System

Abstract

A system is provided.SOLUTION: A system comprising: uploading means for uploading digital content including old information; analyzing means for inputting the digital content into a generative artificial intelligence model and analyzing the content; information acquiring means for identifying the old information based on an analysis result of the digital content and acquiring latest information; replacing means for replacing the old information using the acquired latest information; generating means for generating new digital content based on the information updated by the replacing means; and storing and providing means for storing the generated new digital content and providing it to a user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Conventional digital content and brand videos require manual editing when information needs to be updated, requiring outsourcing costs and in-house resources. This not only increases costs and workload, but also delays information updates, making it difficult to provide customers with the latest information promptly. The objective of this invention is to solve these problems by providing a system that automatically replaces outdated information with the latest information, always providing the latest digital content. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system including an uploading means for uploading digital content including old information, an analyzing means for inputting the digital content into a generative artificial intelligence model and analyzing the content, an information acquiring means for identifying old information based on the analysis results of the digital content and acquiring the latest information, a replacing means for replacing the old information with the acquired latest information, a generating means for generating new digital content based on the information updated by the replacing means, and a storing and providing means for storing the generated new digital content and providing it to users. This system allows old information to be quickly and automatically updated with the latest information, reducing outsourcing costs and workload and enabling customers to always be provided with the latest information.

[0006] "Outdated information" refers to outdated information contained within digital content that needs to be updated compared to current information.

[0007] "Digital content" is a general term for information recorded electronically in the form of video, audio, text, etc.

[0008] "Uploading means" refers to a function that allows a user to transfer digital content to an online storage such as a server.

[0009] A "generative artificial intelligence model" refers to a technical method that automatically analyzes digital content and replaces it with the latest information.

[0010] "Analysis means" refers to a function for analyzing the content of digital content and identifying outdated information contained therein.

[0011] "Information acquisition means" refers to the function for acquiring the latest information from databases and external information sources.

[0012] "Replacement means" refers to a function for replacing old analyzed information with the latest information.

[0013] "Generation means" refers to the function for generating new digital content including the latest information.

[0014] "Storage and provision means" refers to the functionality for storing the newly generated digital content and making it accessible to users. [Brief explanation of the drawings]

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

[0016] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

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

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

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

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

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

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

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

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

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0032] 2, in the data processing device 12, a specific process 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" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process 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.

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

[0034] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

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

[0036] System Overview

[0037] The present invention relates to a system that automatically updates digital content containing outdated information to the latest information and generates new digital content. The system includes an uploading unit, an analyzing unit, an information acquiring unit, a replacing unit, a generating unit, and a storing and providing unit. The operation of each unit is described below.

[0038] How it works

[0039] Upload method

[0040] User Input

[0041] Users upload digital content, including old information, from their devices (PCs, tablets, smartphones, etc.) by clicking an upload button using a web interface or a dedicated application.

[0042] Analysis means

[0043] Server Operations

[0044] The server inputs the uploaded digital content into a generative AI model to analyze the content. The analysis method analyzes the video content frame by frame, converts audio and subtitle data into text, and extracts specific outdated information.

[0045] Information acquisition means

[0046] Server Operations

[0047] The server retrieves the latest information from an internal database or an external source, thereby obtaining the latest data corresponding to the outdated information identified by the analysis means.

[0048] replacement means

[0049] Server Operations

[0050] The analyzed information is replaced with the latest information. This applies not only to text data, but also to audio data and visual elements.

[0051] generation means

[0052] Server Operations

[0053] New digital content is generated based on the data replaced with the latest information. Specifically, using synthetic voice and video editing tools, old information is updated with the latest information in a natural way to create videos.

[0054] Storage and provision means

[0055] Server Operations

[0056] The newly generated digital content is transferred to a database for long-term storage and made accessible to users. The server generates a download link for the new content and notifies the user.

[0057] Specific examples

[0058] As a concrete example, consider a company's product introduction video. For example, if a product introduction video shows that the "latest model ABC" is currently priced at $1,000, then one year from now, that information will change to the "new model ABC" with a price of $1,200.

[0059] 1. User Input

[0060] The user uses the terminal to upload the old "Introduction video for the latest model ABC" to the server via the web interface.

[0061] 2. Server Operation - Analysis

[0062] The server inputs the uploaded video file into the generative AI model and identifies the "latest model ABC" and "current price $1,000."

[0063] 3. Server Operation - Getting the Latest Information

[0064] Retrieve information about "New Model ABC" and "New Price $1200" from the database.

[0065] 4. Server Operations - Information Replacement

[0066] Using a generative AI model, "Latest Model ABC" is replaced with "New Model ABC" and "Current Price $1,000" is replaced with "New Price $1,200."

[0067] 5. Server Operation - Creating a New Video

[0068] Generate a new introductory video based on new information.

[0069] 6. Server Operation - Storage and Serving

[0070] The new introductory video is saved in the database, a new download link is generated and notified to the user.

[0071] This allows users to quickly obtain digital content that always reflects the latest information without any hassle.

[0072] The processing flow will be explained below.

[0073] Step 1:

[0074] User operations

[0075] Users select the old brand video file from their device and click the upload button using the web interface or a dedicated application, which sends the video file to the server.

[0076] Step 2:

[0077] Server Operations

[0078] The server receives the video file sent by the user and saves it in a temporary directory in the file system, while recording the video file path and metadata in a database.

[0079] Step 3:

[0080] Server Operations

[0081] The server passes the video file to a generative AI model and activates an analytical method. The generative AI model analyzes the video content frame by frame, converts audio to text, and extracts subtitle data, thereby identifying outdated information in the video.

[0082] Step 4:

[0083] Server Operations

[0084] The server accesses a database or external information source to retrieve up-to-date information that corresponds to outdated information identified by the analytical means, and retrieves up-to-date product and pricing information using database queries or API requests.

[0085] Step 5:

[0086] Server Operations

[0087] The server then uses the latest information to replace the old analyzed information. This includes not only text data, but also audio data and visual elements. The replacement process is automated, using voice synthesis and video editing techniques.

[0088] Step 6:

[0089] Server Operations

[0090] The server generates new digital content based on the data replaced with the latest information. The generation means integrates preprocessed text, audio data, and visual elements into a single video file.

[0091] Step 7:

[0092] Server Operations

[0093] The newly generated digital content is moved to a long-term storage directory, the database metadata is updated, and a download link is generated and provided to users to notify them.

[0094] Step 8:

[0095] User operations

[0096] The user clicks the link provided on the device to download the new digital content from the server. The downloaded video contains the latest updated information, so it can be provided to customers immediately.

[0097] Example 1

[0098] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0099] Digital content often becomes outdated after it is created, which can lead to misunderstandings among viewers. For example, price and model information in product introduction videos changes very quickly. However, manually updating this information is time-consuming, costly, and inefficient. Therefore, there is a need to provide a method for automatically updating outdated information and generating new digital content.

[0100] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0101] In this invention, the server includes uploading means for uploading digital content including old information from a device used by a user, analysis means for inputting the digital content into a generative AI model to analyze the content and extract specific old information, information acquisition means for acquiring latest information corresponding to the old information based on the analysis results, replacement means for replacing the old information with the acquired latest information, generation means for generating new digital content based on the information replaced by the replacement means, and storage and provision means for saving the generated new digital content and making it accessible to users. This makes it possible to automatically update old information included in digital content with the latest information.

[0102] The "uploading means" is a means by which a user uses a terminal to send digital content including old information to a server.

[0103] "Analysis means" means a means for analyzing uploaded digital content using a generative AI model to extract certain outdated information.

[0104] The "information acquisition means" is a means for acquiring the latest information from an internal database or an external information source based on the old information identified by the analysis means.

[0105] The "replacement means" is a means for updating the old information identified by the analysis means using the latest information obtained by the acquisition means.

[0106] The "generating means" is a means for generating new digital content based on the data replaced with the latest information by the replacing means.

[0107] The "storage and provision means" is a means for storing new digital content generated by the generation means in a database for long-term storage and making it accessible to users.

[0108] System Overview

[0109] The present invention provides a system for automatically updating digital content containing outdated information with the latest information and generating new digital content. The system includes an uploading unit, an analyzing unit, an information acquiring unit, a replacing unit, a generating unit, and a storing and providing unit. The following description describes the specific operation of each unit.

[0110] Upload method

[0111] Users upload digital content, including old information, using a web browser or dedicated application on their device (e.g., personal computer, tablet, or smartphone). The user clicks the upload button on the web interface or application to send the selected file to the server. For example, this is the operation of uploading a company's product introduction video.

[0112] Analysis means

[0113] The server receives the uploaded digital content and stores it in a temporary storage area. The server then analyzes the content using a generative AI model. The generative AI model analyzes the video frame by frame and converts the audio data into text. From the analysis results, "old information" is extracted. For example, information such as "latest model ABC" and "price $1,000" is extracted.

[0114] Information acquisition means

[0115] The server retrieves the latest information from an internal database or an external source (e.g., API) based on the old information extracted from the analysis. It uses a database query or API request to get the latest information, such as "New Model ABC" and "Price: $1200."

[0116] replacement means

[0117] The server replaces the outdated information identified by the analytical means with the latest information retrieved. This includes not only text data, but also audio data and visual elements. For example, "latest model ABC" could be replaced with "new model ABC" and "price $1,000" could be replaced with "price $1,200."

[0118] generation means

[0119] The server generates new digital content based on the new information, using synthetic speech technology and video editing tools to generate a naturally updated video, resulting in a new introductory video in which the old information is replaced with the latest information.

[0120] Storage and provision means

[0121] The server stores the new digital content in a database for long-term storage, and then generates and notifies the user of the new content with a link to access it, for example, via an email notification.

[0122] Specific examples

[0123] As a concrete example, consider a company's product introduction video. For example, a video introducing the latest model ABC at a price of $1,000 is uploaded one year later. In this example, the video is updated to include the latest information, "New Model ABC" and "Price: $1,200."

[0124] Example of input prompt for generative AI model

[0125] Here are some examples of prompts to input to a generative AI model:

[0126] Please analyze your old introduction video and update it with the latest model name and price information based on the information below:

[0127] New model name: New model ABC

[0128] New price: $1,200

[0129] This prompt ensures that the generative AI model generates digital content that is updated with the latest information.

[0130] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0131] Step 1:

[0132] Users upload content

[0133] The user uses a terminal to upload digital content including old information. The user clicks the upload button in the web interface or dedicated application to send the selected file to the server. The input is the digital content file specified by the user (e.g., "Old Product Introduction Video.mp4"), and the output is the file uploaded to the server.

[0134] Step 2:

[0135] The server analyzes the digital content

[0136] The server receives the uploaded digital content and stores it in a temporary storage area. The server inputs the video file into a generative AI model, which analyzes the content frame by frame. It converts the audio data into text and extracts old information from the analysis results. The input is the uploaded digital content file, and the output is the analyzed text data (e.g., "Latest Model ABC" and "Price: $1,000").

[0137] Step 3:

[0138] The server retrieves the latest information

[0139] Based on the analysis results, the server sends a query to obtain the latest information from an internal database or an external information source. The input is the analyzed text data, and the output is the obtained latest information data (e.g., "New model ABC" and "New price $1,200"). This is done using a database query or an API request.

[0140] Step 4:

[0141] The server replaces the old information with the latest information.

[0142] The server uses the acquired latest information to replace the old information identified by the analysis means. This includes text data, audio data, and visual elements. The input is the acquired latest information data and analyzed text data, and the output is the data replaced with the new information (e.g., updated text to "New Model ABC" and "New Price $1,200"). Specifically, the replacement operation is performed using a generative AI model.

[0143] Step 5:

[0144] The server generates new digital content.

[0145] The server generates new digital content based on the replaced information. Using synthetic voice technology and video editing tools, it generates a new introductory video and saves it in a temporary storage area. The input is the data replaced with the new information, and the output is the generated new digital content (e.g., a new video introducing "New Model ABC").

[0146] Step 6:

[0147] Servers store and serve new digital content

[0148] The server stores the generated new digital content in a database for long-term storage. It then generates a download link and notifies the user to make it accessible to the user. The input is the generated new digital content, and the output is the stored content and a notification message to the user (e.g., sending a link via email notification).

[0149] (Application example 1)

[0150] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0151] In the food service industry, menu information, prices, campaign information, and other information change frequently, making it important to keep this information up to date. However, traditional methods often require these updates to be done manually, which not only takes time and effort but also carries the risk of providing customers with incorrect information. To solve this problem, an automatic system for updating menu and price information is needed.

[0152] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0153] In this invention, the server includes an uploading means for uploading digital content including old information, an analyzing means for inputting the digital content into a generative AI model and analyzing the content, an information acquiring means for identifying old information based on the analysis results of the digital content and acquiring the latest information, a replacing means for replacing the old information with the acquired latest information, a generating means for generating new digital content based on the information updated by the replacing means, a storing and providing means for storing the generated new digital content and providing it to users, and a function for always keeping menu information and prices in food service up to date, thereby enabling the food service industry to always provide the latest information quickly and accurately.

[0154] "Uploading means" refers to the function by which a user sends digital content, including old information, to a server.

[0155] "Analysis means" refers to the function of using a generative AI model to analyze uploaded digital content and understand its contents.

[0156] "Information acquisition means" refers to the function of acquiring the latest information from external or internal information sources based on the analysis results.

[0157] The "replacement means" refers to a function that uses the acquired latest information to replace old information in the digital content with new information.

[0158] "Generation means" refers to the function of creating new digital content based on updated information.

