system

Abstract

Provide a system. 【Solution means】 Means for collecting information to generate a virtual human model based on user information, Means for using the information and creating a virtual human model using a generation model, Means for analyzing data to detect inappropriate elements in the generated visual and audio data, Means for correcting inappropriate elements that may occur, Means for generating an action plan for a virtual human model based on the provided activities, Means for generating recommendations for optimizing strategies based on information obtained from the analyzed action data, Means for utilizing the human model generated by leveraging smart devices, A system including the above.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the modern advertising market, since it is costly for companies to employ existing influencers, there is a demand for efficient and economical brand promotion. Also, the risks due to influencer schedule adjustments and scandals are significant, which are obstacles to effectively promoting advertising activities. Therefore, it is necessary to provide a means for companies to effectively promote their brands in a flexible and creative way that has never been seen before.

Means for Solving the Problems

[0005] This invention provides means for acquiring input information to generate a virtual character according to the customer's input requirements. Furthermore, it includes means for creating a virtual character using a generation model and analyzing inappropriate elements within the generated content. It also includes means for correcting the inappropriate elements that occur and means for generating an activity plan for the virtual character based on the provided digital events. In addition, it provides means for analyzing the data obtained based on the activity plan and automatically generating suggestions for optimizing the strategy, thereby supporting low-cost and efficient digital marketing for companies.

[0006] "Customer requirements" refer to information about the brand image and promotional objectives provided by a company that are considered when creating a virtual influencer.

[0007] "Input information" refers to the data and parameters necessary to generate a virtual character based on customer requirements.

[0008] A "generative model" is an artificial intelligence algorithm used to generate the appearance and voice of a virtual character.

[0009] A "virtual character" is a character created in a digital environment using a generative model, customized to suit a specific brand or promotional purpose.

[0010] "Content" refers to digital media such as images, audio, and video generated using virtual characters.

[0011] "Inappropriate elements" refer to elements or content included in the generated content that may damage the brand image.

[0012] A "digital event" refers to an activity or campaign on an online platform in which virtual characters participate or are used.

[0013] An "activity plan" is a plan to optimize promotional activities, including the posting schedule and content themes for the virtual character.

[0014] "Suggestions for optimizing strategy" are recommendations generated from data analysis to improve the efficiency of promotional activities. [Brief explanation of the drawing]

[0015] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13]It is a sequence diagram showing the processing flow of a data processing system in Embodiment 2 when a sentiment engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Mode for Carrying Out the Invention

[0016] 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.

[0017] First, the language used in the following description will be explained.

[0018] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), etc.

[0019] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0028] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0035] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0036] This invention provides a platform for companies to conduct efficient brand promotions using virtual influencers. The system begins with the user inputting specific brand requirements via a terminal. Based on the user's input, the server uses image generation AI and voice generation AI to generate a customizable virtual character.

[0037] The generated characters have appearances and voices that conform to the brand's requirements, and further fine-tuning is performed by the server. Users can further customize the character's appearance and personality through their devices.

[0038] The server is equipped with a security check function that detects potential inappropriate elements in the generated content. If inappropriate elements are detected, the server automatically corrects them and regenerates the content appropriately. This process ensures that the content does not damage the company's brand image.

[0039] Next, the server creates an activity plan for the virtual influencer based on the user's advertising campaign goals. This activity plan is optimized according to the characteristics of the digital event and includes the character's posting schedule and themes. This dynamic planning maximizes the campaign's effectiveness.

[0040] During the activity, the server monitors the virtual influencer's performance in real time. The collected data is used as a basis for evaluating and optimizing marketing strategies. For example, it is possible to identify the times when follower engagement is highest and adjust posts to match those times.

[0041] This enables companies to conduct flexible and creative digital marketing activities and promote their brands efficiently. This system represents a new way to maximize the effectiveness of virtual influencers and reduce marketing risks.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] Users access the platform using their devices and input specific requirements for the brand and characteristics of the characters. This includes the characters' age, gender, appearance, and content style.

[0045] Step 2:

[0046] Based on the information received from the user, the server activates an image generation AI to generate the appearance of a virtual character. In this process, the AI ​​considers the specified parameters and creates an appearance that meets the requirements.

[0047] Step 3:

[0048] The server uses voice generation AI to generate voices that are suitable for the virtual character. This creates a speaking style and tone that matches the character's personality.

[0049] Step 4:

[0050] The server presents the generated character to the user, who then customizes the character in detail via their device. At this stage, it is possible to adjust hairstyles, clothing, accessories, and other elements.

[0051] Step 5:

[0052] The server completes the final character and performs security checks on the generated content. The AI ​​detects inappropriate elements and automatically corrects them if necessary.

[0053] Step 6:

[0054] The server generates an activity plan for the virtual influencer based on the advertising campaign goals set by the user. The plan includes post content, frequency, and optimal timing.

[0055] Step 7:

[0056] The server monitors the virtual influencer's activities in real time and collects the data obtained. The collected data is used to analyze engagement rates and follower growth.

[0057] Step 8:

[0058] Based on the analysis results, the server automatically generates suggestions for optimizing campaigns and strategies and reports them to the user. This can improve the effectiveness of promotional activities.

[0059] (Example 1)

[0060] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0061] Traditional brand promotion methods struggle to create virtual influencers who can effectively and engagingly communicate information to target audiences. Furthermore, inappropriate content can damage the brand image. Additionally, creating activity plans for virtual influencers and evaluating and optimizing their effectiveness requires significant effort and time.

[0062] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0063] In this invention, the server includes means for acquiring information to generate a virtual person based on customer requirements, means for creating a virtual person using the information and a generation AI model, means for analyzing and automatically correcting the content to detect inappropriate elements in the generated content, and means for generating a schedule for the virtual person based on the provided activities. This enables efficient and accurate generation and management of virtual influencers, maximizing the effectiveness of brand promotions.

[0064] "Customer requirements" refer to information that describes the conditions and characteristics that a fictional character should meet in brand promotion.

[0065] "Means of acquiring information" refers to methods or devices for collecting data in order to understand customer requirements.

[0066] A "generative AI model" is an algorithm or software system that uses artificial intelligence technology to create virtual people, images, voices, and so on.

[0067] "Means for creating a virtual character" refers to a method or apparatus that utilizes a generative AI model to generate a virtual character based on specified conditions.

[0068] "Means for analyzing content to detect inappropriate elements" refers to a method or apparatus for analyzing data to identify inappropriate elements that may be contained within the generated content.

[0069] "Means of automatic correction" refers to a method or apparatus that uses predefined rules or algorithms to correct detected inappropriate elements and regenerate them into appropriate content.

[0070] "Means for generating a virtual person's schedule based on activities" refers to a method or apparatus for setting the activity schedule and content of a virtual influencer, taking into account the characteristics of the provided event or campaign.

[0071] This invention will now describe embodiments for carrying out this invention. This system is for generating and managing virtual influencers in order to efficiently carry out brand promotion.

[0072] First, the user accesses the system via a terminal and enters the requirements necessary for promoting the brand. This includes the appearance and voice characteristics that the virtual influencer should meet, personality, and the profile of the target audience. The user can communicate detailed requests to the system using prompt messages.

[0073] Upon receiving this input information, the server utilizes an image generation AI model (e.g., DALL-E) and a speech generation AI model (e.g., Google® Cloud Text-to-Speech) to generate a virtual influencer. The generated character will have appearance and voice characteristics tailored to the brand's requirements.

[0074] After generation, the server uses a security check function to analyze the generated content for any inappropriate elements. If inappropriate elements are found, the server automatically corrects them and regenerates the content to be appropriate. This helps protect the company's brand image.

[0075] Afterward, users can further customize their characters through their devices. For example, they can add clothing and accessories, and fine-tune the character's personality. This can be done intuitively through an interactive UI.

[0076] Furthermore, the server automatically generates activity plans for virtual influencers based on the characteristics of the provided digital events and campaigns. These plans are designed to reach the target audience at the most effective time.

[0077] For example, if a user enters the prompt "Generate a fresh and energetic virtual influencer to introduce our new spring collection," the server will create an appropriate character and content based on that information.

[0078] Real-time monitoring allows the server to evaluate the effectiveness of virtual influencer activities and optimize marketing strategies based on the collected data. For example, it can analyze the times of day when more engagement is achieved and reflect this in the next posting schedule. In this way, a flexible and efficient system is created to maximize the effectiveness of brand promotions.

[0079] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0080] Step 1:

[0081] The user inputs brand promotion requirements via a terminal. This input includes the desired appearance and voice characteristics of the virtual influencer, personality, and target audience profile. This information is transmitted to the system as prompts. This input allows the system to specifically understand the customization requirements.

[0082] Step 2:

[0083] The server generates virtual influencers using image generation AI models and voice generation AI models based on input information received from the user. Here, the server analyzes the input prompt text and applies it to the generation model to generate a character that meets specific requirements. For example, it generates image data according to specified hair color and whether or not the character is wearing a hat, and processes voice data according to specified tone and accent.

[0084] Step 3:

[0085] The server analyzes the generated characters through a security check function and automatically detects inappropriate elements. Specifically, it scans the generated text and audio data using a machine learning model to check for inappropriate words or expressions. If inappropriate elements are detected, the server automatically corrects them and converts them into appropriate data.

[0086] Step 4:

[0087] Users can use their devices to further customize the generated virtual influencers. For example, they can manipulate clothing styles and add or change accessories in real time through an interactive user interface. They can also fine-tune the character's personality and energy level.

[0088] Step 5:

[0089] The server generates an activity plan for virtual influencers based on the specifications of the provided digital event. This plan selects the most effective time slots based on user requirements and determines posting schedules and content. Data analysis is performed, taking into account past engagement data, to aim for optimal reach to the target audience.

[0090] Step 6:

[0091] The server monitors the activities of virtual influencers in real time and collects their performance data. For example, it analyzes data on post reactions and engagement to help optimize marketing strategies. This allows for identifying areas for improvement in future campaign plans and enabling continuous, effective promotion.

[0092] (Application Example 1)

[0093] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0094] In traditional promotional activities, it is difficult to efficiently generate virtual characters that match the characteristics of a brand and to use those characters to conduct effective advertising campaigns. Furthermore, there are challenges in optimizing advertising strategies in real time while minimizing the risk of inappropriate content.

[0095] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0096] In this invention, the server includes means for generating a virtual person model based on user information, means for analyzing the data to detect inappropriate elements in the generated visual and audio data, and means for generating an action plan for the virtual person model based on the provided activities. This makes it possible to flexibly and accurately carry out promotional activities for the virtual person model and suppress the generation of inappropriate content.

[0097] "User information" refers to data, including brand requirements and characteristics, that are acquired for the purpose of generating a virtual persona model.

[0098] A "virtual character model" is a digital character created using generative AI, possessing an appearance and conversational abilities tailored to a specific brand or promotion.

[0099] A "generative model" refers to a set of algorithms and technologies used to generate a virtual human model based on input information.

[0100] "Visual and audio data" refers to the graphic and audio elements of the generated virtual character model.

[0101] "Inappropriate elements" are content elements that may damage the brand image or be considered socially inappropriate.

[0102] "Data analysis" refers to analytical methods used to identify inappropriate elements from generated visual and audio data.

[0103] An "action plan" outlines a schedule and content strategy for how a fictional character model can effectively operate and promote the brand.

[0104] A "smart device" refers to electronic devices or applications used to utilize the generated virtual human model.

[0105] To implement this invention, the server first collects information from the user and generates a virtual person model. The server utilizes input data based on brand requirements and characteristics, and uses a generative AI model to create the virtual person model. This model is a digital character customized by image generation AI and voice generation AI.

[0106] For visual and audio data, the server analyzes the data to detect inappropriate elements. Specifically, data analysis tools such as Amazon Rekognition are used to identify and correct inappropriate elements within the content. This process ensures that the content is socially appropriate and does not damage the brand image.

[0107] The server also generates an action plan for the virtual character model. This action plan details how the generated character model will act and promote the brand. This makes it possible to develop content strategies optimized for digital events and promotions.

[0108] Smart devices utilize these generated virtual person models for promotional activities. For example, users can watch promotional videos or experience interactive content through smartphone apps.

[0109] As a concrete example, when a cosmetics brand conducts a promotion to introduce a new product, a video is generated featuring a virtual model highlighting the product's features. When users watch this video on their devices, its appeal to the target audience increases.

