a way that will make the user even happier.

[1173] "Example 3"

[1174] There is also a system that includes a means for the emotion engine to accumulate and analyze user emotion data and reflect the results in improving the AI ​​crew. In this system, the emotion engine accumulates user emotion data and analyzes the data. The analysis results are used to improve the AI ​​crew. For example, if information is obtained that a particular user is likely to become angry about a particular topic, the information is used to improve the AI ​​crew's response, so that the AI ​​crew will respond in a way that does not make the user angry.

[1175] The process flow of each embodiment will be described below.

[1176] "Example 1"

[1177] Step 1: A conversation is initiated between the user and the AI ​​crew member.

[1178] Step 2: The AI ​​crew reads the user's emotions through conversation.

[1179] Step 3: The AI ​​Crew sends the user's emotions to the emotion engine.

[1180] Step 4: The emotion engine analyzes the transmitted information.

[1181] Step 5: Based on the analysis results, the emotion engine instructs the AI ​​crew on how to calm the user down.

[1182] "Example 2"

[1183] Step 1: A conversation is initiated between the user and the AI ​​crew member.

[1184] Step 2: The emotion engine listens to the conversation in real time and reads changes in the user's emotions.

[1185] Step 3: The emotion engine adjusts the AI ​​crew's response based on the emotions it reads.

[1186] Step 4: For example, if the user feels happy, the emotion engine will instruct the AI ​​crew on how to make the user even happier.

[1187] "Example 3"

[1188] Step 1: A conversation is initiated between the user and the AI ​​crew member.

[1189] Step 2: The emotion engine reads the user's emotions through conversation and accumulates the data.

[1190] Step 3: The emotion engine analyzes the accumulated emotion data.

[1191] Step 4: The analysis results are used to improve the AI ​​crew.

[1192] Step 5: For example, if information is obtained that a particular user is prone to becoming angry about a particular topic, this information can be used to improve the AI ​​crew's response so that the user does not become angry.

[1193] Example 1

[1194] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[1195] Conventional AI assistant systems have the problem that it is difficult to generate an assistant that matches the individual preferences of the user, and they cannot recognize the user's emotions and respond appropriately. Furthermore, there is a lack of means to create an optimal AI assistant through the accumulation and analysis of customer service data.

[1196] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1197] In this invention, the server includes a means for generating an AI assistant according to the user's preferences, a means for enabling a conversation with the generated AI assistant, a means for carrying out consultations and contract procedures related to communication devices using the AI ​​assistant, a means for accumulating and analyzing customer service data of the AI ​​assistant, a means including an emotion engine for recognizing the user's emotions, and a means for providing an appropriate response to the user based on the analysis results of the emotion engine. This makes it possible to generate an AI assistant according to the individual preferences of the user and to provide an appropriate response according to the user's emotions.

[1198] "User" refers to any individual or legal entity that uses the System.

[1199] An "artificial intelligence assistant" is a digital agent that is generated based on the user's preferences and can converse with the user and carry out various procedures.

[1200] "Means for generating" refers to a combination of software and hardware for creating an artificial intelligence assistant based on user input.

[1201] "Conversational enablement" refers to technology that allows an artificial intelligence assistant to communicate with the user in natural language.

[1202] "Means for consultations and contract procedures related to telecommunications devices" refers to functions that enable an artificial intelligence assistant to answer users' questions about telecommunications devices and support contract procedures.

[1203] "Means of accumulating and analyzing customer service data" refers to technology that enables an artificial intelligence assistant to record interactions with users and analyze that data.

[1204] "Emotion engine" refers to a combination of software and hardware for recognizing a user's emotions and analyzing that information.

[1205] "Means of taking appropriate action based on the analysis results" refers to the function that enables the artificial intelligence assistant to take appropriate action toward the user based on the analysis results of the emotion engine.

[1206] An "optimal artificial intelligence assistant" refers to an artificial intelligence assistant that is best suited to a user's preferences and needs through the accumulation and analysis of customer service data.

[1207] "Appearance" refers to the visual characteristics and design of the artificial intelligence assistant.

[1208] "Conversational capabilities" refers to the ability of an artificial intelligence assistant to effectively communicate with users in natural language.

[1209] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[1210] The present invention is a system that generates an artificial intelligence assistant according to the user's preferences, and that converses with the user, provides advice on communication devices, and handles contract procedures. A specific embodiment of this system will be described below.

[1211] System Configuration

[1212] The system consists of a device used by the user, a server that processes the data, a generative AI model, an emotion engine, and software to link these together.

[1213] Hardware and Software Used

[1214] Device: The device used by the user, such as a smartphone or computer.

[1215] Server: A computer system for processing data and running generative AI models.

[1216] Generative AI models: Models for generating artificial intelligence assistants based on user input (e.g., OpenAI's GPT-4).

[1217] Emotion engine: Software for recognising and analysing user emotions (e.g. Affectiva).

[1218] Natural language processing engine: An engine that allows an artificial intelligence assistant to converse with users (e.g. Google Dialogflow).

[1219] Program Processing

[1220] A user inputs his / her preferred characteristics (e.g., face shape, hair color, tone of voice, etc.) using a dedicated application or web interface on a smartphone or PC. For example, a user inputs "hair color is blue, voice tone is calm."

[1221] The device sends the input data to a server, which uses a generative AI model to generate an artificial intelligence assistant based on the user's input. The generation process creates a digital avatar and voice profile that reflects the user's preferred characteristics.

[1222] The generated AI assistant is equipped with a natural language processing engine to enable conversation with the user. In addition, the AI ​​assistant can recognize the user's emotions using an emotion engine.

[1223] Examples

[1224] As a concrete example, consider a scenario in which a user opens an app on their smartphone and enters the following characteristics:

[1225] Example user input:

[1226] Face Shape: Round Face

[1227] Hair Color: Blue

[1228] Tone of voice: Calm

[1229] The device sends this information to the server, which then uses a generative AI model to generate a prompt like this:

[1230] Example prompt for a generative AI model:

[1231] A user wants to create an artificial intelligence assistant with the following characteristics:

[1232] Face Shape: Round Face

[1233] Hair Color: Blue

[1234] Tone of voice: Calm

[1235] Based on this, generate an artificial intelligence assistant that can hold a conversation with the user.

[1236] The server inputs this prompt into a generative AI model to generate an AI assistant that meets the user's needs. The AI ​​assistant can then consult with the user about telecommunications devices and handle contract procedures through conversations with the user. If the user feels angry, the AI ​​assistant sends that information to an emotion engine, which then uses the analysis results to provide instructions on how to calm the user down.

[1237] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1238] Step 1:

[1239] User enters characteristics

[1240] A user inputs his / her preferred features (e.g., face shape, hair color, tone of voice, etc.) using a dedicated application or web interface on a smartphone or PC. The input data is structured in JSON format. For example, a user inputs "hair color is blue, voice tone is calm."

[1241] Step 2:

[1242] The terminal sends the input data to the server

[1243] The device transmits the user-entered feature data in real time to the server, which receives the data structured in JSON format. The input data includes the user's preference details.

[1244] Step 3:

[1245] The server sends a prompt to the generative AI model.

[1246] The server generates a prompt sentence based on the received feature data. The generated prompt sentence specifically describes the features desired by the user. For example, the following prompt sentence is generated:

[1247] A user wants to create an artificial intelligence assistant with the following characteristics:

[1248] Face Shape: Round Face

[1249] Hair Color: Blue

[1250] Tone of voice: Calm

[1251] Based on this, generate an artificial intelligence assistant that can hold a conversation with the user.

[1252] The server sends this prompt to the generative AI model.

[1253] Step 4:

[1254] A generative AI model generates an AI crew

[1255] The generative AI model generates a personalized AI assistant based on the prompt text. In the process, a digital avatar and voice profile are created. The generated AI assistant has the user's preferred characteristics.

[1256] Step 5:

[1257] The server sends the generated AI crew to the device.

[1258] The server transmits the generated AI assistant data to the terminal. This data includes a 3D model of the AI ​​assistant and audio files. The terminal receives this data.

[1259] Step 6:

[1260] The device displays the AI ​​crew and starts a conversation with the user.

[1261] The device displays the AI ​​assistant on the screen based on the received AI assistant data. The user can start a conversation with the AI ​​assistant. For example, the user asks, "What's the weather like today?"

[1262] Step 7:

[1263] AI Crew uses emotion engine to recognize user emotions

[1264] The AI ​​assistant uses the emotion engine to recognize the user's emotions through conversation with the user. For example, if the user is angry, it sends that information to the emotion engine. The emotion engine analyzes the user's tone of voice and facial expressions.

[1265] Step 8:

[1266] The emotion engine sends the analysis results to the AI ​​crew.

[1267] The emotion engine analyzes the received emotion data and sends the results to the AI ​​assistant. The analysis results contain detailed information about the user's emotional state. For example, the result "The user is angry" may be sent.