[0159] "Storage and provision means" refers to the function of storing the newly generated digital content and providing it to users.

[0160] "Food service" refers to the general industry that provides food and beverages, including restaurants and food delivery services.

[0161] The present invention relates to a system for automatically keeping menu and pricing information up to date in the food service industry. The system includes the following major components:

[0162] Upload method

[0163] Users use their devices to upload digital content (e.g., menu images) containing outdated information to the server. This operation is performed through a dedicated application or a web interface.

[0164] Analysis means

[0165] The server then feeds the uploaded digital content into a generative AI model to analyze its contents. This involves using optical character recognition (OCR) technology to extract text from images and identify outdated information. For this purpose, the pytesseract and opencv libraries are used.

[0166] Information acquisition means

[0167] The server retrieves the latest menu information and prices from external or internal sources, typically by using the requests library to retrieve data from a remote API.

[0168] replacement means

[0169] The server uses the retrieved updated information to replace the old information identified by the analysis means with new information. This process is performed by text replacement, and the new menu information and prices are reflected in the digital content.

[0170] generation means

[0171] The server generates new digital content based on the updated information, and uses the OpenCV library to draw new text information on the image and generate a new menu image.

[0172] Storage and provision means

[0173] The server stores the newly generated digital content in a database and makes it accessible to users, so a download link for the new digital content is generated and notified to the user.

[0174] Main hardware and software used

[0175] Hardware: PC or Server

[0176] Software: Python, pytesseract, opencv, requests

[0177] Specific examples

[0178] For example, consider a restaurant that updates its weekly lunch menu. Users can upload an image of the old menu, and the system automatically updates it to reflect the new lunch menu. The old information in the uploaded image, "Curry rice 800 yen," is replaced with the new information, "Beef curry 900 yen."

[0179] Example prompts for generative AI models

[0180] Analyze the old lunch menu in the image below and update it with the new information: menu name, price, and description. For example, if the old menu item was "Curry rice 800 yen," change it to "Beef curry 900 yen."

[0181] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0182] Step 1: Upload your old digital content

[0183] A user uses a terminal to upload digital content (e.g., menu images) containing old menu information for a food service to a server. This operation is performed through a dedicated application or a web interface, and the content file is sent to the server. The input is the old menu image selected by the user, and the output is the uploaded image file.

[0184] Step 2: Analyzing the digital content

[0185] The server inputs the uploaded digital content into a generative AI model to analyze its contents. The server first uses the pytesseract library to extract text from images using optical character recognition (OCR) technology, and then identifies outdated menu information from the extracted text. The input is the uploaded image file, and the output is the extracted text data.

[0186] Step 3: Stay up to date

[0187] Based on the analysis results, the server retrieves the latest menu information and prices from external or internal sources. During this process, it uses the requests library to retrieve the necessary data from a remote API. The input is the parsed text data, and the output is the retrieved latest menu information.

[0188] Step 4: Replace old information

[0189] The server uses the acquired latest information to replace the old information identified by the analysis means with new information. This process is performed by text replacement. Specifically, the extracted old menu information is replaced with new menu information. The input is text data containing the old information and the latest information, and the output is text data containing the new menu information.

[0190] Step 5: Generate new digital content

[0191] The server generates new digital content based on the updated information. Using the OpenCV library, it draws the new text information on the image and generates a new menu image. The input is text data containing the new menu information, and the output is the new menu image.

[0192] Step 6: Store and serve

[0193] The server saves the generated new digital content in a database and makes it accessible to users. A download link for the new digital content is generated and notified to the user. The input is a new menu image, and the output is the image file saved in the database and notification information.

[0194] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0195] System Overview

[0196] The present invention combines a system that automatically updates digital content containing outdated information with the latest information and generates new digital content, with an emotion engine that recognizes user emotions. This system includes an uploading means, an analyzing means, an information acquisition means, a replacement means, a generating means, a storage and provision means, and an emotion engine. The operation of each means will be described below.

[0197] How it works

[0198] Upload method

[0199] User operations

[0200] Users upload old digital content from their devices (PCs, tablets, smartphones, etc.) by clicking an upload button using a web interface or a dedicated application.

[0201] Analysis means

[0202] Server Operations

[0203] The server inputs the uploaded digital content into a generative AI model to analyze the content. The analysis method analyzes the video content frame by frame, converts audio and subtitle data into text, and extracts specific outdated information.

[0204] Information acquisition means

[0205] Server Operations

[0206] The server retrieves the latest information from an internal database or an external source, and retrieves the latest data corresponding to the outdated information identified by the analysis means.

[0207] replacement means

[0208] Server Operations

[0209] The analyzed information is replaced with the latest information. This applies not only to text data, but also to audio data and visual elements.

[0210] generation means

[0211] Server Operations

[0212] New digital content is generated based on the data replaced with the latest information. The generation method uses synthesized voice and video editing tools to generate videos that naturally update old information with the latest information.

[0213] Storage and provision means

[0214] Server Operations

[0215] The newly generated digital content is transferred to a database for long-term storage and made accessible to users. The server generates a download link for the new content and notifies the user.

[0216] Emotion Engine

[0217] Server Operations

[0218] The server activates an emotion engine that recognizes emotions from the user's facial expressions, tone of voice, language, etc. The emotion engine analyzes emotions while the user is viewing digital content and customizes the content in real time.

[0219] Specific examples

[0220] For example, consider a company's product introduction video. If a product introduction video shows that the "latest model ABC" is currently priced at $1,000, then one year from now, that information will change to the "new model ABC" with a price of $1,200. In this case, the process will be as follows:

[0221] 1. User Input

[0222] The user uses the terminal to upload the old "Introduction video for the latest model ABC" to the server via the web interface.

[0223] 2. Server Operation - Analysis

[0224] The server inputs the uploaded video file into the generative AI model and identifies the "latest model ABC" and "current price $1,000."

[0225] 3. Server Operation - Getting the Latest Information

[0226] Retrieve information about "New Model ABC" and "New Price $1200" from the database.

[0227] 4. Server Operations - Information Replacement

[0228] Using a generative AI model, "Latest Model ABC" is replaced with "New Model ABC" and "Current Price $1,000" is replaced with "New Price $1,200."

[0229] 5. Server Operation - Creating a New Video

[0230] Generate a new introductory video based on new information.

[0231] 6. Server Operation - Storage and Serving

[0232] The new introductory video is saved in the database, a new download link is generated and notified to the user.

[0233] 7. Manipulating the Emotion Engine

[0234] As users watch new videos, the emotion engine analyzes their emotions and customizes the content in real time.

[0235] This allows users to quickly obtain digital content that always reflects the latest information without any hassle, and provides an optimal viewing experience that suits each individual's emotions.

[0236] The processing flow will be explained below.

[0237] Step 1:

[0238] User operations

[0239] Users select the old brand video file from their device and click the upload button using the web interface or a dedicated application, which sends the video file to the server.

[0240] Step 2:

[0241] Server Operations

[0242] The server receives the video file sent by the user and saves it in a temporary directory in the file system, while recording the video file path and metadata in a database.

[0243] Step 3:

[0244] Server Operations

[0245] The server passes the video file to a generative AI model and activates an analytical method. The generative AI model analyzes the video content frame by frame, converts audio to text, and extracts subtitle data, thereby identifying outdated information in the video.

[0246] Step 4:

[0247] Server Operations

[0248] The server accesses a database or external information source to retrieve up-to-date information that corresponds to outdated information identified by the analytical means, and retrieves up-to-date product and pricing information using database queries or API requests.

[0249] Step 5:

[0250] Server Operations

[0251] The server then uses the latest information to replace the old analyzed information. This includes not only text data, but also audio data and visual elements. The replacement process is automated, using voice synthesis and video editing techniques.

[0252] Step 6:

[0253] Server Operations

[0254] The server generates new digital content based on the data replaced with the latest information. The generation means integrates preprocessed text, audio data, and visual elements into a single video file.

[0255] Step 7:

[0256] Server Operations

[0257] The newly generated digital content is moved to a long-term storage directory, the database metadata is updated, and a download link is generated and provided to users to notify them.

[0258] Step 8:

[0259] User operations

[0260] The user clicks the link provided on the device to download the new digital content from the server. The downloaded video contains the latest updated information, so it can be provided to customers immediately.

[0261] Step 9:

[0262] Server Operations

[0263] The server activates an emotion engine to recognize emotions from the user's facial expressions, tone of voice, language, etc. While the user is viewing digital content, the emotion engine analyzes the user's emotions in real time.

[0264] Step 10:

[0265] Server Operations

[0266] The server changes the presentation order and content of digital content in real time based on the user's emotions recognized by the emotion engine, providing a viewing experience optimized for each user's emotional state.

[0267] Example 2

[0268] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0269] Modern digital content faces the challenge of becoming outdated quickly and requiring a great deal of time and effort to update. It is also difficult to customize digital content in real time to reflect the emotions and interests of each user. This leads to a homogenous user experience that fails to address individual needs.

[0270] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0271] In this invention, the server includes an uploading means for uploading digital content including old information, an analyzing means for inputting the digital content into a generative AI model and analyzing the content, an information acquiring means for identifying old information based on the analysis results of the digital content and acquiring the latest information, a replacing means for replacing the old information with the acquired latest information, a generating means for generating new digital content based on the information updated by the replacing means, a storing and providing means for storing the generated new digital content and providing it to the user, and an emotion engine for recognizing the user's emotions and customizing the digital content in real time, thereby enabling rapid updating of digital content and an optimized viewing experience for each user.

[0272] An "uploading mechanism" is a mechanism by which a user transfers digital content, including old information, to the system.

[0273] "Analysis means" refers to the means for inputting uploaded digital content into a generative AI model and analyzing its contents to identify outdated information.

[0274] The "information acquisition means" is a means for acquiring the latest information corresponding to the old information identified by the analysis means from an internal database or an external information source.

[0275] The "replacement means" is a means for replacing old information with new information using the acquired latest information.

[0276] The "generation means" is a means for generating new digital content based on data replaced with the latest information.

[0277] The "storage and provision means" refers to a means for storing the newly generated digital content and providing it in a form accessible to users.

[0278] An "emotion engine" is a means of analyzing a user's facial expressions, tone of voice, and language, and customizing digital content in real time according to the user's emotions.

[0279] A "generative AI model" is an artificial intelligence model used to analyze uploaded digital content and identify and replace outdated information.

[0280] To implement this invention, a system involving three main elements is used: a server, a terminal, and a user. This system automatically updates digital content, including old information, with the latest information, generates new digital content, and also incorporates an emotion engine that recognizes the user's emotions. Each means of this system is described in detail below.

[0281] Upload method

[0282] Users upload old digital content using a device (PC, tablet, smartphone, etc.). Specifically, users operate a web interface or dedicated application, click the upload button, and select the desired digital content file. This transfers the digital content to the server.

[0283] Analysis means

[0284] The server inputs the uploaded digital content into a generative AI model and analyzes its contents. During this process, the analysis means analyzes each frame of the video and converts the audio and subtitle data into text. From the analyzed text data, outdated information is identified. The generative AI model uses natural language processing and machine learning techniques.

[0285] Information acquisition means

[0286] The server retrieves the latest information from an internal database or an external source (such as an API). It searches for and retrieves the latest data corresponding to outdated information identified by the analysis method. For example, if a specific product name or price is outdated, it retrieves the corresponding latest product name and price information from the database.

[0287] replacement means

[0288] The server then uses the latest information to replace the old information it has analyzed. This replacement process involves not only text data, but also audio and visual elements. For example, the old product name is replaced with the new product name, and audio data is also replaced with the new information using synthesized speech technology.

[0289] generation means

[0290] The server generates new digital content based on the data replaced with the latest information. This generation method uses video editing tools (e.g., FFmpeg) and synthetic voice technology to create new, natural-looking, and consistent digital content.

[0291] Storage and provision means

[0292] The server then transfers the newly generated digital content to a long-term storage database, makes it accessible to users, generates a download link for the new digital content, and notifies the user via email or in-app notification.

[0293] Emotion Engine

[0294] While the user is viewing new digital content, the server activates an emotion engine that analyzes the user's facial expressions, tone of voice, and language data. This emotion engine analyzes the user's emotions in real time and customizes the digital content accordingly. For example, it adapts by displaying detailed information related to parts that the user is interested in and reducing the amount of information in parts that the user is not interested in.

[0295] Specific examples

[0296] For example, if a company has a product introduction video that includes the product name "old model XYZ" and the price "$100," the following steps would be taken:

[0297] 1. The user uses a terminal to upload an old product introduction video to the server via a web interface.

[0298] 2. The server inputs the video file into the generative AI model and identifies "old model XYZ" and "$100."

[0299] 3. Retrieve the new product name "New Model XYZ" and new price "$120" from the internal database.

[0300] 4. Use a generative AI model to replace "Old Model XYZ" with "New Model XYZ" and "$100" with "$120."

[0301] 5. Generate new digital content using video editing tools.

[0302] 6. Save the new video to the database, generate a download link and notify the user.

[0303] 7. As users watch new videos, the emotion engine analyzes their emotions and customizes their viewing experience in real time.

[0304] Prompt Sentence Examples

[0305] "Program the system to update the content of the video and customize it based on the user's emotions. For example, replace the old model name in a product introduction video with the new model name, and adjust the content in real time based on the user's emotions while watching."

[0306] This allows users to quickly obtain digital content that always reflects the latest information, and to have the optimal viewing experience that suits their individual emotions.

