system

Abstract

We provide the system. [Solution] A first method of receiving brand requirements and generating original virtual influencers based on them, A second method involves using generated virtual influencers to automatically generate content based on a specified campaign theme, A third method involves analyzing the generated content to verify that it does not contain inappropriate elements, A fourth method for delivering verified content to a target audience in real time, A fifth method involves monitoring the effectiveness of campaigns based on collected interaction data and making improvement suggestions. A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of the chatbot's 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] Influencer marketing has problems such as the cost of utilizing existing influencers, the burden of schedule adjustment, the decline of the brand image due to scandals, and the lack of affinity and uniqueness with advertisements. There is a need to solve these problems and provide a method that enables companies to conduct marketing activities efficiently and safely.

Means for Solving the Problems

[0005] This invention provides a system that uses AI to generate virtual influencers based on brand requirements and automatically generates content using those influencers, thereby achieving cost reduction, risk mitigation, and efficient operation. Furthermore, it automatically verifies the generated content, confirming its appropriateness before distributing it to the target audience, thereby protecting brand image and maximizing advertising effectiveness. In this way, companies can promote highly flexible marketing activities without damaging their brand image. The system also includes a function to monitor campaign effectiveness based on interaction data and provide improvement suggestions.

[0006] "Brand requirements" refer to the specific characteristics, target audience, and style of expression that a company expects from virtual influencers in its marketing activities.

[0007] A "virtual influencer" is a digital entity created using AI, whose role is to deliver messages to specific target audiences and build relationships with brands.

[0008] "Automatic content generation" refers to the process of automatically creating promotional materials such as PR videos, images, and text using AI technology.

[0009] "Inappropriate elements" refer to information that may damage the brand's image, violate laws and regulations, or contain messages that are contrary to social ethics.

[0010] "Real-time communication" is a process in which virtual influencers instantly exchange information with end users, enabling two-way dialogue.

[0011] "Interaction data" refers to data on user behavior and reactions generated during interactions with virtual influencers, and is used to analyze the effectiveness of marketing campaigns.

[0012] A "KPI (Key Performance Indicator)" is a specific metric that a company sets to evaluate the success of a marketing campaign, and is used to measure campaign performance. [Brief explanation of the drawing]

[0013] [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] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [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.

Embodiments for Carrying out the Invention

[0014] 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.

[0015] First, the terms used in the following description will be explained.

[0016] 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.

[0017] 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.

[0018] 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.

[0019] 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).

[0020] 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."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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".

[0034] This invention is a system that utilizes AI technology to enable companies to generate their own virtual influencers and conduct efficient and secure marketing activities. This system functions through the coordinated efforts of a server, terminals, and users.

[0035] First, the user, acting as a company representative, accesses the system through a dedicated terminal. The user inputs information such as the characteristics of the target audience, the brand message, and the desired influencer's character as brand requirements. This specification information is then sent to the server.

[0036] Next, the server uses AI technology to generate a virtual influencer based on the received brand requirements. Leveraging past success stories and database information, the server creates a prototype of the most suitable influencer for the specified conditions. This virtual influencer is designed to match the brand's appearance, voice, personality, and other characteristics.

[0037] The generated virtual influencers are used through a server-managed platform to automatically generate promotional videos, advertising images, and text content using AI technology. The server also analyzes the generated material to ensure its safety and verify that it does not contain any inappropriate elements.

[0038] Content whose safety has been confirmed will be distributed to designated media platforms. Users will be able to interact with virtual influencers in real time via their devices and receive direct feedback from end users in real time.

[0039] For example, when running a campaign for a new product, three promotional videos featuring virtual influencers are generated, each targeting a different audience. Users can instantly understand which message is most effective based on their reactions to these videos. The server then analyzes the reaction and interaction data to provide more specific suggestions for improvement and proposals for future campaigns.

[0040] This system will be a powerful tool for achieving flexible and creative marketing while minimizing costs and risks.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] Users access the system using a dedicated terminal and input their brand's requirements. This includes characteristics of the target audience, the type of influencer they expect, and key brand messages. Once input is complete, the information is sent to the server.

[0044] Step 2:

[0045] The server analyzes the received requirements and uses an AI model to automatically generate the optimal virtual influencer. Based on data learned from past performance and case studies, the server determines appearance, voice, personality, etc., and creates a prototype.

[0046] Step 3:

[0047] The server utilizes the generated virtual influencers to automatically create advertising content such as promotional videos, images, and text based on the specified campaign theme. Multiple variations are prepared and can be customized for different target audiences.

[0048] Step 4:

[0049] The server checks the generated content for inappropriate elements. This process uses natural language processing (NLP) technology to automatically verify the safety of the content. If inappropriate content is detected, it generates suggested corrections.

[0050] Step 5:

[0051] The user reviews the generated content through their device and sends approval or correction instructions to the server as needed. Content approved by the user proceeds to the next step.

[0052] Step 6:

[0053] The server prepares approved content for distribution to designated media platforms and social media. It sets distribution schedules and delivers content to the target audience at the optimal time.

[0054] Step 7:

[0055] Users configure real-time interactions with virtual influencers using their devices. Feedback from end users is collected to measure the campaign's effectiveness.

[0056] Step 8:

[0057] The server analyzes the collected interaction data to evaluate the campaign's effectiveness. Based on this data, it provides users with suggestions for improvement and feedback for future campaigns.

[0058] (Example 1)

[0059] 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."

[0060] Traditional marketing activities have faced challenges in effectively engaging consumers and maintaining brand image using virtual promotional characters. Furthermore, the process of rapidly distributing generated content while ensuring its safety is complex, highlighting the need for an efficient and secure system.

[0061] 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.

[0062] In this invention, the server includes means for receiving brand information and constructing an appropriate digital character based on it; means for automatically creating digital content in line with the campaign theme using the generated digital character; and means for analyzing the created digital content and checking for elements that do not conform to the norms. This enables the safe and effective generation and distribution of digital content.

[0063] "Brand information" refers to data that includes attributes such as the target audience, the message to be conveyed, and the brand image associated with a particular product or service.

[0064] A "digital character" is a virtual person or character created on a computer and used in marketing activities to convey a brand's message.

[0065] "Digital content" refers to media files such as videos, images, and text created using generated digital characters and used for marketing purposes.

[0066] "Information media" refers to communication methods such as online platforms and applications through which generated digital content is delivered to consumers.

[0067] "User data" refers to digital information collected from consumers' reactions and interactions with delivered content, and is used to evaluate the effectiveness of marketing activities.

[0068] "Non-compliant elements" refer to content or expressions within the generated content that are deemed inappropriate and are subject to inspection to ensure safety.

[0069] This invention is a system for companies to conduct effective marketing activities, in which servers, terminals, and users work in coordination with each other. The following describes its specific embodiments.

[0070] Users access the system using a dedicated terminal. They input brand information and send it to the server. This information includes the target customer base, product and service characteristics, and the brand message to be conveyed.

[0071] The server analyzes brand information received from the user. AI technology is used for the analysis, and appropriate prompt sentences are generated by a specific generative AI model. For example, a prompt sentence such as, "Generate a promotional video for a new skincare product aimed at women in their 20s. The motif should be natural, emphasizing natural beauty," might be used.

[0072] The generation AI model constructs a virtual digital character based on this prompt text. AI technology adjusts the digital character's appearance, movements, voice, and personality to be appropriate for the brand. Specific technologies, such as graphics generation engines and speech synthesis software, are utilized in the generation process.

[0073] The generated digital characters are managed on a server platform, and digital content based on the specified campaign theme is automatically created. In this process, the server uses natural language processing technology to inspect the generated content for elements that do not conform to the standards, ensuring safety.

[0074] Once security is confirmed, the server quickly delivers the content to the designated media. User reactions and interactions to the delivered content are collected on the server and analyzed to evaluate marketing activities and make effective suggestions for future campaigns. This implementation allows companies to implement digital marketing efficiently and securely.

[0075] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0076] Step 1:

[0077] Users access the system via a dedicated terminal. They input their brand message, target audience, and desired specifications for their digital character, and send this information to the server. This input includes the brand's attributes and intended message.

[0078] Step 2:

[0079] The server analyzes the received brand information. Using an AI model, the server generates the optimal prompt sentence based on the input information. This prompt sentence serves as an instruction to define the appearance and personality of the digital character. The prompt sentence is output as a result of the analysis.

[0080] Step 3:

[0081] The server takes the generated prompt text as input and runs a generation AI model to construct a virtual digital character. Specifically, the AI ​​model generates the character's visuals, voice, and behavioral patterns based on the prompt text. The output of this step is a detailed profile of the digital character.

[0082] Step 4:

[0083] The server automatically creates the digital content necessary for the campaign based on the generated digital characters. Using AI technology, the server generates the images, videos, and text included in the content and assembles the overall content. The output is complete digital marketing content.

[0084] Step 5:

[0085] The server analyzes the generated digital content and checks for any elements that do not conform to the standards. This check uses natural language processing technology, and only content that is deemed safe proceeds to the next step. The output of the check is content that has been confirmed safe.

[0086] Step 6:

[0087] The server delivers secure digital content to the designated media. Delivery utilizes the API of the distribution platform via the internet, transmitting content to the target audience in real time. The output indicates a status signifying successful delivery.

[0088] Step 7:

[0089] The server collects end-user responses to delivered content and analyzes user data. The server uses data analysis tools to evaluate which content was effective and provides suggestions for improvement for future campaigns. The output is a marketing analysis report.

[0090] (Application Example 1)

[0091] 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."

[0092] In marketing using virtual influencers, there is a need to provide personalized advertising information based on the interests of target consumers and to realize effective technology-driven campaigns through real-time interaction. Furthermore, ensuring the safety of the generated content and conducting effective advertising activities without damaging the brand image are also crucial challenges.

[0093] 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.

[0094] This invention includes a server that receives brand requirements and generates original virtual influencers based on those requirements, a server that utilizes the generated virtual influencers to automatically generate content based on a specified campaign theme, and a server that provides advertising information from virtual influencers based on the user's interests. This enables the delivery of personalized advertisements to target audiences, allowing for the development of more effective and secure marketing strategies.

[0095] "Brand requirements" refer to information about the characteristics and target audience that a company expects from virtual influencers for the purpose of conducting an advertising campaign.

[0096] A "virtual influencer" is a digital, simulated persona created using AI technology to disseminate brand messages in advertising and content creation.

[0097] A "campaign theme" is a subject that is set based on the characteristics of a product that you want to highlight in a particular marketing activity, or the demands of the target market.

[0098] "Automatic content generation" refers to the process of generating advertising materials such as videos, images, and text using AI technology without human intervention.

[0099] "Verified content" refers to content that has been confirmed to be free of inappropriate elements and to be safe.

[0100] A "target audience" is a group of consumers who are expected to be attracted to a particular product or brand in advertising and marketing activities.

[0101] "Interaction data" refers to data on reactions and behaviors that show how content created by virtual influencers was received by users.

[0102] "Personalized advertising information" refers to advertising content that is customized based on the interests and preferences of individual users.

[0103] The system for implementing this invention operates through the coordinated efforts of a server, a terminal, and a user. First, the user accesses the system using a dedicated terminal and inputs the brand's requirements. This specification information includes the target audience, brand message, and desired influencer character. The specification information is sent to the server, which receives it and uses AI technology to generate a virtual influencer.

[0104] The server utilizes a generative AI model to configure the appearance and personality of virtual influencers based on specifications. Content is then automatically generated using these generated influencers. This requires high-performance server equipment and software incorporating AI models (e.g., machine learning models or natural language processing algorithms).

[0105] The generated content is validated by the server and analyzed for any inappropriate elements. Once this safety check is complete, the content is distributed to the designated media platform. Users can interact with virtual influencers in real time through their devices and receive immediate feedback from end users.

[0106] As a concrete example, users interested in fashion will be shown videos from virtual influencers featuring the latest fashion items. Because this content is personalized to each user's interests, higher engagement can be expected. An example of a prompt for the generative AI model would be: "The user's hobby is fashion. Please create an engaging video showcasing the latest trends."

[0107] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0108] Step 1:

[0109] The user accesses the system via a terminal. Here, the user inputs the brand's requirements, which include information such as the target audience, brand message, and desired influencer characters. This input data is sent to the server for use in the next step.

[0110] Step 2:

[0111] The server receives brand requirements from users and generates virtual influencers based on an AI model. Using brand specification data as input, the AI ​​model performs data calculations to output virtual influencers with defined appearances and personalities. The server then uses this data to optimize the process by referencing similar past cases and database information.

[0112] Step 3:

[0113] The server automatically generates content that fits the specified campaign theme using the generated virtual influencers. The user's brand specifications are input as prompts, and the generating AI model outputs digital content (e.g., videos and text) based on this. At this time, the AI ​​also utilizes natural language processing technology to generate more engaging content.

[0114] Step 4:

[0115] The server analyzes the generated content and verifies that it does not contain any inappropriate elements. The server uses content analysis software to analyze the data to confirm the safety of the content. The input is the generated digital content, and the output is the safety status of that content.

[0116] Step 5:

[0117] The server delivers verified and secure content in real time to the designated media platform. The server develops an optimal delivery plan based on the platform's requirements and target audience characteristics, and then transmits the content via the platform's API.