[0110] An example of a prompt message would be: "Generate a promotional video for a new cosmetic product aimed at women. This product features a vibrant red color."

[0111] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0112] Step 1:

[0113] Users input brand requirements and characteristics using smart devices. This input data is sent to the server, initiating the generation of a virtual persona model. The input data includes detailed brand information, such as prompt text.

[0114] Step 2:

[0115] The server creates a virtual person model using a generative AI model based on the received brand requirements. Based on the prompt text received as input, the image generation AI generates a visual model, and the voice generation AI creates voice data. This results in a virtual person model that matches the user's brand.

[0116] Step 3:

[0117] The server analyzes the generated visual and audio data to detect inappropriate elements. This analysis uses AI tools such as Amazon Rekognition. If the server detects inappropriate elements, it corrects them, regenerates the data in an appropriate state, and outputs clean model data.

[0118] Step 4:

[0119] The server generates an action plan for a virtual character model based on the acquired visual and audio data. This plan includes the schedule and content details of promotional activities. The server then processes the data and optimizes the strategy, outputting an action plan based on these optimizations.

[0120] Step 5:

[0121] On smart devices, action plans are utilized, and users are provided with interactive promotional experiences. Users can view content generated through smartphone apps and other means, and understand the brand's characteristics. User engagement data from each device is fed back to the server.

[0122] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0123] This invention is a virtual influencer system incorporating an emotion engine, providing a platform that enables companies to achieve more personalized interactions with users. The system begins with a process in which a server generates a virtual character in real time based on brand requirements entered by the user through a terminal.

[0124] The server uses an emotion engine to recognize the user's emotional state in real time and dynamically adjust the virtual character's responses based on that data. This emotion engine includes an AI algorithm to analyze the user's emotions from the feedback and interactions they provide. This allows the virtual character to display a tone and response appropriate to the user's emotions.

[0125] Furthermore, the server runs security features to check the generated character content for inappropriate elements and makes corrections as needed. This process is performed in real time, minimizing the risk of inappropriate content being created.

[0126] The virtual influencer's activity plan is automatically generated by the server according to the advertising campaign's goals. Based on user feedback obtained through the emotion engine, this activity plan can be dynamically adjusted. This feedback loop enables the implementation of effective marketing strategies that resonate with user emotions.

[0127] Ultimately, the server analyzes multiple data points derived from the virtual influencer's performance and automatically generates suggestions for optimizing the strategy. This data also includes user sentiment data collected by the sentiment engine, enabling deeper insights. For example, it might analyze how specific character portrayals affect users emotionally and recommend adjusting content based on the results.

[0128] Thus, virtual influencer systems that combine emotion engines can provide companies with a new dimension of brand engagement and further enrich the user experience.

[0129] The following describes the processing flow.

[0130] Step 1:

[0131] Users access the platform using their devices and enter their brand requirements and desired character traits. This sends detailed data about the virtual influencer's appearance and behavior to the server.

[0132] Step 2:

[0133] The server uses image generation AI to create a virtual character in real time based on the received data. In this process, the character's visual appearance is constructed according to the specified features.

[0134] Step 3:

[0135] The server utilizes voice generation AI to generate voices that are suitable for the virtual character. These voices will be in line with the character's personality and the brand's tone.

[0136] Step 4:

[0137] The server presents the user with an initial version of the character, and the user provides feedback via their device. The user can further customize the character's appearance and voice as needed.

[0138] Step 5:

[0139] The server activates the emotion engine and collects emotional data provided by the user through the device. The emotion engine analyzes the user's emotions from nonverbal cues and direct feedback.

[0140] Step 6:

[0141] Based on this emotional data, the server dynamically adjusts the virtual character's responses and behavior. For example, if the user shows a positive reaction, the character will respond in a more friendly tone.

[0142] Step 7:

[0143] The server performs security checks on the generated content, automatically detecting and correcting inappropriate elements. This eliminates any parts that do not conform to the brand image.

[0144] Step 8:

[0145] The server generates an activity plan for virtual influencers based on the user's advertising campaign goals. This activity plan includes adjustments based on feedback from the sentiment engine.

[0146] Step 9:

[0147] The server monitors the activity of virtual influencers and analyzes real-time data. This includes sentiment data, providing deeper insights into understanding user reactions.

[0148] Step 10:

[0149] The server uses these analysis results to automatically generate and provide suggestions for optimizing the strategy. This enables more effective marketing activities.

[0150] (Example 2)

[0151] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0152] Traditional virtual character systems have struggled to dynamically adjust responses based on user emotions and to immediately correct inappropriate content. Furthermore, their activity plans are static, resulting in insufficient marketing strategy efficiency. This has led to a limited user experience and hindered companies from improving brand engagement.

[0153] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0154] In this invention, the server includes means for acquiring input information to generate a virtual character based on customer requirements, means for creating a virtual character using a generative model, and means for analyzing the user's emotional state using an emotion analysis engine and dynamically adjusting the virtual character's response. This enables real-time, personalized interaction that responds to the user's emotions.

[0155] "Customer requirements" refer to information that indicates the attributes and conditions that users desire regarding the creation and response of virtual characters.

[0156] A "virtual character" is a digital character created on a computer that engages in dialogue and interaction with the user.

[0157] "Input information" refers to digital data provided by the user from their device, including the requirements and instructions the system needs to generate characters.

[0158] A "generative model" is an algorithm or program used to create virtual characters, determining the character's appearance and behavior based on specific inputs.

[0159] An "emotion analysis engine" refers to artificial intelligence technology used to analyze a user's emotional state in real time, inferring emotions from the user's responses and feedback.

[0160] "Inappropriate elements" refer to expressions or information that may be included in the generated content but do not meet the required standards.

[0161] An "activity plan" is a plan that specifies the schedule and procedures for interactions that a virtual character should perform, and is set based on the goals of an advertising campaign, etc.

[0162] A "feedback loop" refers to a system that continuously receives user feedback and opinions, and dynamically adjusts its characters and plans based on that feedback.

[0163] "Suggestions for optimizing strategy" involve analyzing the results of a character's activities and then identifying areas for improvement and strategies to make future interactions and activities more effective.

[0164] This invention is a virtual character generation system equipped with an emotion analysis engine, providing a platform for companies to realize personalized interactions with users. Specific embodiments for carrying out this invention are described below.

[0165] The user uses a terminal to provide the system with input information regarding brand requirements and target profile. This information is entered in text format, and the system receives it. For example, the user might input branding instructions such as "a youthful and healthy image."

[0166] The server utilizes a generative AI model to process this input information. A commonly used language generation model is employed for this purpose. Based on the input information, the server generates a profile for a virtual character. During this process, prompt statements are sent to the AI ​​model. For example, a possible prompt statement might be, "Generate a character with a healthy image aimed at young people."

[0167] Subsequently, the server uses an emotion analysis engine to analyze the user's emotional state in real time. This allows the virtual character's responses to dynamically adjust to the user's current emotions. Data such as user feedback and dialogue history are used for emotion analysis.

[0168] The content of generated virtual characters is constantly checked for inappropriate elements. The server uses AI-based filtering technology to perform content checks, and any elements deemed inappropriate are corrected immediately.

[0169] Furthermore, the server automatically generates an action plan based on the advertising campaign's goals and dynamically updates it based on actual user feedback. This ensures that the virtual character always acts in a way that is in line with the user's preferences and emotions.

[0170] Ultimately, this system analyzes the data collected by the server and generates suggestions to help optimize marketing strategies. The server analyzes multiple data points, including sentiment data, and based on this, provides companies with more effective strategies. This enables companies to improve the user experience and strengthen brand engagement.

[0171] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0172] Step 1:

[0173] The user uses a terminal to input information about the brand's requirements and target image. This input is sent to the server in text format. For example, the user might input the requirement "a youthful and healthy image." This information is then transferred to the server and prepared for the next processing step.

[0174] Step 2:

[0175] The server creates a prompt for the generative AI model based on the input information it receives. The model receives a prompt that reflects the characteristics derived from the input information, such as "Generate a character with a healthy image aimed at young people." The generative AI model uses the prompt as input to generate a profile of a virtual character and provides the server with specific character information as output.

[0176] Step 3:

[0177] The server uses an emotion analysis engine to analyze the user's emotional state based on user interactions after the virtual character is generated. This analysis uses user feedback and chat logs as input data. The emotion analysis engine processes this data and generates the user's emotional state as output. Based on this emotional information, the server adjusts the virtual character's responses in real time.

[0178] Step 4:

[0179] The server uses AI filtering technology to check whether the generated virtual character content contains any inappropriate elements. The generated character's text and images become input data, and the AI ​​filter searches for inappropriate elements. If inappropriate elements are detected, the corrected content is regenerated as a new output.

[0180] Step 5:

[0181] The server automatically generates an activity plan. This plan is created using emotional feedback from the user and past interaction data of the virtual character. The server analyzes this data and outputs an activity plan tailored to the target audience. Furthermore, this activity plan is dynamically adjusted through a feedback loop, proposing a strategy that reflects the latest user preferences.

[0182] (Application Example 2)

[0183] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0184] In today's digital advertising market, there is a demand for advertising experiences tailored to individual consumers, but achieving this remains challenging. In particular, there is a lack of effective methods for responding to consumer emotions in the development of personalized advertising. Furthermore, there is a risk that inappropriate advertising content will cause discomfort to users, necessitating the establishment of systems that efficiently adjust these factors in real time.

[0185] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0186] In this invention, the server includes means for analyzing customer information to obtain construction information, means for using a generation program to create a virtual construct using the construction information, and means for analyzing a function obtained based on the operation plan and generating a proposal for optimizing the strategy. This makes it possible to display advertisements that are in line with the consumer's emotions in real time and optimize the advertising experience.

[0187] "Customer information" refers to foundational information for generating virtual constructs, and specifically data related to consumers.

[0188] "Construction information" refers to detailed data for generating constructs obtained by analyzing customer information.

[0189] A "virtual construct" refers to a digital character or object that is generated based on digital information.

[0190] A "generation program" is a program used to create a virtual construct using construction information.

[0191] "Non-conforming factors" refer to inappropriate elements or problems contained within the constructed information.

[0192] An "action plan" is a proposed plan for constructing the behavior of a virtual construct based on the informational events provided.

[0193] "Policy" refers to a set of action guidelines optimized based on an action plan.

[0194] An "emotional analysis program" is a program designed to analyze the emotional state of a passive recipient and adjust the response of a virtual construct.

[0195] "Advertising content" refers to the content of advertisements presented to consumers, which is selected and displayed accordingly.

[0196] In this embodiment of the invention, a camera function and a dedicated application are installed on the terminal accessed by the user to acquire the user's emotional information in real time. An emotional analysis program analyzes this emotional information and generates data to dynamically adjust the response of the virtual construct. The server executes a generation program based on the generated construct information to create a virtual construct suitable for the user.

[0197] The server combines acquired user emotion information with provided information events to formulate an action plan. This forms the basis for dynamically selecting ad content. The ad content selected through emotion analysis is displayed on the user's device to optimize the user experience. The processing uses image processing libraries such as OpenCV and emotion recognition software called EmotionRecognizer, which uses AI algorithms.

[0198] For example, if a user smiles while using the application, the system recognizes the smile and displays positive and energetic advertisements. This ensures that the advertisements align with the user's emotions, enabling the implementation of effective advertising campaigns.

[0199] An example of a prompt might be: "When the user looks into the camera and is smiling, display an ad promoting a trending product in a positive tone." This allows the ad content to provide an appropriate response that aligns with the user's current emotional state.

[0200] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0201] Step 1:

[0202] The user launches an application on their device and enables the camera function. At this time, the device inputs video data from the camera in real time and sends that data to the server.

[0203] Step 2:

[0204] The server performs face detection on the received video data using the OpenCV library. The detected face data is used as input, and EmotionRecognizer is used to analyze the user's emotions. The analysis results are output as the user's emotional state (e.g., joy, sadness, surprise).

[0205] Step 3:

[0206] The server develops an action plan for the virtual construct based on the analyzed emotional state. The inputs to this action plan are the user's emotional state and the campaign objective, and the output is an action plan that includes adjusted responses and expression parameters. This plan influences the selected ad content.