[0307] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0308] Step 1: Upload

[0309] Specific operation: Users use a device (PC, tablet, smartphone, etc.) to upload old digital content via a web interface or dedicated application.

[0310] Input: Digital content file (e.g. product introduction video)

[0311] Output: Digital content files uploaded to the server

[0312] Step 2: Analysis

[0313] How it works: The server feeds uploaded digital content into a generative AI model that analyzes its content, parsing each frame of video, converting audio and subtitle data into text, and identifying outdated information.

[0314] Input: Uploaded digital content file

[0315] Output: Text data containing outdated information (e.g., "Old Model XYZ", "$100")

[0316] Step 3: Information Acquisition

[0317] Specific operation: The server retrieves the latest information from an internal database or external information source (e.g., API). It searches for and retrieves the latest data corresponding to the old information identified by the analysis method.

[0318] Input: Text data containing outdated information (e.g., "Old Model XYZ," "$100")

[0319] Output: Data containing the latest information (e.g., "New Model XYZ," "$120")

[0320] Step 4: Substitution

[0321] What it does: The server replaces the old parsed information with the latest information it has retrieved. This replacement process involves not only replacing text data, but also synthesizing audio data and changing visual elements.

[0322] Input: Text data containing old information, data containing the latest information

[0323] Output: Data replaced with the latest information

[0324] Step 5: Generate

[0325] Specific operation: The server generates new digital content based on the data replaced with the latest information. The generation method uses video editing tools (e.g., FFmpeg) and synthetic voice technology to create new, natural, and consistent digital content.

[0326] Input: Data replaced with the latest information

[0327] Output: The new digital content file generated

[0328] Step 6: Store and serve

[0329] Specific operations: The server migrates the generated new digital content to a database for long-term storage and makes it accessible to users. It also generates a download link for the new digital content and notifies the user.

[0330] Input: The new digital content file that was generated

[0331] Output: Content stored in database and download link notification to user

[0332] Step 7: Launching the Emotion Engine and Customizing It in Real Time

[0333] Specific operation: The server activates the emotion engine while the user is viewing new digital content. The emotion engine analyzes the user's facial expressions, tone of voice, language data, etc., and customizes the digital content in real time. For example, it displays detailed related information in areas that the user is interested in, and reduces the amount of information in areas that the user is not interested in.

[0334] Input: User viewing data (e.g., facial expressions, tone of voice, language data) and digital content files

[0335] Output: Real-time customized digital content

[0336] This allows users to quickly obtain digital content that always reflects the latest information, and to have the optimal viewing experience that suits their individual emotions.

[0337] (Application example 2)

[0338] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0339] Modern digital content requires rapid updates, and the presence of outdated product information, especially on online shopping sites, can detract from the customer experience. In addition, a lack of real-time customization based on user preferences can also impact customer satisfaction. However, manual updates and customization require significant time and effort, creating a growing need for automated systems. The present invention aims to address these issues and provide an optimal digital experience that reflects the latest information while responding to user preferences.

[0340] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0341] In this invention, the server includes an uploading means for uploading digital content including old information, an analyzing means for inputting the digital content into a generating artificial intelligence model and analyzing the content, an information acquiring means for identifying old information based on the analysis result of the digital content and acquiring the latest information, a replacing means for replacing the old information with the acquired latest information, a generating means for generating new digital content based on the information updated by the replacing means, a storing and providing means for storing the generated new digital content and providing it to the user, a sentiment analyzing means for analyzing the user's sentiment and customizing the viewing experience in real time, and a prompt generating means for uploading information about specific products and generating new product introductions and reviews based on the latest information. This allows the latest information to be always reflected and enables the provision of an optimal shopping experience tailored to the user's sentiment.

[0342] "Outdated information" refers to information contained in digital content created in the past that is no longer accurate today.

[0343] "Digital content" means information or media represented or stored in electronic form.

[0344] "Uploading means" refers to a means by which a user transmits digital content, including old information, to a server.

[0345] A "generative artificial intelligence model" refers to an algorithm or entire system that uses machine learning and deep learning to analyze digital content and generate new content.

[0346] "Analysis means" means a means for inputting uploaded digital content into a generative artificial intelligence model to analyze the content and extract information.

[0347] The "information acquisition means" refers to a means for acquiring the latest information corresponding to the old information identified by the analysis means.

[0348] The "replacement means" refers to a means for replacing old information in the digital content with new information using the acquired latest information.

[0349] The "generation means" refers to a means for creating new digital content based on the information updated by the replacement means.

[0350] "Storage and provision means" refers to the means for storing the newly generated digital content and providing it in a form that allows users to access it.

[0351] An "emotion analysis means" is a means for analyzing emotions from a user's facial expressions, voice, etc., and using that information to customize the viewing experience in real time.

[0352] A "prompt generation means" is a means for uploading specific product information and generating new product introductions and reviews based on the latest information.

[0353] The present invention provides a system for automatically updating digital content, including outdated information, on an online shopping site to provide a customized shopping experience based on user emotions. The system includes an uploading unit, an analyzing unit, an information acquiring unit, a replacing unit, a generating unit, a storing and providing unit, an emotion analyzing unit, and a prompt generating unit.

[0354] Hardware and software used

[0355] Hardware: Smartphone (with camera and microphone)

[0356] software:

[0357] Generative AI models (e.g., GPT-4)

[0358] Synthetic speech tools (e.g., Amazon Polly)

[0359] Video editing software (e.g. Adobe Premiere Pro)

[0360] Emotion recognition engines (e.g., Affectiva, Emotion AI)

[0361] How it works

[0362] Upload method

[0363] Users first upload old product introduction videos and reviews using their smartphones, then use a dedicated application to click the upload button, which sends the data to the server.

[0364] Analysis means

[0365] The server then analyzes the uploaded digital content by feeding it into a generative AI model (e.g., GPT-4), which identifies outdated information in the content, such as "current price: $1,000."

[0366] Information acquisition means

[0367] The server collects the latest information from an internal database or external sources, for example, the latest product information and pricing data.

[0368] replacement means

[0369] The old parsed information is replaced with the latest information retrieved. For example, "Current price $1000" is replaced with "New price $1200."

[0370] generation means

[0371] Based on the replaced information, new product introduction videos and reviews are generated using synthetic voice tools and video editing software, creating new digital content that is natural to the eye and ear.

[0372] Storage and provision means

[0373] The new content generated is stored in a long-term database and made available on the server for user access, who receives a download link for the new content.

[0374] Emotion analysis means

[0375] While a user is viewing new content, an emotion recognition engine (e.g., Affectiva) uses the smartphone's camera and microphone to analyze emotions in real time, providing a customized viewing experience, such as displaying positive product reviews if the user is happy.

[0376] Specific examples

[0377] For example, if a user wants to update the "Product Description with Current Price of $1000," they would enter the following prompt text:

[0378] "Please update the product description from its current price of $1000 to $1200."

[0379] Based on this, the server generates new digital content based on the latest price information and provides it to users at the appropriate time using sentiment analysis.

[0380] This allows the system of the present invention to always reflect the latest information and provide the optimal shopping experience according to the user's emotions.

[0381] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0382] Step 1:

[0383] Users upload old product videos and reviews using their own devices by clicking the upload button within a specific application. The input of this step is the old digital content, and the output is the data sent to the server.

[0384] Step 2:

[0385] The server inputs the uploaded digital content into a generative AI model (e.g., GPT-4). This starts the analysis of the digital content. The input of this step is the digital content sent by the user, and the output is the analysis results. The specific operation of the analysis is to analyze the text and audio in the digital content and identify outdated information.

[0386] Step 3:

[0387] The server identifies outdated information based on the analysis results and retrieves the latest information from an internal database or external information source. The input to this step is the outdated information identified as a result of the analysis, and the output is the latest information. Specifically, the latest price information and product specifications are retrieved from the database using an API.

[0388] Step 4:

[0389] The server replaces the identified outdated information with the latest information. The inputs to this step are the identified outdated information and the acquired latest information, and the output is the replaced new information. The specific operation is to edit the text data, audio data, and visual data to reflect the latest information.

[0390] Step 5:

[0391] The server generates new product introduction videos and reviews based on the replaced information. The input of this step is the replaced information, and the output is new digital content. Specifically, the new digital content is generated using a synthetic voice tool (e.g., Amazon Polly) or video editing software (e.g., Adobe Premiere Pro).

[0392] Step 6:

[0393] The server stores the generated new digital content and provides it to the user. The input of this step is the new digital content, and the output is data stored in a long-term storage database and information provided to the user. Specific operations include storing the digital content in the database, generating a sharing link, and notifying the user.

[0394] Step 7:

[0395] While a user is viewing new digital content, emotion analysis is performed using the smartphone's built-in camera and microphone. The input for this step is the user's facial and voice data, and the output is analyzed emotional information. Specifically, an emotion recognition engine (e.g., Affectiva, Emotion AI) is used to monitor the user's emotions in real time.

[0396] Step 8:

[0397] Based on the results of the emotion analysis, the server uses a prompt generation means to display customized product introductions and reviews according to the user's emotions. The input of this step is the analyzed emotion information, and the output is customized viewing content. Specifically, the server generates prompts to provide new product introductions and reviews to the user in real time.

[0398] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0399] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0400] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0401] [Second embodiment]

[0402] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0403] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0404] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0405] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0406] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0407] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0408] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0409] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0410] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0411] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0412] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0413] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0414] System Overview

[0415] The present invention relates to a system that automatically updates digital content containing outdated information to the latest information and generates new digital content. The system includes an uploading unit, an analyzing unit, an information acquiring unit, a replacing unit, a generating unit, and a storing and providing unit. The operation of each unit is described below.

[0416] How it works

[0417] Upload method

[0418] User Input

[0419] Users upload digital content, including old information, from their devices (PCs, tablets, smartphones, etc.) by clicking an upload button using a web interface or a dedicated application.

[0420] Analysis means

[0421] Server Operations

[0422] The server inputs the uploaded digital content into a generative AI model to analyze the content. The analysis method analyzes the video content frame by frame, converts audio and subtitle data into text, and extracts specific outdated information.

[0423] Information acquisition means

[0424] Server Operations

[0425] The server retrieves the latest information from an internal database or an external source, thereby obtaining the latest data corresponding to the outdated information identified by the analysis means.

[0426] replacement means

[0427] Server Operations

[0428] The analyzed information is replaced with the latest information. This applies not only to text data, but also to audio data and visual elements.

[0429] generation means

[0430] Server Operations

[0431] New digital content is generated based on the data replaced with the latest information. Specifically, using synthetic voice and video editing tools, old information is updated with the latest information in a natural way to create videos.

[0432] Storage and provision means

[0433] Server Operations

[0434] The newly generated digital content is transferred to a database for long-term storage and made accessible to users. The server generates a download link for the new content and notifies the user.

[0435] Specific examples

[0436] As a concrete example, consider a company's product introduction video. For example, if a product introduction video shows that the "latest model ABC" is currently priced at $1,000, then one year from now, that information will change to the "new model ABC" with a price of $1,200.

[0437] 1. User Input

[0438] The user uses the terminal to upload the old "Introduction video for the latest model ABC" to the server via the web interface.

[0439] 2. Server Operation - Analysis

[0440] The server inputs the uploaded video file into the generative AI model and identifies the "latest model ABC" and "current price $1,000."

[0441] 3. Server Operation - Getting the Latest Information

[0442] Retrieve information about "New Model ABC" and "New Price $1200" from the database.

[0443] 4. Server Operations - Information Replacement

[0444] Using a generative AI model, "Latest Model ABC" is replaced with "New Model ABC" and "Current Price $1,000" is replaced with "New Price $1,200."

[0445] 5. Server Operation - Creating a New Video

[0446] Generate a new introductory video based on new information.

[0447] 6. Server Operation - Storage and Serving

[0448] The new introductory video is saved in the database, a new download link is generated and notified to the user.

[0449] This allows users to quickly obtain digital content that always reflects the latest information without any hassle.

[0450] The processing flow will be explained below.

[0451] Step 1:

[0452] User operations

[0453] Users select the old brand video file from their device and click the upload button using the web interface or a dedicated application, which sends the video file to the server.

[0454] Step 2:

[0455] Server Operations

[0456] The server receives the video file sent by the user and saves it in a temporary directory in the file system, while recording the video file path and metadata in a database.

[0457] Step 3:

[0458] Server Operations

[0459] The server passes the video file to a generative AI model and activates an analytical method. The generative AI model analyzes the video content frame by frame, converts audio to text, and extracts subtitle data, thereby identifying outdated information in the video.

[0460] Step 4:

[0461] Server Operations

[0462] The server accesses a database or external information source to retrieve up-to-date information that corresponds to outdated information identified by the analytical means, and retrieves up-to-date product and pricing information using database queries or API requests.

[0463] Step 5:

[0464] Server Operations

[0465] The server then uses the latest information to replace the old analyzed information. This includes not only text data, but also audio data and visual elements. The replacement process is automated, using voice synthesis and video editing techniques.

[0466] Step 6:

[0467] Server Operations

[0468] The server generates new digital content based on the data replaced with the latest information. The generation means integrates preprocessed text, audio data, and visual elements into a single video file.

[0469] Step 7:

[0470] Server Operations

[0471] The newly generated digital content is moved to a long-term storage directory, the database metadata is updated, and a download link is generated and provided to users to notify them.

[0472] Step 8:

[0473] User operations

[0474] The user clicks the link provided on the device to download the new digital content from the server. The downloaded video contains the latest updated information, so it can be provided to customers immediately.