[1268] Step 9:

[1269] AI crew responds appropriately to users

[1270] The AI ​​assistant responds appropriately to the user based on the analysis results of the emotion engine. For example, if the user is angry, the AI ​​assistant will say to the user, "Please calm down. Is there anything I can help you with?"

[1271] (Application example 1)

[1272] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[1273] Conventional customer service systems have difficulty recognizing customer emotions in real time and responding appropriately. It is also difficult to provide personalized responses that match the customer's preferences. This has made it difficult to improve customer satisfaction.

[1274] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1275] In this invention, the server includes a means for generating an AI crew member according to the user's preferences, a means for enabling a conversation with the generated AI crew member, a means for the AI ​​crew member to handle consultations and contract procedures related to smart devices, a means for accumulating and analyzing customer service data of the AI ​​crew member, a means for recognizing the user's emotions and generating an appropriate response, and a means for displaying the generated response. This makes it possible to recognize the customer's emotions in real time and provide personalized responses.

[1276] "User" means an individual or legal entity that uses the System.

[1277] "Preferences" are personal tastes or preferences that a user has for particular features or attributes.

[1278] "AI Crew" is a virtual assistant generated using artificial intelligence that interacts with users and provides services.

[1279] A "means for generating" is a method or apparatus for creating an AI crew member based on user input.

[1280] A "conversational means" is a method or device that allows the user and the AI ​​crew to communicate through voice or text.

[1281] A "smart device" is an electronic device with Internet connectivity, such as a smartphone or smart glasses.

[1282] "Means for consultation and contract procedures" refers to a method or device that allows a user to ask questions about a smart device or complete contract procedures through an AI crew.

[1283] "Customer service data" refers to information collected by the AI ​​crew through conversations with users.

[1284] "Means of storing and analyzing" refers to methods and devices for storing and analyzing collected customer service data.

[1285] "Means for recognizing emotions" refers to a method or device for determining emotions from a user's facial expressions, tone of voice, etc.

[1286] A "means for generating an appropriate response" is a method or apparatus for determining an optimal response or action for a user based on a recognized emotion.

[1287] A "means for displaying" is a method or device for visually presenting the generated correspondence to a user.

[1288] The system for implementing this invention generates an AI crew member according to the user's preferences, recognizes the user's emotions through conversation with the generated AI crew member, and responds appropriately. A specific embodiment of this system will be described below.

[1289] First, the server receives information about the user's preferences and generates an AI crew member based on this. The user inputs preferences such as face shape, hair color, and tone of voice through a smart device. The server analyzes this information and uses a generative AI model to create an AI crew member that matches the user's preferences.

[1290] Next, the generated AI crew can converse with the user. The user can communicate with the AI ​​crew by voice or text through a smart device. The content of the conversation is analyzed in real time and the user's emotions are recognized. The EmotionRecognition library is used for emotion recognition.

[1291] In addition, the server generates an appropriate response based on the user's emotions. For example, if the user is angry, the AI ​​crew will generate a response such as "Sir, please let us know if there is anything we can help you with." This response is determined using a generative AI model.

[1292] The generated response is displayed on the display of the smart device, allowing the user to receive appropriate responses from the AI ​​crew. Devices such as smart glasses and smartphones are used for display.

[1293] As a concrete example, the following prompt sentence can be input into a generative AI model to generate an appropriate response:

[1294] "If the customer emotion is identified as 'anger', generate an appropriate response."

[1295] This system will be able to recognize user emotions in real time and provide personalized responses, which is expected to improve customer satisfaction.

[1296] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1297] Step 1:

[1298] Users use their smart devices to input preferences such as face shape, hair color, and tone of voice.

[1299] Input: Information about the user's preferences (face shape, hair color, tone of voice, etc.)

[1300] Output: User preference data

[1301] Specific operations: The user inputs preferred features into the application interface via a smartphone or smart glasses.

[1302] Step 2:

[1303] The server receives the user's preference data and generates an AI crew using a generative AI model.

[1304] Input: User preference data

[1305] Output: Generated AI crew

[1306] Specific operation: The server analyzes the received preference data and inputs it into a generative AI model to create an AI crew that matches the user's preferences.

[1307] Step 3:

[1308] The generated AI crew will begin a conversation with the user.

[1309] Input: Conversational data from the user (voice or text)

[1310] Output: Response data from AI crew

[1311] Specific operation: The user communicates with the AI ​​crew via voice or text through a smart device. The AI ​​crew responds.

[1312] Step 4:

[1313] The server analyzes the conversation data in real time and recognizes the user's emotions using the EmotionRecognition library.

[1314] Input: Conversation data from the user

[1315] Output: User emotion data

[1316] Specific operation: The server inputs the conversation data into the EmotionRecognition library and determines the user's emotions.

[1317] Step 5:

[1318] The server uses a generative AI model to generate an appropriate response based on the user's emotional data.

[1319] Input: User emotion data

[1320] Output: Appropriate corresponding data

[1321] Specific operation: The server analyzes the emotion data and inputs a prompt sentence into the generative AI model to generate an appropriate response. For example, a prompt sentence such as "If the customer's emotion is recognized as 'anger,' please generate an appropriate response" can be used.

[1322] Step 6:

[1323] The generated response is displayed on the smart device display.

[1324] Input: Appropriate corresponding data

[1325] Output: The corresponding message that is displayed to the user.

[1326] Specific operation: The server sends the generated response data to the smart device and displays it on the display, allowing the user to visually confirm the appropriate response from the AI ​​crew.

[1327] Example 2

[1328] Next, a description will be given of Example 2 of the embodiment 2. In the following description, the data processing device 12 is referred to as a "server" and the smart glasses 214 are referred to as a "terminal".

[1329] Conventional AI assistant systems had the problem of not responding adequately to the user's emotions, which did not improve the user experience. In addition, the accumulation and analysis of customer service data was insufficient, making it difficult to create an optimal AI assistant.

[1330] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for generating an AI assistant according to the user's preferences, a means for enabling a conversation with the generated AI assistant, a means for carrying out consultations and contract procedures related to communication devices by the AI ​​assistant, a means for accumulating and analyzing customer service data of the AI ​​assistant, and a means for analyzing the user's emotions in real time and adjusting the response of the AI ​​assistant according to the emotions. This enables optimal response according to the user's emotions, improving the user experience and creating an optimal AI assistant.

[1331] "User" refers to any individual or legal entity that uses the System.

[1332] An "artificial intelligence assistant" refers to artificial intelligence generated to interact with users and handle contract procedures.

[1333] "Means for generating" refers to methods or techniques for creating an artificial intelligence assistant based on a user's preferences.

[1334] "Conversational enablement" refers to methods and technologies that allow a user to interact with an artificial intelligence assistant.

[1335] "Consultations and contract procedures related to telecommunications devices" refers to questions and contract procedures related to smartphones and other telecommunications devices.

[1336] "Means of storage" refers to the methods and technologies that an artificial intelligence assistant uses to store the data it obtains from its interactions with users.

[1337] "Means of analysis" refers to the methods and techniques used to analyze accumulated data and extract meaningful information.

[1338] "Means of analyzing emotions in real time" refers to methods and technologies for instantly determining a user's emotions from their statements and facial expressions.

[1339] "Means for tailoring responses" refers to methods or techniques for modifying the responses or behavior of an artificial intelligence assistant based on the analyzed emotions.

[1340] An "optimal artificial intelligence assistant" refers to an artificial intelligence assistant that can respond in a way that is most appropriate to the user's preferences and emotions.

[1341] A "dialogue script" refers to a set of responses and / or questions that an artificial intelligence assistant uses to interact with a user.

[1342] This invention is a system that generates an AI assistant according to the user's preferences, and communicates with the user and handles contract procedures. It also includes a function that analyzes the user's emotions in real time and adjusts the AI ​​assistant's response according to those emotions.

[1343] The server first generates an artificial intelligence assistant based on the user's preferences. A generative AI model is used for this generation. The generated artificial intelligence assistant uses natural language processing (NLP) techniques to enable conversation with the user. Specifically, it uses libraries such as Python's NLTK and spaCy.

[1344] Next, the server collects data obtained by the AI ​​assistant through conversations with the user and through contract procedures, and stores it in a database, including what the user said, the contents of the contract, time, location, etc. The accumulated data will be analyzed later.

[1345] The server uses data analysis tools to analyze the accumulated data. Specifically, it uses Python and R to analyze the data. In particular, it uses natural language processing technology to analyze the content of user comments and perform sentiment analysis.

[1346] The emotion engine analyzes the user's remarks and facial expressions to grasp changes in the user's emotions in real time. The emotion engine adjusts the AI ​​assistant's response according to different emotional states, such as when the user is happy or angry. For example, if the emotion engine determines that the user is happy, it instructs the AI ​​assistant to respond in a way that will make the user even happier. This instruction is executed by dynamically changing the AI ​​assistant's dialogue script.

[1347] Examples

[1348] Example 1: Collecting and storing conversation data with users

[1349] If a user says to an artificial intelligence assistant, "I'm so happy to have found a new job today," the server will collect this statement in real time and store it in a database as follows:

[1350] User ID: 67890

[1351] What he said: I got a new job today and I'm very happy.