[0207] Step 4:

[0208] The server selects appropriate ad content based on the action plan. Using the sentiment state and action plan received as input, it selects the most suitable ad from the ad database. This ad content is output and sent to the terminal.

[0209] Step 5:

[0210] The device displays advertising content sent from the server to the user. Specifically, selected advertisements are shown on the device's display. This display ensures that the user experience matches the emotionally tailored advertisement content, improving engagement.

[0211] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0212] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0213] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0214] [Second Embodiment]

[0215] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0216] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0217] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0218] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0219] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0220] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0221] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0222] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0223] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0224] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0225] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0226] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0227] This invention provides a platform for companies to conduct efficient brand promotions using virtual influencers. The system begins with the user inputting specific brand requirements via a terminal. Based on the user's input, the server uses image generation AI and voice generation AI to generate a customizable virtual character.

[0228] The generated characters have appearances and voices that conform to the brand's requirements, and further fine-tuning is performed by the server. Users can further customize the character's appearance and personality through their devices.

[0229] The server is equipped with a security check function that detects potential inappropriate elements in the generated content. If inappropriate elements are detected, the server automatically corrects them and regenerates the content appropriately. This process ensures that the content does not damage the company's brand image.

[0230] Next, the server creates an activity plan for the virtual influencer based on the user's advertising campaign goals. This activity plan is optimized according to the characteristics of the digital event and includes the character's posting schedule and themes. This dynamic planning maximizes the campaign's effectiveness.

[0231] During the activity, the server monitors the virtual influencer's performance in real time. The collected data is used as a basis for evaluating and optimizing marketing strategies. For example, it is possible to identify the times when follower engagement is highest and adjust posts to match those times.

[0232] This enables companies to conduct flexible and creative digital marketing activities and promote their brands efficiently. This system represents a new way to maximize the effectiveness of virtual influencers and reduce marketing risks.

[0233] The following describes the processing flow.

[0234] Step 1:

[0235] Users access the platform using their devices and input specific requirements for the brand and characteristics of the characters. This includes the characters' age, gender, appearance, and content style.

[0236] Step 2:

[0237] Based on the information received from the user, the server activates an image generation AI to generate the appearance of a virtual character. In this process, the AI ​​considers the specified parameters and creates an appearance that meets the requirements.

[0238] Step 3:

[0239] The server uses voice generation AI to generate voices that are suitable for the virtual character. This creates a speaking style and tone that matches the character's personality.

[0240] Step 4:

[0241] The server presents the generated character to the user, who then customizes the character in detail via their device. At this stage, it is possible to adjust hairstyles, clothing, accessories, and other elements.

[0242] Step 5:

[0243] The server completes the final character and performs security checks on the generated content. The AI ​​detects inappropriate elements and automatically corrects them if necessary.

[0244] Step 6:

[0245] The server generates an activity plan for the virtual influencer based on the advertising campaign goals set by the user. The plan includes post content, frequency, and optimal timing.

[0246] Step 7:

[0247] The server monitors the virtual influencer's activities in real time and collects the data obtained. The collected data is used to analyze engagement rates and follower growth.

[0248] Step 8:

[0249] Based on the analysis results, the server automatically generates suggestions for optimizing campaigns and strategies and reports them to the user. This can improve the effectiveness of promotional activities.

[0250] (Example 1)

[0251] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0252] Traditional brand promotion methods struggle to create virtual influencers who can effectively and engagingly communicate information to target audiences. Furthermore, inappropriate content can damage the brand image. Additionally, creating activity plans for virtual influencers and evaluating and optimizing their effectiveness requires significant effort and time.

[0253] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0254] In this invention, the server includes means for acquiring information to generate a virtual person based on customer requirements, means for creating a virtual person using the information and a generation AI model, means for analyzing and automatically correcting the content to detect inappropriate elements in the generated content, and means for generating a schedule for the virtual person based on the provided activities. This enables efficient and accurate generation and management of virtual influencers, maximizing the effectiveness of brand promotions.

[0255] "Customer requirements" refer to information that describes the conditions and characteristics that a fictional character should meet in brand promotion.

[0256] "Means of acquiring information" refers to methods or devices for collecting data in order to understand customer requirements.

[0257] A "generative AI model" is an algorithm or software system that uses artificial intelligence technology to create virtual people, images, voices, and so on.

[0258] "Means for creating a virtual character" refers to a method or apparatus that utilizes a generative AI model to generate a virtual character based on specified conditions.

[0259] "Means for analyzing content to detect inappropriate elements" refers to a method or apparatus for analyzing data to identify inappropriate elements that may be contained within the generated content.

[0260] "Means of automatic correction" refers to a method or apparatus that uses predefined rules or algorithms to correct detected inappropriate elements and regenerate them into appropriate content.

[0261] "Means for generating a virtual person's schedule based on activities" refers to a method or apparatus for setting the activity schedule and content of a virtual influencer, taking into account the characteristics of the provided event or campaign.

[0262] This invention will now describe embodiments for carrying out this invention. This system is for generating and managing virtual influencers in order to efficiently carry out brand promotion.

[0263] First, the user accesses the system via a terminal and enters the requirements necessary for promoting the brand. This includes the appearance and voice characteristics that the virtual influencer should meet, personality, and the profile of the target audience. The user can communicate detailed requests to the system using prompt messages.

[0264] Upon receiving this input information, the server utilizes image generation AI models (e.g., DALL-E) and speech generation AI models (e.g., Google Cloud Text-to-Speech) to generate a virtual influencer. The generated character will have appearance and voice characteristics tailored to the brand's requirements.

[0265] After generation, the server uses a security check function to analyze the generated content for any inappropriate elements. If inappropriate elements are found, the server automatically corrects them and regenerates the content to be appropriate. This helps protect the company's brand image.

[0266] Afterward, users can further customize their characters through their devices. For example, they can add clothing and accessories, and fine-tune the character's personality. This can be done intuitively through an interactive UI.

[0267] Furthermore, the server automatically generates activity plans for virtual influencers based on the characteristics of the provided digital events and campaigns. These plans are designed to reach the target audience at the most effective time.

[0268] For example, if a user enters the prompt "Generate a fresh and energetic virtual influencer to introduce our new spring collection," the server will create an appropriate character and content based on that information.

[0269] Real-time monitoring allows the server to evaluate the effectiveness of virtual influencer activities and optimize marketing strategies based on the collected data. For example, it can analyze the times of day when more engagement is achieved and reflect this in the next posting schedule. In this way, a flexible and efficient system is created to maximize the effectiveness of brand promotions.

[0270] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0271] Step 1:

[0272] The user inputs brand promotion requirements via a terminal. This input includes the desired appearance and voice characteristics of the virtual influencer, personality, and target audience profile. This information is transmitted to the system as prompts. This input allows the system to specifically understand the customization requirements.

[0273] Step 2:

[0274] The server generates virtual influencers using image generation AI models and voice generation AI models based on input information received from the user. Here, the server analyzes the input prompt text and applies it to the generation model to generate a character that meets specific requirements. For example, it generates image data according to specified hair color and whether or not the character is wearing a hat, and processes voice data according to specified tone and accent.

[0275] Step 3:

[0276] The server analyzes the generated characters through a security check function and automatically detects inappropriate elements. Specifically, it scans the generated text and audio data using a machine learning model to check for inappropriate words or expressions. If inappropriate elements are detected, the server automatically corrects them and converts them into appropriate data.

[0277] Step 4:

[0278] Users can use their devices to further customize the generated virtual influencers. For example, they can manipulate clothing styles and add or change accessories in real time through an interactive user interface. They can also fine-tune the character's personality and energy level.

[0279] Step 5:

[0280] Based on the provided specifications of the digital event, the server generates an activity plan for the virtual influencer. In this plan, the most effective time slots are selected based on user requirements, and the posting schedule and content are determined. Data analysis is performed, taking into account past engagement data, aiming for optimal reach to the target audience.

[0281] Step 6:

[0282] The server monitors the activities of the virtual influencer in real time and collects its performance data. For example, it analyzes data on post reactions and engagement, which is useful for optimizing the marketing strategy. This enables identifying areas for improvement in the next campaign plan and continuously conducting effective promotions.

[0283] (Application Example 1)

[0284] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0285] In conventional promotion activities, it is difficult to efficiently generate a virtual character that suits the brand's characteristics and conduct effective promotional activities using that character. There is also an issue that it is difficult to optimize the advertising strategy in real time while minimizing the risk of generating inappropriate content.

[0286] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0287] In this invention, the server includes means for generating a virtual person model based on user information, means for analyzing the data to detect inappropriate elements in the generated visual and audio data, and means for generating an action plan for the virtual person model based on the provided activities. This makes it possible to flexibly and accurately carry out promotional activities for the virtual person model and suppress the generation of inappropriate content.

[0288] "User information" refers to data, including brand requirements and characteristics, that are acquired for the purpose of generating a virtual persona model.

[0289] A "virtual character model" is a digital character created using generative AI, possessing an appearance and conversational abilities tailored to a specific brand or promotion.

[0290] A "generative model" refers to a set of algorithms and technologies used to generate a virtual human model based on input information.

[0291] "Visual and audio data" refers to the graphic and audio elements of the generated virtual character model.

[0292] "Inappropriate elements" are content elements that may damage the brand image or be considered socially inappropriate.

[0293] "Data analysis" refers to analytical methods used to identify inappropriate elements from generated visual and audio data.

[0294] An "action plan" outlines a schedule and content strategy for how a fictional character model can effectively operate and promote the brand.

[0295] A "smart device" refers to electronic devices or applications used to utilize the generated virtual human model.

[0296] To implement this invention, the server first collects information from the user and generates a virtual person model. The server utilizes input data based on brand requirements and characteristics, and uses a generative AI model to create the virtual person model. This model is a digital character customized by image generation AI and voice generation AI.

[0297] For visual and audio data, the server analyzes the data to detect inappropriate elements. Specifically, data analysis tools such as Amazon Rekognition are used to identify and correct inappropriate elements within the content. This process ensures that the content is socially appropriate and does not damage the brand image.

[0298] The server also generates an action plan for the virtual character model. This action plan details how the generated character model will act and promote the brand. This makes it possible to develop content strategies optimized for digital events and promotions.

[0299] Smart devices utilize these generated virtual person models for promotional activities. For example, users can watch promotional videos or experience interactive content through smartphone apps.

[0300] As a concrete example, when a cosmetics brand conducts a promotion to introduce a new product, a video is generated featuring a virtual model highlighting the product's features. When users watch this video on their devices, its appeal to the target audience increases.

[0301] An example of a prompt message would be: "Generate a promotional video for a new cosmetic product aimed at women. This product features a vibrant red color."

[0302] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0303] Step 1:

[0304] The user uses a smart device to input brand requirements and characteristics. By sending this input data to the server, the generation of a virtual character model is initiated. The input data includes detailed brand information such as a prompt sentence.

[0305] Step 2:

[0306] Based on the received brand requirements, the server creates a virtual character model using a generative AI model. Based on the prompt sentence received as input, an image generation AI generates a visual model, and an audio generation AI creates audio data. As a result, a virtual character model that matches the user's brand is output.

[0307] Step 3:

[0308] The server analyzes the generated visual and audio data and detects inappropriate elements. AI tools such as Amazon Rekognition are used for this analysis. If the server detects inappropriate elements, it corrects them and regenerates them into an appropriate state, and outputs clean model data.

[0309] Step 4:

[0310] Based on the obtained visual and audio data, the server generates an action plan for the virtual character model. This plan includes the schedule of promotional activities and details of the content. The data is processed and the strategy is optimized, and an action plan based on this is output.

[0311] Step 5:

[0312] On smart devices, action plans are utilized, and users are provided with interactive promotional experiences. Users can view content generated through smartphone apps and other means, and understand the brand's characteristics. User engagement data from each device is fed back to the server.

[0313] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0314] This invention is a virtual influencer system incorporating an emotion engine, providing a platform that enables companies to achieve more personalized interactions with users. The system begins with a process in which a server generates a virtual character in real time based on brand requirements entered by the user through a terminal.

[0315] The server uses an emotion engine to recognize the user's emotional state in real time and dynamically adjust the virtual character's responses based on that data. This emotion engine includes an AI algorithm to analyze the user's emotions from the feedback and interactions they provide. This allows the virtual character to display a tone and response appropriate to the user's emotions.