[0475] Example 1

[0476] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0477] Digital content often becomes outdated after it is created, which can lead to misunderstandings among viewers. For example, price and model information in product introduction videos changes very quickly. However, manually updating this information is time-consuming, costly, and inefficient. Therefore, there is a need to provide a method for automatically updating outdated information and generating new digital content.

[0478] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0479] In this invention, the server includes uploading means for uploading digital content including old information from a device used by a user, analysis means for inputting the digital content into a generative AI model to analyze the content and extract specific old information, information acquisition means for acquiring latest information corresponding to the old information based on the analysis results, replacement means for replacing the old information with the acquired latest information, generation means for generating new digital content based on the information replaced by the replacement means, and storage and provision means for saving the generated new digital content and making it accessible to users. This makes it possible to automatically update old information included in digital content with the latest information.

[0480] The "uploading means" is a means by which a user uses a terminal to send digital content including old information to a server.

[0481] "Analysis means" means a means for analyzing uploaded digital content using a generative AI model to extract certain outdated information.

[0482] The "information acquisition means" is a means for acquiring the latest information from an internal database or an external information source based on the old information identified by the analysis means.

[0483] The "replacement means" is a means for updating the old information identified by the analysis means using the latest information obtained by the acquisition means.

[0484] The "generating means" is a means for generating new digital content based on the data replaced with the latest information by the replacing means.

[0485] The "storage and provision means" is a means for storing new digital content generated by the generation means in a database for long-term storage and making it accessible to users.

[0486] System Overview

[0487] The present invention provides a system for automatically updating digital content containing outdated information with the latest information and generating new digital content. The system includes an uploading unit, an analyzing unit, an information acquiring unit, a replacing unit, a generating unit, and a storing and providing unit. The following description describes the specific operation of each unit.

[0488] Upload method

[0489] Users upload digital content, including old information, using a web browser or dedicated application on their device (e.g., personal computer, tablet, or smartphone). The user clicks the upload button on the web interface or application to send the selected file to the server. For example, this is the operation of uploading a company's product introduction video.

[0490] Analysis means

[0491] The server receives the uploaded digital content and stores it in a temporary storage area. The server then analyzes the content using a generative AI model. The generative AI model analyzes the video frame by frame and converts the audio data into text. From the analysis results, "old information" is extracted. For example, information such as "latest model ABC" and "price $1,000" is extracted.

[0492] Information acquisition means

[0493] The server retrieves the latest information from an internal database or an external source (e.g., API) based on the old information extracted from the analysis. It uses a database query or API request to get the latest information, such as "New Model ABC" and "Price: $1200."

[0494] replacement means

[0495] The server replaces the outdated information identified by the analytical means with the latest information retrieved. This includes not only text data, but also audio data and visual elements. For example, "latest model ABC" could be replaced with "new model ABC" and "price $1,000" could be replaced with "price $1,200."

[0496] generation means

[0497] The server generates new digital content based on the new information, using synthetic speech technology and video editing tools to generate a naturally updated video, resulting in a new introductory video in which the old information is replaced with the latest information.

[0498] Storage and provision means

[0499] The server stores the new digital content in a database for long-term storage, and then generates and notifies the user of the new content with a link to access it, for example, via an email notification.

[0500] Specific examples

[0501] As a concrete example, consider a company's product introduction video. For example, a video introducing the latest model ABC at a price of $1,000 is uploaded one year later. In this example, the video is updated to include the latest information, "New Model ABC" and "Price: $1,200."

[0502] Example of input prompt for generative AI model

[0503] Here are some examples of prompts to input to a generative AI model:

[0504] Please analyze your old introduction video and update it with the latest model name and price information based on the information below:

[0505] New model name: New model ABC

[0506] New price: $1,200

[0507] This prompt ensures that the generative AI model generates digital content that is updated with the latest information.

[0508] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0509] Step 1:

[0510] Users upload content

[0511] The user uses a terminal to upload digital content including old information. The user clicks the upload button in the web interface or dedicated application to send the selected file to the server. The input is the digital content file specified by the user (e.g., "Old Product Introduction Video.mp4"), and the output is the file uploaded to the server.

[0512] Step 2:

[0513] The server analyzes the digital content

[0514] The server receives the uploaded digital content and stores it in a temporary storage area. The server inputs the video file into a generative AI model, which analyzes the content frame by frame. It converts the audio data into text and extracts old information from the analysis results. The input is the uploaded digital content file, and the output is the analyzed text data (e.g., "Latest Model ABC" and "Price: $1,000").

[0515] Step 3:

[0516] The server retrieves the latest information

[0517] Based on the analysis results, the server sends a query to obtain the latest information from an internal database or an external information source. The input is the analyzed text data, and the output is the obtained latest information data (e.g., "New model ABC" and "New price $1,200"). This is done using a database query or an API request.

[0518] Step 4:

[0519] The server replaces the old information with the latest information.

[0520] The server uses the acquired latest information to replace the old information identified by the analysis means. This includes text data, audio data, and visual elements. The input is the acquired latest information data and analyzed text data, and the output is the data replaced with the new information (e.g., updated text to "New Model ABC" and "New Price $1,200"). Specifically, the replacement operation is performed using a generative AI model.

[0521] Step 5:

[0522] The server generates new digital content.

[0523] The server generates new digital content based on the replaced information. Using synthetic voice technology and video editing tools, it generates a new introductory video and saves it in a temporary storage area. The input is the data replaced with the new information, and the output is the generated new digital content (e.g., a new video introducing "New Model ABC").

[0524] Step 6:

[0525] Servers store and serve new digital content

[0526] The server stores the generated new digital content in a database for long-term storage. It then generates a download link and notifies the user to make it accessible to the user. The input is the generated new digital content, and the output is the stored content and a notification message to the user (e.g., sending a link via email notification).

[0527] (Application example 1)

[0528] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0529] In the food service industry, menu information, prices, campaign information, and other information change frequently, making it important to keep this information up to date. However, traditional methods often require these updates to be done manually, which not only takes time and effort but also carries the risk of providing customers with incorrect information. To solve this problem, an automatic system for updating menu and price information is needed.

[0530] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0531] In this invention, the server includes an uploading means for uploading digital content including old information, an analyzing means for inputting the digital content into a generative AI model and analyzing the content, an information acquiring means for identifying old information based on the analysis results of the digital content and acquiring the latest information, a replacing means for replacing the old information with the acquired latest information, a generating means for generating new digital content based on the information updated by the replacing means, a storing and providing means for storing the generated new digital content and providing it to users, and a function for always keeping menu information and prices in food service up to date, thereby enabling the food service industry to always provide the latest information quickly and accurately.

[0532] "Uploading means" refers to the function by which a user sends digital content, including old information, to a server.

[0533] "Analysis means" refers to the function of using a generative AI model to analyze uploaded digital content and understand its contents.

[0534] "Information acquisition means" refers to the function of acquiring the latest information from external or internal information sources based on the analysis results.

[0535] The "replacement means" refers to a function that uses the acquired latest information to replace old information in the digital content with new information.

[0536] "Generation means" refers to the function of creating new digital content based on updated information.

[0537] "Storage and provision means" refers to the function of storing the newly generated digital content and providing it to users.

[0538] "Food service" refers to the general industry that provides food and beverages, including restaurants and food delivery services.

[0539] The present invention relates to a system for automatically keeping menu and pricing information up to date in the food service industry. The system includes the following major components:

[0540] Upload method

[0541] Users use their devices to upload digital content (e.g., menu images) containing outdated information to the server. This operation is performed through a dedicated application or a web interface.

[0542] Analysis means

[0543] The server then feeds the uploaded digital content into a generative AI model to analyze its contents. This involves using optical character recognition (OCR) technology to extract text from images and identify outdated information. For this purpose, the pytesseract and opencv libraries are used.

[0544] Information acquisition means

[0545] The server retrieves the latest menu information and prices from external or internal sources, typically by using the requests library to retrieve data from a remote API.

[0546] replacement means

[0547] The server uses the retrieved updated information to replace the old information identified by the analysis means with new information. This process is performed by text replacement, and the new menu information and prices are reflected in the digital content.

[0548] generation means

[0549] The server generates new digital content based on the updated information, and uses the OpenCV library to draw new text information on the image and generate a new menu image.

[0550] Storage and provision means

[0551] The server stores the newly generated digital content in a database and makes it accessible to users, so a download link for the new digital content is generated and notified to the user.

[0552] Main hardware and software used

[0553] Hardware: PC or Server

[0554] Software: Python, pytesseract, opencv, requests

[0555] Specific examples

[0556] For example, consider a restaurant that updates its weekly lunch menu. Users can upload an image of the old menu, and the system automatically updates it to reflect the new lunch menu. The old information in the uploaded image, "Curry rice 800 yen," is replaced with the new information, "Beef curry 900 yen."

[0557] Example prompts for generative AI models

[0558] Analyze the old lunch menu in the image below and update it with the new information: menu name, price, and description. For example, if the old menu item was "Curry rice 800 yen," change it to "Beef curry 900 yen."

[0559] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0560] Step 1: Upload your old digital content

[0561] A user uses a terminal to upload digital content (e.g., menu images) containing old menu information for a food service to a server. This operation is performed through a dedicated application or a web interface, and the content file is sent to the server. The input is the old menu image selected by the user, and the output is the uploaded image file.

[0562] Step 2: Analyzing the digital content

[0563] The server inputs the uploaded digital content into a generative AI model to analyze its contents. The server first uses the pytesseract library to extract text from images using optical character recognition (OCR) technology, and then identifies outdated menu information from the extracted text. The input is the uploaded image file, and the output is the extracted text data.

[0564] Step 3: Stay up to date

[0565] Based on the analysis results, the server retrieves the latest menu information and prices from external or internal sources. During this process, it uses the requests library to retrieve the necessary data from a remote API. The input is the parsed text data, and the output is the retrieved latest menu information.

[0566] Step 4: Replace old information

[0567] The server uses the acquired latest information to replace the old information identified by the analysis means with new information. This process is performed by text replacement. Specifically, the extracted old menu information is replaced with new menu information. The input is text data containing the old information and the latest information, and the output is text data containing the new menu information.

[0568] Step 5: Generate new digital content

[0569] The server generates new digital content based on the updated information. Using the OpenCV library, it draws the new text information on the image and generates a new menu image. The input is text data containing the new menu information, and the output is the new menu image.

[0570] Step 6: Store and serve

[0571] The server saves the generated new digital content in a database and makes it accessible to users. A download link for the new digital content is generated and notified to the user. The input is a new menu image, and the output is the image file saved in the database and notification information.

[0572] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0573] System Overview

[0574] The present invention combines a system that automatically updates digital content containing outdated information with the latest information and generates new digital content, with an emotion engine that recognizes user emotions. This system includes an uploading means, an analyzing means, an information acquisition means, a replacement means, a generating means, a storage and provision means, and an emotion engine. The operation of each means will be described below.

[0575] How it works

[0576] Upload method

[0577] User operations

[0578] Users upload old digital content from their devices (PCs, tablets, smartphones, etc.) by clicking an upload button using a web interface or a dedicated application.

[0579] Analysis means

[0580] Server Operations

[0581] The server inputs the uploaded digital content into a generative AI model to analyze the content. The analysis method analyzes the video content frame by frame, converts audio and subtitle data into text, and extracts specific outdated information.

[0582] Information acquisition means

[0583] Server Operations

[0584] The server retrieves the latest information from an internal database or an external source, and retrieves the latest data corresponding to the outdated information identified by the analysis means.

[0585] replacement means

[0586] Server Operations

[0587] The analyzed information is replaced with the latest information. This applies not only to text data, but also to audio data and visual elements.

[0588] generation means

[0589] Server Operations

[0590] New digital content is generated based on the data replaced with the latest information. The generation method uses synthesized voice and video editing tools to generate videos that naturally update old information with the latest information.

[0591] Storage and provision means

[0592] Server Operations

[0593] The newly generated digital content is transferred to a database for long-term storage and made accessible to users. The server generates a download link for the new content and notifies the user.

[0594] Emotion Engine

[0595] Server Operations

[0596] The server activates an emotion engine that recognizes emotions from the user's facial expressions, tone of voice, language, etc. The emotion engine analyzes emotions while the user is viewing digital content and customizes the content in real time.

[0597] Specific examples

[0598] For example, consider a company's product introduction video. If a product introduction video shows that the "latest model ABC" is currently priced at $1,000, then one year from now, that information will change to the "new model ABC" with a price of $1,200. In this case, the process will be as follows:

[0599] 1. User Input

[0600] The user uses the terminal to upload the old "Introduction video for the latest model ABC" to the server via the web interface.

[0601] 2. Server Operation - Analysis

[0602] The server inputs the uploaded video file into the generative AI model and identifies the "latest model ABC" and "current price $1,000."

[0603] 3. Server Operation - Getting the Latest Information

[0604] Retrieve information about "New Model ABC" and "New Price $1200" from the database.

[0605] 4. Server Operations - Information Replacement

[0606] Using a generative AI model, "Latest Model ABC" is replaced with "New Model ABC" and "Current Price $1,000" is replaced with "New Price $1,200."

[0607] 5. Server Operation - Creating a New Video

[0608] Generate a new introductory video based on new information.

[0609] 6. Server Operation - Storage and Serving

[0610] The new introductory video is saved in the database, a new download link is generated and notified to the user.

[0611] 7. Manipulating the Emotion Engine

[0612] As users watch new videos, the emotion engine analyzes their emotions and customizes the content in real time.

[0613] This allows users to quickly obtain digital content that always reflects the latest information without any hassle, and provides an optimal viewing experience that suits each individual's emotions.