[1352] Speaking time: 2023-10-01 11:00:00

[1353] Contract details: None

[1354] Example 2: Emotion engine behavior and corresponding adjustment of artificial intelligence assistant

[1355] If a user says, "I got a new job today and I'm so happy," the emotion engine analyzes the statement and determines that the user is happy. Based on this analysis, the server instructs the AI ​​assistant to respond with something like, "That's great! Tell me more about your new job."

[1356] Examples of prompt statements

[1357] Examples of prompt sentences to be input to a generative AI model include the following:

[1358] If a user says, "Today I got a new job and I'm so happy," explain how the emotion engine would adjust its response.

[1359] By feeding this prompt into the generative AI model, we can get a detailed explanation of the emotion engine's specific behavior and how to respond.

[1360] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1361] Step 1: Generate an artificial intelligence assistant based on user preferences

[1362] The server generates an artificial intelligence assistant based on the user's preferences and requests. As input, it receives data on the user's preferences and requests. It uses a generative AI model to create an artificial intelligence assistant that matches the user's preferences. As output, it obtains the generated artificial intelligence assistant. As a specific operation, an artificial intelligence assistant with an appearance and dialogue script that reflects the user's preferences is generated.

[1363] Step 2: Start a conversation with the user

[1364] The user initiates a conversation with the AI ​​assistant through the device. As input, the user's statements and questions are sent to the server through the device. The server uses natural language processing technology to analyze the user's statements and generate an appropriate response. As output, the AI ​​assistant's response is returned to the user. Specifically, Python's NLTK and spaCy libraries are used to analyze the content of the user's statements and generate an appropriate response.

[1365] Step 3: Collect and store conversation data

[1366] The server collects conversation data with the user in real time and stores it in a database. Data such as the content of the user's comments, the time of the comments, and the place where the comments were made are collected as input. The server saves this data in the database. The accumulated conversation data is obtained as output. In concrete terms, the content of the user's comments and the details of the contract are saved in the database in chronological order.

[1367] Step 4: Analyze the data

[1368] The server analyzes the accumulated conversation data. The conversation data stored in the database is used as input. The server analyzes the data using natural language processing technology to extract the user's emotions and tendencies. The analysis results are obtained as output. In concrete terms, data analysis is performed using Python and R to analyze the content of the user's comments and their emotional state.

[1369] Step 5: Sentiment analysis using the emotion engine

[1370] The server uses an emotion engine to analyze the user's emotions in real time. The user's remarks and facial expression data are used as input. The emotion engine analyzes this data and determines the user's emotional state. The user's emotional state is obtained as output. Specifically, analysis is performed to instantly determine emotions from the user's remarks and facial expressions.

[1371] Step 6: Adjusting the AI ​​assistant’s response

[1372] The server adjusts the response of the artificial intelligence assistant based on the analysis results of the emotion engine. The analysis results of the emotion engine are used as input. The server dynamically changes the dialogue script of the artificial intelligence assistant based on the analysis results. The adjusted dialogue script is obtained as output. As a specific operation, the response content of the artificial intelligence assistant is changed so that the optimal response according to the user's emotions is performed.

[1373] Step 7: Creating the perfect artificial intelligence assistant

[1374] The server creates an optimal AI assistant based on the accumulated data and analysis results. Past conversation data and analysis results are used as input. The server analyzes this data and generates an AI assistant that best suits the user's preferences and emotions. The optimal AI assistant is obtained as output. As a specific operation, an AI assistant with an appearance and dialogue script that matches the user's preferences and emotions is generated.

[1375] (Application example 2)

[1376] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server", and the smart glasses 214 will be referred to as a "terminal".

[1377] With conventional customer service systems, it was difficult to respond to the user's emotions, and customer service data was not sufficiently accumulated and analyzed, making it difficult to provide optimal customer service. Furthermore, customer service support in physical stores was insufficient, making it difficult to improve customer satisfaction.

[1378] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1379] In this invention, the server includes a means for generating an AI crew member according to the user's preferences, a means for enabling a conversation with the generated AI crew member, a means for the AI ​​crew member to handle consultations and contract procedures related to smart devices, a means for accumulating and analyzing customer service data of the AI ​​crew member, a means for adjusting the AI ​​crew member's response according to the user's emotions using an emotion engine, and a means for providing a smart customer service assistant to support customer service in a physical store. This makes it possible to provide optimal customer service according to the user's emotions and improve customer satisfaction in a physical store.

[1380] "Means of generating an AI crew according to the user's preferences" refers to a function that automatically creates an optimal AI crew based on the user's individual preferences and needs.

[1381] "Means for enabling conversation with the generated AI crew" refers to a function that allows a user to have natural conversations with the generated AI crew.

[1382] "A means for AI crew to handle smart device-related consultations and contract procedures" is a function that allows AI crew to handle questions and contract procedures related to devices such as smartphones and tablets.

[1383] "Means of accumulating and analyzing customer service data from AI crews" refers to a function that collects and analyzes data obtained by the AI ​​crews through their interactions with users.

[1384] "A means for adjusting the AI ​​crew's response in accordance with the user's emotions using an emotion engine" is a function that analyzes the user's emotional state in real time and appropriately adjusts the AI ​​crew's responses based on the results.

[1385] "A means of providing a smart customer service assistant to support customer service in physical stores" is a function that enables AI crew members to assist in customer service in physical stores and improve customer satisfaction.

[1386] The following system configuration is used as an embodiment of the present invention. The system includes a means for generating an AI crew member according to the user's preferences, a means for enabling a conversation with the generated AI crew member, a means for the AI ​​crew member to handle consultations and contract procedures related to smart devices, a means for accumulating and analyzing customer service data of the AI ​​crew member, a means for adjusting the response of the AI ​​crew member according to the user's emotions using an emotion engine, and a means for providing a smart customer service assistant to support customer service in physical stores.

[1387] Hardware and Software Configuration

[1388] Hardware:

[1389] Smartphones, smart glasses, head-mounted displays

[1390] software:

[1391] Python

[1392] scikit-learn (for data analysis)

[1393] sentiment_analysis (a custom library for sentiment analysis)

[1394] ai_assistant (custom library of AI crew)

[1395] Data processing and calculation

[1396] server:

[1397] The server collects user interaction data and stores it in a database. The collected data is analyzed using a clustering method (KMeans) with scikit-learn, which clarifies the user's preferences and behavioral patterns.

[1398] Device:

[1399] The device (smartphone, smart glasses, head-mounted display) enables real-time interaction with the user. The emotion engine uses the sentiment_analysis library to analyze the user's emotions and adjust the AI ​​crew's response based on the results.

[1400] User:

[1401] The user interacts with the AI ​​crew through the terminal to ask questions about smart devices and to complete contract procedures. Depending on the user's emotional state, the AI ​​crew will provide appropriate responses.

[1402] Examples

[1403] For example, if a user says, "I'm having so much fun today!", the emotion engine will detect the positive emotion and suggest a way to make the user even happier. In this way, the system can provide optimal customer service according to the user's emotions.

[1404] Examples of prompt statements

[1405] “If a user says, ‘I’m having so much fun today!’ detect that positive emotion and prescribe a response that will make the user even happier.”

[1406] This system will make it possible to improve customer satisfaction in physical stores.

[1407] The flow of the identification process in the application example 2 will be described with reference to FIG.

[1408] Step 1:

[1409] The server collects interaction data with the user. It records the content of the conversation and behavioral data when the user interacts with the AI ​​crew through the terminal in real time and accumulates them in a database. The input is the user's dialogue data, and the output is the accumulated interaction data.

[1410] Step 2:

[1411] The server analyzes the accumulated interaction data. It uses scikit-learn to analyze the data using a clustering method (KMeans) to clarify user preferences and behavioral patterns. The input is the accumulated interaction data, and the output is the clustering results.

[1412] Step 3:

[1413] The terminal enables real-time dialogue with the user. When the user speaks to the terminal, the voice data is converted into text and sent to the AI ​​crew. The input is the user's voice data, and the output is text data.

[1414] Step 4:

[1415] The server analyzes the user's emotions using the emotion engine. It uses the sentiment_analysis library to detect emotions from the user's text data and feeds the results back to the AI ​​crew. The input is the user's text data, and the output is the emotion analysis result.

[1416] Step 5:

[1417] The AI ​​Crew tailors its response based on the sentiment analysis results: if positive sentiment is detected, it responds to make the user more pleased, and if negative sentiment is detected, it responds to comfort. The input is the sentiment analysis results, and the output is the tailored response.

[1418] Step 6:

[1419] The terminal provides the adjusted response to the user, or communicates the response from the AI ​​crew to the user via voice or text. The input is the adjusted response, and the output is the feedback to the user.

[1420] Step 7:

[1421] The server provides a smart customer service assistant to support customer service in brick-and-mortar stores. Based on the AI ​​crew's response data and the results of emotion analysis, the server optimizes the customer service strategy in the brick-and-mortar store. The input is the AI ​​crew's response data and the results of emotion analysis, and the output is the optimized customer service strategy.