[0316] Furthermore, the server runs security features to check the generated character content for inappropriate elements and makes corrections as needed. This process is performed in real time, minimizing the risk of inappropriate content being created.

[0317] The virtual influencer's activity plan is automatically generated by the server according to the advertising campaign's goals. Based on user feedback obtained through the emotion engine, this activity plan can be dynamically adjusted. This feedback loop enables the implementation of effective marketing strategies that resonate with user emotions.

[0318] Ultimately, the server analyzes multiple data points derived from the virtual influencer's performance and automatically generates suggestions for optimizing the strategy. This data also includes user sentiment data collected by the sentiment engine, enabling deeper insights. For example, it might analyze how specific character portrayals affect users emotionally and recommend adjusting content based on the results.

[0319] Thus, virtual influencer systems that combine emotion engines can provide companies with a new dimension of brand engagement and further enrich the user experience.

[0320] The following describes the processing flow.

[0321] Step 1:

[0322] Users access the platform using their devices and enter their brand requirements and desired character traits. This sends detailed data about the virtual influencer's appearance and behavior to the server.

[0323] Step 2:

[0324] The server uses image generation AI to create a virtual character in real time based on the received data. In this process, the character's visual appearance is constructed according to the specified features.

[0325] Step 3:

[0326] The server utilizes voice generation AI to generate voices that are suitable for the virtual character. These voices will be in line with the character's personality and the brand's tone.

[0327] Step 4:

[0328] The server presents the user with an initial version of the character, and the user provides feedback via their device. The user can further customize the character's appearance and voice as needed.

[0329] Step 5:

[0330] The server activates the emotion engine and collects emotional data provided by the user through the device. The emotion engine analyzes the user's emotions from nonverbal cues and direct feedback.

[0331] Step 6:

[0332] Based on this emotional data, the server dynamically adjusts the virtual character's responses and behavior. For example, if the user shows a positive reaction, the character will respond in a more friendly tone.

[0333] Step 7:

[0334] The server performs security checks on the generated content, automatically detecting and correcting inappropriate elements. This eliminates any parts that do not conform to the brand image.

[0335] Step 8:

[0336] The server generates an activity plan for virtual influencers based on the user's advertising campaign goals. This activity plan includes adjustments based on feedback from the sentiment engine.

[0337] Step 9:

[0338] The server monitors the activity of virtual influencers and analyzes real-time data. This includes sentiment data, providing deeper insights into understanding user reactions.

[0339] Step 10:

[0340] The server uses these analysis results to automatically generate and provide suggestions for optimizing the strategy. This enables more effective marketing activities.

[0341] (Example 2)

[0342] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0343] Traditional virtual character systems have struggled to dynamically adjust responses based on user emotions and to immediately correct inappropriate content. Furthermore, their activity plans are static, resulting in insufficient marketing strategy efficiency. This has led to a limited user experience and hindered companies from improving brand engagement.

[0344] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0345] In this invention, the server includes means for acquiring input information to generate a virtual character based on customer requirements, means for creating a virtual character using a generative model, and means for analyzing the user's emotional state using an emotion analysis engine and dynamically adjusting the virtual character's response. This enables real-time, personalized interaction that responds to the user's emotions.

[0346] "Customer requirements" refer to information that indicates the attributes and conditions that users desire regarding the creation and response of virtual characters.

[0347] A "virtual character" is a digital character created on a computer that engages in dialogue and interaction with the user.

[0348] "Input information" refers to digital data provided by the user from their device, including the requirements and instructions the system needs to generate characters.

[0349] A "generative model" is an algorithm or program used to create virtual characters, determining the character's appearance and behavior based on specific inputs.

[0350] An "emotion analysis engine" refers to artificial intelligence technology used to analyze a user's emotional state in real time, inferring emotions from the user's responses and feedback.

[0351] "Inappropriate elements" refer to expressions or information that may be included in the generated content but do not meet the required standards.

[0352] An "activity plan" is a plan that specifies the schedule and procedures for interactions that a virtual character should perform, and is set based on the goals of an advertising campaign, etc.

[0353] A "feedback loop" refers to a system that continuously receives user feedback and opinions, and dynamically adjusts its characters and plans based on that feedback.

[0354] "Suggestions for optimizing strategy" involve analyzing the results of a character's activities and then identifying areas for improvement and strategies to make future interactions and activities more effective.

[0355] This invention is a virtual character generation system equipped with an emotion analysis engine, providing a platform for companies to realize personalized interactions with users. Specific embodiments for carrying out this invention are described below.

[0356] The user uses a terminal to provide the system with input information regarding brand requirements and target profile. This information is entered in text format, and the system receives it. For example, the user might input branding instructions such as "a youthful and healthy image."

[0357] The server utilizes a generative AI model to process this input information. A commonly used language generation model is employed for this purpose. Based on the input information, the server generates a profile for a virtual character. During this process, prompt statements are sent to the AI ​​model. For example, a possible prompt statement might be, "Generate a character with a healthy image aimed at young people."

[0358] Subsequently, the server uses an emotion analysis engine to analyze the user's emotional state in real time. This allows the virtual character's responses to dynamically adjust to the user's current emotions. Data such as user feedback and dialogue history are used for emotion analysis.

[0359] The content of generated virtual characters is constantly checked for inappropriate elements. The server uses AI-based filtering technology to perform content checks, and any elements deemed inappropriate are corrected immediately.

[0360] Furthermore, the server automatically generates an action plan based on the advertising campaign's goals and dynamically updates it based on actual user feedback. This ensures that the virtual character always acts in a way that is in line with the user's preferences and emotions.

[0361] Ultimately, this system analyzes the data collected by the server and generates suggestions to help optimize marketing strategies. The server analyzes multiple data points, including sentiment data, and based on this, provides companies with more effective strategies. This enables companies to improve the user experience and strengthen brand engagement.

[0362] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0363] Step 1:

[0364] The user uses a terminal to input information about the brand's requirements and target image. This input is sent to the server in text format. For example, the user might input the requirement "a youthful and healthy image." This information is then transferred to the server and prepared for the next processing step.

[0365] Step 2:

[0366] The server creates a prompt for the generative AI model based on the input information it receives. The model receives a prompt that reflects the characteristics derived from the input information, such as "Generate a character with a healthy image aimed at young people." The generative AI model uses the prompt as input to generate a profile of a virtual character and provides the server with specific character information as output.

[0367] Step 3:

[0368] The server uses an emotion analysis engine to analyze the user's emotional state based on user interactions after the virtual character is generated. This analysis uses user feedback and chat logs as input data. The emotion analysis engine processes this data and generates the user's emotional state as output. Based on this emotional information, the server adjusts the virtual character's responses in real time.

[0369] Step 4:

[0370] The server uses AI filtering technology to check whether the generated virtual character content contains any inappropriate elements. The generated character's text and images become input data, and the AI ​​filter searches for inappropriate elements. If inappropriate elements are detected, the corrected content is regenerated as a new output.

[0371] Step 5:

[0372] The server automatically generates an activity plan. This plan is created using emotional feedback from the user and past interaction data of the virtual character. The server analyzes this data and outputs an activity plan tailored to the target audience. Furthermore, this activity plan is dynamically adjusted through a feedback loop, proposing a strategy that reflects the latest user preferences.

[0373] (Application Example 2)

[0374] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0375] In today's digital advertising market, there is a demand for advertising experiences tailored to individual consumers, but achieving this remains challenging. In particular, there is a lack of effective methods for responding to consumer emotions in the development of personalized advertising. Furthermore, there is a risk that inappropriate advertising content will cause discomfort to users, necessitating the establishment of systems that efficiently adjust these factors in real time.

[0376] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0377] In this invention, the server includes means for analyzing customer information to obtain construction information, means for using a generation program to create a virtual construct using the construction information, and means for analyzing a function obtained based on the operation plan and generating a proposal for optimizing the strategy. This makes it possible to display advertisements that are in line with the consumer's emotions in real time and optimize the advertising experience.

[0378] "Customer information" refers to foundational information for generating virtual constructs, and specifically data related to consumers.

[0379] "Construction information" refers to detailed data for generating constructs obtained by analyzing customer information.

[0380] A "virtual construct" refers to a digital character or object that is generated based on digital information.

[0381] A "generation program" is a program used to create a virtual construct using construction information.

[0382] "Non-conforming factors" refer to inappropriate elements or problems contained within the constructed information.

[0383] An "action plan" is a proposed plan for constructing the behavior of a virtual construct based on the informational events provided.

[0384] "Policy" refers to a set of action guidelines optimized based on an action plan.

[0385] An "emotional analysis program" is a program designed to analyze the emotional state of a passive recipient and adjust the response of a virtual construct.

[0386] "Advertising content" refers to the content of advertisements presented to consumers, which is selected and displayed accordingly.

[0387] In this embodiment of the invention, a camera function and a dedicated application are installed on the terminal accessed by the user to acquire the user's emotional information in real time. An emotional analysis program analyzes this emotional information and generates data to dynamically adjust the response of the virtual construct. The server executes a generation program based on the generated construct information to create a virtual construct suitable for the user.

[0388] The server combines acquired user emotion information with provided information events to formulate an action plan. This forms the basis for dynamically selecting ad content. The ad content selected through emotion analysis is displayed on the user's device to optimize the user experience. The processing uses image processing libraries such as OpenCV and emotion recognition software called EmotionRecognizer, which uses AI algorithms.

[0389] For example, if a user smiles while using the application, the system recognizes the smile and displays positive and energetic advertisements. This ensures that the advertisements align with the user's emotions, enabling the implementation of effective advertising campaigns.

[0390] An example of a prompt might be: "When the user looks into the camera and is smiling, display an ad promoting a trending product in a positive tone." This allows the ad content to provide an appropriate response that aligns with the user's current emotional state.

[0391] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0392] Step 1:

[0393] The user launches an application on their device and enables the camera function. At this time, the device inputs video data from the camera in real time and sends that data to the server.

[0394] Step 2:

[0395] The server performs face detection on the received video data using the OpenCV library. The detected face data is used as input, and EmotionRecognizer is used to analyze the user's emotions. The analysis results are output as the user's emotional state (e.g., joy, sadness, surprise).

[0396] Step 3:

[0397] The server develops an action plan for the virtual construct based on the analyzed emotional state. The inputs to this action plan are the user's emotional state and the campaign objective, and the output is an action plan that includes adjusted responses and expression parameters. This plan influences the selected ad content.

[0398] Step 4:

[0399] The server selects appropriate ad content based on the action plan. Using the sentiment state and action plan received as input, it selects the most suitable ad from the ad database. This ad content is output and sent to the terminal.

[0400] Step 5:

[0401] The device displays advertising content sent from the server to the user. Specifically, selected advertisements are shown on the device's display. This display ensures that the user experience matches the emotionally tailored advertisement content, improving engagement.

[0402] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0403] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0404] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0405] [Third Embodiment]

[0406] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0407] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0408] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0409] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0410] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0411] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0412] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0413] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0414] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0415] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0416] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0417] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0418] This invention provides a platform for companies to conduct efficient brand promotions using virtual influencers. The system begins with the user inputting specific brand requirements via a terminal. Based on the user's input, the server uses image generation AI and voice generation AI to generate a customizable virtual character.

[0419] The generated characters have appearances and voices that conform to the brand's requirements, and further fine-tuning is performed by the server. Users can further customize the character's appearance and personality through their devices.

[0420] The server is equipped with a security check function that detects potential inappropriate elements in the generated content. If inappropriate elements are detected, the server automatically corrects them and regenerates the content appropriately. This process ensures that the content does not damage the company's brand image.

[0421] Next, the server creates an activity plan for the virtual influencer based on the user's advertising campaign goals. This activity plan is optimized according to the characteristics of the digital event and includes the character's posting schedule and themes. This dynamic planning maximizes the campaign's effectiveness.

[0422] During the activity, the server monitors the virtual influencer's performance in real time. The collected data is used as a basis for evaluating and optimizing marketing strategies. For example, it is possible to identify the times when follower engagement is highest and adjust posts to match those times.

[0423] This enables companies to conduct flexible and creative digital marketing activities and promote their brands efficiently. This system represents a new way to maximize the effectiveness of virtual influencers and reduce marketing risks.

[0424] The following describes the processing flow.