[0614] The processing flow will be explained below.

[0615] Step 1:

[0616] User operations

[0617] Users select the old brand video file from their device and click the upload button using the web interface or a dedicated application, which sends the video file to the server.

[0618] Step 2:

[0619] Server Operations

[0620] The server receives the video file sent by the user and saves it in a temporary directory in the file system, while recording the video file path and metadata in a database.

[0621] Step 3:

[0622] Server Operations

[0623] The server passes the video file to a generative AI model and activates an analytical method. The generative AI model analyzes the video content frame by frame, converts audio to text, and extracts subtitle data, thereby identifying outdated information in the video.

[0624] Step 4:

[0625] Server Operations

[0626] The server accesses a database or external information source to retrieve up-to-date information that corresponds to outdated information identified by the analytical means, and retrieves up-to-date product and pricing information using database queries or API requests.

[0627] Step 5:

[0628] Server Operations

[0629] The server then uses the latest information to replace the old analyzed information. This includes not only text data, but also audio data and visual elements. The replacement process is automated, using voice synthesis and video editing techniques.

[0630] Step 6:

[0631] Server Operations

[0632] The server generates new digital content based on the data replaced with the latest information. The generation means integrates preprocessed text, audio data, and visual elements into a single video file.

[0633] Step 7:

[0634] Server Operations

[0635] The newly generated digital content is moved to a long-term storage directory, the database metadata is updated, and a download link is generated and provided to users to notify them.

[0636] Step 8:

[0637] User operations

[0638] The user clicks the link provided on the device to download the new digital content from the server. The downloaded video contains the latest updated information, so it can be provided to customers immediately.

[0639] Step 9:

[0640] Server Operations

[0641] The server activates an emotion engine to recognize emotions from the user's facial expressions, tone of voice, language, etc. While the user is viewing digital content, the emotion engine analyzes the user's emotions in real time.

[0642] Step 10:

[0643] Server Operations

[0644] The server changes the presentation order and content of digital content in real time based on the user's emotions recognized by the emotion engine, providing a viewing experience optimized for each user's emotional state.

[0645] Example 2

[0646] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0647] Modern digital content faces the challenge of becoming outdated quickly and requiring a great deal of time and effort to update. It is also difficult to customize digital content in real time to reflect the emotions and interests of each user. This leads to a homogenous user experience that fails to address individual needs.

[0648] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0649] In this invention, the server includes an uploading means for uploading digital content including old information, an analyzing means for inputting the digital content into a generative AI model and analyzing the content, an information acquiring means for identifying old information based on the analysis results of the digital content and acquiring the latest information, a replacing means for replacing the old information with the acquired latest information, a generating means for generating new digital content based on the information updated by the replacing means, a storing and providing means for storing the generated new digital content and providing it to the user, and an emotion engine for recognizing the user's emotions and customizing the digital content in real time, thereby enabling rapid updating of digital content and an optimized viewing experience for each user.

[0650] An "uploading mechanism" is a mechanism by which a user transfers digital content, including old information, to the system.

[0651] "Analysis means" refers to the means for inputting uploaded digital content into a generative AI model and analyzing its contents to identify outdated information.

[0652] The "information acquisition means" is a means for acquiring the latest information corresponding to the old information identified by the analysis means from an internal database or an external information source.

[0653] The "replacement means" is a means for replacing old information with new information using the acquired latest information.

[0654] The "generation means" is a means for generating new digital content based on data replaced with the latest information.

[0655] The "storage and provision means" refers to a means for storing the newly generated digital content and providing it in a form accessible to users.

[0656] An "emotion engine" is a means of analyzing a user's facial expressions, tone of voice, and language, and customizing digital content in real time according to the user's emotions.

[0657] A "generative AI model" is an artificial intelligence model used to analyze uploaded digital content and identify and replace outdated information.

[0658] To implement this invention, a system involving three main elements is used: a server, a terminal, and a user. This system automatically updates digital content, including old information, with the latest information, generates new digital content, and also incorporates an emotion engine that recognizes the user's emotions. Each means of this system is described in detail below.

[0659] Upload method

[0660] Users upload old digital content using a device (PC, tablet, smartphone, etc.). Specifically, users operate a web interface or dedicated application, click the upload button, and select the desired digital content file. This transfers the digital content to the server.

[0661] Analysis means

[0662] The server inputs the uploaded digital content into a generative AI model and analyzes its contents. During this process, the analysis means analyzes each frame of the video and converts the audio and subtitle data into text. From the analyzed text data, outdated information is identified. The generative AI model uses natural language processing and machine learning techniques.

[0663] Information acquisition means

[0664] The server retrieves the latest information from an internal database or an external source (such as an API). It searches for and retrieves the latest data corresponding to outdated information identified by the analysis method. For example, if a specific product name or price is outdated, it retrieves the corresponding latest product name and price information from the database.

[0665] replacement means

[0666] The server then uses the latest information to replace the old information it has analyzed. This replacement process involves not only text data, but also audio and visual elements. For example, the old product name is replaced with the new product name, and audio data is also replaced with the new information using synthesized speech technology.

[0667] generation means

[0668] The server generates new digital content based on the data replaced with the latest information. This generation method uses video editing tools (e.g., FFmpeg) and synthetic voice technology to create new, natural-looking, and consistent digital content.

[0669] Storage and provision means

[0670] The server then transfers the newly generated digital content to a long-term storage database, makes it accessible to users, generates a download link for the new digital content, and notifies the user via email or in-app notification.

[0671] Emotion Engine

[0672] While the user is viewing new digital content, the server activates an emotion engine that analyzes the user's facial expressions, tone of voice, and language data. This emotion engine analyzes the user's emotions in real time and customizes the digital content accordingly. For example, it adapts by displaying detailed information related to parts that the user is interested in and reducing the amount of information in parts that the user is not interested in.

[0673] Specific examples

[0674] For example, if a company has a product introduction video that includes the product name "old model XYZ" and the price "$100," the following steps would be taken:

[0675] 1. The user uses a terminal to upload an old product introduction video to the server via a web interface.

[0676] 2. The server inputs the video file into the generative AI model and identifies "old model XYZ" and "$100."

[0677] 3. Retrieve the new product name "New Model XYZ" and new price "$120" from the internal database.

[0678] 4. Use a generative AI model to replace "Old Model XYZ" with "New Model XYZ" and "$100" with "$120."

[0679] 5. Generate new digital content using video editing tools.

[0680] 6. Save the new video to the database, generate a download link and notify the user.

[0681] 7. As users watch new videos, the emotion engine analyzes their emotions and customizes their viewing experience in real time.

[0682] Prompt Sentence Examples

[0683] "Program the system to update the content of the video and customize it based on the user's emotions. For example, replace the old model name in a product introduction video with the new model name, and adjust the content in real time based on the user's emotions while watching."

[0684] This allows users to quickly obtain digital content that always reflects the latest information, and to have the optimal viewing experience that suits their individual emotions.

[0685] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0686] Step 1: Upload

[0687] Specific operation: Users use a device (PC, tablet, smartphone, etc.) to upload old digital content via a web interface or dedicated application.

[0688] Input: Digital content file (e.g. product introduction video)

[0689] Output: Digital content files uploaded to the server

[0690] Step 2: Analysis

[0691] How it works: The server feeds uploaded digital content into a generative AI model that analyzes its content, parsing each frame of video, converting audio and subtitle data into text, and identifying outdated information.

[0692] Input: Uploaded digital content file

[0693] Output: Text data containing outdated information (e.g., "Old Model XYZ", "$100")

[0694] Step 3: Information Acquisition

[0695] Specific operation: The server retrieves the latest information from an internal database or external information source (e.g., API). It searches for and retrieves the latest data corresponding to the old information identified by the analysis method.

[0696] Input: Text data containing outdated information (e.g., "Old Model XYZ," "$100")

[0697] Output: Data containing the latest information (e.g., "New Model XYZ," "$120")

[0698] Step 4: Substitution

[0699] What it does: The server replaces the old parsed information with the latest information it has retrieved. This replacement process involves not only replacing text data, but also synthesizing audio data and changing visual elements.

[0700] Input: Text data containing old information, data containing the latest information

[0701] Output: Data replaced with the latest information

[0702] Step 5: Generate

[0703] Specific operation: The server generates new digital content based on the data replaced with the latest information. The generation method uses video editing tools (e.g., FFmpeg) and synthetic voice technology to create new, natural, and consistent digital content.

[0704] Input: Data replaced with the latest information

[0705] Output: The new digital content file generated

[0706] Step 6: Store and serve

[0707] Specific operations: The server migrates the generated new digital content to a database for long-term storage and makes it accessible to users. It also generates a download link for the new digital content and notifies the user.

[0708] Input: The new digital content file that was generated

[0709] Output: Content stored in database and download link notification to user

[0710] Step 7: Launching the Emotion Engine and Customizing It in Real Time

[0711] Specific operation: The server activates the emotion engine while the user is viewing new digital content. The emotion engine analyzes the user's facial expressions, tone of voice, language data, etc., and customizes the digital content in real time. For example, it displays detailed related information in areas that the user is interested in, and reduces the amount of information in areas that the user is not interested in.

[0712] Input: User viewing data (e.g., facial expressions, tone of voice, language data) and digital content files

[0713] Output: Real-time customized digital content

[0714] This allows users to quickly obtain digital content that always reflects the latest information, and to have the optimal viewing experience that suits their individual emotions.

[0715] (Application example 2)

[0716] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0717] Modern digital content requires rapid updates, and the presence of outdated product information, especially on online shopping sites, can detract from the customer experience. In addition, a lack of real-time customization based on user preferences can also impact customer satisfaction. However, manual updates and customization require significant time and effort, creating a growing need for automated systems. The present invention aims to address these issues and provide an optimal digital experience that reflects the latest information while responding to user preferences.

[0718] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0719] In this invention, the server includes an uploading means for uploading digital content including old information, an analyzing means for inputting the digital content into a generating artificial intelligence model and analyzing the content, an information acquiring means for identifying old information based on the analysis result of the digital content and acquiring the latest information, a replacing means for replacing the old information with the acquired latest information, a generating means for generating new digital content based on the information updated by the replacing means, a storing and providing means for storing the generated new digital content and providing it to the user, a sentiment analyzing means for analyzing the user's sentiment and customizing the viewing experience in real time, and a prompt generating means for uploading information about specific products and generating new product introductions and reviews based on the latest information. This allows the latest information to be always reflected and enables the provision of an optimal shopping experience tailored to the user's sentiment.

[0720] "Outdated information" refers to information contained in digital content created in the past that is no longer accurate today.

[0721] "Digital content" means information or media represented or stored in electronic form.

[0722] "Uploading means" refers to a means by which a user transmits digital content, including old information, to a server.

[0723] A "generative artificial intelligence model" refers to an algorithm or entire system that uses machine learning and deep learning to analyze digital content and generate new content.

[0724] "Analysis means" means a means for inputting uploaded digital content into a generative artificial intelligence model to analyze the content and extract information.

[0725] The "information acquisition means" refers to a means for acquiring the latest information corresponding to the old information identified by the analysis means.

[0726] The "replacement means" refers to a means for replacing old information in the digital content with new information using the acquired latest information.

[0727] The "generation means" refers to a means for creating new digital content based on the information updated by the replacement means.

[0728] "Storage and provision means" refers to the means for storing the newly generated digital content and providing it in a form that allows users to access it.

[0729] An "emotion analysis means" is a means for analyzing emotions from a user's facial expressions, voice, etc., and using that information to customize the viewing experience in real time.

[0730] A "prompt generation means" is a means for uploading specific product information and generating new product introductions and reviews based on the latest information.

[0731] The present invention provides a system for automatically updating digital content, including outdated information, on an online shopping site to provide a customized shopping experience based on user emotions. The system includes an uploading unit, an analyzing unit, an information acquiring unit, a replacing unit, a generating unit, a storing and providing unit, an emotion analyzing unit, and a prompt generating unit.

[0732] Hardware and software used

[0733] Hardware: Smartphone (with camera and microphone)

[0734] software:

[0735] Generative AI models (e.g., GPT-4)

[0736] Synthetic speech tools (e.g., Amazon Polly)

[0737] Video editing software (e.g. Adobe Premiere Pro)

[0738] Emotion recognition engines (e.g., Affectiva, Emotion AI)

[0739] How it works

[0740] Upload method

[0741] Users first upload old product introduction videos and reviews using their smartphones, then use a dedicated application to click the upload button, which sends the data to the server.

[0742] Analysis means

[0743] The server then analyzes the uploaded digital content by feeding it into a generative AI model (e.g., GPT-4), which identifies outdated information in the content, such as "current price: $1,000."

[0744] Information acquisition means

[0745] The server collects the latest information from an internal database or external sources, for example, the latest product information and pricing data.

[0746] replacement means

[0747] The old parsed information is replaced with the latest information retrieved. For example, "Current price $1000" is replaced with "New price $1200."

[0748] generation means

[0749] Based on the replaced information, new product introduction videos and reviews are generated using synthetic voice tools and video editing software, creating new digital content that is natural to the eye and ear.

[0750] Storage and provision means

[0751] The new content generated is stored in a long-term database and made available on the server for user access, who receives a download link for the new content.

[0752] Emotion analysis means

[0753] While a user is viewing new content, an emotion recognition engine (e.g., Affectiva) uses the smartphone's camera and microphone to analyze emotions in real time, providing a customized viewing experience, such as displaying positive product reviews if the user is happy.