[0118] Step 6:

[0119] Users can interact with virtual influencers through their devices. Users monitor the collected interaction data, receive reactions and feedback, and use this data to improve future campaigns. Input is end-user response data, and output is the analysis results necessary for improvement suggestions.

[0120] 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.

[0121] This invention provides a system that efficiently generates custom-designed virtual influencers for businesses and combines AI-powered emotion recognition with user interactions to achieve more flexible and effective marketing activities. This system operates through the collaborative efforts of a server, terminal, and user, with particular emphasis on optimizing interactions based on emotion recognition.

[0122] First, the user inputs the brand's requirements into the system via their device. This includes the emotional characteristics of the target audience, the character settings the virtual influencer should have, and the expected emotional responses. The input information is sent to the server and becomes the basis for subsequent processing.

[0123] The server uses AI technology to generate virtual influencers based on the input requirements. The generated influencers possess not only appearance and personality, but also response patterns that respond to the user's emotions. This is achieved by an emotion engine that determines the user's emotions in real time through facial expressions and voice input, and dynamically adjusts the influencer's responses based on the results.

[0124] Next, the server automatically generates content according to the specified campaign theme. Here, it selects the most appropriate expressions and tones based on emotion to create a message that resonates with the audience. The generated content is analyzed using natural language processing (NLP) techniques to detect inappropriate elements.

[0125] Content approved by users is delivered to the platform specified by the server. Leveraging real-time sentiment recognition, virtual influencers engage in two-way communication with end users. For example, during a live streaming event, they can change their tone based on the audience's emotional state or present specific products in an emotionally resonant way.

[0126] The server collects interaction data with users and provides feedback to users based on the analysis results. This allows for real-time monitoring of campaign effectiveness and enables specific improvement suggestions for future initiatives.

[0127] This system allows companies to effectively communicate their brand in a way that appeals to the emotions of their target audience and create interactive marketing activities.

[0128] The following describes the processing flow.

[0129] Step 1:

[0130] Users access the system using a dedicated terminal and input brand requirements. This includes target audience profiles, desired appearance and personality traits of influencers, and campaign objectives.

[0131] Step 2:

[0132] The server analyzes the received brand requirements and uses an AI model to generate virtual influencers. The generation process establishes characters with specific emotional response patterns, incorporating optimizations based on historical datasets.

[0133] Step 3:

[0134] The server activates the emotion engine and incorporates the emotion recognition capabilities of the virtual influencer. This prepares the influencer to judge the user's emotions from their facial expressions and tone and to interact accordingly.

[0135] Step 4:

[0136] The server automatically generates ad content based on the campaign theme. Here, the emotion engine selects the most effective emotional expression and adjusts the content to appeal to the user's target emotions.

[0137] Step 5:

[0138] The server analyzes the generated content using natural language processing (NLP) techniques to detect inappropriate elements. If any are found, it creates a proposed correction and provides the user with a preview for approval.

[0139] Step 6:

[0140] The user reviews the generated content through their device and gives final approval. Content approved by the user proceeds to the next execution stage.

[0141] Step 7:

[0142] The server delivers approved content to the designated platform in real time, deploying it to the target audience. It utilizes an emotion engine to implement interactions tailored to the recipient's emotions.

[0143] Step 8:

[0144] Users use their devices to observe end-user emotional responses in real time. Virtual influencers use this data to adjust their responses and engage in more personalized communication.

[0145] Step 9:

[0146] The server collects and analyzes interaction data to evaluate the effectiveness of the campaign. Based on the analysis results, it provides users with suggestions for improvement and feedback for future campaigns.

[0147] (Example 2)

[0148] 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".

[0149] In traditional marketing activities using information processing devices, feedback on audience emotions was not reflected in real time, limiting the effectiveness of interactions. Furthermore, the quality and optimization of generated content were insufficient, resulting in low appeal to target audiences. Consequently, companies were unable to effectively communicate their brand image, and the quality of interactions was not guaranteed.

[0150] 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.

[0151] In this invention, the server includes, firstly, means for receiving brand requirements and generating its own information processing device based thereon; secondly, means for automatically generating information based on a specified subject using the generated information processing device; thirdly, means for analyzing the generated information and verifying the presence or absence of inappropriate elements; and fourthly, means for the generated information processing device to analyze the emotional state through voice or visual input and adjust the response in real time accordingly. This makes it possible to provide effective and emotionally appealing interactions to the target audience and effectively convey the brand image.

[0152] A "brand" refers to a name, design, or symbol used to distinguish a particular company or product from others.

[0153] An "information processing device" refers to a device that performs calculations and data transformations based on specified input data and generates the desired output.

[0154] "Generation" refers to the act of creating new digital content or data through specific algorithms or processes.

[0155] "Subject" refers to a specific purpose or focus in content or activities.

[0156] "Information" refers to content composed of knowledge, data, and facts, which possesses meaning and value directed towards a specific recipient.

[0157] "Analysis" refers to the methods and processes used to investigate information and data and to clarify their structure and meaning.

[0158] "Input" refers to the data or commands provided to an information processing device.

[0159] "Response" refers to the reply or action given in response to an input or situation.

[0160] "Audience" refers to the group of people who receive and engage with specific content or information.

[0161] "Interaction" refers to the actions or processes in which two or more parties exchange information with each other.

[0162] This invention is implemented using an information processing system comprised of a server, a terminal, and a user. The server functions as a platform for running advanced AI models by combining languages ​​such as Python and SQL with machine learning frameworks such as TENSORFLOW® and PyTorch. The terminal provides an interface for the user to input data and exchange data bidirectionally with the information processing device. This terminal is typically a personal computer or mobile device and requires a robust internet connection.

[0163] First, the user inputs brand requirements through their device. These requirements include characteristics of the target audience, influencer character settings, and desired emotional responses. The data entered by the user on their device is transmitted to a server via the internet.

[0164] The server analyzes the received data and generates virtual influencers using a generative AI model. The generated influencers possess not only visual appeal and personality traits, but also an emotion recognition engine. This engine utilizes an open-source emotion recognition library and analyzes changes in emotion in real time by analyzing the user's facial expressions and voice input, generating appropriate responses.

[0165] A concrete example would be an influencer targeted at a young user base for a new cosmetics product campaign. This influencer monitors the audience's emotions through live streaming and presents the product more appealingly based on user feedback. An example of a prompt that might be used is, "Present the latest cosmetics in a bright and friendly tone."

[0166] Ultimately, the server delivers the generated content to the designated digital platform, collects audience interaction data, and provides it to the user as analytical feedback. This increases the effectiveness of the campaign and optimizes the marketing strategy based on more data.

[0167] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0168] Step 1:

[0169] Users input brand requirements through their devices. During input, they use a user interface to specify characteristics of the target audience, the character settings of virtual influencers, and expected emotional responses. This data is formatted in JSON and sent to the server via the internet. Specific examples of input include information such as "target audience is teenage girls, and the influencer has a bright and friendly personality."

[0170] Step 2:

[0171] The server analyzes the request specification data received from the terminal. It uses a Python data analysis library to convert the data into the required format and store it in the database. Here, it performs tasks such as detecting outliers and checking the format, preparing the data for model generation. The output is cleaned data ready to be input into the generated AI model.

[0172] Step 3:

[0173] The server generates virtual influencers using a generative AI model. This model, built using TensorFlow, generates the influencer's visual appearance and personality traits based on the received data. Specifically, it incorporates image generation algorithms and personality mapping algorithms. The output is a virtual influencer object represented in digital file format.

[0174] Step 4:

[0175] The server uses an emotion recognition engine to configure the virtual influencer's response patterns. This step utilizes open-source emotion recognition libraries to analyze user facial expressions and voice input in real time and prepare responses. Prompts include instructions such as, "If the viewer is smiling, make the response tone positive." The output is a response sequence that responds to real-time emotional changes.

[0176] Step 5:

[0177] The server automatically generates content by inputting prompt text into a generative AI model based on the specified campaign theme. This process utilizes a text generation algorithm to create messages with human-like and natural language. For example, the prompt text "Speak to the audience with enthusiasm and highlight the unique benefits of the product" is used, and the output is visually and textually refined campaign content.

[0178] Step 6:

[0179] The server analyzes the generated content and detects inappropriate elements. Using natural language processing techniques, it evaluates contextual consistency and social appropriateness, and generates suggested corrections if problems arise. The output is content tailored to the target audience.

[0180] Step 7:

[0181] The user reviews the content generated on the server and gives final approval. Throughout the process, the user evaluates whether the visual presentation and linguistic expression of the content align with the brand image. The output is the approved campaign content.

[0182] Step 8:

[0183] The server delivers approved content to the designated platform. It optimizes content according to the digital marketing channel, enabling real-time interaction between influencers and end-users. The output is the marketing message deployed on the distribution platform.

[0184] (Application Example 2)

[0185] 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".

[0186] Traditional marketing activities struggle to respond flexibly to consumer emotions, making it difficult to enhance the effectiveness of interactive advertising. Furthermore, there are limited means of obtaining real-time feedback from target audiences, hindering the immediate improvement of advertising strategies.

[0187] 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.

[0188] In this invention, the server includes means for receiving brand requirements and generating original virtual influencers based thereon, means for recognizing the user's emotions based on visual and auditory input, and means for dynamically adjusting the virtual influencer's responses according to the user's emotions. This enables effective interaction based on the emotions of the target audience and immediate improvement of advertising strategies through real-time feedback.

[0189] A "requirements specification" is a document that describes in detail the requirements and conditions necessary to achieve a specific target outcome.

[0190] A "virtual influencer" is a digital entity created using artificial intelligence technology that has the same influence as a human being in marketing activities.

[0191] "Audiovisual information" refers to digital information that can be perceived through sight and hearing, and is an important element in advertising and promotion.

[0192] "Target audience" refers to the market or group of consumers that are targeted by a particular marketing activity or advertisement.

[0193] "Two-way communication data" refers to information about interactions between the user and the system, and is used to measure the effectiveness of real-time interactions.

[0194] "Brand impression" is a concept that relates to the image and reputation of a company or product as perceived by consumers and society.

[0195] A "promotional theme" refers to the central idea or message in a particular advertisement or marketing campaign.

[0196] "Real-time interaction" is a technology that enables instant communication with users and can instantly adjust responses based on emotions.

[0197] The system for implementing this invention enables efficient and flexible marketing activities through the cooperation of servers, terminals, and users.

[0198] First, the terminal receives brand requirements from the user, which include the emotional characteristics of the target audience and the character settings of the virtual influencer. This information becomes the foundational data within the system and is sent to the server.

[0199] The server generates virtual influencers using artificial intelligence technology based on the received request specifications. Furthermore, it analyzes the user's emotions in real time using an emotion recognition engine such as EmotionRecognitionEngine, based on visual and auditory input data. Based on these results, the influencer's response is dynamically adjusted using a generated AI model (e.g., GPT-4®).

[0200] The generated audiovisual information is automatically created for each promotional theme and verified by a server. Content with inappropriate elements removed is delivered to the target audience in real time, during which a virtual influencer interacts with the audience in real time. This allows consumers to receive promotional information tailored to their own emotions.

[0201] The server can also collect two-way communication data between users and virtual influencers, and by continuously monitoring its effectiveness, it can suggest improvements for future advertising strategies. This contributes to the continuous optimization of advertisements and campaigns.

[0202] As a concrete example, in the announcement of a new car model, if a user shows interest in a particular part while watching a test drive video, a virtual influencer may provide more detailed information or a special offer related to that part. An example of a prompt might be: "Generate a jacket description for when the user shows positive emotions. The response should be in a friendly tone and include humor."

[0203] By using this system, companies can communicate more effectively with their target audience and improve the effectiveness of their advertising through real-time feedback.

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

[0205] Step 1:

[0206] The user inputs the brand's requirements into a terminal. Specifically, they input specifications, including the emotional characteristics of the target audience and the character settings of the virtual influencer, through an input interface provided on the terminal. The input data is sent to the server as an initial dataset.

[0207] Step 2:

[0208] The server generates virtual influencers based on the received requirements specifications. In this process, a generation AI model is used to create virtual influencers with appearances and personalities that conform to the specifications. Furthermore, emotional response patterns are also configured. The input is the requirements specifications, and the output is a prototype of the virtual influencer.

[0209] Step 3:

[0210] The server uses visual and auditory data to recognize the user's emotions. At this stage, the EmotionRecognitionEngine is used to analyze the emotional state based on the user's real-time facial expressions and vocal characteristics, which are the input data. The output is the result of the emotional state determination.

[0211] Step 4:

[0212] The server dynamically adjusts the virtual influencer's response based on the emotion recognition results. A generative AI model is used to generate prompt messages appropriate to the emotion. Specifically, it creates a message in a tone that matches the detected emotion. The output is the adjusted response message for the user.

[0213] Step 5:

[0214] The server automatically generates audiovisual information based on the promotional theme. This includes designing and structuring the content to match the promotional strategy. The output content is verified for inappropriate elements and is ready for use after safety checks.

[0215] Step 6:

[0216] The server delivers verified audiovisual information to the target audience in real time. It optimizes the format for the distribution channel and configures it for interactive presentations by virtual influencers. The output is the delivered content.

[0217] Step 7:

[0218] The server collects two-way communication data with users and monitors its effectiveness along with emotional response data. This provides foundational data for suggesting improvements to future advertising strategies. Specifically, it generates user engagement analysis reports.