[0425] Step 1:

[0426] Users access the platform using their devices and input specific requirements for the brand and characteristics of the characters. This includes the characters' age, gender, appearance, and content style.

[0427] Step 2:

[0428] Based on the information received from the user, the server activates an image generation AI to generate the appearance of a virtual character. In this process, the AI ​​considers the specified parameters and creates an appearance that meets the requirements.

[0429] Step 3:

[0430] The server uses voice generation AI to generate voices that are suitable for the virtual character. This creates a speaking style and tone that matches the character's personality.

[0431] Step 4:

[0432] The server presents the generated character to the user, who then customizes the character in detail via their device. At this stage, it is possible to adjust hairstyles, clothing, accessories, and other elements.

[0433] Step 5:

[0434] The server completes the final character and performs security checks on the generated content. The AI ​​detects inappropriate elements and automatically corrects them if necessary.

[0435] Step 6:

[0436] The server generates an activity plan for the virtual influencer based on the advertising campaign goals set by the user. The plan includes post content, frequency, and optimal timing.

[0437] Step 7:

[0438] The server monitors the virtual influencer's activities in real time and collects the data obtained. The collected data is used to analyze engagement rates and follower growth.

[0439] Step 8:

[0440] Based on the analysis results, the server automatically generates suggestions for optimizing campaigns and strategies and reports them to the user. This can improve the effectiveness of promotional activities.

[0441] (Example 1)

[0442] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0443] Traditional brand promotion methods struggle to create virtual influencers who can effectively and engagingly communicate information to target audiences. Furthermore, inappropriate content can damage the brand image. Additionally, creating activity plans for virtual influencers and evaluating and optimizing their effectiveness requires significant effort and time.

[0444] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0445] In this invention, the server includes means for acquiring information to generate a virtual person based on customer requirements, means for creating a virtual person using the information and a generation AI model, means for analyzing and automatically correcting the content to detect inappropriate elements in the generated content, and means for generating a schedule for the virtual person based on the provided activities. This enables efficient and accurate generation and management of virtual influencers, maximizing the effectiveness of brand promotions.

[0446] "Customer requirements" refer to information that describes the conditions and characteristics that a fictional character should meet in brand promotion.

[0447] "Means of acquiring information" refers to methods or devices for collecting data in order to understand customer requirements.

[0448] A "generative AI model" is an algorithm or software system that uses artificial intelligence technology to create virtual people, images, voices, and so on.

[0449] "Means for creating a virtual character" refers to a method or apparatus that utilizes a generative AI model to generate a virtual character based on specified conditions.

[0450] "Means for analyzing content to detect inappropriate elements" refers to a method or apparatus for analyzing data to identify inappropriate elements that may be contained within the generated content.

[0451] "Means of automatic correction" refers to a method or apparatus that uses predefined rules or algorithms to correct detected inappropriate elements and regenerate them into appropriate content.

[0452] "Means for generating a virtual person's schedule based on activities" refers to a method or apparatus for setting the activity schedule and content of a virtual influencer, taking into account the characteristics of the provided event or campaign.

[0453] This invention will now describe embodiments for carrying out this invention. This system is for generating and managing virtual influencers in order to efficiently carry out brand promotion.

[0454] First, the user accesses the system via a terminal and enters the requirements necessary for promoting the brand. This includes the appearance and voice characteristics that the virtual influencer should meet, personality, and the profile of the target audience. The user can communicate detailed requests to the system using prompt messages.

[0455] Upon receiving this input information, the server utilizes image generation AI models (e.g., DALL-E) and speech generation AI models (e.g., Google Cloud Text-to-Speech) to generate a virtual influencer. The generated character will have appearance and voice characteristics tailored to the brand's requirements.

[0456] After generation, the server uses a security check function to analyze the generated content for any inappropriate elements. If inappropriate elements are found, the server automatically corrects them and regenerates the content to be appropriate. This helps protect the company's brand image.

[0457] Afterward, users can further customize their characters through their devices. For example, they can add clothing and accessories, and fine-tune the character's personality. This can be done intuitively through an interactive UI.

[0458] Furthermore, the server automatically generates activity plans for virtual influencers based on the characteristics of the provided digital events and campaigns. These plans are designed to reach the target audience at the most effective time.

[0459] For example, if a user enters the prompt "Generate a fresh and energetic virtual influencer to introduce our new spring collection," the server will create an appropriate character and content based on that information.

[0460] Real-time monitoring allows the server to evaluate the effectiveness of virtual influencer activities and optimize marketing strategies based on the collected data. For example, it can analyze the times of day when more engagement is achieved and reflect this in the next posting schedule. In this way, a flexible and efficient system is created to maximize the effectiveness of brand promotions.

[0461] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0462] Step 1:

[0463] The user inputs brand promotion requirements via a terminal. This input includes the desired appearance and voice characteristics of the virtual influencer, personality, and target audience profile. This information is transmitted to the system as prompts. This input allows the system to specifically understand the customization requirements.

[0464] Step 2:

[0465] The server generates virtual influencers using image generation AI models and voice generation AI models based on input information received from the user. Here, the server analyzes the input prompt text and applies it to the generation model to generate a character that meets specific requirements. For example, it generates image data according to specified hair color and whether or not the character is wearing a hat, and processes voice data according to specified tone and accent.

[0466] Step 3:

[0467] The server analyzes the generated characters through a security check function and automatically detects inappropriate elements. Specifically, it scans the generated text and audio data using a machine learning model to check for inappropriate words or expressions. If inappropriate elements are detected, the server automatically corrects them and converts them into appropriate data.

[0468] Step 4:

[0469] Users can use their devices to further customize the generated virtual influencers. For example, they can manipulate clothing styles and add or change accessories in real time through an interactive user interface. They can also fine-tune the character's personality and energy level.

[0470] Step 5:

[0471] The server generates an activity plan for virtual influencers based on the specifications of the provided digital event. This plan selects the most effective time slots based on user requirements and determines posting schedules and content. Data analysis is performed, taking into account past engagement data, to aim for optimal reach to the target audience.

[0472] Step 6:

[0473] The server monitors the activities of virtual influencers in real time and collects their performance data. For example, it analyzes data on post reactions and engagement to help optimize marketing strategies. This allows for identifying areas for improvement in future campaign plans and enabling continuous, effective promotion.

[0474] (Application Example 1)

[0475] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0476] In traditional promotional activities, it is difficult to efficiently generate virtual characters that match the characteristics of a brand and to use those characters to conduct effective advertising campaigns. Furthermore, there are challenges in optimizing advertising strategies in real time while minimizing the risk of inappropriate content.

[0477] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0478] In this invention, the server includes means for generating a virtual person model based on user information, means for analyzing the data to detect inappropriate elements in the generated visual and audio data, and means for generating an action plan for the virtual person model based on the provided activities. This makes it possible to flexibly and accurately carry out promotional activities for the virtual person model and suppress the generation of inappropriate content.

[0479] "User information" refers to data, including brand requirements and characteristics, that are acquired for the purpose of generating a virtual persona model.

[0480] A "virtual character model" is a digital character created using generative AI, possessing an appearance and conversational abilities tailored to a specific brand or promotion.

[0481] A "generative model" refers to a set of algorithms and technologies used to generate a virtual human model based on input information.

[0482] "Visual and audio data" refers to the graphic and audio elements of the generated virtual character model.

[0483] "Inappropriate elements" are content elements that may damage the brand image or be considered socially inappropriate.

[0484] "Data analysis" refers to analytical methods used to identify inappropriate elements from generated visual and audio data.

[0485] An "action plan" outlines a schedule and content strategy for how a fictional character model can effectively operate and promote the brand.

[0486] A "smart device" refers to electronic devices or applications used to utilize the generated virtual human model.

[0487] To implement this invention, the server first collects information from the user and generates a virtual person model. The server utilizes input data based on brand requirements and characteristics, and uses a generative AI model to create the virtual person model. This model is a digital character customized by image generation AI and voice generation AI.

[0488] For visual and audio data, the server analyzes the data to detect inappropriate elements. Specifically, data analysis tools such as Amazon Rekognition are used to identify and correct inappropriate elements within the content. This process ensures that the content is socially appropriate and does not damage the brand image.

[0489] The server also generates an action plan for the virtual character model. This action plan details how the generated character model will act and promote the brand. This makes it possible to develop content strategies optimized for digital events and promotions.

[0490] Smart devices utilize these generated virtual person models for promotional activities. For example, users can watch promotional videos or experience interactive content through smartphone apps.

[0491] As a concrete example, when a cosmetics brand conducts a promotion to introduce a new product, a video is generated featuring a virtual model highlighting the product's features. When users watch this video on their devices, its appeal to the target audience increases.

[0492] An example of a prompt message would be: "Generate a promotional video for a new cosmetic product aimed at women. This product features a vibrant red color."

[0493] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0494] Step 1:

[0495] Users input brand requirements and characteristics using smart devices. This input data is sent to the server, initiating the generation of a virtual persona model. The input data includes detailed brand information, such as prompt text.

[0496] Step 2:

[0497] The server creates a virtual person model using a generative AI model based on the received brand requirements. Based on the prompt text received as input, the image generation AI generates a visual model, and the voice generation AI creates voice data. This results in a virtual person model that matches the user's brand.

[0498] Step 3:

[0499] The server analyzes the generated visual and audio data to detect inappropriate elements. This analysis uses AI tools such as Amazon Rekognition. If the server detects inappropriate elements, it corrects them, regenerates the data in an appropriate state, and outputs clean model data.

[0500] Step 4:

[0501] The server generates an action plan for a virtual character model based on the acquired visual and audio data. This plan includes the schedule and content details of promotional activities. The server then processes the data and optimizes the strategy, outputting an action plan based on these optimizations.

[0502] Step 5:

[0503] On smart devices, action plans are utilized, and users are provided with interactive promotional experiences. Users can view content generated through smartphone apps and other means, and understand the brand's characteristics. User engagement data from each device is fed back to the server.

[0504] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0505] This invention is a virtual influencer system incorporating an emotion engine, providing a platform that enables companies to achieve more personalized interactions with users. The system begins with a process in which a server generates a virtual character in real time based on brand requirements entered by the user through a terminal.

[0506] The server uses an emotion engine to recognize the user's emotional state in real time and dynamically adjust the virtual character's responses based on that data. This emotion engine includes an AI algorithm to analyze the user's emotions from the feedback and interactions they provide. This allows the virtual character to display a tone and response appropriate to the user's emotions.

[0507] Furthermore, the server runs security features to check the generated character content for inappropriate elements and makes corrections as needed. This process is performed in real time, minimizing the risk of inappropriate content being created.

[0508] The virtual influencer's activity plan is automatically generated by the server according to the advertising campaign's goals. Based on user feedback obtained through the emotion engine, this activity plan can be dynamically adjusted. This feedback loop enables the implementation of effective marketing strategies that resonate with user emotions.

[0509] Ultimately, the server analyzes multiple data points derived from the virtual influencer's performance and automatically generates suggestions for optimizing the strategy. This data also includes user sentiment data collected by the sentiment engine, enabling deeper insights. For example, it might analyze how specific character portrayals affect users emotionally and recommend adjusting content based on the results.

[0510] Thus, virtual influencer systems that combine emotion engines can provide companies with a new dimension of brand engagement and further enrich the user experience.

[0511] The following describes the processing flow.

[0512] Step 1:

[0513] Users access the platform using their devices and enter their brand requirements and desired character traits. This sends detailed data about the virtual influencer's appearance and behavior to the server.

[0514] Step 2:

[0515] The server uses image generation AI to create a virtual character in real time based on the received data. In this process, the character's visual appearance is constructed according to the specified features.

[0516] Step 3:

[0517] The server utilizes voice generation AI to generate voices that are suitable for the virtual character. These voices will be in line with the character's personality and the brand's tone.

[0518] Step 4:

[0519] The server presents the user with an initial version of the character, and the user provides feedback via their device. The user can further customize the character's appearance and voice as needed.

[0520] Step 5:

[0521] The server activates the emotion engine and collects emotional data provided by the user through the device. The emotion engine analyzes the user's emotions from nonverbal cues and direct feedback.

[0522] Step 6:

[0523] Based on this emotional data, the server dynamically adjusts the virtual character's responses and behavior. For example, if the user shows a positive reaction, the character will respond in a more friendly tone.