[0754] Specific examples

[0755] For example, if a user wants to update the "Product Description with Current Price of $1000," they would enter the following prompt text:

[0756] "Please update the product description from its current price of $1000 to $1200."

[0757] Based on this, the server generates new digital content based on the latest price information and provides it to users at the appropriate time using sentiment analysis.

[0758] This allows the system of the present invention to always reflect the latest information and provide the optimal shopping experience according to the user's emotions.

[0759] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0760] Step 1:

[0761] Users upload old product videos and reviews using their own devices by clicking the upload button within a specific application. The input of this step is the old digital content, and the output is the data sent to the server.

[0762] Step 2:

[0763] The server inputs the uploaded digital content into a generative AI model (e.g., GPT-4). This starts the analysis of the digital content. The input of this step is the digital content sent by the user, and the output is the analysis results. The specific operation of the analysis is to analyze the text and audio in the digital content and identify outdated information.

[0764] Step 3:

[0765] The server identifies outdated information based on the analysis results and retrieves the latest information from an internal database or external information source. The input to this step is the outdated information identified as a result of the analysis, and the output is the latest information. Specifically, the latest price information and product specifications are retrieved from the database using an API.

[0766] Step 4:

[0767] The server replaces the identified outdated information with the latest information. The inputs to this step are the identified outdated information and the acquired latest information, and the output is the replaced new information. The specific operation is to edit the text data, audio data, and visual data to reflect the latest information.

[0768] Step 5:

[0769] The server generates new product introduction videos and reviews based on the replaced information. The input of this step is the replaced information, and the output is new digital content. Specifically, the new digital content is generated using a synthetic voice tool (e.g., Amazon Polly) or video editing software (e.g., Adobe Premiere Pro).

[0770] Step 6:

[0771] The server stores the generated new digital content and provides it to the user. The input of this step is the new digital content, and the output is data stored in a long-term storage database and information provided to the user. Specific operations include storing the digital content in the database, generating a sharing link, and notifying the user.

[0772] Step 7:

[0773] While a user is viewing new digital content, emotion analysis is performed using the smartphone's built-in camera and microphone. The input for this step is the user's facial and voice data, and the output is analyzed emotional information. Specifically, an emotion recognition engine (e.g., Affectiva, Emotion AI) is used to monitor the user's emotions in real time.

[0774] Step 8:

[0775] Based on the results of the emotion analysis, the server uses a prompt generation means to display customized product introductions and reviews according to the user's emotions. The input of this step is the analyzed emotion information, and the output is customized viewing content. Specifically, the server generates prompts to provide new product introductions and reviews to the user in real time.

[0776] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0777] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0778] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0779] [Third embodiment]

[0780] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0781] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0782] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0783] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0784] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0785] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0786] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0787] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0788] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0789] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0790] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0791] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0792] System Overview

[0793] The present invention relates to a system that automatically updates digital content containing outdated information to the latest information and generates new digital content. The system includes an uploading unit, an analyzing unit, an information acquiring unit, a replacing unit, a generating unit, and a storing and providing unit. The operation of each unit is described below.

[0794] How it works

[0795] Upload method

[0796] User Input

[0797] Users upload digital content, including old information, from their devices (PCs, tablets, smartphones, etc.) by clicking an upload button using a web interface or a dedicated application.

[0798] Analysis means

[0799] Server Operations

[0800] The server inputs the uploaded digital content into a generative AI model to analyze the content. The analysis method analyzes the video content frame by frame, converts audio and subtitle data into text, and extracts specific outdated information.

[0801] Information acquisition means

[0802] Server Operations

[0803] The server retrieves the latest information from an internal database or an external source, thereby obtaining the latest data corresponding to the outdated information identified by the analysis means.

[0804] replacement means

[0805] Server Operations

[0806] The analyzed information is replaced with the latest information. This applies not only to text data, but also to audio data and visual elements.

[0807] generation means

[0808] Server Operations

[0809] New digital content is generated based on the data replaced with the latest information. Specifically, using synthetic voice and video editing tools, old information is updated with the latest information in a natural way to create videos.

[0810] Storage and provision means

[0811] Server Operations

[0812] The newly generated digital content is transferred to a database for long-term storage and made accessible to users. The server generates a download link for the new content and notifies the user.

[0813] Specific examples

[0814] As a concrete example, consider a company's product introduction video. For example, if a product introduction video shows that the "latest model ABC" is currently priced at $1,000, then one year from now, that information will change to the "new model ABC" with a price of $1,200.

[0815] 1. User Input

[0816] The user uses the terminal to upload the old "Introduction video for the latest model ABC" to the server via the web interface.

[0817] 2. Server Operation - Analysis

[0818] The server inputs the uploaded video file into the generative AI model and identifies the "latest model ABC" and "current price $1,000."

[0819] 3. Server Operation - Getting the Latest Information

[0820] Retrieve information about "New Model ABC" and "New Price $1200" from the database.

[0821] 4. Server Operations - Information Replacement

[0822] Using a generative AI model, "Latest Model ABC" is replaced with "New Model ABC" and "Current Price $1,000" is replaced with "New Price $1,200."

[0823] 5. Server Operation - Creating a New Video

[0824] Generate a new introductory video based on new information.

[0825] 6. Server Operation - Storage and Serving

[0826] The new introductory video is saved in the database, a new download link is generated and notified to the user.

[0827] This allows users to quickly obtain digital content that always reflects the latest information without any hassle.

[0828] The processing flow will be explained below.

[0829] Step 1:

[0830] User operations

[0831] Users select the old brand video file from their device and click the upload button using the web interface or a dedicated application, which sends the video file to the server.

[0832] Step 2:

[0833] Server Operations

[0834] The server receives the video file sent by the user and saves it in a temporary directory in the file system, while recording the video file path and metadata in a database.

[0835] Step 3:

[0836] Server Operations

[0837] The server passes the video file to a generative AI model and activates an analytical method. The generative AI model analyzes the video content frame by frame, converts audio to text, and extracts subtitle data, thereby identifying outdated information in the video.

[0838] Step 4:

[0839] Server Operations

[0840] The server accesses a database or external information source to retrieve up-to-date information that corresponds to outdated information identified by the analytical means, and retrieves up-to-date product and pricing information using database queries or API requests.

[0841] Step 5:

[0842] Server Operations

[0843] The server then uses the latest information to replace the old analyzed information. This includes not only text data, but also audio data and visual elements. The replacement process is automated, using voice synthesis and video editing techniques.

[0844] Step 6:

[0845] Server Operations

[0846] The server generates new digital content based on the data replaced with the latest information. The generation means integrates preprocessed text, audio data, and visual elements into a single video file.

[0847] Step 7:

[0848] Server Operations

[0849] The newly generated digital content is moved to a long-term storage directory, the database metadata is updated, and a download link is generated and provided to users to notify them.

[0850] Step 8:

[0851] User operations

[0852] The user clicks the link provided on the device to download the new digital content from the server. The downloaded video contains the latest updated information, so it can be provided to customers immediately.

[0853] Example 1

[0854] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0855] Digital content often becomes outdated after it is created, which can lead to misunderstandings among viewers. For example, price and model information in product introduction videos changes very quickly. However, manually updating this information is time-consuming, costly, and inefficient. Therefore, there is a need to provide a method for automatically updating outdated information and generating new digital content.

[0856] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0857] In this invention, the server includes uploading means for uploading digital content including old information from a device used by a user, analysis means for inputting the digital content into a generative AI model to analyze the content and extract specific old information, information acquisition means for acquiring latest information corresponding to the old information based on the analysis results, replacement means for replacing the old information with the acquired latest information, generation means for generating new digital content based on the information replaced by the replacement means, and storage and provision means for saving the generated new digital content and making it accessible to users. This makes it possible to automatically update old information included in digital content with the latest information.

[0858] The "uploading means" is a means by which a user uses a terminal to send digital content including old information to a server.

[0859] "Analysis means" means a means for analyzing uploaded digital content using a generative AI model to extract certain outdated information.

[0860] The "information acquisition means" is a means for acquiring the latest information from an internal database or an external information source based on the old information identified by the analysis means.

[0861] The "replacement means" is a means for updating the old information identified by the analysis means using the latest information obtained by the acquisition means.

[0862] The "generating means" is a means for generating new digital content based on the data replaced with the latest information by the replacing means.

[0863] The "storage and provision means" is a means for storing new digital content generated by the generation means in a database for long-term storage and making it accessible to users.

[0864] System Overview

[0865] The present invention provides a system for automatically updating digital content containing outdated information with the latest information and generating new digital content. The system includes an uploading unit, an analyzing unit, an information acquiring unit, a replacing unit, a generating unit, and a storing and providing unit. The following description describes the specific operation of each unit.

[0866] Upload method

[0867] Users upload digital content, including old information, using a web browser or dedicated application on their device (e.g., personal computer, tablet, or smartphone). The user clicks the upload button on the web interface or application to send the selected file to the server. For example, this is the operation of uploading a company's product introduction video.

[0868] Analysis means

[0869] The server receives the uploaded digital content and stores it in a temporary storage area. The server then analyzes the content using a generative AI model. The generative AI model analyzes the video frame by frame and converts the audio data into text. From the analysis results, "old information" is extracted. For example, information such as "latest model ABC" and "price $1,000" is extracted.

[0870] Information acquisition means

[0871] The server retrieves the latest information from an internal database or an external source (e.g., API) based on the old information extracted from the analysis. It uses a database query or API request to get the latest information, such as "New Model ABC" and "Price: $1200."

[0872] replacement means

[0873] The server replaces the outdated information identified by the analytical means with the latest information retrieved. This includes not only text data, but also audio data and visual elements. For example, "latest model ABC" could be replaced with "new model ABC" and "price $1,000" could be replaced with "price $1,200."

[0874] generation means

[0875] The server generates new digital content based on the new information, using synthetic speech technology and video editing tools to generate a naturally updated video, resulting in a new introductory video in which the old information is replaced with the latest information.

[0876] Storage and provision means

[0877] The server stores the new digital content in a database for long-term storage, and then generates and notifies the user of the new content with a link to access it, for example, via an email notification.

[0878] Specific examples

[0879] As a concrete example, consider a company's product introduction video. For example, a video introducing the latest model ABC at a price of $1,000 is uploaded one year later. In this example, the video is updated to include the latest information, "New Model ABC" and "Price: $1,200."

[0880] Example of input prompt for generative AI model

[0881] Here are some examples of prompts to input to a generative AI model:

[0882] Please analyze your old introduction video and update it with the latest model name and price information based on the information below:

[0883] New model name: New model ABC

[0884] New price: $1,200

[0885] This prompt ensures that the generative AI model generates digital content that is updated with the latest information.

[0886] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0887] Step 1:

[0888] Users upload content

[0889] The user uses a terminal to upload digital content including old information. The user clicks the upload button in the web interface or dedicated application to send the selected file to the server. The input is the digital content file specified by the user (e.g., "Old Product Introduction Video.mp4"), and the output is the file uploaded to the server.

[0890] Step 2:

[0891] The server analyzes the digital content

[0892] The server receives the uploaded digital content and stores it in a temporary storage area. The server inputs the video file into a generative AI model, which analyzes the content frame by frame. It converts the audio data into text and extracts old information from the analysis results. The input is the uploaded digital content file, and the output is the analyzed text data (e.g., "Latest Model ABC" and "Price: $1,000").

[0893] Step 3:

[0894] The server retrieves the latest information

[0895] Based on the analysis results, the server sends a query to obtain the latest information from an internal database or an external information source. The input is the analyzed text data, and the output is the obtained latest information data (e.g., "New model ABC" and "New price $1,200"). This is done using a database query or an API request.

[0896] Step 4:

[0897] The server replaces the old information with the latest information.

[0898] The server uses the acquired latest information to replace the old information identified by the analysis means. This includes text data, audio data, and visual elements. The input is the acquired latest information data and analyzed text data, and the output is the data replaced with the new information (e.g., updated text to "New Model ABC" and "New Price $1,200"). Specifically, the replacement operation is performed using a generative AI model.

[0899] Step 5:

[0900] The server generates new digital content.

[0901] The server generates new digital content based on the replaced information. Using synthetic voice technology and video editing tools, it generates a new introductory video and saves it in a temporary storage area. The input is the data replaced with the new information, and the output is the generated new digital content (e.g., a new video introducing "New Model ABC").

[0902] Step 6:

[0903] Servers store and serve new digital content

[0904] The server stores the generated new digital content in a database for long-term storage. It then generates a download link and notifies the user to make it accessible to the user. The input is the generated new digital content, and the output is the stored content and a notification message to the user (e.g., sending a link via email notification).

[0905] (Application example 1)

[0906] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0907] In the food service industry, menu information, prices, campaign information, and other information change frequently, making it important to keep this information up to date. However, traditional methods often require these updates to be done manually, which not only takes time and effort but also carries the risk of providing customers with incorrect information. To solve this problem, an automatic system for updating menu and price information is needed.

[0908] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0909] In this invention, the server includes an uploading means for uploading digital content including old information, an analyzing means for inputting the digital content into a generative AI model and analyzing the content, an information acquiring means for identifying old information based on the analysis results of the digital content and acquiring the latest information, a replacing means for replacing the old information with the acquired latest information, a generating means for generating new digital content based on the information updated by the replacing means, a storing and providing means for storing the generated new digital content and providing it to users, and a function for always keeping menu information and prices in food service up to date, thereby enabling the food service industry to always provide the latest information quickly and accurately.

[0910] "Uploading means" refers to the function by which a user sends digital content, including old information, to a server.