[1422] Example 3

[1423] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[1424] Conventional AI character systems do not adequately generate characters that match the user's preferences or respond to the user's emotions, resulting in limited user experience. In addition, when consulting about communication devices or going through contract procedures, the system is unable to respond optimally based on the user's emotional data, which may result in reduced user satisfaction. To solve these issues, there is a demand for a system that can generate AI characters that reflect the user's preferences and emotional data and provide optimal sales pitches.

[1425] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1426] In this invention, the server includes means for generating an AI character according to the user's preferences, means for enabling conversation with the generated AI character, means for carrying out consultations and contract procedures related to communication devices using the AI ​​character, means for accumulating and analyzing customer service data of the AI ​​character, means for collecting and analyzing user emotion data, and means for improving the AI ​​character's response based on the analysis results. This makes it possible to generate an optimal AI character according to the user's preferences and emotions, and provide a service that provides high user satisfaction.

[1427] "User" means an individual or legal entity that uses the System.

[1428] An "artificial intelligence character" is a virtual being that is generated based on the user's preferences and is capable of conversation and other actions.

[1429] "Means of generation" refers to methods and technologies for creating an artificial intelligence character based on user preference data.

[1430] "Means for enabling conversation" refers to methods or technologies that allow a user to interact with an artificial intelligence character.

[1431] "Means of consultation and contract procedures related to telecommunications devices" refers to methods and technologies that allow users to ask questions about telecommunications devices or make contracts through artificial intelligence characters.

[1432] "Customer service data" is information that artificial intelligence characters collect through their interactions with users.

[1433] "Means of storage and analysis" refers to the methods and technologies for storing and analyzing collected data.

[1434] "Emotion data" refers to information about emotions obtained from the user's facial expressions, tone of voice, etc.

[1435] "Means of collection and analysis" refers to methods and technologies for obtaining emotion data and analyzing it.

[1436] "Means for improving response" refers to methods and technologies for optimizing the responses and actions of artificial intelligence characters based on the results of analysis.

[1437] An "optimal AI character" is an AI character that reflects the user's preferences and emotional data and delivers the most effective sales pitch.

[1438] "Sales talk" refers to the way of speaking and the content of a sales pitch used to introduce a product or service to a user and encourage them to sign a contract.

[1439] The present invention is a system for generating an AI character according to the user's preferences and for carrying out consultations and contract procedures related to communication devices. A specific embodiment of this system will be described below.

[1440] System Overview

[1441] The system generates an AI character that combines the user's preferred facial features with the most effective sales pitch. Users can enjoy conversations with this character while consulting about telecommunications devices or completing contract procedures. The emotion engine also accumulates and analyzes the user's emotional data, and reflects the results in improving the AI ​​character.

[1442] Hardware and Software Used

[1443] Terminal: A device through which a user accesses the system, such as a smartphone or PC.

[1444] Server: A server for processing data and running generative AI models.

[1445] Generative AI models: Models for generating sales pitches, such as OpenAI's GPT-4.

[1446] Generative models: Models such as StyleGAN that generate facial features that suit the user's preferences.

[1447] Emotion recognition software: Software used to collect and analyze user emotion data, such as Microsoft Azure's Emotion API.

[1448] Program Processing

[1449] Get the user's preferred facial features

[1450] A user accesses the system using a terminal and inputs the facial features they prefer. Specifically, the user selects eye shape, hairstyle, skin color, etc. on the interface. For example, a user may input "a face with big eyes and a nice smile" as their preference.

[1451] Sales pitch generation

[1452] The server receives the user's input data and uses a generative AI model (e.g., OpenAI's GPT-4) to generate the most effective sales pitch. For example, it generates a "sales pitch for a new smartphone plan."

[1453] AI character generation

[1454] The server generates a facial image using an image generation model (e.g., StyleGAN) based on the user's preferred facial features. Then, it combines the generated sales pitch with the facial image to generate an AI character. For example, an AI character with big eyes and a lovely smile gives a sales pitch about a new smartphone plan.

[1455] Talk to users

[1456] The user uses the device to start a conversation with the generated AI character. The user can ask for advice or complete contract procedures related to telecommunications devices. For example, the user might ask, "What is the plan for my new smartphone?"

[1457] Collecting and analyzing emotion data

[1458] The server uses an emotion engine (e.g., Microsoft Azure's Emotion API) to collect the user's emotion data in real time. Emotion data is obtained from the user's facial expressions, tone of voice, etc. For example, it detects whether the user is smiling or angry.

[1459] Improved AI characters

[1460] The server analyzes the collected emotion data and improves the AI ​​character's response. For example, if the server learns that a certain user is prone to getting angry about a certain topic, it can adjust the AI ​​character's response based on that information. This allows the AI ​​character to respond in a way that does not make the user angry.

[1461] Examples and prompts

[1462] Examples

[1463] A user accesses the system and inputs "a face with big eyes and a nice smile" as their preference. The server uses the generative AI model to generate a "sales pitch for a new smartphone plan." The generated AI character has the facial features the user prefers and delivers an effective sales pitch.

[1464] Examples of prompt statements

[1465] "Users input their preferred facial features, such as eye shape, hairstyle, skin color, etc."

[1466] "Generate a sales pitch for a new smartphone plan."

[1467] In this way, the user can consult about communication devices or carry out contract procedures while enjoying a conversation with the AI ​​character of his / her choice. The flow of the specific process in the third embodiment will be described with reference to FIG.

[1468] Step 1:

[1469] The user inputs preferred facial features.

[1470] A user accesses the system using a terminal and selects preferred facial features such as eye shape, hairstyle, skin color, etc. on the interface. For example, a user may input "big eyes and a nice smile" as their preference. The input data is sent to the server.

[1471] Step 2:

[1472] The server receives the input data and generates a sales pitch using a generative AI model.

[1473] The server receives the preferred facial feature data sent by the user. It then sends prompt sentences to a generative AI model (e.g., OpenAI's GPT-4) to generate the most effective sales pitch. For example, it generates a "sales pitch about a new smartphone plan." The generated sales pitch is stored on the server.

[1474] Step 3:

[1475] The server combines the user's preferred facial features with the generated sales pitch to generate an AI character.

[1476] The server sends a prompt to an image generation model (e.g., StyleGAN) based on the user's preferred facial features to generate a facial image. The server then combines the generated sales pitch with the facial image to generate an AI character. For example, an AI character with big eyes and a lovely smile gives a sales pitch about a new smartphone plan. The generated AI character is stored on the server.

[1477] Step 4:

[1478] The user initiates a conversation with an artificial intelligence character.

[1479] The user uses the terminal to start a conversation with the generated AI character. The user can ask for advice on communication devices or make contracts. For example, the user asks, "Please tell me about the plan for my new smartphone." The user's input is sent to the server, and the AI ​​character responds.

[1480] Step 5:

[1481] The server uses an emotion engine to collect emotion data of the user.

[1482] The server uses an emotion engine (e.g., Microsoft Azure's Emotion API) to collect the user's emotion data in real time. The emotion data is obtained from the user's facial expressions and tone of voice. For example, it detects whether the user is smiling or angry. The collected emotion data is stored on the server.

[1483] Step 6:

[1484] The server analyzes the emotional data and improves the responses of the artificial intelligence characters.

[1485] The server analyzes the collected emotion data and improves the AI ​​character's response. For example, if information is obtained that a particular user is prone to becoming angry about a particular topic, the AI ​​character's response can be adjusted based on that information. This allows the AI ​​character to respond in a way that does not anger the user. The analysis results are stored on the server and reflected in the next conversation.

[1486] (Application example 3)

[1487] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server", and the smart glasses 214 will be referred to as a "terminal".

[1488] Conventional AI crews had difficulty providing faces and sales pitches that matched the user's preferences, and could not effectively utilize the user's emotional data to improve service. As a result, the user experience did not improve, and improving customer satisfaction was an issue, especially in physical stores.

[1489] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1490] In this invention, the server includes a means for generating an AI crew member according to the user's preferences, a means for enabling a conversation with the generated AI crew member, a means for recognizing the user through a smart device, a means for generating a face that the user likes, a means for providing an effective sales pitch, a means for accumulating and analyzing the user's emotional data, a means for improving the AI ​​crew member's response based on the analysis results, a means for the AI ​​crew member to handle smartphone-related consultations and contract procedures, and a means for accumulating and analyzing the customer service data of the AI ​​crew member. This makes it possible to provide an AI crew member with a face and sales pitch that matches the user's preferences, and to improve the response based on the user's emotional data.

[1491] "Means for generating an AI crew based on user preferences" refers to technology that automatically creates an optimal AI crew based on the user's individual preferences and characteristics.

[1492] "Means for enabling conversation with the generated AI crew" refers to technology that provides an interface or algorithm that allows users to engage in natural conversation with the generated AI crew.

[1493] "Means of recognizing a user through a smart device" refers to technology that uses a device such as a smartphone or smart glasses to recognize the user's face or other features.