[0524] Step 7:

[0525] The server performs security checks on the generated content, automatically detecting and correcting inappropriate elements. This eliminates any parts that do not conform to the brand image.

[0526] Step 8:

[0527] The server generates an activity plan for virtual influencers based on the user's advertising campaign goals. This activity plan includes adjustments based on feedback from the sentiment engine.

[0528] Step 9:

[0529] The server monitors the activity of virtual influencers and analyzes real-time data. This includes sentiment data, providing deeper insights into understanding user reactions.

[0530] Step 10:

[0531] The server uses these analysis results to automatically generate and provide suggestions for optimizing the strategy. This enables more effective marketing activities.

[0532] (Example 2)

[0533] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0534] Traditional virtual character systems have struggled to dynamically adjust responses based on user emotions and to immediately correct inappropriate content. Furthermore, their activity plans are static, resulting in insufficient marketing strategy efficiency. This has led to a limited user experience and hindered companies from improving brand engagement.

[0535] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0536] In this invention, the server includes means for acquiring input information to generate a virtual character based on customer requirements, means for creating a virtual character using a generative model, and means for analyzing the user's emotional state using an emotion analysis engine and dynamically adjusting the virtual character's response. This enables real-time, personalized interaction that responds to the user's emotions.

[0537] "Customer requirements" refer to information that indicates the attributes and conditions that users desire regarding the creation and response of virtual characters.

[0538] A "virtual character" is a digital character created on a computer that engages in dialogue and interaction with the user.

[0539] "Input information" refers to digital data provided by the user from their device, including the requirements and instructions the system needs to generate characters.

[0540] A "generative model" is an algorithm or program used to create virtual characters, determining the character's appearance and behavior based on specific inputs.

[0541] An "emotion analysis engine" refers to artificial intelligence technology used to analyze a user's emotional state in real time, inferring emotions from the user's responses and feedback.

[0542] "Inappropriate elements" refer to expressions or information that may be included in the generated content but do not meet the required standards.

[0543] An "activity plan" is a plan that specifies the schedule and procedures for interactions that a virtual character should perform, and is set based on the goals of an advertising campaign, etc.

[0544] A "feedback loop" refers to a system that continuously receives user feedback and opinions, and dynamically adjusts its characters and plans based on that feedback.

[0545] "Suggestions for optimizing strategy" involve analyzing the results of a character's activities and then identifying areas for improvement and strategies to make future interactions and activities more effective.

[0546] This invention is a virtual character generation system equipped with an emotion analysis engine, providing a platform for companies to realize personalized interactions with users. Specific embodiments for carrying out this invention are described below.

[0547] The user uses a terminal to provide the system with input information regarding brand requirements and target profile. This information is entered in text format, and the system receives it. For example, the user might input branding instructions such as "a youthful and healthy image."

[0548] The server utilizes a generative AI model to process this input information. A commonly used language generation model is employed for this purpose. Based on the input information, the server generates a profile for a virtual character. During this process, prompt statements are sent to the AI ​​model. For example, a possible prompt statement might be, "Generate a character with a healthy image aimed at young people."

[0549] Subsequently, the server uses an emotion analysis engine to analyze the user's emotional state in real time. This allows the virtual character's responses to dynamically adjust to the user's current emotions. Data such as user feedback and dialogue history are used for emotion analysis.

[0550] The content of generated virtual characters is constantly checked for inappropriate elements. The server uses AI-based filtering technology to perform content checks, and any elements deemed inappropriate are corrected immediately.

[0551] Furthermore, the server automatically generates an action plan based on the advertising campaign's goals and dynamically updates it based on actual user feedback. This ensures that the virtual character always acts in a way that is in line with the user's preferences and emotions.

[0552] Ultimately, this system analyzes the data collected by the server and generates suggestions to help optimize marketing strategies. The server analyzes multiple data points, including sentiment data, and based on this, provides companies with more effective strategies. This enables companies to improve the user experience and strengthen brand engagement.

[0553] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0554] Step 1:

[0555] The user uses a terminal to input information about the brand's requirements and target image. This input is sent to the server in text format. For example, the user might input the requirement "a youthful and healthy image." This information is then transferred to the server and prepared for the next processing step.

[0556] Step 2:

[0557] The server creates a prompt for the generative AI model based on the input information it receives. The model receives a prompt that reflects the characteristics derived from the input information, such as "Generate a character with a healthy image aimed at young people." The generative AI model uses the prompt as input to generate a profile of a virtual character and provides the server with specific character information as output.

[0558] Step 3:

[0559] The server uses an emotion analysis engine to analyze the user's emotional state based on user interactions after the virtual character is generated. This analysis uses user feedback and chat logs as input data. The emotion analysis engine processes this data and generates the user's emotional state as output. Based on this emotional information, the server adjusts the virtual character's responses in real time.

[0560] Step 4:

[0561] The server uses AI filtering technology to check whether the generated virtual character content contains any inappropriate elements. The generated character's text and images become input data, and the AI ​​filter searches for inappropriate elements. If inappropriate elements are detected, the corrected content is regenerated as a new output.

[0562] Step 5:

[0563] The server automatically generates an activity plan. This plan is created using emotional feedback from the user and past interaction data of the virtual character. The server analyzes this data and outputs an activity plan tailored to the target audience. Furthermore, this activity plan is dynamically adjusted through a feedback loop, proposing a strategy that reflects the latest user preferences.

[0564] (Application Example 2)

[0565] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0566] In today's digital advertising market, there is a demand for advertising experiences tailored to individual consumers, but achieving this remains challenging. In particular, there is a lack of effective methods for responding to consumer emotions in the development of personalized advertising. Furthermore, there is a risk that inappropriate advertising content will cause discomfort to users, necessitating the establishment of systems that efficiently adjust these factors in real time.

[0567] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0568] In this invention, the server includes means for analyzing customer information to obtain construction information, means for using a generation program to create a virtual construct using the construction information, and means for analyzing a function obtained based on the operation plan and generating a proposal for optimizing the strategy. This makes it possible to display advertisements that are in line with the consumer's emotions in real time and optimize the advertising experience.

[0569] "Customer information" refers to foundational information for generating virtual constructs, and specifically data related to consumers.

[0570] "Construction information" refers to detailed data for generating constructs obtained by analyzing customer information.

[0571] A "virtual construct" refers to a digital character or object that is generated based on digital information.

[0572] A "generation program" is a program used to create a virtual construct using construction information.

[0573] "Non-conforming factors" refer to inappropriate elements or problems contained within the constructed information.

[0574] An "action plan" is a proposed plan for constructing the behavior of a virtual construct based on the informational events provided.

[0575] "Policy" refers to a set of action guidelines optimized based on an action plan.

[0576] An "emotional analysis program" is a program designed to analyze the emotional state of a passive recipient and adjust the response of a virtual construct.

[0577] "Advertising content" refers to the content of advertisements presented to consumers, which is selected and displayed accordingly.

[0578] In this embodiment of the invention, a camera function and a dedicated application are installed on the terminal accessed by the user to acquire the user's emotional information in real time. An emotional analysis program analyzes this emotional information and generates data to dynamically adjust the response of the virtual construct. The server executes a generation program based on the generated construct information to create a virtual construct suitable for the user.

[0579] The server combines acquired user emotion information with provided information events to formulate an action plan. This forms the basis for dynamically selecting ad content. The ad content selected through emotion analysis is displayed on the user's device to optimize the user experience. The processing uses image processing libraries such as OpenCV and emotion recognition software called EmotionRecognizer, which uses AI algorithms.

[0580] For example, if a user smiles while using the application, the system recognizes the smile and displays positive and energetic advertisements. This ensures that the advertisements align with the user's emotions, enabling the implementation of effective advertising campaigns.

[0581] An example of a prompt might be: "When the user looks into the camera and is smiling, display an ad promoting a trending product in a positive tone." This allows the ad content to provide an appropriate response that aligns with the user's current emotional state.

[0582] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0583] Step 1:

[0584] The user launches an application on their device and enables the camera function. At this time, the device inputs video data from the camera in real time and sends that data to the server.

[0585] Step 2:

[0586] The server performs face detection on the received video data using the OpenCV library. The detected face data is used as input, and EmotionRecognizer is used to analyze the user's emotions. The analysis results are output as the user's emotional state (e.g., joy, sadness, surprise).

[0587] Step 3:

[0588] The server develops an action plan for the virtual construct based on the analyzed emotional state. The inputs to this action plan are the user's emotional state and the campaign objective, and the output is an action plan that includes adjusted responses and expression parameters. This plan influences the selected ad content.

[0589] Step 4:

[0590] The server selects appropriate ad content based on the action plan. Using the sentiment state and action plan received as input, it selects the most suitable ad from the ad database. This ad content is output and sent to the terminal.

[0591] Step 5:

[0592] The device displays advertising content sent from the server to the user. Specifically, selected advertisements are shown on the device's display. This display ensures that the user experience matches the emotionally tailored advertisement content, improving engagement.

[0593] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0594] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0595] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0596] [Fourth Embodiment]

[0597] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0598] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0599] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0600] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0601] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0602] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0603] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0604] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0605] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0606] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0607] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0608] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0609] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0610] This invention provides a platform for companies to conduct efficient brand promotions using virtual influencers. The system begins with the user inputting specific brand requirements via a terminal. Based on the user's input, the server uses image generation AI and voice generation AI to generate a customizable virtual character.

[0611] The generated characters have appearances and voices that conform to the brand's requirements, and further fine-tuning is performed by the server. Users can further customize the character's appearance and personality through their devices.

[0612] The server is equipped with a security check function that detects potential inappropriate elements in the generated content. If inappropriate elements are detected, the server automatically corrects them and regenerates the content appropriately. This process ensures that the content does not damage the company's brand image.

[0613] Next, the server creates an activity plan for the virtual influencer based on the user's advertising campaign goals. This activity plan is optimized according to the characteristics of the digital event and includes the character's posting schedule and themes. This dynamic planning maximizes the campaign's effectiveness.

[0614] During the activity, the server monitors the virtual influencer's performance in real time. The collected data is used as a basis for evaluating and optimizing marketing strategies. For example, it is possible to identify the times when follower engagement is highest and adjust posts to match those times.

[0615] This enables companies to conduct flexible and creative digital marketing activities and promote their brands efficiently. This system represents a new way to maximize the effectiveness of virtual influencers and reduce marketing risks.

[0616] The following describes the processing flow.

[0617] Step 1:

[0618] Users access the platform using their devices and input specific requirements for the brand and characteristics of the characters. This includes the characters' age, gender, appearance, and content style.

[0619] Step 2:

[0620] Based on the information received from the user, the server activates an image generation AI to generate the appearance of a virtual character. In this process, the AI ​​considers the specified parameters and creates an appearance that meets the requirements.

[0621] Step 3:

[0622] The server uses voice generation AI to generate voices that are suitable for the virtual character. This creates a speaking style and tone that matches the character's personality.

[0623] Step 4:

[0624] The server presents the generated character to the user, who then customizes the character in detail via their device. At this stage, it is possible to adjust hairstyles, clothing, accessories, and other elements.

[0625] Step 5:

[0626] The server completes the final character and performs security checks on the generated content. The AI ​​detects inappropriate elements and automatically corrects them if necessary.

[0627] Step 6:

[0628] The server generates an activity plan for the virtual influencer based on the advertising campaign goals set by the user. The plan includes post content, frequency, and optimal timing.

[0629] Step 7:

[0630] The server monitors the virtual influencer's activities in real time and collects the data obtained. The collected data is used to analyze engagement rates and follower growth.

[0631] Step 8:

[0632] Based on the analysis results, the server automatically generates suggestions for optimizing campaigns and strategies and reports them to the user. This can improve the effectiveness of promotional activities.

[0633] (Example 1)

[0634] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0635] Traditional brand promotion methods struggle to create virtual influencers who can effectively and engagingly communicate information to target audiences. Furthermore, inappropriate content can damage the brand image. Additionally, creating activity plans for virtual influencers and evaluating and optimizing their effectiveness requires significant effort and time.

[0636] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0637] In this invention, the server includes means for acquiring information to generate a virtual person based on customer requirements, means for creating a virtual person using the information and a generation AI model, means for analyzing and automatically correcting the content to detect inappropriate elements in the generated content, and means for generating a schedule for the virtual person based on the provided activities. This enables efficient and accurate generation and management of virtual influencers, maximizing the effectiveness of brand promotions.