[0911] "Analysis means" refers to the function of using a generative AI model to analyze uploaded digital content and understand its contents.

[0912] "Information acquisition means" refers to the function of acquiring the latest information from external or internal information sources based on the analysis results.

[0913] The "replacement means" refers to a function that uses the acquired latest information to replace old information in the digital content with new information.

[0914] "Generation means" refers to the function of creating new digital content based on updated information.

[0915] "Storage and provision means" refers to the function of storing the newly generated digital content and providing it to users.

[0916] "Food service" refers to the general industry that provides food and beverages, including restaurants and food delivery services.

[0917] The present invention relates to a system for automatically keeping menu and pricing information up to date in the food service industry. The system includes the following major components:

[0918] Upload method

[0919] Users use their devices to upload digital content (e.g., menu images) containing outdated information to the server. This operation is performed through a dedicated application or a web interface.

[0920] Analysis means

[0921] The server then feeds the uploaded digital content into a generative AI model to analyze its contents. This involves using optical character recognition (OCR) technology to extract text from images and identify outdated information. For this purpose, the pytesseract and opencv libraries are used.

[0922] Information acquisition means

[0923] The server retrieves the latest menu information and prices from external or internal sources, typically by using the requests library to retrieve data from a remote API.

[0924] replacement means

[0925] The server uses the retrieved updated information to replace the old information identified by the analysis means with new information. This process is performed by text replacement, and the new menu information and prices are reflected in the digital content.

[0926] generation means

[0927] The server generates new digital content based on the updated information, and uses the OpenCV library to draw new text information on the image and generate a new menu image.

[0928] Storage and provision means

[0929] The server stores the newly generated digital content in a database and makes it accessible to users, so a download link for the new digital content is generated and notified to the user.

[0930] Main hardware and software used

[0931] Hardware: PC or Server

[0932] Software: Python, pytesseract, opencv, requests

[0933] Specific examples

[0934] For example, consider a restaurant that updates its weekly lunch menu. Users can upload an image of the old menu, and the system automatically updates it to reflect the new lunch menu. The old information in the uploaded image, "Curry rice 800 yen," is replaced with the new information, "Beef curry 900 yen."

[0935] Example prompts for generative AI models

[0936] Analyze the old lunch menu in the image below and update it with the new information: menu name, price, and description. For example, if the old menu item was "Curry rice 800 yen," change it to "Beef curry 900 yen."

[0937] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0938] Step 1: Upload your old digital content

[0939] A user uses a terminal to upload digital content (e.g., menu images) containing old menu information for a food service to a server. This operation is performed through a dedicated application or a web interface, and the content file is sent to the server. The input is the old menu image selected by the user, and the output is the uploaded image file.

[0940] Step 2: Analyzing the digital content

[0941] The server inputs the uploaded digital content into a generative AI model to analyze its contents. The server first uses the pytesseract library to extract text from images using optical character recognition (OCR) technology, and then identifies outdated menu information from the extracted text. The input is the uploaded image file, and the output is the extracted text data.

[0942] Step 3: Stay up to date

[0943] Based on the analysis results, the server retrieves the latest menu information and prices from external or internal sources. During this process, it uses the requests library to retrieve the necessary data from a remote API. The input is the parsed text data, and the output is the retrieved latest menu information.

[0944] Step 4: Replace old information

[0945] The server uses the acquired latest information to replace the old information identified by the analysis means with new information. This process is performed by text replacement. Specifically, the extracted old menu information is replaced with new menu information. The input is text data containing the old information and the latest information, and the output is text data containing the new menu information.

[0946] Step 5: Generate new digital content

[0947] The server generates new digital content based on the updated information. Using the OpenCV library, it draws the new text information on the image and generates a new menu image. The input is text data containing the new menu information, and the output is the new menu image.

[0948] Step 6: Store and serve

[0949] The server saves the generated new digital content in a database and makes it accessible to users. A download link for the new digital content is generated and notified to the user. The input is a new menu image, and the output is the image file saved in the database and notification information.

[0950] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0951] System Overview

[0952] The present invention combines a system that automatically updates digital content containing outdated information with the latest information and generates new digital content, with an emotion engine that recognizes user emotions. This system includes an uploading means, an analyzing means, an information acquisition means, a replacement means, a generating means, a storage and provision means, and an emotion engine. The operation of each means will be described below.

[0953] How it works

[0954] Upload method

[0955] User operations

[0956] Users upload old digital content from their devices (PCs, tablets, smartphones, etc.) by clicking an upload button using a web interface or a dedicated application.

[0957] Analysis means

[0958] Server Operations

[0959] The server inputs the uploaded digital content into a generative AI model to analyze the content. The analysis method analyzes the video content frame by frame, converts audio and subtitle data into text, and extracts specific outdated information.

[0960] Information acquisition means

[0961] Server Operations

[0962] The server retrieves the latest information from an internal database or an external source, and retrieves the latest data corresponding to the outdated information identified by the analysis means.

[0963] replacement means

[0964] Server Operations

[0965] The analyzed information is replaced with the latest information. This applies not only to text data, but also to audio data and visual elements.

[0966] generation means

[0967] Server Operations

[0968] New digital content is generated based on the data replaced with the latest information. The generation method uses synthesized voice and video editing tools to generate videos that naturally update old information with the latest information.

[0969] Storage and provision means

[0970] Server Operations

[0971] The newly generated digital content is transferred to a database for long-term storage and made accessible to users. The server generates a download link for the new content and notifies the user.

[0972] Emotion Engine

[0973] Server Operations

[0974] The server activates an emotion engine that recognizes emotions from the user's facial expressions, tone of voice, language, etc. The emotion engine analyzes emotions while the user is viewing digital content and customizes the content in real time.

[0975] Specific examples

[0976] For example, consider a company's product introduction video. If a product introduction video shows that the "latest model ABC" is currently priced at $1,000, then one year from now, that information will change to the "new model ABC" with a price of $1,200. In this case, the process will be as follows:

[0977] 1. User Input

[0978] The user uses the terminal to upload the old "Introduction video for the latest model ABC" to the server via the web interface.

[0979] 2. Server Operation - Analysis

[0980] The server inputs the uploaded video file into the generative AI model and identifies the "latest model ABC" and "current price $1,000."

[0981] 3. Server Operation - Getting the Latest Information

[0982] Retrieve information about "New Model ABC" and "New Price $1200" from the database.

[0983] 4. Server Operations - Information Replacement

[0984] Using a generative AI model, "Latest Model ABC" is replaced with "New Model ABC" and "Current Price $1,000" is replaced with "New Price $1,200."

[0985] 5. Server Operation - Creating a New Video

[0986] Generate a new introductory video based on new information.

[0987] 6. Server Operation - Storage and Serving

[0988] The new introductory video is saved in the database, a new download link is generated and notified to the user.

[0989] 7. Manipulating the Emotion Engine

[0990] As users watch new videos, the emotion engine analyzes their emotions and customizes the content in real time.

[0991] This allows users to quickly obtain digital content that always reflects the latest information without any hassle, and provides an optimal viewing experience that suits each individual's emotions.

[0992] The processing flow will be explained below.

[0993] Step 1:

[0994] User operations

[0995] Users select the old brand video file from their device and click the upload button using the web interface or a dedicated application, which sends the video file to the server.

[0996] Step 2:

[0997] Server Operations

[0998] The server receives the video file sent by the user and saves it in a temporary directory in the file system, while recording the video file path and metadata in a database.

[0999] Step 3:

[1000] Server Operations

[1001] The server passes the video file to a generative AI model and activates an analytical method. The generative AI model analyzes the video content frame by frame, converts audio to text, and extracts subtitle data, thereby identifying outdated information in the video.

[1002] Step 4:

[1003] Server Operations

[1004] The server accesses a database or external information source to retrieve up-to-date information that corresponds to outdated information identified by the analytical means, and retrieves up-to-date product and pricing information using database queries or API requests.

[1005] Step 5:

[1006] Server Operations

[1007] The server then uses the latest information to replace the old analyzed information. This includes not only text data, but also audio data and visual elements. The replacement process is automated, using voice synthesis and video editing techniques.

[1008] Step 6:

[1009] Server Operations

[1010] The server generates new digital content based on the data replaced with the latest information. The generation means integrates preprocessed text, audio data, and visual elements into a single video file.

[1011] Step 7:

[1012] Server Operations

[1013] The newly generated digital content is moved to a long-term storage directory, the database metadata is updated, and a download link is generated and provided to users to notify them.

[1014] Step 8:

[1015] User operations

[1016] The user clicks the link provided on the device to download the new digital content from the server. The downloaded video contains the latest updated information, so it can be provided to customers immediately.

[1017] Step 9:

[1018] Server Operations

[1019] The server activates an emotion engine to recognize emotions from the user's facial expressions, tone of voice, language, etc. While the user is viewing digital content, the emotion engine analyzes the user's emotions in real time.

[1020] Step 10:

[1021] Server Operations

[1022] The server changes the presentation order and content of digital content in real time based on the user's emotions recognized by the emotion engine, providing a viewing experience optimized for each user's emotional state.

[1023] Example 2

[1024] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1025] Modern digital content faces the challenge of becoming outdated quickly and requiring a great deal of time and effort to update. It is also difficult to customize digital content in real time to reflect the emotions and interests of each user. This leads to a homogenous user experience that fails to address individual needs.

[1026] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1027] In this invention, the server includes an uploading means for uploading digital content including old information, an analyzing means for inputting the digital content into a generative AI model and analyzing the content, an information acquiring means for identifying old information based on the analysis results of the digital content and acquiring the latest information, a replacing means for replacing the old information with the acquired latest information, a generating means for generating new digital content based on the information updated by the replacing means, a storing and providing means for storing the generated new digital content and providing it to the user, and an emotion engine for recognizing the user's emotions and customizing the digital content in real time, thereby enabling rapid updating of digital content and an optimized viewing experience for each user.

[1028] An "uploading mechanism" is a mechanism by which a user transfers digital content, including old information, to the system.

[1029] "Analysis means" refers to the means for inputting uploaded digital content into a generative AI model and analyzing its contents to identify outdated information.

[1030] The "information acquisition means" is a means for acquiring the latest information corresponding to the old information identified by the analysis means from an internal database or an external information source.

[1031] The "replacement means" is a means for replacing old information with new information using the acquired latest information.

[1032] The "generation means" is a means for generating new digital content based on data replaced with the latest information.

[1033] The "storage and provision means" refers to a means for storing the newly generated digital content and providing it in a form accessible to users.

[1034] An "emotion engine" is a means of analyzing a user's facial expressions, tone of voice, and language, and customizing digital content in real time according to the user's emotions.

[1035] A "generative AI model" is an artificial intelligence model used to analyze uploaded digital content and identify and replace outdated information.

[1036] To implement this invention, a system involving three main elements is used: a server, a terminal, and a user. This system automatically updates digital content, including old information, with the latest information, generates new digital content, and also incorporates an emotion engine that recognizes the user's emotions. Each means of this system is described in detail below.

[1037] Upload method

[1038] Users upload old digital content using a device (PC, tablet, smartphone, etc.). Specifically, users operate a web interface or dedicated application, click the upload button, and select the desired digital content file. This transfers the digital content to the server.

[1039] Analysis means

[1040] The server inputs the uploaded digital content into a generative AI model and analyzes its contents. During this process, the analysis means analyzes each frame of the video and converts the audio and subtitle data into text. From the analyzed text data, outdated information is identified. The generative AI model uses natural language processing and machine learning techniques.

[1041] Information acquisition means

[1042] The server retrieves the latest information from an internal database or an external source (such as an API). It searches for and retrieves the latest data corresponding to outdated information identified by the analysis method. For example, if a specific product name or price is outdated, it retrieves the corresponding latest product name and price information from the database.

[1043] replacement means

[1044] The server then uses the latest information to replace the old information it has analyzed. This replacement process involves not only text data, but also audio and visual elements. For example, the old product name is replaced with the new product name, and audio data is also replaced with the new information using synthesized speech technology.

[1045] generation means

[1046] The server generates new digital content based on the data replaced with the latest information. This generation method uses video editing tools (e.g., FFmpeg) and synthetic voice technology to create new, natural-looking, and consistent digital content.

[1047] Storage and provision means

[1048] The server then transfers the newly generated digital content to a long-term storage database, makes it accessible to users, generates a download link for the new digital content, and notifies the user via email or in-app notification.

[1049] Emotion Engine

[1050] While the user is viewing new digital content, the server activates an emotion engine that analyzes the user's facial expressions, tone of voice, and language data. This emotion engine analyzes the user's emotions in real time and customizes the digital content accordingly. For example, it adapts by displaying detailed information related to parts that the user is interested in and reducing the amount of information in parts that the user is not interested in.

[1051] Specific examples

[1052] For example, if a company has a product introduction video that includes the product name "old model XYZ" and the price "$100," the following steps would be taken:

[1053] 1. The user uses a terminal to upload an old product introduction video to the server via a web interface.

[1054] 2. The server inputs the video file into the generative AI model and identifies "old model XYZ" and "$100."

[1055] 3. Retrieve the new product name "New Model XYZ" and new price "$120" from the internal database.

[1056] 4. Use a generative AI model to replace "Old Model XYZ" with "New Model XYZ" and "$100" with "$120."

[1057] 5. Generate new digital content using video editing tools.

[1058] 6. Save the new video to the database, generate a download link and notify the user.

[1059] 7. As users watch new videos, the emotion engine analyzes their emotions and customizes their viewing experience in real time.