[1494] "Means for generating a face that suits the user's preferences" refers to technology that generates an AI crew face with optimal facial features based on the user's preferences and requests.

[1495] "Means for providing an effective sales pitch" refers to technology that generates and provides the most effective sales pitch depending on the user's characteristics and situation.

[1496] "Means for accumulating and analyzing user emotional data" refers to technology that collects data on the user's emotions and analyzes it to understand the user's emotional state.

[1497] "Means for improving the AI ​​crew's response based on the analysis results" refers to technology that optimizes and improves the AI ​​crew's response methods based on the results of analysis of users' emotional data.

[1498] "A means for handling smartphone-related inquiries and contract procedures through an AI crew" refers to technology that allows users to ask questions about smartphones and complete contract procedures through an AI crew.

[1499] "Means of accumulating and analyzing customer service data of AI crews" refers to technology that collects data on when the AI ​​crews serve users and analyzes it to evaluate the performance of the AI ​​crews.

[1500] The system for implementing the present invention generates an AI crew member according to the user's preferences and enables conversation with the generated AI crew member. A specific embodiment of this system will be described below.

[1501] 1. System Configuration

[1502] The system consists of the following main components:

[1503] Server: Generates AI crew members based on user preferences, and accumulates and analyzes emotional data.

[1504] Terminal: Includes smart devices such as smartphones and smart glasses. Users are recognized through these devices and can converse with the AI ​​crew.

[1505] User: An individual who uses the system.

[1506] 2. Hardware and Software Used

[1507] Hardware: Smartphones, smart glasses

[1508] Software: OpenCV, DeepFace, GPT-3

[1509] 3. Data processing and calculation

[1510] User Awareness

[1511] The terminal captures the user's face through a smart device and uses DeepFace to analyze the user's age, gender, and emotions, thereby obtaining basic information about the user.

[1512] Face Generation

[1513] The server runs an algorithm to generate a face that matches the user's preferences. Based on the user's information, it generates an AI crew member's face with optimal facial features.

[1514] Sales pitch generation

[1515] The server uses GPT-3 to generate effective sales pitches based on user information. The generated sales pitches are optimized according to the user's characteristics and circumstances.

[1516] sentiment analysis

[1517] The server accumulates and analyzes the user's emotional data, which allows the user's emotional state to be understood.

[1518] Response improvement

[1519] The server optimizes and improves the AI ​​crew's response methods based on the analysis results of the emotion data, enabling the AI ​​crew to respond optimally according to the user's emotions.

[1520] 4. Specific Examples

[1521] User Information

[1522] Age: 30

[1523] Gender: Male

[1524] Emotion: Joy

[1525] Generated sales pitch

[1526] "Hello! What products are you looking for today?"

[1527] Examples of prompt statements

[1528] User Age: 30, Gender: Male, Emotion: Joy

[1529] In this way, AI crew members with faces and sales pitches tailored to the user's preferences can be provided, making it possible to improve service based on the user's emotional data.

[1530] The flow of the specific process in the application example 3 will be described with reference to FIG.

[1531] Step 1:

[1532] The terminal captures the user's face using a smart device. The input is the user's face image, and the output is face image data. Specifically, the terminal captures the user's face using a camera on a smartphone or smart glasses.

[1533] Step 2:

[1534] The device inputs the captured facial image into DeepFace to analyze the user's age, gender, and emotions. The input is facial image data, and the output is age, gender, and emotional information. Specifically, the device uses the DeepFace library to analyze the facial image and obtain basic information about the user.

[1535] Step 3:

[1536] The server receives the user's age, gender, and emotional information and generates a face of the user's preference. The input is the user's basic information, and the output is the generated facial image. Specifically, the server runs a face generation algorithm based on the user information to generate an AI crew member's face with optimal facial features.

[1537] Step 4:

[1538] The server generates a prompt sentence based on the user information and inputs it into GPT-3 to generate an effective sales pitch. The input is user information and a prompt sentence, and the output is a sales pitch. The specific operation is to create a prompt sentence and input it into the GPT-3 model to generate a sales pitch.

[1539] Step 5:

[1540] The server accumulates and analyzes the emotional data obtained during the dialogue with the user. The input is the emotional data during the dialogue, and the output is the analysis result. Specifically, the server stores the emotional data in a database and uses an analysis algorithm to grasp the user's emotional state.

[1541] Step 6:

[1542] The server optimizes and improves the AI ​​crew's response methods based on the analysis results of the emotion data. The input is the analysis results of the emotion data, and the output is the improved response method. In concrete terms, the server adjusts the response algorithm based on the analysis results and provides the optimal response according to the user's emotions.

[1543] Step 7:

[1544] The terminal displays the generated face image and sales pitch to the user and starts a dialogue. The input is the generated face image and sales pitch, and the output is a dialogue with the user. In concrete terms, the system displays the face image on the screen of the smart device and provides the sales pitch to the user in voice or text.

[1545] 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 a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1546] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1547] Another example of generative AI is Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1548] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1549] [Third embodiment]

[1550] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1551] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1552] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a wide area network (WAN) and / or a local area network (LAN).

[1553] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1554] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs the voice according to instructions from the processor 46.

[1555] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[1556] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[1557] Fig. 6 shows an example of main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1558] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32, and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1559] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1560] In the headset type terminal 314, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50, and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1561] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1562] "Example 1"

[1563] One embodiment of the present invention is a system that allows a user to generate an AI crew member based on their preferences. Specifically, the user inputs their preferred features (e.g., face shape, hair color, tone of voice, etc.), and an AI crew member is generated based on the input. The generated AI crew member can converse with the user and can provide smartphone-related advice and handle contract procedures. "Example 2"

[1564] Furthermore, a system for accumulating and analyzing customer service data of AI crew members is also one embodiment of the present invention. Specifically, the system accumulates data that AI crew members obtain through conversations with users and contract procedures, and analyzes that data to create the strongest AI crew members.

[1565] "Example 3"

[1566] The best AI crew members have the face that the user likes and the best sales pitch. Specifically, they are generated by combining the facial features that the user likes the most with the most effective sales pitch. In this way, users can enjoy conversations with their favorite AI crew members while consulting about smartphones or completing contract procedures.

[1567] The process flow of each embodiment will be described below.

[1568] "Example 1"

[1569] Step 1: The user inputs their preferred features (e.g. face shape, hair color, tone of voice, etc.) into the system.

[1570] Step 2: The system generates an AI crew based on the input features.

[1571] Step 3: The generated AI crew can converse with the user and handle smartphone-related inquiries and contract procedures.

[1572] "Example 2"

[1573] Step 1: The AI ​​crew accumulates data obtained through conversations with users and contract procedures.

[1574] Step 2: The system analyzes the accumulated data.

[1575] Step 3: Create the strongest AI crew based on the analysis results.

[1576] "Example 3"

[1577] Step 1: The system generates the strongest AI crew by combining the user's most preferred facial features with the most effective sales pitches.

[1578] Step 2: The generated AI crew can enjoy conversation with the user and assist with smartphone-related issues and contract procedures.

[1579] Example 1

[1580] Next, a description will be given of Example 1 of the embodiment 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal".

[1581] Conventional AI crew generation systems did not adequately customize the system to meet the user's preferences, limiting the user experience. In addition, the quality and performance of the generated AI crews were inconsistent, resulting in a lack of reliability in smartphone-related consultations and contract procedures. Furthermore, the accumulation and analysis of customer service data was insufficient, making it difficult to generate optimal AI crews.

[1582] The specification process by the specification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes a means for inputting feature information according to the user's preferences, a means for transmitting the input feature information to the server, a means for the server to receive the feature information and store it in a database, a means for the server to generate a prompt sentence based on the feature information, a means for inputting a prompt sentence into the generation AI model and generating an AI crew member, a means for transmitting data of the generated AI crew member to the user's terminal, a means for enabling a conversation with the generated AI crew member, a means for the AI ​​crew member to carry out smartphone-related consultations and contract procedures, and a means for accumulating and analyzing customer service data of the AI ​​crew member. This makes it possible to generate a high-quality AI crew member according to the user's preferences, and to realize highly reliable smartphone-related consultations and contract procedures. Furthermore, the accumulation and analysis of customer service data makes it possible to generate an optimal AI crew member.

[1583] The "means for inputting characteristic information according to user preferences" refers to a means for providing an interface for a user to input characteristic information such as face shape, hair color, and tone of voice based on his or her own preferences.

[1584] The "means for transmitting the input characteristic information to the server" refers to a communication means for securely transmitting the characteristic information input by the user to the server.

[1585] The "means for the server to receive the characteristic information and store it in the database" refers to the means for the server to receive the characteristic information sent from the user and store the information in the database.

[1586] "Means for the server to generate a prompt sentence based on feature information" refers to means for the server to generate a prompt sentence to be input into the generative AI model based on feature information stored in the database.