[0219] 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.

[0220] 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.

[0221] 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.

[0222] [Second Embodiment]

[0223] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0224] 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.

[0225] 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).

[0226] 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.

[0227] 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.

[0228] 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).

[0229] 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.

[0230] 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.

[0231] 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.

[0232] 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.

[0233] 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.

[0234] 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".

[0235] This invention is a system that utilizes AI technology to enable companies to generate their own virtual influencers and conduct efficient and secure marketing activities. This system functions through the coordinated efforts of a server, terminals, and users.

[0236] First, the user, acting as a company representative, accesses the system through a dedicated terminal. The user inputs information such as the characteristics of the target audience, the brand message, and the desired influencer's character as brand requirements. This specification information is then sent to the server.

[0237] Next, the server uses AI technology to generate a virtual influencer based on the received brand requirements. Leveraging past success stories and database information, the server creates a prototype of the most suitable influencer for the specified conditions. This virtual influencer is designed to match the brand's appearance, voice, personality, and other characteristics.

[0238] The generated virtual influencers are used through a server-managed platform to automatically generate promotional videos, advertising images, and text content using AI technology. The server also analyzes the generated material to ensure its safety and verify that it does not contain any inappropriate elements.

[0239] Content whose safety has been confirmed will be distributed to designated media platforms. Users will be able to interact with virtual influencers in real time via their devices and receive direct feedback from end users in real time.

[0240] For example, when running a campaign for a new product, three promotional videos featuring virtual influencers are generated, each targeting a different audience. Users can instantly understand which message is most effective based on their reactions to these videos. The server then analyzes the reaction and interaction data to provide more specific suggestions for improvement and proposals for future campaigns.

[0241] This system will be a powerful tool for achieving flexible and creative marketing while minimizing costs and risks.

[0242] The following describes the processing flow.

[0243] Step 1:

[0244] Users access the system using a dedicated terminal and input their brand's requirements. This includes characteristics of the target audience, the type of influencer they expect, and key brand messages. Once input is complete, the information is sent to the server.

[0245] Step 2:

[0246] The server analyzes the received requirements and uses an AI model to automatically generate the optimal virtual influencer. Based on data learned from past performance and case studies, the server determines appearance, voice, personality, etc., and creates a prototype.

[0247] Step 3:

[0248] The server utilizes the generated virtual influencers to automatically create advertising content such as promotional videos, images, and text based on the specified campaign theme. Multiple variations are prepared and can be customized for different target audiences.

[0249] Step 4:

[0250] The server checks the generated content for inappropriate elements. This process uses natural language processing (NLP) technology to automatically verify the safety of the content. If inappropriate content is detected, it generates suggested corrections.

[0251] Step 5:

[0252] The user reviews the generated content through their device and sends approval or correction instructions to the server as needed. Content approved by the user proceeds to the next step.

[0253] Step 6:

[0254] The server prepares approved content for distribution to designated media platforms and social media. It sets distribution schedules and delivers content to the target audience at the optimal time.

[0255] Step 7:

[0256] Users configure real-time interactions with virtual influencers using their devices. Feedback from end users is collected to measure the campaign's effectiveness.

[0257] Step 8:

[0258] The server analyzes the collected interaction data to evaluate the campaign's effectiveness. Based on this data, it provides users with suggestions for improvement and feedback for future campaigns.

[0259] (Example 1)

[0260] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0261] Traditional marketing activities have faced challenges in effectively engaging consumers and maintaining brand image using virtual promotional characters. Furthermore, the process of rapidly distributing generated content while ensuring its safety is complex, highlighting the need for an efficient and secure system.

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

[0263] In this invention, the server includes means for receiving brand information and constructing an appropriate digital character based on it; means for automatically creating digital content in line with the campaign theme using the generated digital character; and means for analyzing the created digital content and checking for elements that do not conform to the norms. This enables the safe and effective generation and distribution of digital content.

[0264] "Brand information" refers to data that includes attributes such as the target audience, the message to be conveyed, and the brand image associated with a particular product or service.

[0265] A "digital character" is a virtual person or character created on a computer and used in marketing activities to convey a brand's message.

[0266] "Digital content" refers to media files such as videos, images, and text created using generated digital characters and used for marketing purposes.

[0267] "Information media" refers to communication methods such as online platforms and applications through which generated digital content is delivered to consumers.

[0268] "User data" refers to digital information collected from consumers' reactions and interactions with delivered content, and is used to evaluate the effectiveness of marketing activities.

[0269] "Non-compliant elements" refer to content or expressions within the generated content that are deemed inappropriate and are subject to inspection to ensure safety.

[0270] This invention is a system for companies to conduct effective marketing activities, in which servers, terminals, and users work in coordination with each other. The following describes its specific embodiments.

[0271] Users access the system using a dedicated terminal. They input brand information and send it to the server. This information includes the target customer base, product and service characteristics, and the brand message to be conveyed.

[0272] The server analyzes brand information received from the user. AI technology is used for the analysis, and appropriate prompt sentences are generated by a specific generative AI model. For example, a prompt sentence such as, "Generate a promotional video for a new skincare product aimed at women in their 20s. The motif should be natural, emphasizing natural beauty," might be used.

[0273] The generation AI model constructs a virtual digital character based on this prompt text. AI technology adjusts the digital character's appearance, movements, voice, and personality to be appropriate for the brand. Specific technologies, such as graphics generation engines and speech synthesis software, are utilized in the generation process.

[0274] The generated digital characters are managed on a server platform, and digital content based on the specified campaign theme is automatically created. In this process, the server uses natural language processing technology to inspect the generated content for elements that do not conform to the standards, ensuring safety.

[0275] Once security is confirmed, the server quickly delivers the content to the designated media. User reactions and interactions to the delivered content are collected on the server and analyzed to evaluate marketing activities and make effective suggestions for future campaigns. This implementation allows companies to implement digital marketing efficiently and securely.

[0276] The flow of the specific process in Example 1 will be described using FIG. 11.

[0277] Step 1:

[0278] The user accesses the system via a dedicated terminal. The user inputs the brand message, target layer, and desired specifications of the digital character and sends them to the server. This input information includes the attributes of the brand and the intended communication content.

[0279] Step 2:

[0280] The server analyzes the received brand information. Based on the input information using an AI model, the server generates an optimal prompt sentence. This prompt sentence serves as an instruction for defining the appearance and personality of the digital character. As an analysis result, the prompt sentence is output.

[0281] Step 3:

[0282] The server uses the generated prompt sentence as an input to execute a generation AI model and constructs a virtual digital character. Specifically, based on the prompt sentence, the AI model generates the visual, audio, and behavior patterns of the character. The output of this step is a detailed profile of the digital character.

[0283] Step 4:

[0284] Based on the generated digital character, the server automatically creates the digital content required for the campaign. Using AI technology, the server generates the images, videos, and texts included in the content and assembles the entire content. The output is complete digital marketing content.

[0285] Step 5:

[0286] The server analyzes the generated digital content and checks whether it contains any non-compliant elements. This inspection uses natural language processing technology, and only the content with confirmed safety will proceed to the next step. The output of the inspection is the content with confirmed safety.

[0287] Step 6:

[0288] The server distributes the digital content with confirmed safety to the specified information medium. For distribution, it uses the API of the distribution platform via the Internet to transmit it to the target audience in real time. The output is the status indicating successful distribution.

[0289] Step 7:

[0290] The server collects the end-user's reaction to the distributed content and analyzes the user data. The server uses data analysis tools to evaluate which content was effective and provides improvement suggestions for the next campaign. The output is a report of the marketing analysis results.

[0291] (Application Example 1)

[0292] 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".

[0293] In marketing using virtual influencers, it is required to provide personalized advertising information based on the interests and concerns of target consumers and to realize a campaign that utilizes effective technology through real-time interaction. Also, ensuring the safety of the generated content and conducting effective advertising activities without damaging the brand image are important issues.

[0294] 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.

[0295] This invention includes a server that receives brand requirements and generates original virtual influencers based on those requirements, a server that utilizes the generated virtual influencers to automatically generate content based on a specified campaign theme, and a server that provides advertising information from virtual influencers based on the user's interests. This enables the delivery of personalized advertisements to target audiences, allowing for the development of more effective and secure marketing strategies.

[0296] "Brand requirements" refer to information about the characteristics and target audience that a company expects from virtual influencers for the purpose of conducting an advertising campaign.

[0297] A "virtual influencer" is a digital, simulated persona created using AI technology to disseminate brand messages in advertising and content creation.

[0298] A "campaign theme" is a subject that is set based on the characteristics of a product that you want to highlight in a particular marketing activity, or the demands of the target market.

[0299] "Automatic content generation" refers to the process of generating advertising materials such as videos, images, and text using AI technology without human intervention.

[0300] "Verified content" refers to content that has been confirmed to be free of inappropriate elements and to be safe.

[0301] A "target audience" is a group of consumers who are expected to be attracted to a particular product or brand in advertising and marketing activities.

[0302] "Interaction data" refers to data on reactions and behaviors that show how content created by virtual influencers was received by users.

[0303] The "personalized advertising information" refers to advertising content customized based on the interests and concerns of individual users.

[0304] The system for implementing the present invention operates with the cooperation of a server, a terminal, and a user. First, the user accesses the system using a dedicated terminal and inputs the brand's requirement specifications. This specification information includes the target layer, brand message, character of the desired influencer, etc. The specification information is sent to the server, and the server receives it and utilizes AI technology to generate a virtual influencer.

[0305] The server utilizes the generated AI model to set the appearance and personality of the virtual influencer based on the specifications. The generated influencer is used to automatically generate content. Here, high-performance server equipment is required for the hardware, and an AI model (e.g., a machine learning model or a natural language processing algorithm) is incorporated in the software.

[0306] The generated content is verified by the server and analyzed for any inappropriate elements. The content that has completed this safety check is distributed to the specified media platform. The user can have real-time interaction with the virtual influencer through the terminal and can immediately receive reactions from end-users.

[0307] As a specific example, for users interested in fashion, a video of a virtual influencer featuring the latest fashion items is distributed. Since this content is personalized according to the interests of individual users, higher engagement can be expected. An example of a prompt sentence for the generated AI model is: "The user's hobby is fashion. Please create an attractive video introducing the latest trends."

[0308] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0309] Step 1:

[0310] The user accesses the system via a terminal. Here, the user inputs the brand's requirements, which include information such as the target audience, brand message, and desired influencer characters. This input data is sent to the server for use in the next step.

[0311] Step 2:

[0312] The server receives brand requirements from users and generates virtual influencers based on an AI model. Using brand specification data as input, the AI ​​model performs data calculations to output virtual influencers with defined appearances and personalities. The server then uses this data to optimize the process by referencing similar past cases and database information.

[0313] Step 3:

[0314] The server automatically generates content that fits the specified campaign theme using the generated virtual influencers. The user's brand specifications are input as prompts, and the generating AI model outputs digital content (e.g., videos and text) based on this. At this time, the AI ​​also utilizes natural language processing technology to generate more engaging content.

[0315] Step 4:

[0316] The server analyzes the generated content and verifies that it does not contain any inappropriate elements. The server uses content analysis software to analyze the data to confirm the safety of the content. The input is the generated digital content, and the output is the safety status of that content.

[0317] Step 5:

[0318] The server delivers verified and secure content in real time to the designated media platform. The server develops an optimal delivery plan based on the platform's requirements and target audience characteristics, and then transmits the content via the platform's API.

[0319] Step 6:

[0320] Users can interact with virtual influencers through their devices. Users monitor the collected interaction data, receive reactions and feedback, and use this data to improve future campaigns. Input is end-user response data, and output is the analysis results necessary for improvement suggestions.

[0321] 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.

[0322] This invention provides a system that efficiently generates custom-designed virtual influencers for businesses and combines AI-powered emotion recognition with user interactions to achieve more flexible and effective marketing activities. This system operates through the collaborative efforts of a server, terminal, and user, with particular emphasis on optimizing interactions based on emotion recognition.

[0323] First, the user inputs the brand's requirements into the system via their device. This includes the emotional characteristics of the target audience, the character settings the virtual influencer should have, and the expected emotional responses. The input information is sent to the server and becomes the basis for subsequent processing.

[0324] The server uses AI technology to generate virtual influencers based on the input requirements. The generated influencers possess not only appearance and personality, but also response patterns that respond to the user's emotions. This is achieved by an emotion engine that determines the user's emotions in real time through facial expressions and voice input, and dynamically adjusts the influencer's responses based on the results.

[0325] Next, the server automatically generates content according to the specified campaign theme. Here, it selects the most appropriate expressions and tones based on emotion to create a message that resonates with the audience. The generated content is analyzed using natural language processing (NLP) techniques to detect inappropriate elements.

[0326] Content approved by users is delivered to the platform specified by the server. Leveraging real-time sentiment recognition, virtual influencers engage in two-way communication with end users. For example, during a live streaming event, they can change their tone based on the audience's emotional state or present specific products in an emotionally resonant way.

[0327] The server collects interaction data with users and provides feedback to users based on the analysis results. This allows for real-time monitoring of campaign effectiveness and enables specific improvement suggestions for future initiatives.