[0638] "Customer requirements" refer to information that describes the conditions and characteristics that a fictional character should meet in brand promotion.

[0639] "Means of acquiring information" refers to methods or devices for collecting data in order to understand customer requirements.

[0640] A "generative AI model" is an algorithm or software system that uses artificial intelligence technology to create virtual people, images, voices, and so on.

[0641] "Means for creating a virtual character" refers to a method or apparatus that utilizes a generative AI model to generate a virtual character based on specified conditions.

[0642] "Means for analyzing content to detect inappropriate elements" refers to a method or apparatus for analyzing data to identify inappropriate elements that may be contained within the generated content.

[0643] "Means of automatic correction" refers to a method or apparatus that uses predefined rules or algorithms to correct detected inappropriate elements and regenerate them into appropriate content.

[0644] "Means for generating a virtual person's schedule based on activities" refers to a method or apparatus for setting the activity schedule and content of a virtual influencer, taking into account the characteristics of the provided event or campaign.

[0645] This invention will now describe embodiments for carrying out this invention. This system is for generating and managing virtual influencers in order to efficiently carry out brand promotion.

[0646] First, the user accesses the system via a terminal and enters the requirements necessary for promoting the brand. This includes the appearance and voice characteristics that the virtual influencer should meet, personality, and the profile of the target audience. The user can communicate detailed requests to the system using prompt messages.

[0647] Upon receiving this input information, the server utilizes image generation AI models (e.g., DALL-E) and speech generation AI models (e.g., Google Cloud Text-to-Speech) to generate a virtual influencer. The generated character will have appearance and voice characteristics tailored to the brand's requirements.

[0648] After generation, the server uses a security check function to analyze the generated content for any inappropriate elements. If inappropriate elements are found, the server automatically corrects them and regenerates the content to be appropriate. This helps protect the company's brand image.

[0649] Afterward, users can further customize their characters through their devices. For example, they can add clothing and accessories, and fine-tune the character's personality. This can be done intuitively through an interactive UI.

[0650] Furthermore, the server automatically generates activity plans for virtual influencers based on the characteristics of the provided digital events and campaigns. These plans are designed to reach the target audience at the most effective time.

[0651] For example, if a user enters the prompt "Generate a fresh and energetic virtual influencer to introduce our new spring collection," the server will create an appropriate character and content based on that information.

[0652] Real-time monitoring allows the server to evaluate the effectiveness of virtual influencer activities and optimize marketing strategies based on the collected data. For example, it can analyze the times of day when more engagement is achieved and reflect this in the next posting schedule. In this way, a flexible and efficient system is created to maximize the effectiveness of brand promotions.

[0653] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0654] Step 1:

[0655] The user inputs brand promotion requirements via a terminal. This input includes the desired appearance and voice characteristics of the virtual influencer, personality, and target audience profile. This information is transmitted to the system as prompts. This input allows the system to specifically understand the customization requirements.

[0656] Step 2:

[0657] The server generates virtual influencers using image generation AI models and voice generation AI models based on input information received from the user. Here, the server analyzes the input prompt text and applies it to the generation model to generate a character that meets specific requirements. For example, it generates image data according to specified hair color and whether or not the character is wearing a hat, and processes voice data according to specified tone and accent.

[0658] Step 3:

[0659] The server analyzes the generated characters through a security check function and automatically detects inappropriate elements. Specifically, it scans the generated text and audio data using a machine learning model to check for inappropriate words or expressions. If inappropriate elements are detected, the server automatically corrects them and converts them into appropriate data.

[0660] Step 4:

[0661] Users can use their devices to further customize the generated virtual influencers. For example, they can manipulate clothing styles and add or change accessories in real time through an interactive user interface. They can also fine-tune the character's personality and energy level.

[0662] Step 5:

[0663] The server generates an activity plan for virtual influencers based on the specifications of the provided digital event. This plan selects the most effective time slots based on user requirements and determines posting schedules and content. Data analysis is performed, taking into account past engagement data, to aim for optimal reach to the target audience.

[0664] Step 6:

[0665] The server monitors the activities of virtual influencers in real time and collects their performance data. For example, it analyzes data on post reactions and engagement to help optimize marketing strategies. This allows for identifying areas for improvement in future campaign plans and enabling continuous, effective promotion.

[0666] (Application Example 1)

[0667] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0668] In traditional promotional activities, it is difficult to efficiently generate virtual characters that match the characteristics of a brand and to use those characters to conduct effective advertising campaigns. Furthermore, there are challenges in optimizing advertising strategies in real time while minimizing the risk of inappropriate content.

[0669] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0670] In this invention, the server includes means for generating a virtual person model based on user information, means for analyzing the data to detect inappropriate elements in the generated visual and audio data, and means for generating an action plan for the virtual person model based on the provided activities. This makes it possible to flexibly and accurately carry out promotional activities for the virtual person model and suppress the generation of inappropriate content.

[0671] "User information" refers to data, including brand requirements and characteristics, that are acquired for the purpose of generating a virtual persona model.

[0672] A "virtual character model" is a digital character created using generative AI, possessing an appearance and conversational abilities tailored to a specific brand or promotion.

[0673] A "generative model" refers to a set of algorithms and technologies used to generate a virtual human model based on input information.

[0674] "Visual and audio data" refers to the graphic and audio elements of the generated virtual character model.

[0675] "Inappropriate elements" are content elements that may damage the brand image or be considered socially inappropriate.

[0676] "Data analysis" refers to analytical methods used to identify inappropriate elements from generated visual and audio data.

[0677] An "action plan" outlines a schedule and content strategy for how a fictional character model can effectively operate and promote the brand.

[0678] A "smart device" refers to electronic devices or applications used to utilize the generated virtual human model.

[0679] To implement this invention, the server first collects information from the user and generates a virtual person model. The server utilizes input data based on brand requirements and characteristics, and uses a generative AI model to create the virtual person model. This model is a digital character customized by image generation AI and voice generation AI.

[0680] For visual and audio data, the server analyzes the data to detect inappropriate elements. Specifically, data analysis tools such as Amazon Rekognition are used to identify and correct inappropriate elements within the content. This process ensures that the content is socially appropriate and does not damage the brand image.

[0681] The server also generates an action plan for the virtual character model. This action plan details how the generated character model will act and promote the brand. This makes it possible to develop content strategies optimized for digital events and promotions.

[0682] Smart devices utilize these generated virtual person models for promotional activities. For example, users can watch promotional videos or experience interactive content through smartphone apps.

[0683] As a concrete example, when a cosmetics brand conducts a promotion to introduce a new product, a video is generated featuring a virtual model highlighting the product's features. When users watch this video on their devices, its appeal to the target audience increases.

[0684] An example of a prompt message would be: "Generate a promotional video for a new cosmetic product aimed at women. This product features a vibrant red color."

[0685] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0686] Step 1:

[0687] Users input brand requirements and characteristics using smart devices. This input data is sent to the server, initiating the generation of a virtual persona model. The input data includes detailed brand information, such as prompt text.

[0688] Step 2:

[0689] The server creates a virtual person model using a generative AI model based on the received brand requirements. Based on the prompt text received as input, the image generation AI generates a visual model, and the voice generation AI creates voice data. This results in a virtual person model that matches the user's brand.

[0690] Step 3:

[0691] The server analyzes the generated visual and audio data to detect inappropriate elements. This analysis uses AI tools such as Amazon Rekognition. If the server detects inappropriate elements, it corrects them, regenerates the data in an appropriate state, and outputs clean model data.

[0692] Step 4:

[0693] The server generates an action plan for a virtual character model based on the acquired visual and audio data. This plan includes the schedule and content details of promotional activities. The server then processes the data and optimizes the strategy, outputting an action plan based on these optimizations.

[0694] Step 5:

[0695] On smart devices, action plans are utilized, and users are provided with interactive promotional experiences. Users can view content generated through smartphone apps and other means, and understand the brand's characteristics. User engagement data from each device is fed back to the server.

[0696] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0697] This invention is a virtual influencer system incorporating an emotion engine, providing a platform that enables companies to achieve more personalized interactions with users. The system begins with a process in which a server generates a virtual character in real time based on brand requirements entered by the user through a terminal.

[0698] The server uses an emotion engine to recognize the user's emotional state in real time and dynamically adjust the virtual character's responses based on that data. This emotion engine includes an AI algorithm to analyze the user's emotions from the feedback and interactions they provide. This allows the virtual character to display a tone and response appropriate to the user's emotions.

[0699] Furthermore, the server runs security features to check the generated character content for inappropriate elements and makes corrections as needed. This process is performed in real time, minimizing the risk of inappropriate content being created.

[0700] The virtual influencer's activity plan is automatically generated by the server according to the advertising campaign's goals. Based on user feedback obtained through the emotion engine, this activity plan can be dynamically adjusted. This feedback loop enables the implementation of effective marketing strategies that resonate with user emotions.

[0701] Ultimately, the server analyzes multiple data points derived from the virtual influencer's performance and automatically generates suggestions for optimizing the strategy. This data also includes user sentiment data collected by the sentiment engine, enabling deeper insights. For example, it might analyze how specific character portrayals affect users emotionally and recommend adjusting content based on the results.

[0702] Thus, virtual influencer systems that combine emotion engines can provide companies with a new dimension of brand engagement and further enrich the user experience.

[0703] The following describes the processing flow.

[0704] Step 1:

[0705] Users access the platform using their devices and enter their brand requirements and desired character traits. This sends detailed data about the virtual influencer's appearance and behavior to the server.

[0706] Step 2:

[0707] The server uses image generation AI to create a virtual character in real time based on the received data. In this process, the character's visual appearance is constructed according to the specified features.

[0708] Step 3:

[0709] The server utilizes voice generation AI to generate voices that are suitable for the virtual character. These voices will be in line with the character's personality and the brand's tone.

[0710] Step 4:

[0711] The server presents the user with an initial version of the character, and the user provides feedback via their device. The user can further customize the character's appearance and voice as needed.

[0712] Step 5:

[0713] The server activates the emotion engine and collects emotional data provided by the user through the device. The emotion engine analyzes the user's emotions from nonverbal cues and direct feedback.

[0714] Step 6:

[0715] Based on this emotional data, the server dynamically adjusts the virtual character's responses and behavior. For example, if the user shows a positive reaction, the character will respond in a more friendly tone.

[0716] Step 7:

[0717] The server performs security checks on the generated content, automatically detecting and correcting inappropriate elements. This eliminates any parts that do not conform to the brand image.

[0718] Step 8:

[0719] The server generates an activity plan for virtual influencers based on the user's advertising campaign goals. This activity plan includes adjustments based on feedback from the sentiment engine.

[0720] Step 9:

[0721] The server monitors the activity of virtual influencers and analyzes real-time data. This includes sentiment data, providing deeper insights into understanding user reactions.

[0722] Step 10:

[0723] The server uses these analysis results to automatically generate and provide suggestions for optimizing the strategy. This enables more effective marketing activities.

[0724] (Example 2)

[0725] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0726] Traditional virtual character systems have struggled to dynamically adjust responses based on user emotions and to immediately correct inappropriate content. Furthermore, their activity plans are static, resulting in insufficient marketing strategy efficiency. This has led to a limited user experience and hindered companies from improving brand engagement.

[0727] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0728] In this invention, the server includes means for acquiring input information to generate a virtual character based on customer requirements, means for creating a virtual character using a generative model, and means for analyzing the user's emotional state using an emotion analysis engine and dynamically adjusting the virtual character's response. This enables real-time, personalized interaction that responds to the user's emotions.

[0729] "Customer requirements" refer to information that indicates the attributes and conditions that users desire regarding the creation and response of virtual characters.

[0730] A "virtual character" is a digital character created on a computer that engages in dialogue and interaction with the user.

[0731] "Input information" refers to digital data provided by the user from their device, including the requirements and instructions the system needs to generate characters.

[0732] A "generative model" is an algorithm or program used to create virtual characters, determining the character's appearance and behavior based on specific inputs.

[0733] An "emotion analysis engine" refers to artificial intelligence technology used to analyze a user's emotional state in real time, inferring emotions from the user's responses and feedback.