[1587] "Means for inputting a prompt sentence into a generative AI model and generating an AI crew member" refers to means for inputting a prompt sentence into a generative AI model and generating image and voice data of an AI crew member based on the prompt sentence.

[1588] "Means for transmitting data of the generated AI crew to the user's terminal" refers to communication means for transmitting data of the generated AI crew to the user's terminal.

[1589] "Means for enabling conversation with the generated AI crew" refers to means for providing an interface for a user to interact with the generated AI crew.

[1590] "A means for users to carry out smartphone-related consultations and contract procedures through an AI crew" refers to a means for users to carry out smartphone-related consultations and contract procedures through an AI crew.

[1591] "Means of accumulating and analyzing customer service data from AI crews" refers to the means by which the AI ​​crews accumulate customer service data obtained through dialogue with users and analyze that data.

[1592] "Means for creating optimal AI crew" refers to a means for analyzing accumulated customer service data and generating optimal AI crew based on the results.

[1593] An "AI crew with the optimal sales pitch" is an AI crew that can deliver the most effective sales pitch to users based on the results of analyzing customer service data.

[1594] This invention relates to a system that allows users to generate AI crew members according to their preferences and interact with the AI ​​crew members. Specifically, it includes a process in which the user inputs characteristic information and generates an AI crew member using a generative AI model based on the information.

[1595] Hardware and Software Used

[1596] Hardware

[1597] Terminal: The device through which the user enters characteristic information (e.g. smartphone, PC).

[1598] Server: A computer system for receiving the feature information, storing it in a database, and generating an AI crew member using a generative AI model.

[1599] software

[1600] Database: A data management system for storing feature information (e.g. MySQL, PostgreSQL).

[1601] Generative AI model: An artificial intelligence model for generating AI crew members based on a prompt sentence (e.g., OpenAI's GPT-4, DALL-E).

[1602] Communication Protocol: A protocol for securely transmitting data between the device and the server (e.g. HTTPS).

[1603] Data processing and calculation

[1604] User Actions

[1605] A user uses a terminal to access the system's interface and inputs characteristic information such as face shape, hair color, tone of voice, etc. For example, a user selects "round face, blonde hair, calm, low-pitched voice."

[1606] Device operation

[1607] The device sends the characteristic information entered by the user to the server, where the data is encrypted and transmitted securely using the HTTPS protocol.

[1608] Server Operations

[1609] The server receives the characteristic information sent from the terminal and stores it in a database. When storing the information, it performs validation to maintain the integrity of the data.

[1610] Next, the server generates a prompt sentence to be input to the generative AI model based on the feature information stored in the database. For example, it generates the following prompt sentence:

[1611] "The characteristics of the AI ​​crew that users prefer are as follows: face shape is round, hair color is blonde, and voice tone is calm and low. Please generate an AI crew with these characteristics."

[1612] The server inputs the generated prompt text into the generative AI model to generate image and voice data of the AI ​​crew. The generated data is then sent to the user's device via the server.

[1613] User Actions

[1614] The user interacts with the AI ​​crew member that is displayed on the device, who answers the user's questions and assists with smartphone-related consultations and contract procedures.

[1615] Examples

[1616] For example, if the user selects "round face, blonde hair, soft, deep voice," the following specific actions will occur:

[1617] 1. A user opens an app on their smartphone and selects "round face" as their face shape, "blonde" as their hair color, and "calm, low-pitched" as their voice tone.

[1618] 2. The device sends this information to the server.

[1619] 3. The server receives the information and stores the characteristic information "round face, blonde hair, calm, low voice" in the database.

[1620] 4. The server generates a prompt sentence saying, "The characteristics of the AI ​​crew member that the user prefers are as follows: a round face, blonde hair, and a calm, low voice tone. Please generate an AI crew member with these characteristics."

[1621] 5. The server inputs the prompt text into the generative AI model and generates image and voice data for the AI ​​crew.

[1622] 6. The server sends the generated AI crew data to the user's smartphone.

[1623] 7. The user interacts with the AI ​​crew generated on their smartphone and completes the smartphone contract procedure.

[1624] In this way, users can generate high-quality AI crew members tailored to their preferences and provide reliable smartphone-related consultations and contract procedures. Furthermore, the accumulation and analysis of customer service data will enable the generation of optimal AI crew members.

[1625] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1626] Step 1:

[1627] The user inputs the characteristic information.

[1628] A user uses a terminal to access the system interface and inputs feature information such as face shape, hair color, and voice tone. For example, a user selects "round face, blonde, calm, low-pitched voice." The input data is feature information such as face shape, hair color, and voice tone.

[1629] Step 2:

[1630] The terminal transmits the input characteristic information to the server.

[1631] The terminal transmits the characteristic information input by the user to the server using the HTTPS protocol. The input data is the characteristic information input by the user, and the output data is the characteristic information transmitted to the server.

[1632] Step 3:

[1633] The server receives the characteristic information and stores it in a database.

[1634] The server receives the feature information sent from the terminal and stores it in a database. When storing the data, validation is performed to maintain data consistency. The input data is the feature information sent from the terminal, and the output data is the feature information stored in the database.

[1635] Step 4:

[1636] The server generates a prompt sentence based on the characteristic information.

[1637] The server generates a prompt sentence to be input to the generative AI model based on the feature information stored in the database. For example, it generates a prompt sentence such as "The features of the AI ​​crew member the user prefers are as follows: a round face, blonde hair, and a calm, low voice. Please generate an AI crew member with these features." The input data is the feature information stored in the database, and the output data is the generated prompt sentence.

[1638] Step 5:

[1639] The server inputs a prompt sentence into the generative AI model and generates an AI crew member.

[1640] The server inputs the generated prompt sentence into the generative AI model to generate image and voice data of the AI ​​crew. The generative AI model generates image and voice data of the AI ​​crew based on the prompt sentence. The input data is the generated prompt sentence, and the output data is the generated image and voice data of the AI ​​crew.

[1641] Step 6:

[1642] The server sends the generated AI crew data to the user's device.

[1643] The server transmits the AI ​​crew data obtained from the generative AI model to the user's device. When transmitting, the data is compressed and encrypted to ensure secure transmission. The input data is the image and audio data of the generated AI crew, and the output data is the AI ​​crew data transmitted to the user's device.

[1644] Step 7:

[1645] The user interacts with the generated AI crew.

[1646] The user interacts with the generated AI crew displayed on the device. The AI ​​crew answers the user's questions and supports smartphone-related consultations and contract procedures. The input data is the user's questions and requests, and the output data is the AI ​​crew's responses and support.

[1647] (Application example 1)

[1648] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server", and the headset type terminal 314 will be referred to as a "terminal".

[1649] Traditional shopping experiences often make it difficult for users to find products that suit their tastes, and the purchasing process is often cumbersome. Furthermore, customer service in physical stores is often inconsistent, so there was a need for effective measures to improve user satisfaction.

[1650] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1651] In this invention, the server includes a means for generating an AI crew member according to the user's preferences, a means for enabling a conversation with the generated AI crew member, a means for the AI ​​crew member to handle consultations and contract procedures related to smart devices, a means for accumulating and analyzing customer service data of the AI ​​crew member, a means for recommending products based on the user's preferences, and a means for supporting the user's purchase procedure, thereby enabling the user to easily find products that match their preferences and smoothly complete the purchase procedure.

[1652] "User" means an individual or legal entity that uses the System.

[1653] "Preferences" are personal tastes or preferences that a user has for particular features or attributes.

[1654] "AI Crew" is an artificial intelligence character that is generated based on the user's preferences and will converse with and provide support to the user.

[1655] "Means for generating" means the technical means for generating an AI crew member based on user input.

[1656] "Means enabling conversation" refers to the technical means that allow a natural dialogue between the user and the AI ​​crew.

[1657] A "smart device" is an electronic device with Internet connectivity, such as a smartphone or smart glasses.

[1658] "Means of consultation and contract procedures" refers to the technological means by which users can ask questions about smart devices or complete contract procedures through an AI crew.

[1659] "Customer service data" is information that the AI ​​crew collects through their interactions with users.

[1660] "Means of accumulation and analysis" refers to the technical means for storing and analyzing customer service data.

[1661] "Means for recommending products" means technical means for suggesting appropriate products based on the user's preferences.

[1662] "Means to support the purchase process" are technological means to assist users in the process of purchasing a product.

[1663] The system for implementing the present invention generates an AI crew according to the user's preferences and improves the shopping experience in a physical store. A specific embodiment of the system is described below.

[1664] 1. System Configuration

[1665] The system consists of the following main components:

[1666] User terminal: Smart devices such as smartphones and smart glasses.

[1667] Servers: Servers for running generative AI models (e.g. GPT-4), facial recognition APIs (e.g. Face++), and speech synthesis APIs (e.g. Google Text-to-Speech).

[1668] Database: A database for accumulating and analyzing customer service data.

[1669] 2. Program Processing

[1670] The server realizes the system using the following means.