[0328] This system allows companies to effectively communicate their brand in a way that appeals to the emotions of their target audience and create interactive marketing activities.

[0329] The following describes the processing flow.

[0330] Step 1:

[0331] Users access the system using a dedicated terminal and input brand requirements. This includes target audience profiles, desired appearance and personality traits of influencers, and campaign objectives.

[0332] Step 2:

[0333] The server analyzes the received brand requirements and uses an AI model to generate virtual influencers. The generation process establishes characters with specific emotional response patterns, incorporating optimizations based on historical datasets.

[0334] Step 3:

[0335] The server activates the emotion engine and incorporates the emotion recognition capabilities of the virtual influencer. This prepares the influencer to judge the user's emotions from their facial expressions and tone and to interact accordingly.

[0336] Step 4:

[0337] The server automatically generates ad content based on the campaign theme. Here, the emotion engine selects the most effective emotional expression and adjusts the content to appeal to the user's target emotions.

[0338] Step 5:

[0339] The server analyzes the generated content using natural language processing (NLP) techniques to detect inappropriate elements. If any are found, it creates a proposed correction and provides the user with a preview for approval.

[0340] Step 6:

[0341] The user reviews the generated content through their device and gives final approval. Content approved by the user proceeds to the next execution stage.

[0342] Step 7:

[0343] The server delivers approved content to the designated platform in real time, deploying it to the target audience. It utilizes an emotion engine to implement interactions tailored to the recipient's emotions.

[0344] Step 8:

[0345] Users use their devices to observe end-user emotional responses in real time. Virtual influencers use this data to adjust their responses and engage in more personalized communication.

[0346] Step 9:

[0347] The server collects and analyzes interaction data to evaluate the effectiveness of the campaign. Based on the analysis results, it provides users with suggestions for improvement and feedback for future campaigns.

[0348] (Example 2)

[0349] 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".

[0350] In traditional marketing activities using information processing devices, feedback on audience emotions was not reflected in real time, limiting the effectiveness of interactions. Furthermore, the quality and optimization of generated content were insufficient, resulting in low appeal to target audiences. Consequently, companies were unable to effectively communicate their brand image, and the quality of interactions was not guaranteed.

[0351] 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.

[0352] In this invention, the server includes, firstly, means for receiving brand requirements and generating its own information processing device based thereon; secondly, means for automatically generating information based on a specified subject using the generated information processing device; thirdly, means for analyzing the generated information and verifying the presence or absence of inappropriate elements; and fourthly, means for the generated information processing device to analyze the emotional state through voice or visual input and adjust the response in real time accordingly. This makes it possible to provide effective and emotionally appealing interactions to the target audience and effectively convey the brand image.

[0353] A "brand" refers to a name, design, or symbol used to distinguish a particular company or product from others.

[0354] An "information processing device" refers to a device that performs calculations and data transformations based on specified input data and generates the desired output.

[0355] "Generation" refers to the act of creating new digital content or data through specific algorithms or processes.

[0356] "Subject" refers to a specific purpose or focus in content or activities.

[0357] "Information" refers to content composed of knowledge, data, and facts, which possesses meaning and value directed towards a specific recipient.

[0358] "Analysis" refers to the methods and processes used to investigate information and data and to clarify their structure and meaning.

[0359] "Input" refers to the data or commands provided to an information processing device.

[0360] "Response" refers to the reply or action given in response to an input or situation.

[0361] "Audience" refers to the group of people who receive and engage with specific content or information.

[0362] "Interaction" refers to the actions or processes in which two or more parties exchange information with each other.

[0363] This invention is implemented using an information processing system comprised of a server, a terminal, and a user. The server functions as a platform for running advanced AI models by combining languages ​​such as Python and SQL with machine learning frameworks such as TensorFlow and PyTorch. The terminal provides an interface for the user to input data and exchange data bidirectionally with the information processing device. This terminal is typically a personal computer or mobile device and requires a robust internet connection.

[0364] First, the user inputs brand requirements through their device. These requirements include characteristics of the target audience, influencer character settings, and desired emotional responses. The data entered by the user on their device is transmitted to a server via the internet.

[0365] The server analyzes the received data and generates virtual influencers using a generative AI model. The generated influencers possess not only visual appeal and personality traits, but also an emotion recognition engine. This engine utilizes an open-source emotion recognition library and analyzes changes in emotion in real time by analyzing the user's facial expressions and voice input, generating appropriate responses.

[0366] A concrete example would be an influencer targeted at a young user base for a new cosmetics product campaign. This influencer monitors the audience's emotions through live streaming and presents the product more appealingly based on user feedback. An example of a prompt that might be used is, "Present the latest cosmetics in a bright and friendly tone."

[0367] Ultimately, the server delivers the generated content to the designated digital platform, collects audience interaction data, and provides it to the user as analytical feedback. This increases the effectiveness of the campaign and optimizes the marketing strategy based on more data.

[0368] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0369] Step 1:

[0370] Users input brand requirements through their devices. During input, they use a user interface to specify characteristics of the target audience, the character settings of virtual influencers, and expected emotional responses. This data is formatted in JSON and sent to the server via the internet. Specific examples of input include information such as "target audience is teenage girls, and the influencer has a bright and friendly personality."

[0371] Step 2:

[0372] The server analyzes the request specification data received from the terminal. It uses a Python data analysis library to convert the data into the required format and store it in the database. Here, it performs tasks such as detecting outliers and checking the format, preparing the data for model generation. The output is cleaned data ready to be input into the generated AI model.

[0373] Step 3:

[0374] The server generates virtual influencers using a generative AI model. This model, built using TensorFlow, generates the influencer's visual appearance and personality traits based on the received data. Specifically, it incorporates image generation algorithms and personality mapping algorithms. The output is a virtual influencer object represented in digital file format.

[0375] Step 4:

[0376] The server uses an emotion recognition engine to configure the virtual influencer's response patterns. This step utilizes open-source emotion recognition libraries to analyze user facial expressions and voice input in real time and prepare responses. Prompts include instructions such as, "If the viewer is smiling, make the response tone positive." The output is a response sequence that responds to real-time emotional changes.

[0377] Step 5:

[0378] The server automatically generates content by inputting prompt text into a generative AI model based on the specified campaign theme. This process utilizes a text generation algorithm to create messages with human-like and natural language. For example, the prompt text "Speak to the audience with enthusiasm and highlight the unique benefits of the product" is used, and the output is visually and textually refined campaign content.

[0379] Step 6:

[0380] The server analyzes the generated content and detects inappropriate elements. Using natural language processing techniques, it evaluates contextual consistency and social appropriateness, and generates suggested corrections if problems arise. The output is content tailored to the target audience.

[0381] Step 7:

[0382] The user reviews the content generated on the server and gives final approval. Throughout the process, the user evaluates whether the visual presentation and linguistic expression of the content align with the brand image. The output is the approved campaign content.

[0383] Step 8:

[0384] The server delivers approved content to the designated platform. It optimizes content according to the digital marketing channel, enabling real-time interaction between influencers and end-users. The output is the marketing message deployed on the distribution platform.

[0385] (Application Example 2)

[0386] 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."

[0387] Traditional marketing activities struggle to respond flexibly to consumer emotions, making it difficult to enhance the effectiveness of interactive advertising. Furthermore, there are limited means of obtaining real-time feedback from target audiences, hindering the immediate improvement of advertising strategies.

[0388] 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.

[0389] In this invention, the server includes means for receiving brand requirements and generating original virtual influencers based thereon, means for recognizing the user's emotions based on visual and auditory input, and means for dynamically adjusting the virtual influencer's responses according to the user's emotions. This enables effective interaction based on the emotions of the target audience and immediate improvement of advertising strategies through real-time feedback.

[0390] A "requirements specification" is a document that describes in detail the requirements and conditions necessary to achieve a specific target outcome.

[0391] A "virtual influencer" is a digital entity created using artificial intelligence technology that has the same influence as a human being in marketing activities.

[0392] "Audiovisual information" refers to digital information that can be perceived through sight and hearing, and is an important element in advertising and promotion.

[0393] "Target audience" refers to the market or group of consumers that are targeted by a particular marketing activity or advertisement.

[0394] "Two-way communication data" refers to information about interactions between the user and the system, and is used to measure the effectiveness of real-time interactions.

[0395] "Brand impression" is a concept that relates to the image and reputation of a company or product as perceived by consumers and society.

[0396] A "promotional theme" refers to the central idea or message in a particular advertisement or marketing campaign.

[0397] "Real-time interaction" is a technology that enables instant communication with users and can instantly adjust responses based on emotions.

[0398] The system for implementing this invention enables efficient and flexible marketing activities through the cooperation of servers, terminals, and users.

[0399] First, the terminal receives brand requirements from the user, which include the emotional characteristics of the target audience and the character settings of the virtual influencer. This information becomes the foundational data within the system and is sent to the server.

[0400] The server generates virtual influencers using artificial intelligence technology based on the received request specifications. Furthermore, it analyzes the user's emotions in real time using an emotion recognition engine such as EmotionRecognitionEngine, based on visual and auditory input data. Based on these results, the influencer's response is dynamically adjusted using a generative AI model (e.g., GPT-4).

[0401] The generated audiovisual information is automatically created for each promotional theme and verified by a server. Content with inappropriate elements removed is delivered to the target audience in real time, during which a virtual influencer interacts with the audience in real time. This allows consumers to receive promotional information tailored to their own emotions.

[0402] The server can also collect two-way communication data between users and virtual influencers, and by continuously monitoring its effectiveness, it can suggest improvements for future advertising strategies. This contributes to the continuous optimization of advertisements and campaigns.

[0403] As a concrete example, in the announcement of a new car model, if a user shows interest in a particular part while watching a test drive video, a virtual influencer may provide more detailed information or a special offer related to that part. An example of a prompt might be: "Generate a jacket description for when the user shows positive emotions. The response should be in a friendly tone and include humor."

[0404] By using this system, companies can communicate more effectively with their target audience and improve the effectiveness of their advertising through real-time feedback.

[0405] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0406] Step 1:

[0407] The user inputs the brand's requirements into a terminal. Specifically, they input specifications, including the emotional characteristics of the target audience and the character settings of the virtual influencer, through an input interface provided on the terminal. The input data is sent to the server as an initial dataset.

[0408] Step 2:

[0409] The server generates virtual influencers based on the received requirements specifications. In this process, a generation AI model is used to create virtual influencers with appearances and personalities that conform to the specifications. Furthermore, emotional response patterns are also configured. The input is the requirements specifications, and the output is a prototype of the virtual influencer.

[0410] Step 3:

[0411] The server uses visual and auditory data to recognize the user's emotions. At this stage, the EmotionRecognitionEngine is used to analyze the emotional state based on the user's real-time facial expressions and vocal characteristics, which are the input data. The output is the result of the emotional state determination.

[0412] Step 4:

[0413] The server dynamically adjusts the virtual influencer's response based on the emotion recognition results. A generative AI model is used to generate prompt messages appropriate to the emotion. Specifically, it creates a message in a tone that matches the detected emotion. The output is the adjusted response message for the user.

[0414] Step 5:

[0415] The server automatically generates audiovisual information based on the promotional theme. This includes designing and structuring the content to match the promotional strategy. The output content is verified for inappropriate elements and is ready for use after safety checks.

[0416] Step 6:

[0417] The server delivers verified audiovisual information to the target audience in real time. It optimizes the format for the distribution channel and configures it for interactive presentations by virtual influencers. The output is the delivered content.

[0418] Step 7:

[0419] The server collects two-way communication data with users and monitors its effectiveness along with emotional response data. This provides foundational data for suggesting improvements to future advertising strategies. Specifically, it generates user engagement analysis reports.

[0420] 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.

[0421] 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.

[0422] 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.

[0423] [Third Embodiment]

[0424] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0425] 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.

[0426] 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).

[0427] 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.

[0428] 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.

[0429] 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).

[0430] 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.

[0431] 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.

[0432] 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.

[0433] 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.

[0434] 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.

[0435] 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".

[0436] This invention is a system that utilizes AI technology to enable companies to generate their own virtual influencers and conduct efficient and secure marketing activities. This system functions through the coordinated efforts of a server, terminals, and users.

[0437] First, the user, acting as a company representative, accesses the system through a dedicated terminal. The user inputs information such as the characteristics of the target audience, the brand message, and the desired influencer's character as brand requirements. This specification information is then sent to the server.

[0438] Next, the server uses AI technology to generate a virtual influencer based on the received brand requirements. Leveraging past success stories and database information, the server creates a prototype of the most suitable influencer for the specified conditions. This virtual influencer is designed to match the brand's appearance, voice, personality, and other characteristics.

[0439] The generated virtual influencers are used through a server-managed platform to automatically generate promotional videos, advertising images, and text content using AI technology. The server also analyzes the generated material to ensure its safety and verify that it does not contain any inappropriate elements.

[0440] Content whose safety has been confirmed will be distributed to designated media platforms. Users will be able to interact with virtual influencers in real time via their devices and receive direct feedback from end users in real time.

[0441] For example, when running a campaign for a new product, three promotional videos featuring virtual influencers are generated, each targeting a different audience. Users can instantly understand which message is most effective based on their reactions to these videos. The server then analyzes the reaction and interaction data to provide more specific suggestions for improvement and proposals for future campaigns.