[0734] "Inappropriate elements" refer to expressions or information that may be included in the generated content but do not meet the required standards.

[0735] An "activity plan" is a plan that specifies the schedule and procedures for interactions that a virtual character should perform, and is set based on the goals of an advertising campaign, etc.

[0736] A "feedback loop" refers to a system that continuously receives user feedback and opinions, and dynamically adjusts its characters and plans based on that feedback.

[0737] "Suggestions for optimizing strategy" involve analyzing the results of a character's activities and then identifying areas for improvement and strategies to make future interactions and activities more effective.

[0738] This invention is a virtual character generation system equipped with an emotion analysis engine, providing a platform for companies to realize personalized interactions with users. Specific embodiments for carrying out this invention are described below.

[0739] The user uses a terminal to provide the system with input information regarding brand requirements and target profile. This information is entered in text format, and the system receives it. For example, the user might input branding instructions such as "a youthful and healthy image."

[0740] The server utilizes a generative AI model to process this input information. A commonly used language generation model is employed for this purpose. Based on the input information, the server generates a profile for a virtual character. During this process, prompt statements are sent to the AI ​​model. For example, a possible prompt statement might be, "Generate a character with a healthy image aimed at young people."

[0741] Subsequently, the server uses an emotion analysis engine to analyze the user's emotional state in real time. This allows the virtual character's responses to dynamically adjust to the user's current emotions. Data such as user feedback and dialogue history are used for emotion analysis.

[0742] The content of generated virtual characters is constantly checked for inappropriate elements. The server uses AI-based filtering technology to perform content checks, and any elements deemed inappropriate are corrected immediately.

[0743] Furthermore, the server automatically generates an action plan based on the advertising campaign's goals and dynamically updates it based on actual user feedback. This ensures that the virtual character always acts in a way that is in line with the user's preferences and emotions.

[0744] Ultimately, this system analyzes the data collected by the server and generates suggestions to help optimize marketing strategies. The server analyzes multiple data points, including sentiment data, and based on this, provides companies with more effective strategies. This enables companies to improve the user experience and strengthen brand engagement.

[0745] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0746] Step 1:

[0747] The user uses a terminal to input information about the brand's requirements and target image. This input is sent to the server in text format. For example, the user might input the requirement "a youthful and healthy image." This information is then transferred to the server and prepared for the next processing step.

[0748] Step 2:

[0749] The server creates a prompt for the generative AI model based on the input information it receives. The model receives a prompt that reflects the characteristics derived from the input information, such as "Generate a character with a healthy image aimed at young people." The generative AI model uses the prompt as input to generate a profile of a virtual character and provides the server with specific character information as output.

[0750] Step 3:

[0751] The server uses an emotion analysis engine to analyze the user's emotional state based on user interactions after the virtual character is generated. This analysis uses user feedback and chat logs as input data. The emotion analysis engine processes this data and generates the user's emotional state as output. Based on this emotional information, the server adjusts the virtual character's responses in real time.

[0752] Step 4:

[0753] The server uses AI filtering technology to check whether the generated virtual character content contains any inappropriate elements. The generated character's text and images become input data, and the AI ​​filter searches for inappropriate elements. If inappropriate elements are detected, the corrected content is regenerated as a new output.

[0754] Step 5:

[0755] The server automatically generates an activity plan. This plan is created using emotional feedback from the user and past interaction data of the virtual character. The server analyzes this data and outputs an activity plan tailored to the target audience. Furthermore, this activity plan is dynamically adjusted through a feedback loop, proposing a strategy that reflects the latest user preferences.

[0756] (Application Example 2)

[0757] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0758] In today's digital advertising market, there is a demand for advertising experiences tailored to individual consumers, but achieving this remains challenging. In particular, there is a lack of effective methods for responding to consumer emotions in the development of personalized advertising. Furthermore, there is a risk that inappropriate advertising content will cause discomfort to users, necessitating the establishment of systems that efficiently adjust these factors in real time.

[0759] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0760] In this invention, the server includes means for analyzing customer information to obtain construction information, means for using a generation program to create a virtual construct using the construction information, and means for analyzing a function obtained based on the operation plan and generating a proposal for optimizing the strategy. This makes it possible to display advertisements that are in line with the consumer's emotions in real time and optimize the advertising experience.

[0761] "Customer information" refers to foundational information for generating virtual constructs, and specifically data related to consumers.

[0762] "Construction information" refers to detailed data for generating constructs obtained by analyzing customer information.

[0763] A "virtual construct" refers to a digital character or object that is generated based on digital information.

[0764] A "generation program" is a program used to create a virtual construct using construction information.

[0765] "Non-conforming factors" refer to inappropriate elements or problems contained within the constructed information.

[0766] An "action plan" is a proposed plan for constructing the behavior of a virtual construct based on the informational events provided.

[0767] "Policy" refers to a set of action guidelines optimized based on an action plan.

[0768] An "emotional analysis program" is a program designed to analyze the emotional state of a passive recipient and adjust the response of a virtual construct.

[0769] "Advertising content" refers to the content of advertisements presented to consumers, which is selected and displayed accordingly.

[0770] In this embodiment of the invention, a camera function and a dedicated application are installed on the terminal accessed by the user to acquire the user's emotional information in real time. An emotional analysis program analyzes this emotional information and generates data to dynamically adjust the response of the virtual construct. The server executes a generation program based on the generated construct information to create a virtual construct suitable for the user.

[0771] The server combines acquired user emotion information with provided information events to formulate an action plan. This forms the basis for dynamically selecting ad content. The ad content selected through emotion analysis is displayed on the user's device to optimize the user experience. The processing uses image processing libraries such as OpenCV and emotion recognition software called EmotionRecognizer, which uses AI algorithms.

[0772] For example, if a user smiles while using the application, the system recognizes the smile and displays positive and energetic advertisements. This ensures that the advertisements align with the user's emotions, enabling the implementation of effective advertising campaigns.

[0773] An example of a prompt might be: "When the user looks into the camera and is smiling, display an ad promoting a trending product in a positive tone." This allows the ad content to provide an appropriate response that aligns with the user's current emotional state.

[0774] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0775] Step 1:

[0776] The user launches an application on their device and enables the camera function. At this time, the device inputs video data from the camera in real time and sends that data to the server.

[0777] Step 2:

[0778] The server performs face detection on the received video data using the OpenCV library. The detected face data is used as input, and EmotionRecognizer is used to analyze the user's emotions. The analysis results are output as the user's emotional state (e.g., joy, sadness, surprise).

[0779] Step 3:

[0780] The server develops an action plan for the virtual construct based on the analyzed emotional state. The inputs to this action plan are the user's emotional state and the campaign objective, and the output is an action plan that includes adjusted responses and expression parameters. This plan influences the selected ad content.

[0781] Step 4:

[0782] The server selects appropriate ad content based on the action plan. Using the sentiment state and action plan received as input, it selects the most suitable ad from the ad database. This ad content is output and sent to the terminal.

[0783] Step 5:

[0784] The device displays advertising content sent from the server to the user. Specifically, selected advertisements are shown on the device's display. This display ensures that the user experience matches the emotionally tailored advertisement content, improving engagement.

[0785] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0786] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0787] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0788] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0789] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0790] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0791] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0792] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0793] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0794] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0795] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0796] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0797] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0798] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0799] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0800] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0801] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0802] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0803] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0804] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0805] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0806] The following is further disclosed regarding the embodiments described above.

[0807] (Claim 1)

[0808] In order to generate a virtual character based on customer requirements, means for obtaining input information,

[0809] A means for creating a virtual character using a generative model with the aforementioned input information,

[0810] A means for analyzing content to detect inappropriate elements within the generated content,

[0811] Means to correct any potentially inappropriate elements,

[0812] A means for generating an activity plan for a virtual character based on provided digital events,

[0813] A means for analyzing data obtained based on the aforementioned activity plan and generating proposals for optimizing the strategy,

[0814] A system that includes this.

[0815] (Claim 2)

[0816] The system according to claim 1, in which content is generated in real time.

[0817] (Claim 3)

[0818] The system according to claim 1, wherein suggestions for optimizing the aforementioned strategy are automatically generated.

[0819] "Example 1"

[0820] (Claim 1)

[0821] Means for obtaining information in order to generate a virtual person based on customer requirements,

[0822] A means of creating a virtual person using the aforementioned information and a generative AI model,

[0823] A means for analyzing the content in order to detect inappropriate elements within the generated content,

[0824] A means to automatically correct detected inappropriate elements,

[0825] A means of generating a virtual person's schedule based on the provided activities,

[0826] A means for analyzing information collected based on the aforementioned schedule and generating proposals for optimizing the plan,

[0827] A system that includes this.

[0828] (Claim 2)

[0829] The system according to claim 1, in which content is generated in real time.

[0830] (Claim 3)

[0831] The system according to claim 1, which automatically generates suggestions for optimizing the aforementioned plan.

[0832] "Application Example 1"

[0833] (Claim 1)

[0834] In order to generate a virtual person model based on user information, means for collecting information,

[0835] A means for creating a virtual human model using the aforementioned information and a generative model,

[0836] Means for analyzing data to detect inappropriate elements in generated visual and audio data,

[0837] Means to correct any potentially inappropriate elements,

[0838] A means for generating an action plan for a virtual character model based on the provided activities,

[0839] A means of generating recommendations to optimize strategies based on information obtained from analyzed behavioral data,

[0840] Means for utilizing human models generated using smart devices,

[0841] A system that includes this.

[0842] (Claim 2)

[0843] The system according to claim 1, wherein the generated activity plan is adjusted according to time.

[0844] (Claim 3)

[0845] The system according to claim 1, wherein the aforementioned recommendation is automatically notified to the user device.

[0846] "Example 2 of combining an emotion engine"

[0847] (Claim 1)

[0848] A means for obtaining input information in order to generate a virtual character based on customer requirements,

[0849] A means for creating a virtual character using a generative model with the aforementioned input information,

[0850] In order to detect inappropriate elements within the generated content, a means for analyzing the content,

[0851] Means to correct any potentially inappropriate elements,

[0852] A means for analyzing the user's emotional state using an emotion analysis engine and dynamically adjusting the virtual character's response,

[0853] A means for generating an activity plan for a virtual character based on provided digital events,

[0854] Means for dynamically adjusting the activity plan based on a feedback loop,

[0855] A means for analyzing data obtained based on the aforementioned activity plan and generating proposals for optimizing the strategy,

[0856] A system that includes this.

[0857] (Claim 2)

[0858] The system according to claim 1, in which content generation and user sentiment analysis are performed in real time.

[0859] (Claim 3)

[0860] The system according to claim 1, wherein suggestions for optimizing the aforementioned strategy are automatically generated based on multiple data points, including emotional data.

[0861] "Application example 2 when combining with an emotional engine"

[0862] (Claim 1)

[0863] A means of obtaining construction information by analyzing customer information,

[0864] A means of using a generation program to create a virtual construct using the aforementioned construction information,

[0865] A means of analyzing information to detect non-conformity factors within the constructed information,

[0866] Means for correcting potential nonconformities,

[0867] Means for generating an operation plan for a virtual construct based on the provided information events,

[0868] A means for analyzing the function obtained based on the aforementioned action plan and generating a proposal for optimizing the policy,

[0869] A means comprising an emotion analysis program for analyzing the emotional state of a passive person and dynamically adjusting the response of a virtual construct,

[0870] A means comprising a program for selecting and displaying advertising content based on the emotions of the recipient,

[0871] A system that includes this.

[0872] (Claim 2)

[0873] The system according to claim 1, wherein information is constructed immediately.

[0874] (Claim 3)

[0875] The system according to claim 1, in which a proposal for optimizing the aforementioned strategy is automatically formed. [Explanation of Symbols]

[0876] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. In order to generate a virtual person model based on user information, means for collecting information, A means for creating a virtual human model using the aforementioned information and a generative model, Means for analyzing data to detect inappropriate elements in generated visual and audio data, Means to correct any potentially inappropriate elements, A means for generating an action plan for a virtual character model based on the provided activities, A means of generating recommendations to optimize strategies based on information obtained from analyzed behavioral data, Means for utilizing human models generated using smart devices, A system that includes this.

2. The system according to claim 1, wherein the generated activity plan is adjusted according to time.

3. The system according to claim 1, wherein the aforementioned recommendation is automatically notified to the user device.

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