[1671] A way to generate AI crew members to suit user preferences

[1672] The user inputs the user's preferred features (e.g. face shape, hair color, tone of voice, etc.) from the user's device. The server uses a generative AI model to generate an AI crew based on the user's input. It uses a facial recognition API to generate a face that matches the specified features, and a voice synthesis API to generate a voice with the specified tone of voice.

[1673] A means to enable conversation with generated AI crew members

[1674] The server performs natural language processing (NLP) to allow the generated AI crew to have a natural dialogue with the user, allowing the user to enjoy shopping while talking to the AI ​​crew.

[1675] A means of consultation and contract procedures related to smart devices

[1676] The AI ​​Crew supports users when they have questions about their smart devices or when they go through contract procedures. The server provides appropriate answers to the user's questions and guides them through the contract procedures.

[1677] A means of accumulating and analyzing customer service data

[1678] The server collects customer service data from interactions between the AI ​​crew and the user, stores it in a database, and analyzes it, allowing the server to understand the user's preferences and behavioral patterns and provide more personalized services.

[1679] A way to recommend products based on user preferences

[1680] The server analyzes the customer service data and recommends appropriate products based on the user's preferences, allowing users to easily find products that match their tastes.

[1681] Ways to help users complete the purchase

[1682] When a user purchases a product, the AI ​​crew will support the purchase process. The server will confirm the user's purchase intention and guide them through the necessary procedures.

[1683] 3. Specific Examples

[1684] The user puts on the smart glasses and talks to the AI ​​crew while walking around the store. The AI ​​crew recommends products based on the user's preferences, and when the user says, "I would like to purchase this product," the AI ​​crew completes the purchase procedure via smartphone.

[1685] 4. Examples of prompts

[1686] Enter the user's preferred characteristics:

[1687] Face Shape:Round face

[1688] Hair color: Black

[1689] Tone of voice: Calm voice

[1690] Generate your AI crew based on these characteristics.

[1691] In this way, a system can be created that allows users to generate AI crew members based on their preferences, improving their shopping experience in physical stores.

[1692] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1693] Step 1:

[1694] The user terminal inputs the user's preferred features (e.g., face shape, hair color, tone of voice, etc.). The input data is sent to the server. The input data includes specific features such as "round face, black hair, calm voice."

[1695] Step 2:

[1696] The server uses a generative AI model (e.g. GPT-4) based on the received user's preferred features to generate the appearance and voice of the AI ​​crew member. It uses a facial recognition API (e.g. Face++) to generate a face that matches the specified features, and a speech synthesis API (e.g. Google Text-to-Speech) to generate a voice with the specified tone of voice. The appearance data and voice data of the generated AI crew member are output.

[1697] Step 3:

[1698] The server builds a conversational interface using natural language processing (NLP) to enable conversation with the generated AI crew. It receives input from the user's device (e.g., "Tell me about this product"), and the server uses NLP to generate an appropriate response and sends it to the user's device. The user's question and the AI ​​crew's response are treated as input and output.

[1699] Step 4:

[1700] When a user device makes an inquiry or performs a contract procedure related to a smart device, the server supports it through the AI ​​crew. The server receives the user's question (e.g., "What is the contract plan for this smartphone?") and provides the appropriate information. The user's question and the server's answer are treated as input and output.

[1701] Step 5:

[1702] The server accumulates and analyzes the customer service data collected through the interaction between the AI ​​crew and the user in a database. The customer service data includes the content of the user's questions, the AI ​​crew's responses, the user's behavioral patterns, etc. The accumulated data is analyzed to understand the user's preferences and behavioral patterns.

[1703] Step 6:

[1704] The server analyzes the customer service data and recommends appropriate products based on the user's preferences. The server receives input from the user's device (e.g., "What products do you recommend?"), recommends products based on the analysis results, and sends them to the user's device. The user's request and the recommended product information are treated as input and output.

[1705] Step 7:

[1706] When a user purchases a product, the server supports the purchase procedure through the AI ​​crew. The server receives input from the user's device (e.g., "I want to purchase this product") and guides the user through the purchase procedure. The user's purchase intention and the procedure guidance from the server are treated as input and output.

[1707] In this way, a system can be created that allows users to generate AI crew members based on their preferences, improving their shopping experience in physical stores.

[1708] Example 2

[1709] Next, a second embodiment of the second form will be described. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal".

[1710] In conventional AI crew systems, it was difficult to effectively collect and analyze conversation data with users and generate optimal responses. In addition, there was a lack of means to generate AI crews that matched the user's preferences, or to create the strongest AI crews through the accumulation and analysis of customer service data. This resulted in a decrease in the quality of the user experience and a decrease in the efficiency of contract procedures.

[1711] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1712] In this invention, the server includes a means for generating an AI crew member according to the user's preferences, a means for enabling a conversation with the generated AI crew member, a means for the AI ​​crew member to carry out consultations and contract procedures related to communication devices, a means for collecting customer service data of the AI ​​crew member, a means for storing the collected data in a database, a means for analyzing the stored data using natural language processing technology, a means for feeding back the analysis results to the generation AI model, a means for the generation AI model to generate an optimal response based on a prompt sentence, and a means for providing the generated response to the user. This makes it possible to effectively collect and analyze conversation data with the user and generate an optimal response. In addition, the strongest AI crew member can be created through the accumulation and analysis of customer service data, improving the quality of the user experience and the efficiency of contract procedures.

[1713] "User" refers to any individual or legal entity that uses the System.

[1714] "Artificial Intelligence Crew" refers to an artificial intelligence program designed to converse with users and process contracts.

[1715] "Means for generating" refers to methods and techniques for creating an artificial intelligence crew based on the user's preferences.

[1716] "Conversational enablement" refers to the methods and technologies that allow the user and the AI ​​crew to communicate with each other.

[1717] "Means of consultation and contract procedures related to telecommunications devices" refers to methods and technologies that allow users to ask questions about telecommunications devices or complete contract procedures through an artificial intelligence crew.

[1718] "Customer service data" refers to information collected by the AI ​​crew through conversations with users and contract procedures.

[1719] "Means of collection" refers to the methods and technologies for efficiently collecting customer service data.

[1720] "Means of storing in a database" refers to the methods and technologies for systematically storing collected data.

[1721] "Natural language processing technology" refers to technology for analyzing text data and understanding its meaning.

[1722] "Means for analysis" refers to methods and techniques for analyzing stored data and extracting useful information.

[1723] A "generative AI model" refers to an artificial intelligence model that generates optimal responses based on feedback.

[1724] A "prompt sentence" refers to an instruction sentence input to a generative AI model.

[1725] "Means for generating an optimal response" refers to the methods or techniques that a generative AI model uses to create an optimal reply to a user based on a prompt.

[1726] "Means of providing" refers to the method or technology used to communicate the generated response to the user.

[1727] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[1728] This invention is a system that generates an AI crew member according to the user's preferences, and accumulates and analyzes data obtained through conversations with the user and contract procedures. A specific embodiment of this system will be described below.

[1729] System Configuration

[1730] This system mainly consists of three elements: a server, a terminal, and a user.

[1731] 1. Server

[1732] The server has a means for generating an AI crew according to the user's preferences. The generated AI crew can converse with the user.

[1733] The server has a means for handling consultations and contract procedures related to communication devices using an artificial intelligence crew.

[1734] The server has the means to collect customer service data from the AI ​​crew and store it in a database using a database management system such as MySQL or PostgreSQL.

[1735] The server has the means to analyze the stored data using natural language processing techniques (e.g., Python's NLTK or spaCy).

[1736] The server has the means to feed the analysis results back to a generative AI model (e.g., OpenAI's GPT-4).

[1737] The server has the means for the generative AI model to generate an optimal response based on the prompt text.

[1738] 2. Terminal

[1739] The device has the means to collect conversation data with the user, which is converted to text using voice recognition software (e.g., Google Speech-to-Text API).

[1740] The terminal has a means for providing the generated response to the user.

[1741] 3. Users

[1742] The user uses the device to initiate a conversation with the AI ​​crew, for example saying, "I'd like to sign up for a new mobile phone contract."

[1743] Examples

[1744] Consider a case where a user says, "I want to get a new mobile phone contract." The device collects this speech and converts it to text using the Google Speech-to-Text API. The converted text data is sent to the server and stored in a MySQL database. The server tokenizes the stored text data using NLTK and analyzes the user's intent. The analysis results are fed back to the generative AI model, which generates the prompt sentence.

[1745] Examples of prompt statements

[1746] If a user says "I want to get a new mobile phone contract", generate the optimal response, taking into account that the user sentiment is positive.

[1747] Based on this prompt, the generative AI model generates a response: "Let me help you with your new mobile phone contract. What plan would you like?" The device can then provide this response to the user and continue the next conversation.

[1748] In this way, the server can accumulate and analyze the customer service data of the AI ​​crew to create the strongest AI crew, which will improve the quality of the user experience and the efficiency of the contract procedure.

[1749] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1750] Program processing flow

[1751] Step 1: User initiates a conversation with the AI ​​crew member

[1752] The user uses the terminal to start a conversation with the AI ​​crew. For example, the user might say, "I'd like to sign up for a new mobile phone contract."