[0442] This system will be a powerful tool for achieving flexible and creative marketing while minimizing costs and risks.

[0443] The following describes the processing flow.

[0444] Step 1:

[0445] Users access the system using a dedicated terminal and input their brand's requirements. This includes characteristics of the target audience, the type of influencer they expect, and key brand messages. Once input is complete, the information is sent to the server.

[0446] Step 2:

[0447] The server analyzes the received requirements and uses an AI model to automatically generate the optimal virtual influencer. Based on data learned from past performance and case studies, the server determines appearance, voice, personality, etc., and creates a prototype.

[0448] Step 3:

[0449] The server utilizes the generated virtual influencers to automatically create advertising content such as promotional videos, images, and text based on the specified campaign theme. Multiple variations are prepared and can be customized for different target audiences.

[0450] Step 4:

[0451] The server checks the generated content for inappropriate elements. This process uses natural language processing (NLP) technology to automatically verify the safety of the content. If inappropriate content is detected, it generates suggested corrections.

[0452] Step 5:

[0453] The user reviews the generated content through their device and sends approval or correction instructions to the server as needed. Content approved by the user proceeds to the next step.

[0454] Step 6:

[0455] The server prepares approved content for distribution to designated media platforms and social media. It sets distribution schedules and delivers content to the target audience at the optimal time.

[0456] Step 7:

[0457] Users configure real-time interactions with virtual influencers using their devices. Feedback from end users is collected to measure the campaign's effectiveness.

[0458] Step 8:

[0459] The server analyzes the collected interaction data to evaluate the campaign's effectiveness. Based on this data, it provides users with suggestions for improvement and feedback for future campaigns.

[0460] (Example 1)

[0461] 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."

[0462] Traditional marketing activities have faced challenges in effectively engaging consumers and maintaining brand image using virtual promotional characters. Furthermore, the process of rapidly distributing generated content while ensuring its safety is complex, highlighting the need for an efficient and secure system.

[0463] 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.

[0464] In this invention, the server includes means for receiving brand information and constructing an appropriate digital character based on it; means for automatically creating digital content in line with the campaign theme using the generated digital character; and means for analyzing the created digital content and checking for elements that do not conform to the norms. This enables the safe and effective generation and distribution of digital content.

[0465] "Brand information" refers to data that includes attributes such as the target audience, the message to be conveyed, and the brand image associated with a particular product or service.

[0466] A "digital character" is a virtual person or character created on a computer and used in marketing activities to convey a brand's message.

[0467] "Digital content" refers to media files such as videos, images, and text created using generated digital characters and used for marketing purposes.

[0468] "Information media" refers to communication methods such as online platforms and applications through which generated digital content is delivered to consumers.

[0469] "User data" refers to digital information collected from consumers' reactions and interactions with delivered content, and is used to evaluate the effectiveness of marketing activities.

[0470] "Non-compliant elements" refer to content or expressions within the generated content that are deemed inappropriate and are subject to inspection to ensure safety.

[0471] This invention is a system for companies to conduct effective marketing activities, in which servers, terminals, and users work in coordination with each other. The following describes its specific embodiments.

[0472] Users access the system using a dedicated terminal. They input brand information and send it to the server. This information includes the target customer base, product and service characteristics, and the brand message to be conveyed.

[0473] The server analyzes brand information received from the user. AI technology is used for the analysis, and appropriate prompt sentences are generated by a specific generative AI model. For example, a prompt sentence such as, "Generate a promotional video for a new skincare product aimed at women in their 20s. The motif should be natural, emphasizing natural beauty," might be used.

[0474] The generation AI model constructs a virtual digital character based on this prompt text. AI technology adjusts the digital character's appearance, movements, voice, and personality to be appropriate for the brand. Specific technologies, such as graphics generation engines and speech synthesis software, are utilized in the generation process.

[0475] The generated digital characters are managed on a server platform, and digital content based on the specified campaign theme is automatically created. In this process, the server uses natural language processing technology to inspect the generated content for elements that do not conform to the standards, ensuring safety.

[0476] Once security is confirmed, the server quickly delivers the content to the designated media. User reactions and interactions to the delivered content are collected on the server and analyzed to evaluate marketing activities and make effective suggestions for future campaigns. This implementation allows companies to implement digital marketing efficiently and securely.

[0477] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0478] Step 1:

[0479] Users access the system via a dedicated terminal. They input their brand message, target audience, and desired specifications for their digital character, and send this information to the server. This input includes the brand's attributes and intended message.

[0480] Step 2:

[0481] The server analyzes the received brand information. Using an AI model, the server generates the optimal prompt sentence based on the input information. This prompt sentence serves as an instruction to define the appearance and personality of the digital character. The prompt sentence is output as a result of the analysis.

[0482] Step 3:

[0483] The server takes the generated prompt text as input and runs a generation AI model to construct a virtual digital character. Specifically, the AI ​​model generates the character's visuals, voice, and behavioral patterns based on the prompt text. The output of this step is a detailed profile of the digital character.

[0484] Step 4:

[0485] The server automatically creates the digital content necessary for the campaign based on the generated digital characters. Using AI technology, the server generates the images, videos, and text included in the content and assembles the overall content. The output is complete digital marketing content.

[0486] Step 5:

[0487] The server analyzes the generated digital content and checks for any elements that do not conform to the standards. This check uses natural language processing technology, and only content that is deemed safe proceeds to the next step. The output of the check is content that has been confirmed safe.

[0488] Step 6:

[0489] The server delivers secure digital content to the designated media. Delivery utilizes the API of the distribution platform via the internet, transmitting content to the target audience in real time. The output indicates a status signifying successful delivery.

[0490] Step 7:

[0491] The server collects end-user responses to delivered content and analyzes user data. The server uses data analysis tools to evaluate which content was effective and provides suggestions for improvement for future campaigns. The output is a marketing analysis report.

[0492] (Application Example 1)

[0493] 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."

[0494] In marketing using virtual influencers, there is a need to provide personalized advertising information based on the interests of target consumers and to realize effective technology-driven campaigns through real-time interaction. Furthermore, ensuring the safety of the generated content and conducting effective advertising activities without damaging the brand image are also crucial challenges.

[0495] 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.

[0496] This invention includes a server that receives brand requirements and generates original virtual influencers based on those requirements, a server that utilizes the generated virtual influencers to automatically generate content based on a specified campaign theme, and a server that provides advertising information from virtual influencers based on the user's interests. This enables the delivery of personalized advertisements to target audiences, allowing for the development of more effective and secure marketing strategies.

[0497] "Brand requirements" refer to information about the characteristics and target audience that a company expects from virtual influencers for the purpose of conducting an advertising campaign.

[0498] A "virtual influencer" is a digital, simulated persona created using AI technology to disseminate brand messages in advertising and content creation.

[0499] A "campaign theme" is a subject that is set based on the characteristics of a product that you want to highlight in a particular marketing activity, or the demands of the target market.

[0500] "Automatic content generation" refers to the process of generating advertising materials such as videos, images, and text using AI technology without human intervention.

[0501] "Verified content" refers to content that has been confirmed to be free of inappropriate elements and to be safe.

[0502] A "target audience" is a group of consumers who are expected to be attracted to a particular product or brand in advertising and marketing activities.

[0503] "Interaction data" refers to data on reactions and behaviors that show how content created by virtual influencers was received by users.

[0504] "Personalized advertising information" refers to advertising content that is customized based on the interests and preferences of individual users.

[0505] The system for implementing this invention operates through the coordinated efforts of a server, a terminal, and a user. First, the user accesses the system using a dedicated terminal and inputs the brand's requirements. This specification information includes the target audience, brand message, and desired influencer character. The specification information is sent to the server, which receives it and uses AI technology to generate a virtual influencer.

[0506] The server utilizes a generative AI model to configure the appearance and personality of virtual influencers based on specifications. Content is then automatically generated using these generated influencers. This requires high-performance server equipment and software incorporating AI models (e.g., machine learning models or natural language processing algorithms).

[0507] The generated content is validated by the server and analyzed for any inappropriate elements. Once this safety check is complete, the content is distributed to the designated media platform. Users can interact with virtual influencers in real time through their devices and receive immediate feedback from end users.

[0508] As a concrete example, users interested in fashion will be shown videos from virtual influencers featuring the latest fashion items. Because this content is personalized to each user's interests, higher engagement can be expected. An example of a prompt for the generative AI model would be: "The user's hobby is fashion. Please create an engaging video showcasing the latest trends."

[0509] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0510] Step 1:

[0511] The user accesses the system via a terminal. Here, the user inputs the brand's requirements, which include information such as the target audience, brand message, and desired influencer characters. This input data is sent to the server for use in the next step.

[0512] Step 2:

[0513] The server receives brand requirements from users and generates virtual influencers based on an AI model. Using brand specification data as input, the AI ​​model performs data calculations to output virtual influencers with defined appearances and personalities. The server then uses this data to optimize the process by referencing similar past cases and database information.

[0514] Step 3:

[0515] The server automatically generates content that fits the specified campaign theme using the generated virtual influencers. The user's brand specifications are input as prompts, and the generating AI model outputs digital content (e.g., videos and text) based on this. At this time, the AI ​​also utilizes natural language processing technology to generate more engaging content.

[0516] Step 4:

[0517] The server analyzes the generated content and verifies that it does not contain any inappropriate elements. The server uses content analysis software to analyze the data to confirm the safety of the content. The input is the generated digital content, and the output is the safety status of that content.

[0518] Step 5:

[0519] The server delivers verified and secure content in real time to the designated media platform. The server develops an optimal delivery plan based on the platform's requirements and target audience characteristics, and then transmits the content via the platform's API.

[0520] Step 6:

[0521] Users can interact with virtual influencers through their devices. Users monitor the collected interaction data, receive reactions and feedback, and use this data to improve future campaigns. Input is end-user response data, and output is the analysis results necessary for improvement suggestions.

[0522] 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.

[0523] This invention provides a system that efficiently generates custom-designed virtual influencers for businesses and combines AI-powered emotion recognition with user interactions to achieve more flexible and effective marketing activities. This system operates through the collaborative efforts of a server, terminal, and user, with particular emphasis on optimizing interactions based on emotion recognition.

[0524] First, the user inputs the brand's requirements into the system via their device. This includes the emotional characteristics of the target audience, the character settings the virtual influencer should have, and the expected emotional responses. The input information is sent to the server and becomes the basis for subsequent processing.

[0525] The server uses AI technology to generate virtual influencers based on the input requirements. The generated influencers possess not only appearance and personality, but also response patterns that respond to the user's emotions. This is achieved by an emotion engine that determines the user's emotions in real time through facial expressions and voice input, and dynamically adjusts the influencer's responses based on the results.

[0526] Next, the server automatically generates content according to the specified campaign theme. Here, it selects the most appropriate expressions and tones based on emotion to create a message that resonates with the audience. The generated content is analyzed using natural language processing (NLP) techniques to detect inappropriate elements.

[0527] Content approved by users is delivered to the platform specified by the server. Leveraging real-time sentiment recognition, virtual influencers engage in two-way communication with end users. For example, during a live streaming event, they can change their tone based on the audience's emotional state or present specific products in an emotionally resonant way.

[0528] The server collects interaction data with users and provides feedback to users based on the analysis results. This allows for real-time monitoring of campaign effectiveness and enables specific improvement suggestions for future initiatives.

[0529] This system allows companies to effectively communicate their brand in a way that appeals to the emotions of their target audience and create interactive marketing activities.

[0530] The following describes the processing flow.

[0531] Step 1:

[0532] Users access the system using a dedicated terminal and input brand requirements. This includes target audience profiles, desired appearance and personality traits of influencers, and campaign objectives.

[0533] Step 2:

[0534] The server analyzes the received brand requirements and uses an AI model to generate virtual influencers. The generation process establishes characters with specific emotional response patterns, incorporating optimizations based on historical datasets.

[0535] Step 3:

[0536] The server activates the emotion engine and incorporates the emotion recognition capabilities of the virtual influencer. This prepares the influencer to judge the user's emotions from their facial expressions and tone and to interact accordingly.

[0537] Step 4:

[0538] The server automatically generates ad content based on the campaign theme. Here, the emotion engine selects the most effective emotional expression and adjusts the content to appeal to the user's target emotions.

[0539] Step 5:

[0540] The server analyzes the generated content using natural language processing (NLP) techniques to detect inappropriate elements. If any are found, it creates a proposed correction and provides the user with a preview for approval.

[0541] Step 6:

[0542] The user reviews the generated content through their device and gives final approval. Content approved by the user proceeds to the next execution stage.

[0543] Step 7:

[0544] The server delivers approved content to the designated platform in real time, deploying it to the target audience. It utilizes an emotion engine to implement interactions tailored to the recipient's emotions.

[0545] Step 8:

[0546] Users use their devices to observe end-user emotional responses in real time. Virtual influencers use this data to adjust their responses and engage in more personalized communication.

[0547] Step 9:

[0548] The server collects and analyzes interaction data to evaluate the effectiveness of the campaign. Based on the analysis results, it provides users with suggestions for improvement and feedback for future campaigns.

[0549] (Example 2)

[0550] 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."

[0551] In traditional marketing activities using information processing devices, feedback on audience emotions was not reflected in real time, limiting the effectiveness of interactions. Furthermore, the quality and optimization of generated content were insufficient, resulting in low appeal to target audiences. Consequently, companies were unable to effectively communicate their brand image, and the quality of interactions was not guaranteed.

[0552] 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.

[0553] In this invention, the server includes, firstly, means for receiving brand requirements and generating its own information processing device based thereon; secondly, means for automatically generating information based on a specified subject using the generated information processing device; thirdly, means for analyzing the generated information and verifying the presence or absence of inappropriate elements; and fourthly, means for the generated information processing device to analyze the emotional state through voice or visual input and adjust the response in real time accordingly. This makes it possible to provide effective and emotionally appealing interactions to the target audience and effectively convey the brand image.

[0554] A "brand" refers to a name, design, or symbol used to distinguish a particular company or product from others.

[0555] An "information processing device" refers to a device that performs calculations and data transformations based on specified input data and generates the desired output.

[0556] "Generation" refers to the act of creating new digital content or data through specific algorithms or processes.

[0557] "Subject" refers to a specific purpose or focus in content or activities.

[0558] "Information" refers to content composed of knowledge, data, and facts, which possesses meaning and value directed towards a specific recipient.

[0559] "Analysis" refers to the methods and processes used to investigate information and data and to clarify their structure and meaning.

[0560] "Input" refers to the data or commands provided to an information processing device.

[0561] "Response" refers to the reply or action given in response to an input or situation.

[0562] "Audience" refers to the group of people who receive and engage with specific content or information.

[0563] "Interaction" refers to the actions or processes in which two or more parties exchange information with each other.

[0564] This invention is implemented using an information processing system comprised of a server, a terminal, and a user. The server functions as a platform for running advanced AI models by combining languages ​​such as Python and SQL with machine learning frameworks such as TensorFlow and PyTorch. The terminal provides an interface for the user to input data and exchange data bidirectionally with the information processing device. This terminal is typically a personal computer or mobile device and requires a robust internet connection.

[0565] First, the user inputs brand requirements through their device. These requirements include characteristics of the target audience, influencer character settings, and desired emotional responses. The data entered by the user on their device is transmitted to a server via the internet.

[0566] The server analyzes the received data and generates virtual influencers using a generative AI model. The generated influencers possess not only visual appeal and personality traits, but also an emotion recognition engine. This engine utilizes an open-source emotion recognition library and analyzes changes in emotion in real time by analyzing the user's facial expressions and voice input, generating appropriate responses.

[0567] A concrete example would be an influencer targeted at a young user base for a new cosmetics product campaign. This influencer monitors the audience's emotions through live streaming and presents the product more appealingly based on user feedback. An example of a prompt that might be used is, "Present the latest cosmetics in a bright and friendly tone."

[0568] Ultimately, the server delivers the generated content to the designated digital platform, collects audience interaction data, and provides it to the user as analytical feedback. This increases the effectiveness of the campaign and optimizes the marketing strategy based on more data.

[0569] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0570] Step 1:

[0571] Users input brand requirements through their devices. During input, they use a user interface to specify characteristics of the target audience, the character settings of virtual influencers, and expected emotional responses. This data is formatted in JSON and sent to the server via the internet. Specific examples of input include information such as "target audience is teenage girls, and the influencer has a bright and friendly personality."

[0572] Step 2:

[0573] The server analyzes the request specification data received from the terminal. It uses a Python data analysis library to convert the data into the required format and store it in the database. Here, it performs tasks such as detecting outliers and checking the format, preparing the data for model generation. The output is cleaned data ready to be input into the generated AI model.

[0574] Step 3:

[0575] The server generates virtual influencers using a generative AI model. This model, built using TensorFlow, generates the influencer's visual appearance and personality traits based on the received data. Specifically, it incorporates image generation algorithms and personality mapping algorithms. The output is a virtual influencer object represented in digital file format.

[0576] Step 4:

[0577] The server uses an emotion recognition engine to configure the virtual influencer's response patterns. This step utilizes open-source emotion recognition libraries to analyze user facial expressions and voice input in real time and prepare responses. Prompts include instructions such as, "If the viewer is smiling, make the response tone positive." The output is a response sequence that responds to real-time emotional changes.

[0578] Step 5:

[0579] The server automatically generates content by inputting prompt text into a generative AI model based on the specified campaign theme. This process utilizes a text generation algorithm to create messages with human-like and natural language. For example, the prompt text "Speak to the audience with enthusiasm and highlight the unique benefits of the product" is used, and the output is visually and textually refined campaign content.

[0580] Step 6:

[0581] The server analyzes the generated content and detects inappropriate elements. Using natural language processing techniques, it evaluates contextual consistency and social appropriateness, and generates suggested corrections if problems arise. The output is content tailored to the target audience.

[0582] Step 7:

[0583] The user reviews the content generated on the server and gives final approval. Throughout the process, the user evaluates whether the visual presentation and linguistic expression of the content align with the brand image. The output is the approved campaign content.

[0584] Step 8:

[0585] The server delivers approved content to the designated platform. It optimizes content according to the digital marketing channel, enabling real-time interaction between influencers and end-users. The output is the marketing message deployed on the distribution platform.

[0586] (Application Example 2)

[0587] 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."

[0588] Traditional marketing activities struggle to respond flexibly to consumer emotions, making it difficult to enhance the effectiveness of interactive advertising. Furthermore, there are limited means of obtaining real-time feedback from target audiences, hindering the immediate improvement of advertising strategies.

[0589] 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.

[0590] In this invention, the server includes means for receiving brand requirements and generating original virtual influencers based thereon, means for recognizing the user's emotions based on visual and auditory input, and means for dynamically adjusting the virtual influencer's responses according to the user's emotions. This enables effective interaction based on the emotions of the target audience and immediate improvement of advertising strategies through real-time feedback.

[0591] A "requirements specification" is a document that describes in detail the requirements and conditions necessary to achieve a specific target outcome.

[0592] A "virtual influencer" is a digital entity created using artificial intelligence technology that has the same influence as a human being in marketing activities.

[0593] "Audiovisual information" refers to digital information that can be perceived through sight and hearing, and is an important element in advertising and promotion.

[0594] "Target audience" refers to the market or group of consumers that are targeted by a particular marketing activity or advertisement.

[0595] "Two-way communication data" refers to information about interactions between the user and the system, and is used to measure the effectiveness of real-time interactions.

[0596] "Brand impression" is a concept that relates to the image and reputation of a company or product as perceived by consumers and society.

[0597] A "promotional theme" refers to the central idea or message in a particular advertisement or marketing campaign.

[0598] "Real-time interaction" is a technology that enables instant communication with users and can instantly adjust responses based on emotions.

[0599] The system for implementing this invention enables efficient and flexible marketing activities through the cooperation of servers, terminals, and users.

[0600] First, the terminal receives brand requirements from the user, which include the emotional characteristics of the target audience and the character settings of the virtual influencer. This information becomes the foundational data within the system and is sent to the server.

[0601] The server generates virtual influencers using artificial intelligence technology based on the received request specifications. Furthermore, it analyzes the user's emotions in real time using an emotion recognition engine such as EmotionRecognitionEngine, based on visual and auditory input data. Based on these results, the influencer's response is dynamically adjusted using a generative AI model (e.g., GPT-4).

[0602] The generated audiovisual information is automatically created for each promotional theme and verified by a server. Content with inappropriate elements removed is delivered to the target audience in real time, during which a virtual influencer interacts with the audience in real time. This allows consumers to receive promotional information tailored to their own emotions.

[0603] The server can also collect two-way communication data between users and virtual influencers, and by continuously monitoring its effectiveness, it can suggest improvements for future advertising strategies. This contributes to the continuous optimization of advertisements and campaigns.

[0604] As a concrete example, in the announcement of a new car model, if a user shows interest in a particular part while watching a test drive video, a virtual influencer may provide more detailed information or a special offer related to that part. An example of a prompt might be: "Generate a jacket description for when the user shows positive emotions. The response should be in a friendly tone and include humor."

[0605] By using this system, companies can communicate more effectively with their target audience and improve the effectiveness of their advertising through real-time feedback.

[0606] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0607] Step 1:

[0608] The user inputs the brand's requirements into a terminal. Specifically, they input specifications, including the emotional characteristics of the target audience and the character settings of the virtual influencer, through an input interface provided on the terminal. The input data is sent to the server as an initial dataset.

[0609] Step 2:

[0610] The server generates virtual influencers based on the received requirements specifications. In this process, a generation AI model is used to create virtual influencers with appearances and personalities that conform to the specifications. Furthermore, emotional response patterns are also configured. The input is the requirements specifications, and the output is a prototype of the virtual influencer.

[0611] Step 3:

[0612] The server uses visual and auditory data to recognize the user's emotions. At this stage, the EmotionRecognitionEngine is used to analyze the emotional state based on the user's real-time facial expressions and vocal characteristics, which are the input data. The output is the result of the emotional state determination.

[0613] Step 4:

[0614] The server dynamically adjusts the virtual influencer's response based on the emotion recognition results. A generative AI model is used to generate prompt messages appropriate to the emotion. Specifically, it creates a message in a tone that matches the detected emotion. The output is the adjusted response message for the user.

[0615] Step 5:

[0616] The server automatically generates audiovisual information based on the promotional theme. This includes designing and structuring the content to match the promotional strategy. The output content is verified for inappropriate elements and is ready for use after safety checks.

[0617] Step 6:

[0618] The server delivers verified audiovisual information to the target audience in real time. It optimizes the format for the distribution channel and configures it for interactive presentations by virtual influencers. The output is the delivered content.

[0619] Step 7:

[0620] The server collects two-way communication data with users and monitors its effectiveness along with emotional response data. This provides foundational data for suggesting improvements to future advertising strategies. Specifically, it generates user engagement analysis reports.

[0621] 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.

[0622] 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.

[0623] 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.

[0624] [Fourth Embodiment]

[0625] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0626] 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.

[0627] 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).

[0628] 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.

[0629] 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.

[0630] 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).

[0631] 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.

[0632] 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.

[0633] 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.

[0634] 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.

[0635] 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.

[0636] 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.

[0637] 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".

[0638] This invention is a system that utilizes AI technology to enable companies to generate their own virtual influencers and conduct efficient and secure marketing activities. This system functions through the coordinated efforts of a server, terminals, and users.

[0639] First, the user, acting as a company representative, accesses the system through a dedicated terminal. The user inputs information such as the characteristics of the target audience, the brand message, and the desired influencer's character as brand requirements. This specification information is then sent to the server.

[0640] Next, the server uses AI technology to generate a virtual influencer based on the received brand requirements. Leveraging past success stories and database information, the server creates a prototype of the most suitable influencer for the specified conditions. This virtual influencer is designed to match the brand's appearance, voice, personality, and other characteristics.

[0641] The generated virtual influencers are used through a server-managed platform to automatically generate promotional videos, advertising images, and text content using AI technology. The server also analyzes the generated material to ensure its safety and verify that it does not contain any inappropriate elements.

[0642] Content whose safety has been confirmed will be distributed to designated media platforms. Users will be able to interact with virtual influencers in real time via their devices and receive direct feedback from end users in real time.

[0643] For example, when running a campaign for a new product, three promotional videos featuring virtual influencers are generated, each targeting a different audience. Users can instantly understand which message is most effective based on their reactions to these videos. The server then analyzes the reaction and interaction data to provide more specific suggestions for improvement and proposals for future campaigns.

[0644] This system will be a powerful tool for achieving flexible and creative marketing while minimizing costs and risks.

[0645] The following describes the processing flow.

[0646] Step 1:

[0647] Users access the system using a dedicated terminal and input their brand's requirements. This includes characteristics of the target audience, the type of influencer they expect, and key brand messages. Once input is complete, the information is sent to the server.

[0648] Step 2:

[0649] The server analyzes the received requirements and uses an AI model to automatically generate the optimal virtual influencer. Based on data learned from past performance and case studies, the server determines appearance, voice, personality, etc., and creates a prototype.

[0650] Step 3:

[0651] The server utilizes the generated virtual influencers to automatically create advertising content such as promotional videos, images, and text based on the specified campaign theme. Multiple variations are prepared and can be customized for different target audiences.

[0652] Step 4:

[0653] The server checks the generated content for inappropriate elements. This process uses natural language processing (NLP) technology to automatically verify the safety of the content. If inappropriate content is detected, it generates suggested corrections.

[0654] Step 5:

[0655] The user reviews the generated content through their device and sends approval or correction instructions to the server as needed. Content approved by the user proceeds to the next step.

[0656] Step 6:

[0657] The server prepares approved content for distribution to designated media platforms and social media. It sets distribution schedules and delivers content to the target audience at the optimal time.

[0658] Step 7:

[0659] Users configure real-time interactions with virtual influencers using their devices. Feedback from end users is collected to measure the campaign's effectiveness.

[0660] Step 8:

[0661] The server analyzes the collected interaction data to evaluate the campaign's effectiveness. Based on this data, it provides users with suggestions for improvement and feedback for future campaigns.

[0662] (Example 1)

[0663] 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".

[0664] Traditional marketing activities have faced challenges in effectively engaging consumers and maintaining brand image using virtual promotional characters. Furthermore, the process of rapidly distributing generated content while ensuring its safety is complex, highlighting the need for an efficient and secure system.

[0665] 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.