[1753] Input: User's voice input

[1754] Output: Audio data

[1755] Step 2: The device collects conversation data

[1756] The device collects conversation data with the user in real time. The voice data is converted into text using voice recognition software (e.g., Google Speech-to-Text API).

[1757] Input: Audio data

[1758] Output: Text data

[1759] Step 3: The server stores the collected data in a database

[1760] The terminal sends the collected text data to the server. The server stores this data in a database (e.g., MySQL, PostgreSQL). The stored data includes the content of the conversation, the date and time, the user ID, etc.

[1761] Input: Text data, user ID, date and time

[1762] Output: Data stored in the database

[1763] Step 4: The server analyzes the stored data

[1764] The server analyzes the stored data using natural language processing techniques (e.g., Python's NLTK or spaCy). Specifically, it performs tokenization, part-of-speech tagging, sentiment analysis, etc. on the text data.

[1765] Input: Text data stored in a database

[1766] Output: Analysis results (user intent, emotions, etc.)

[1767] Step 5: The server feeds the analysis results back to the generative AI model

[1768] The server feeds the analysis results back to the generative AI model (e.g., OpenAI's GPT-4), which includes the user's intentions, emotions, and contract tendencies.

[1769] Input: Analysis results

[1770] Output: Feedback to the generative AI model

[1771] Step 6: The generative AI model generates the optimal response based on the prompt.

[1772] The generative AI model generates a prompt sentence based on the feedback and creates an optimal response. For example, if the prompt sentence is "If the user says, 'I want to sign a new mobile phone contract,' generate the optimal response. Please consider that the user's emotion is positive," the generative AI model generates the response "I'll help you with your new mobile phone contract. What kind of plan are you looking for?"

[1773] Input: prompt, feedback

[1774] Output: Best response

[1775] Step 7: The terminal provides the generated response to the user.

[1776] The terminal provides the user with the response generated by the generative AI model. The user can then receive the response from the AI ​​crew through the terminal and continue the next conversation.

[1777] Input: Best response

[1778] Output: Providing a response to the user

[1779] (Application example 2)

[1780] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server", and the headset type terminal 314 will be referred to as a "terminal".

[1781] Conventional AI crew systems had issues with the difficulty of providing services tailored to the user's preferences and the inability to respond to customers in real time. Furthermore, the accumulation and analysis of customer service data was insufficient, making it difficult to propose optimal customer service methods.

[1782] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means. In this invention, the server includes a means for generating an AI crew member according to the user's preferences, a means for enabling a conversation with the generated AI crew member, a means for the AI ​​crew member to handle consultations and contract procedures related to smart devices, a means for accumulating and analyzing customer service data of the AI ​​crew member, a means for collecting conversations with customers in real time using smart glasses and displaying the analysis results, and a means for proposing an optimal customer service method using the generated AI model. This makes it possible to provide optimal customer service in real time according to the user's preferences.

[1783] "User" refers to any individual or legal entity that uses the System.

[1784] "AI Crew" refers to a virtual customer service representative who uses artificial intelligence to converse with users and handle contract procedures.

[1785] "Means for generating" refers to a method or apparatus for creating an AI crew based on user preferences.

[1786] "Means enabling conversation" refers to a method or device that allows the user and the AI ​​crew to communicate through voice or text.

[1787] "Smart devices" refers to electronic devices with Internet connectivity, such as smartphones and smart glasses.

[1788] "Means for consultation and contract procedures" refers to a method or device that allows a user to ask questions or make contracts regarding a smart device through an AI crew.

[1789] "Customer service data" refers to information collected by the AI ​​crew through their interactions with users.

[1790] "Means of storing and analyzing" refers to methods and devices for storing and analyzing collected customer service data.

[1791] "Smart glasses" refers to electronic glasses-type devices equipped with a display, camera, microphone, and Internet connectivity.

[1792] "Means for collecting data in real time and displaying analytical results" refers to a method or device for instantly recording conversations with customers, analyzing the data, and displaying the results.

[1793] A "generative AI model" refers to a model that uses artificial intelligence to suggest the optimal way to serve customers.

[1794] "Means for proposing the optimal customer service method" refers to a method or device for using a generative AI model to present the most appropriate customer service method to a user.

[1795] The system for implementing this invention generates an AI crew member according to the user's preferences and enables conversation with the generated AI crew member. The system also uses the AI ​​crew member to handle smart device-related consultations and contract procedures, and accumulates and analyzes customer service data of the AI ​​crew member. Furthermore, the system uses smart glasses to collect conversations with customers in real time and displays the analysis results. The system can use the generated AI model to suggest optimal customer service methods.

[1796] System Configuration

[1797] The system uses the following hardware and software:

[1798] Hardware: smart glasses, microphone, server

[1799] Software: Python, SpeechRecognition library, OpenAI API

[1800] Processing flow

[1801] 1. Speech Recognition: The microphone on the smart glasses is used to collect the customer's speech as voice data. The collected voice data is converted to text data using the SpeechRecognition library.

[1802] 2. Data Analysis: The converted text data is sent to a server and analyzed using OpenAI's generative AI model. The analysis results suggest the optimal way to serve the customer.

[1803] 3. Display of results: The analysis results are displayed in real time on the smart glasses display, allowing store clerks to provide optimal customer service.

[1804] Examples

[1805] For example, if a customer says, "I'd like to know more about this product," the generative AI model can generate suggestions such as, "This product uses the latest technology and is particularly durable. Plus, it's currently on special discount."

[1806] Examples of prompt statements

[1807] Customer conversation: I want to know more about this product

[1808] Please suggest the best way to serve customers.

[1809] In this way, it is possible to provide optimal customer service in real time according to the user's preferences.

[1810] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1811] Step 1:

[1812] A user puts on the smart glasses and starts a conversation with a customer. A microphone installed in the smart glasses collects what the customer says as voice data. The input is the customer's voice, and the output is voice data.

[1813] Step 2:

[1814] The voice data collected by the device (smart glasses) is converted to text data using the SpeechRecognition library. The input is voice data, and the output is text data. This conversion process allows the voice data to be treated as text information.

[1815] Step 3:

[1816] The terminal sends the converted text data to the server. The input is the text data, and the output is the data sent to the server. The server prepares the received text data for analysis.

[1817] Step 4:

[1818] The server inputs the received text data into OpenAI's generative AI model to generate a prompt that suggests the optimal way to serve the customer. The input is text data, and the output is the generated prompt. The generative AI model analyzes the text data and generates an appropriate response.

[1819] Step 5:

[1820] The server analyzes the generated prompt text and generates a text that suggests the best way to serve the customer. The input is the prompt text, and the output is the suggested text. This suggested text includes a specific way to serve the customer.

[1821] Step 6:

[1822] The server sends the generated suggested text to the terminal (smart glasses). The input is the suggested text, and the output is data transmission to the terminal. The terminal prepares the received suggested text for display.

[1823] Step 7:

[1824] The terminal displays the proposed text received on the display of the smart glasses in real time. The input is the proposed text, and the output is the display on the display. This allows the user to provide optimal customer service to the customer.

[1825] Example 3

[1826] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal".

[1827] Conventional systems using AI characters had difficulty responding to individual user preferences and were unable to generate effective sales pitches. In addition, there was a lack of means to utilize facial feature data and past reaction data provided by users, making it impossible to provide users with AI characters that were optimal for them. This resulted in a decrease in user satisfaction and a failure to improve the efficiency of contract procedures.

[1828] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1829] In this invention, the server includes a means for generating an AI character according to the user's preferences, a means for enabling a conversation with the generated AI character, a means for carrying out consultations and contract procedures related to communication devices using the AI ​​character, a means for accumulating and analyzing customer service data of the AI ​​character, a means for analyzing fac...

Claims

1. A means for inputting characteristic information according to a user's preferences; means for transmitting the input characteristic information to a server; A means for storing the characteristic information received by the server in a database; a means for generating a prompt sentence based on the characteristic information by the server; A means for inputting the prompt sentence into a generative AI model to generate an AI crew member; A means for transmitting the generated data of the AI ​​crew to the user's terminal; A means for enabling a conversation with the generated AI crew; A means for carrying out smartphone-related consultations and contract procedures by the AI ​​crew; A system including a means for accumulating and analyzing customer service data of the AI ​​crew.

2. means for analyzing facial feature data provided by a user; A means for collecting past reaction data of said users; means for generating a sales pitch directed to said user; A means for combining the facial feature data with a sales pitch to generate an AI crew member according to the user's preferences; A means for enabling a conversation with the generated AI crew; and a means for the AI ​​crew to carry out smartphone-related consultations and contract procedures using the past response data.

3. A way to generate AI crew members based on user preferences; A means for enabling a conversation with the generated AI crew; A means for accumulating and analyzing customer service data of the AI ​​crew; means for detecting an emotion of the user, the means including an emotion engine; and a means for the AI ​​crew to handle smartphone-related consultations and contract procedures based on the recognition results of the emotion engine and the customer service data.

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