[0666] In this invention, the server includes means for receiving brand information and constructing an appropriate digital character based on it; means for automatically creating digital content in line with the campaign theme using the generated digital character; and means for analyzing the created digital content and checking for elements that do not conform to the norms. This enables the safe and effective generation and distribution of digital content.

[0667] "Brand information" refers to data that includes attributes such as the target audience, the message to be conveyed, and the brand image associated with a particular product or service.

[0668] A "digital character" is a virtual person or character created on a computer and used in marketing activities to convey a brand's message.

[0669] "Digital content" refers to media files such as videos, images, and text created using generated digital characters and used for marketing purposes.

[0670] "Information media" refers to communication methods such as online platforms and applications through which generated digital content is delivered to consumers.

[0671] "User data" refers to digital information collected from consumers' reactions and interactions with delivered content, and is used to evaluate the effectiveness of marketing activities.

[0672] "Non-compliant elements" refer to content or expressions within the generated content that are deemed inappropriate and are subject to inspection to ensure safety.

[0673] This invention is a system for companies to conduct effective marketing activities, in which servers, terminals, and users work in coordination with each other. The following describes its specific embodiments.

[0674] Users access the system using a dedicated terminal. They input brand information and send it to the server. This information includes the target customer base, product and service characteristics, and the brand message to be conveyed.

[0675] The server analyzes brand information received from the user. AI technology is used for the analysis, and appropriate prompt sentences are generated by a specific generative AI model. For example, a prompt sentence such as, "Generate a promotional video for a new skincare product aimed at women in their 20s. The motif should be natural, emphasizing natural beauty," might be used.

[0676] The generation AI model constructs a virtual digital character based on this prompt text. AI technology adjusts the digital character's appearance, movements, voice, and personality to be appropriate for the brand. Specific technologies, such as graphics generation engines and speech synthesis software, are utilized in the generation process.

[0677] The generated digital characters are managed on a server platform, and digital content based on the specified campaign theme is automatically created. In this process, the server uses natural language processing technology to inspect the generated content for elements that do not conform to the standards, ensuring safety.

[0678] Once security is confirmed, the server quickly delivers the content to the designated media. User reactions and interactions to the delivered content are collected on the server and analyzed to evaluate marketing activities and make effective suggestions for future campaigns. This implementation allows companies to implement digital marketing efficiently and securely.

[0679] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0680] Step 1:

[0681] Users access the system via a dedicated terminal. They input their brand message, target audience, and desired specifications for their digital character, and send this information to the server. This input includes the brand's attributes and intended message.

[0682] Step 2:

[0683] The server analyzes the received brand information. Using an AI model, the server generates the optimal prompt sentence based on the input information. This prompt sentence serves as an instruction to define the appearance and personality of the digital character. The prompt sentence is output as a result of the analysis.

[0684] Step 3:

[0685] The server takes the generated prompt text as input and runs a generation AI model to construct a virtual digital character. Specifically, the AI ​​model generates the character's visuals, voice, and behavioral patterns based on the prompt text. The output of this step is a detailed profile of the digital character.

[0686] Step 4:

[0687] The server automatically creates the digital content necessary for the campaign based on the generated digital characters. Using AI technology, the server generates the images, videos, and text included in the content and assembles the overall content. The output is complete digital marketing content.

[0688] Step 5:

[0689] The server analyzes the generated digital content and checks for any elements that do not conform to the standards. This check uses natural language processing technology, and only content that is deemed safe proceeds to the next step. The output of the check is content that has been confirmed safe.

[0690] Step 6:

[0691] The server delivers secure digital content to the designated media. Delivery utilizes the API of the distribution platform via the internet, transmitting content to the target audience in real time. The output indicates a status signifying successful delivery.

[0692] Step 7:

[0693] The server collects end-user responses to delivered content and analyzes user data. The server uses data analysis tools to evaluate which content was effective and provides suggestions for improvement for future campaigns. The output is a marketing analysis report.

[0694] (Application Example 1)

[0695] 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".

[0696] In marketing using virtual influencers, there is a need to provide personalized advertising information based on the interests of target consumers and to realize effective technology-driven campaigns through real-time interaction. Furthermore, ensuring the safety of the generated content and conducting effective advertising activities without damaging the brand image are also crucial challenges.

[0697] 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.

[0698] This invention includes a server that receives brand requirements and generates original virtual influencers based on those requirements, a server that utilizes the generated virtual influencers to automatically generate content based on a specified campaign theme, and a server that provides advertising information from virtual influencers based on the user's interests. This enables the delivery of personalized advertisements to target audiences, allowing for the development of more effective and secure marketing strategies.

[0699] "Brand requirements" refer to information about the characteristics and target audience that a company expects from virtual influencers for the purpose of conducting an advertising campaign.

[0700] A "virtual influencer" is a digital, simulated persona created using AI technology to disseminate brand messages in advertising and content creation.

[0701] A "campaign theme" is a subject that is set based on the characteristics of a product that you want to highlight in a particular marketing activity, or the demands of the target market.

[0702] "Automatic content generation" refers to the process of generating advertising materials such as videos, images, and text using AI technology without human intervention.

[0703] "Verified content" refers to content that has been confirmed to be free of inappropriate elements and to be safe.

[0704] A "target audience" is a group of consumers who are expected to be attracted to a particular product or brand in advertising and marketing activities.

[0705] "Interaction data" refers to data on reactions and behaviors that show how content created by virtual influencers was received by users.

[0706] "Personalized advertising information" refers to advertising content that is customized based on the interests and preferences of individual users.

[0707] The system for implementing this invention operates through the coordinated efforts of a server, a terminal, and a user. First, the user accesses the system using a dedicated terminal and inputs the brand's requirements. This specification information includes the target audience, brand message, and desired influencer character. The specification information is sent to the server, which receives it and uses AI technology to generate a virtual influencer.

[0708] The server utilizes a generative AI model to configure the appearance and personality of virtual influencers based on specifications. Content is then automatically generated using these generated influencers. This requires high-performance server equipment and software incorporating AI models (e.g., machine learning models or natural language processing algorithms).

[0709] The generated content is validated by the server and analyzed for any inappropriate elements. Once this safety check is complete, the content is distributed to the designated media platform. Users can interact with virtual influencers in real time through their devices and receive immediate feedback from end users.

[0710] As a concrete example, users interested in fashion will be shown videos from virtual influencers featuring the latest fashion items. Because this content is personalized to each user's interests, higher engagement can be expected. An example of a prompt for the generative AI model would be: "The user's hobby is fashion. Please create an engaging video showcasing the latest trends."

[0711] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0712] Step 1:

[0713] The user accesses the system via a terminal. Here, the user inputs the brand's requirements, which include information such as the target audience, brand message, and desired influencer characters. This input data is sent to the server for use in the next step.

[0714] Step 2:

[0715] The server receives brand requirements from users and generates virtual influencers based on an AI model. Using brand specification data as input, the AI ​​model performs data calculations to output virtual influencers with defined appearances and personalities. The server then uses this data to optimize the process by referencing similar past cases and database information.

[0716] Step 3:

[0717] The server automatically generates content that fits the specified campaign theme using the generated virtual influencers. The user's brand specifications are input as prompts, and the generating AI model outputs digital content (e.g., videos and text) based on this. At this time, the AI ​​also utilizes natural language processing technology to generate more engaging content.

[0718] Step 4:

[0719] The server analyzes the generated content and verifies that it does not contain any inappropriate elements. The server uses content analysis software to analyze the data to confirm the safety of the content. The input is the generated digital content, and the output is the safety status of that content.

[0720] Step 5:

[0721] The server delivers verified and secure content in real time to the designated media platform. The server develops an optimal delivery plan based on the platform's requirements and target audience characteristics, and then transmits the content via the platform's API.

[0722] Step 6:

[0723] Users can interact with virtual influencers through their devices. Users monitor the collected interaction data, receive reactions and feedback, and use this data to improve future campaigns. Input is end-user response data, and output is the analysis results necessary for improvement suggestions.

[0724] 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.

[0725] This invention provides a system that efficiently generates custom-designed virtual influencers for businesses and combines AI-powered emotion recognition with user interactions to achieve more flexible and effective marketing activities. This system operates through the collaborative efforts of a server, terminal, and user, with particular emphasis on optimizing interactions based on emotion recognition.

[0726] First, the user inputs the brand's requirements into the system via their device. This includes the emotional characteristics of the target audience, the character settings the virtual influencer should have, and the expected emotional responses. The input information is sent to the server and becomes the basis for subsequent processing.

[0727] The server uses AI technology to generate virtual influencers based on the input requirements. The generated influencers possess not only appearance and personality, but also response patterns that respond to the user's emotions. This is achieved by an emotion engine that determines the user's emotions in real time through facial expressions and voice input, and dynamically adjusts the influencer's responses based on the results.

[0728] Next, the server automatically generates content according to the specified campaign theme. Here, it selects the most appropriate expressions and tones based on emotion to create a message that resonates with the audience. The generated content is analyzed using natural language processing (NLP) techniques to detect inappropriate elements.

[0729] Content approved by users is delivered to the platform specified by the server. Leveraging real-time sentiment recognition, virtual influencers engage in two-way communication with end users. For example, during a live streaming event, they can change their tone based on the audience's emotional state or present specific products in an emotionally resonant way.

[0730] The server collects interaction data with users and provides feedback to users based on the analysis results. This allows for real-time monitoring of campaign effectiveness and enables specific improvement suggestions for future initiatives.

[0731] This system allows companies to effectively communicate their brand in a way that appeals to the emotions of their target audience and create interactive marketing activities.

[0732] The following describes the processing flow.

[0733] Step 1:

[0734] Users access the system using a dedicated terminal and input brand requirements. This includes target audience profiles, desired appearance and personality traits of influencers, and campaign objectives.

[0735] Step 2:

[0736] The server analyzes the received brand requirements and uses an AI model to generate virtual influencers. The generation process establishes characters with specific emotional response patterns, incorporating optimizations based on historical datasets.

[0737] Step 3:

[0738] The server activates the emotion engine and incorporates the emotion recognition capabilities of the virtual influencer. This prepares the influencer to judge the user's emotions from their facial expressions and tone and to interact accordingly.

[0739] Step 4:

[0740] The server automatically generates ad content based on the campaign theme. Here, the emotion engine selects the most effective emotional expression and adjusts the content to appeal to the user's target emotions.

[0741] Step 5:

[0742] The server analyzes the generated content using natural language processing (NLP) techniques to detect inappropriate elements. If any are found, it creates a proposed correction and provides the user with a preview for approval.

[0743] Step 6:

[0744] The user reviews the generated content through their device and gives final approval. Content approved by the user proceeds to the next execution stage.

[0745] Step 7:

[0746] The server delivers approved content to the designated platform in real time, deploying it to the target audience. It utilizes an emotion engine to implement interactions tailored to the recipient's emotions.

[0747] Step 8:

[0748] Users use their devices to observe end-user emotional responses in real time. Virtual influencers use this data to adjust their responses and engage in more personalized communication.

[0749] Step 9:

[0750] The server collects and analyzes interaction data to evaluate the effectiveness of the campaign. Based on the analysis results, it provides users with suggestions for improvement and feedback for future campaigns.

[0751] (Example 2)

[0752] 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".

[0753] In traditional marketing activities using information processing devices, feedback on audience emotions was not reflected in real time, limiting the effectiveness of interactions. Furthermore, the quality and optimization of generated content were insufficient, resulting in low appeal to target audiences. Consequently, companies were unable to effectively communicate their brand image, and the quality of interactions was not guaranteed.

[0754] 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.

[0755] In this invention, the server includes, firstly, means for receiving brand requirements and generating its own information processing device based thereon; secondly, means for automatically generating information based on a specified subject using the generated information processing device; thirdly, means for analyzing the generated information and verifying the presence or absence of inappropriate elements; and fourthly, means for the generated information processing device to analyze the emotional state through voice or visual input and adjust the response in real time accordingly. This makes it possible to provide effective and emotionally appealing interactions to the target audience and effectively convey the brand image.

[0756] A "brand" refers to a name, design, or symbol used to distinguish a particular company or product from others.

[0757] An "information processing device" refers to a device that performs calculations and data transformations based on specified input data and generates the desired output.

[0758] "Generation" refers to the act of creating new digital content or data through specific algorithms or processes.

[0759] "Subject" refers to a specific purpose or focus in content or activities.

[0760] "Information" refers to content composed of knowledge, data, and facts, which possesses meaning and value directed towards a specific recipient.

[0761] "Analysis" refers to the methods and processes used to investigate information and data and to clarify their structure and meaning.

[0762] "Input" refers to the data or commands provided to an information processing device.

[0763] "Response" refers to the reply or action given in response to an input or situation.

[0764] "Audience" refers to the group of people who receive and engage with specific content or information.

[0765] "Interaction" refers to the actions or processes in which two or more parties exchange information with each other.

[0766] This invention is implemented using an information processing system comprised of a server, a terminal, and a user. The server functions as a platform for running advanced AI models by combining languages ​​such as Python and SQL with machine learning frameworks such as TensorFlow and PyTorch. The terminal provides an interface for the user to input data and exchange data bidirectionally with the information processing device. This terminal is typically a personal computer or mobile device and requires a robust internet connection.

[0767] First, the user inputs brand requirements through their device. These requirements include characteristics of the target audience, influencer character settings, and desired emotional responses. The data entered by the user on their device is transmitted to a server via the internet.

[0768] The server analyzes the received data and generates virtual influencers using a generative AI model. The generated influencers possess not only visual appeal and personality traits, but also an emotion recognition engine. This engine utilizes an open-source emotion recognition library and analyzes changes in emotion in real time by analyzing the user's facial expressions and voice input, generating appropriate responses.

[0769] A concrete example would be an influencer targeted at a young user base for a new cosmetics product campaign. This influencer monitors the audience's emotions through live streaming and presents the product more appealingly based on user feedback. An example of a prompt that might be used is, "Present the latest cosmetics in a bright and friendly tone."

[0770] Ultimately, the server delivers the generated content to the designated digital platform, collects audience interaction data, and provides it to the user as analytical feedback. This increases the effectiveness of the campaign and optimizes the marketing strategy based on more data.

[0771] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0772] Step 1:

[0773] Users input brand requirements through their devices. During input, they use a user interface to specify characteristics of the target audience, the character settings of virtual influencers, and expected emotional responses. This data is formatted in JSON and sent to the server via the internet. Specific examples of input include information such as "target audience is teenage girls, and the influencer has a bright and friendly personality."

[0774] Step 2:

[0775] The server analyzes the request specification data received from the terminal. It uses a Python data analysis library to convert the data into the required format and store it in the database. Here, it performs tasks such as detecting outliers and checking the format, preparing the data for model generation. The output is cleaned data ready to be input into the generated AI model.

[0776] Step 3:

[0777] The server generates virtual influencers using a generative AI model. This model, built using TensorFlow, generates the influencer's visual appearance and personality traits based on the received data. Specifically, it incorporates image generation algorithms and personality mapping algorithms. The output is a virtual influencer object represented in digital file format.

[0778] Step 4:

[0779] The server uses an emotion recognition engine to configure the virtual influencer's response patterns. This step utilizes open-source emotion recognition libraries to analyze user facial expressions and voice input in real time and prepare responses. Prompts include instructions such as, "If the viewer is smiling, make the response tone positive." The output is a response sequence that responds to real-time emotional changes.

[0780] Step 5:

[0781] The server automatically generates content by inputting prompt text into a generative AI model based on the specified campaign theme. This process utilizes a text generation algorithm to create messages with human-like and natural language. For example, the prompt text "Speak to the audience with enthusiasm and highlight the unique benefits of the product" is used, and the output is visually and textually refined campaign content.

[0782] Step 6:

[0783] The server analyzes the generated content and detects inappropriate elements. Using natural language processing techniques, it evaluates contextual consistency and social appropriateness, and generates suggested corrections if problems arise. The output is content tailored to the target audience.

[0784] Step 7:

[0785] The user reviews the content generated on the server and gives final approval. Throughout the process, the user evaluates whether the visual presentation and linguistic expression of the content align with the brand image. The output is the approved campaign content.

[0786] Step 8:

[0787] The server delivers approved content to the designated platform. It optimizes content according to the digital marketing channel, enabling real-time interaction between influencers and end-users. The output is the marketing message deployed on the distribution platform.

[0788] (Application Example 2)

[0789] 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".

[0790] Traditional marketing activities struggle to respond flexibly to consumer emotions, making it difficult to enhance the effectiveness of interactive advertising. Furthermore, there are limited means of obtaining real-time feedback from target audiences, hindering the immediate improvement of advertising strategies.

[0791] 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.

[0792] In this invention, the server includes means for receiving brand requirements and generating original virtual influencers based thereon, means for recognizing the user's emotions based on visual and auditory input, and means for dynamically adjusting the virtual influencer's responses according to the user's emotions. This enables effective interaction based on the emotions of the target audience and immediate improvement of advertising strategies through real-time feedback.

[0793] A "requirements specification" is a document that describes in detail the requirements and conditions necessary to achieve a specific target outcome.

[0794] A "virtual influencer" is a digital entity created using artificial intelligence technology that has the same influence as a human being in marketing activities.

[0795] "Audiovisual information" refers to digital information that can be perceived through sight and hearing, and is an important element in advertising and promotion.

[0796] "Target audience" refers to the market or group of consumers that are targeted by a particular marketing activity or advertisement.

[0797] "Two-way communication data" refers to information about interactions between the user and the system, and is used to measure the effectiveness of real-time interactions.

[0798] "Brand impression" is a concept that relates to the image and reputation of a company or product as perceived by consumers and society.

[0799] A "promotional theme" refers to the central idea or message in a particular advertisement or marketing campaign.

[0800] "Real-time interaction" is a technology that enables instant communication with users and can instantly adjust responses based on emotions.

[0801] The system for implementing this invention enables efficient and flexible marketing activities through the cooperation of servers, terminals, and users.

[0802] First, the terminal receives brand requirements from the user, which include the emotional characteristics of the target audience and the character settings of the virtual influencer. This information becomes the foundational data within the system and is sent to the server.

[0803] The server generates virtual influencers using artificial intelligence technology based on the received request specifications. Furthermore, it analyzes the user's emotions in real time using an emotion recognition engine such as EmotionRecognitionEngine, based on visual and auditory input data. Based on these results, the influencer's response is dynamically adjusted using a generative AI model (e.g., GPT-4).

[0804] The generated audiovisual information is automatically created for each promotional theme and verified by a server. Content with inappropriate elements removed is delivered to the target audience in real time, during which a virtual influencer interacts with the audience in real time. This allows consumers to receive promotional information tailored to their own emotions.

[0805] The server can also collect two-way communication data between users and virtual influencers, and by continuously monitoring its effectiveness, it can suggest improvements for future advertising strategies. This contributes to the continuous optimization of advertisements and campaigns.

[0806] As a concrete example, in the announcement of a new car model, if a user shows interest in a particular part while watching a test drive video, a virtual influencer may provide more detailed information or a special offer related to that part. An example of a prompt might be: "Generate a jacket description for when the user shows positive emotions. The response should be in a friendly tone and include humor."

[0807] By using this system, companies can communicate more effectively with their target audience and improve the effectiveness of their advertising through real-time feedback.

[0808] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0809] Step 1:

[0810] The user inputs the brand's requirements into a terminal. Specifically, they input specifications, including the emotional characteristics of the target audience and the character settings of the virtual influencer, through an input interface provided on the terminal. The input data is sent to the server as an initial dataset.

[0811] Step 2:

[0812] The server generates virtual influencers based on the received requirements specifications. In this process, a generation AI model is used to create virtual influencers with appearances and personalities that conform to the specifications. Furthermore, emotional response patterns are also configured. The input is the requirements specifications, and the output is a prototype of the virtual influencer.

[0813] Step 3:

[0814] The server uses visual and auditory data to recognize the user's emotions. At this stage, the EmotionRecognitionEngine is used to analyze the emotional state based on the user's real-time facial expressions and vocal characteristics, which are the input data. The output is the result of the emotional state determination.

[0815] Step 4:

[0816] The server dynamically adjusts the virtual influencer's response based on the emotion recognition results. A generative AI model is used to generate prompt messages appropriate to the emotion. Specifically, it creates a message in a tone that matches the detected emotion. The output is the adjusted response message for the user.

[0817] Step 5:

[0818] The server automatically generates audiovisual information based on the promotional theme. This includes designing and structuring the content to match the promotional strategy. The output content is verified for inappropriate elements and is ready for use after safety checks.

[0819] Step 6:

[0820] The server delivers verified audiovisual information to the target audience in real time. It optimizes the format for the distribution channel and configures it for interactive presentations by virtual influencers. The output is the delivered content.

[0821] Step 7:

[0822] The server collects two-way communication data with users and monitors its effectiveness along with emotional response data. This provides foundational data for suggesting improvements to future advertising strategies. Specifically, it generates user engagement analysis reports.

[0823] 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.

[0824] 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.

[0825] 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.

[0826] 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.

[0827] 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.

[0828] 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.

[0829] 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.

[0830] 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.

[0831] 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."

[0832] 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.

[0833] 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.

[0834] 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.

[0835] 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.

[0836] 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.

[0837] 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.

[0838] 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.

[0839] 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.

[0840] 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.

[0841] 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.

[0842] 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.

[0843] 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.

[0844] The following is further disclosed regarding the embodiments described above.

[0845] (Claim 1)

[0846] A first method of receiving brand requirements and generating original virtual influencers based on them,

[0847] A second method involves using generated virtual influencers to automatically generate content based on a specified campaign theme,

[0848] A third method involves analyzing the generated content to verify that it does not contain inappropriate elements,

[0849] A fourth method for delivering verified content to a target audience in real time,

[0850] A fifth method involves monitoring the effectiveness of campaigns based on collected interaction data and making improvement suggestions.

[0851] A system that includes this.

[0852] (Claim 2)

[0853] The system according to claim 1, comprising a sixth means for realizing real-time communication between a virtual influencer and an end user.

[0854] (Claim 3)

[0855] The system according to claim 1, further comprising a seventh means for modeling influencer behavior that is adjusted so as not to damage the brand image, using the collected data.

[0856] "Example 1"

[0857] (Claim 1)

[0858] A means of receiving brand information and building an appropriate digital character based on it,

[0859] A means of automatically creating digital content in line with the campaign theme using generated digital characters,

[0860] A means of analyzing the created digital content and inspecting elements that do not conform to the standards,

[0861] A means of quickly disseminating digital content that has passed inspection to designated information media,

[0862] A means of evaluating the effectiveness of advertising activities using acquired user data and providing suggestions for efficiency improvements,

[0863] A system that includes this.

[0864] (Claim 2)

[0865] The system according to claim 1, comprising means that enable a digital character and a consumer to communicate instantly.

[0866] (Claim 3)

[0867] The system according to claim 1, comprising means for using acquired data to design digital character movements that are adjusted so as not to damage brand reputation.

[0868] "Application Example 1"

[0869] (Claim 1)

[0870] A first method of receiving brand requirements and generating original virtual influencers based on them,

[0871] A second method involves using generated virtual influencers to automatically generate content based on a specified campaign theme,

[0872] A third method involves analyzing the generated content to verify that it does not contain inappropriate elements,

[0873] A fourth method for delivering verified content to a target audience in real time,

[0874] A fifth method involves monitoring the effectiveness of campaigns based on collected interaction data and making improvement suggestions.

[0875] A sixth method of providing advertising information by virtual influencers based on users' interests,

[0876] A system that includes this.

[0877] (Claim 2)

[0878] The system according to claim 1, comprising a seventh means for real-time communication between a virtual influencer and an end user.

[0879] (Claim 3)

[0880] The system according to claim 1, further comprising an eighth means for using collected data to model influencer behavior that is adjusted so as not to damage the brand image.

[0881] "Example 2 of combining an emotion engine"

[0882] (Claim 1)

[0883] A first means for receiving brand requirements specifications and generating a proprietary information processing device based thereon,

[0884] A second means for automatically generating information based on a specified subject using the generated information processing device,

[0885] A third method involves analyzing the generated information and verifying the presence or absence of inappropriate elements.

[0886] A fourth method for providing verified information to the target population in real time,

[0887] A fifth method involves monitoring the effectiveness of activities and making improvement suggestions based on the collected interaction information,

[0888] A sixth method for generating responses based on emotional characteristics using a conceptual model,

[0889] A system that includes this.

[0890] (Claim 2)

[0891] The system according to claim 1, wherein the generated information processing device includes means for analyzing an emotional state through voice or visual input and adjusting the response in real time accordingly.

[0892] (Claim 3)

[0893] The system according to claim 1, wherein the generated information has a structure that facilitates bidirectional communication between a human and an information processing device.

[0894] "Application example 2 when combining with an emotional engine"

[0895] (Claim 1)

[0896] A means of receiving brand requirements and generating original virtual influencers based on them,

[0897] A means for automatically generating audiovisual information based on a specified promotional theme, utilizing generated virtual influencers,

[0898] A means of analyzing the generated audiovisual information and verifying whether it contains inappropriate elements,

[0899] A means of delivering verified audiovisual information to the target audience in real time,

[0900] A means of recognizing the user's emotions based on visual and auditory input,

[0901] A means of dynamically adjusting the response of a virtual influencer according to the user's emotions,

[0902] A means of monitoring the effectiveness of advertising based on collected two-way communication data and suggesting improvements,

[0903] A system that includes this.

[0904] (Claim 2)

[0905] The system according to claim 1, comprising means for real-time interaction between a virtual influencer and a user.

[0906] (Claim 3)

[0907] The system according to claim 1, comprising means for modeling influencer behavior that is adjusted so as not to damage brand image, using collected information. [Explanation of Symbols]

[0908] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A first method for receiving brand requirements and generating original virtual influencers based on them, A second method involves using generated virtual influencers to automatically generate content based on a specified campaign theme, A third method involves analyzing the generated content to verify that it does not contain inappropriate elements, A fourth method for delivering verified content to the target audience in real time, A fifth method involves monitoring the effectiveness of the campaign based on the collected interaction data and making improvement suggestions. A system that includes this.

2. The system according to claim 1, comprising a sixth means for realizing real-time communication between a virtual influencer and an end user.

3. The system according to claim 1, further comprising a seventh means for modeling influencer behavior that is adjusted so as not to damage the brand image, using the collected data.

Images