[1060] Prompt Sentence Examples

[1061] "Program the system to update the content of the video and customize it based on the user's emotions. For example, replace the old model name in a product introduction video with the new model name, and adjust the content in real time based on the user's emotions while watching."

[1062] This allows users to quickly obtain digital content that always reflects the latest information, and to have the optimal viewing experience that suits their individual emotions.

[1063] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1064] Step 1: Upload

[1065] Specific operation: Users use a device (PC, tablet, smartphone, etc.) to upload old digital content via a web interface or dedicated application.

[1066] Input: Digital content file (e.g. product introduction video)

[1067] Output: Digital content files uploaded to the server

[1068] Step 2: Analysis

[1069] How it works: The server feeds uploaded digital content into a generative AI model that analyzes its content, parsing each frame of video, converting audio and subtitle data into text, and identifying outdated information.

[1070] Input: Uploaded digital content file

[1071] Output: Text data containing outdated information (e.g., "Old Model XYZ", "$100")

[1072] Step 3: Information Acquisition

[1073] Specific operation: The server retrieves the latest information from an internal database or external information source (e.g., API). It searches for and retrieves the latest data corresponding to the old information identified by the analysis method.

[1074] Input: Text data containing outdated information (e.g., "Old Model XYZ," "$100")

[1075] Output: Data containing the latest information (e.g., "New Model XYZ," "$120")

[1076] Step 4: Substitution

[1077] What it does: The server replaces the old parsed information with the latest information it has retrieved. This replacement process involves not only replacing text data, but also synthesizing audio data and changing visual elements.

[1078] Input: Text data containing old information, data containing the latest information

[1079] Output: Data replaced with the latest information

[1080] Step 5: Generate

[1081] Specific operation: The server generates new digital content based on the data replaced with the latest information. The generation method uses video editing tools (e.g., FFmpeg) and synthetic voice technology to create new, natural, and consistent digital content.

[1082] Input: Data replaced with the latest information

[1083] Output: The new digital content file generated

[1084] Step 6: Store and serve

[1085] Specific operations: The server migrates the generated new digital content to a database for long-term storage and makes it accessible to users. It also generates a download link for the new digital content and notifies the user.

[1086] Input: The new digital content file that was generated

[1087] Output: Content stored in database and download link notification to user

[1088] Step 7: Launching the Emotion Engine and Customizing It in Real Time

[1089] Specific operation: The server activates the emotion engine while the user is viewing new digital content. The emotion engine analyzes the user's facial expressions, tone of voice, language data, etc., and customizes the digital content in real time. For example, it displays detailed related information in areas that the user is interested in, and reduces the amount of information in areas that the user is not interested in.

[1090] Input: User viewing data (e.g., facial expressions, tone of voice, language data) and digital content files

[1091] Output: Real-time customized digital content

[1092] This allows users to quickly obtain digital content that always reflects the latest information, and to have the optimal viewing experience that suits their individual emotions.

[1093] (Application example 2)

[1094] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1095] Modern digital content requires rapid updates, and the presence of outdated product information, especially on online shopping sites, can detract from the customer experience. In addition, a lack of real-time customization based on user preferences can also impact customer satisfaction. However, manual updates and customization require significant time and effort, creating a growing need for automated systems. The present invention aims to address these issues and provide an optimal digital experience that reflects the latest information while responding to user preferences.

[1096] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1097] In this invention, the server includes an uploading means for uploading digital content including old information, an analyzing means for inputting the digital content into a generating artificial intelligence model and analyzing the content, an information acquiring means for identifying old information based on the analysis result of the digital content and acquiring the latest information, a replacing means for replacing the old information with the acquired latest information, a generating means for generating new digital content based on the information updated by the replacing means, a storing and providing means for storing the generated new digital content and providing it to the user, a sentiment analyzing means for analyzing the user's sentiment and customizing the viewing experience in real time, and a prompt generating means for uploading information about specific products and generating new product introductions and reviews based on the latest information. This allows the latest information to be always reflected and enables the provision of an optimal shopping experience tailored to the user's sentiment.

[1098] "Outdated information" refers to information contained in digital content created in the past that is no longer accurate today.

[1099] "Digital content" means information or media represented or stored in electronic form.

[1100] "Uploading means" refers to a means by which a user transmits digital content, including old information, to a server.

[1101] A "generative artificial intelligence model" refers to an algorithm or entire system that uses machine learning and deep learning to analyze digital content and generate new content.

[1102] "Analysis means" means a means for inputting uploaded digital content into a generative artificial intelligence model to analyze the content and extract information.

[1103] The "information acquisition means" refers to a means for acquiring the latest information corresponding to the old information identified by the analysis means.

[1104] The "replacement means" refers to a means for replacing old information in the digital content with new information using the acquired latest information.

[1105] The "generation means" refers to a means for creating new digital content based on the information updated by the replacement means.

[1106] "Storage and provision means" refers to the means for storing the newly generated digital content and providing it in a form that allows users to access it.

[1107] An "emotion analysis means" is a means for analyzing emotions from a user's facial expressions, voice, etc., and using that information to customize the viewing experience in real time.

[1108] A "prompt generation means" is a means for uploading specific product information and generating new product introductions and reviews based on the latest information.

[1109] The present invention provides a system for automatically updating digital content, including outdated information, on an online shopping site to provide a customized shopping experience based on user emotions. The system includes an uploading unit, an analyzing unit, an information acquiring unit, a replacing unit, a generating unit, a storing and providing unit, an emotion analyzing unit, and a prompt generating unit.

[1110] Hardware and software used

[1111] Hardware: Smartphone (with camera and microphone)

[1112] software:

[1113] Generative AI models (e.g., GPT-4)

[1114] Synthetic speech tools (e.g., Amazon Polly)

[1115] Video editing software (e.g. Adobe Premiere Pro)

[1116] Emotion recognition engines (e.g., Affectiva, Emotion AI)

[1117] How it works

[1118] Upload method

[1119] Users first upload old product introduction videos and reviews using their smartphones, then use a dedicated application to click the upload button, which sends the data to the server.

[1120] Analysis means

[1121] The server then analyzes the uploaded digital content by feeding it into a generative AI model (e.g., GPT-4), which identifies outdated information in the content, such as "current price: $1,000."

[1122] Information acquisition means

[1123] The server collects the latest information from an internal database or external sources, for example, the latest product information and pricing data.

[1124] replacement means

[1125] The old parsed information is replaced with the latest information retrieved. For example, "Current price $1000" is replaced with "New price $1200."

[1126] generation means

[1127] Based on the replaced information, new product introduction videos and reviews are generated using synthetic voice tools and video editing software, creating new digital content that is natural to the eye and ear.

[1128] Storage and provision means

[1129] The new content generated is stored in a long-term database and made available on the server for user access, who receives a download link for the new content.

[1130] Emotion analysis means

[1131] While a user is viewing new content, an emotion recognition engine (e.g., Affectiva) uses the smartphone's camera and microphone to analyze emotions in real time, providing a customized viewing experience, such as displaying positive product reviews if the user is happy.

[1132] Specific examples

[1133] For example, if a user wants to update the "Product Description with Current Price of $1000," they would enter the following prompt text:

[1134] "Please update the product description from its current price of $1000 to $1200."

[1135] Based on this, the server generates new digital content based on the latest price information and provides it to users at the appropriate time using sentiment analysis.

[1136] This allows the system of the present invention to always reflect the latest information and provide the optimal shopping experience according to the user's emotions.

[1137] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1138] Step 1:

[1139] Users upload old product videos and reviews using their own devices by clicking the upload button within a specific application. The input of this step is the old digital content, and the output is the data sent to the server.

[1140] Step 2:

[1141] The server inputs the uploaded digital content into a generative AI model (e.g., GPT-4). This starts the analysis of the digital content. The input of this step is the digital content sent by the user, and the output is the analysis results. The specific operation of the analysis is to analyze the text and audio in the digital content and identify outdated information.

[1142] Step 3:

[1143] The server identifies outdated information based on the analysis results and retrieves the latest information from an internal database or external information source. The input to this step is the outdated information identified as a result of the analysis, and the output is the latest information. Specifically, the latest price information and product specifications are retrieved from the database using an API.

[1144] Step 4:

[1145] The server replaces the identified outdated information with the latest information. The inputs to this step are the identified outdated information and the acquired latest information, and the output is the replaced new information. The specific operation is to edit the text data, audio data, and visual data to reflect the latest information.

[1146] Step 5:

[1147] The server generates new product introduction videos and reviews based on the replaced information. The input of this step is the replaced information, and the output is new digital content. Specifically, the new digital content is generated using a synthetic voice tool (e.g., Amazon Polly) or video editing software (e.g., Adobe Premiere Pro).

[1148] Step 6:

[1149] The server stores the generated new digital content and provides it to the user. The input of this step is the new digital content, and the output is data stored in a long-term storage database and information provided to the user. Specific operations include storing the digital content in the database, generating a sharing link, and notifying the user.

[1150] Step 7:

[1151] While a user is viewing new digital content, emotion analysis is performed using the smartphone's built-in camera and microphone. The input for this step is the user's facial and voice data, and the output is analyzed emotional information. Specifically, an emotion recognition engine (e.g., Affectiva, Emotion AI) is used to monitor the user's emotions in real time.

[1152] Step 8:

[1153] Based on the results of the emotion analysis, the server uses a prompt generation means to display customized product introductions and reviews according to the user's emotions. The input of this step is the analyzed emotion information, and the output is customized viewing content. Specifically, the server generates prompts to provide new product introductions and reviews to the user in real time.

[1154] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1155] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1156] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1157] [Fourth embodiment]

[1158] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1159] 7, a 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.

[1160] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1161] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1162] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1163] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1164] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1165] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1166] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1167] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1168] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1169] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1170] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1171] System Overview

[1172] The present invention relates to a system that automatically updates digital content containing outdated information to the latest information and generates new digital content. The system includes an uploading unit, an analyzing unit, an information acquiring unit, a replacing unit, a generating unit, and a storing and providing unit. The operation of each unit is described below.

[1173] How it works

[1174] Upload method

[1175] User Input

[1176] Users upload digital content, including old information, from their devices (PCs, tablets, smartphones, etc.) by clicking an upload button using a web interface or a dedicated application.

[1177] Analysis means

[1178] Server Operations

[1179] The server inputs the uploaded digital content into a generative AI model to analyze the content. The analysis method analyzes the video content frame by frame, converts audio and subtitle data into text, and extracts specific outdated information.

[1180] Information acquisition means

[1181] Server Operations

[1182] The server retrieves the latest information from an internal database or an external source, thereby obtaining the latest data corresponding to the outdated information identified by the analysis means.

[1183] replacement means

[1184] Server Operations

[1185] The analyzed information is replaced with the latest information. This applies not only to text data, but also to audio data and visual elements.

[1186] generation means

[1187] Server Operations

[1188] New digital content is generated based on the data replaced with the latest information. Specifically, using synthetic voice and video editing tools, old information is updated with the latest information in a natural way to create videos.

[1189] Storage and provision means

[1190] Server Operations

[1191] The newly generated digital content is transferred to a database for long-term storage and made accessible to users. The server generates a download link for the new content and notifies the user.

[1192] Specific examples

[1193] As a concrete example, consider a company's product introduction video. For example, if a product introduction video shows that the "latest model ABC" is currently priced at $1,000, then one year from now, that information will change to the "new model ABC" with a price of $1,200.

[1194] 1. User Input

[1195] The user uses the terminal to upload the old "Introduction video for the latest model ABC" to the server via the web interface.

[1196] 2. Server Operation - Analysis

[1197] The server inputs the uploaded video file into the generative AI model and identifies the "latest model ABC" and "current price $1,000."

[1198] 3. Server Operation - Getting the Latest Information

[1199] Retrieve information about "New Model ABC" and "New Price $1200" from the database.

[1200] 4. Server Operations - Information Replacement

[1201] Using a generative AI model, "Latest Model ABC" is replaced with "New Model ABC" and "Current Price $1,000" is replaced with "New Price $1,200."

[1202] 5. Server Operation - Creating a New Video

[1203] Generate a new introductory video based on new information.

[1204] 6. Server Operation - Storage and Serving

[1205] The new introductory video is saved in the database, a new download link is generated and notified to the user.

[1206] This allows users to quickly obtain digital content that always reflects the latest information without any hassle.

[1207] The processing flow will be explained below.

[1208] Step 1:

[1209] User operations

[1210] Users select the old brand video file from their device and click the upload button using the web interface or a dedicated application, which sends the video file to the server.

[1211] Step 2:

[1212] Server Operations

[1213] The server receives the video file sent by the user and saves it in a temporary directory in the file system, while recording the video file path and metadata in a database.

[1214] Step 3:

[1215] Server Operations

[1216] The server passes the video file to a generative AI model and activates an analytical method. The generative AI model analyzes the video content frame by frame, converts audio to text, and extracts subtitle data, thereby identifying outdated information in the video.

[1217] Step 4:

[1218] Server Operations

[1219] The server accesses a database or external information source to retrieve up-to-date information that corresponds to outdated information identified by the analytical means, and retrieves up-to-date product and pricing information using database queries or API requests.

[1220] Step 5:

[1221] Server Operations

[1222] The server then uses the latest information to replace the old analyzed information. This includes not only text data, but also audio data and visual elements. The replacement process is automated, using voice synthesis and video editing techniques.

[1223] Step 6:

[1224] Server Operations

[1225] The server generates new digital content based on the data replaced with the latest information. The generation means integrates preprocessed text, audio data, and visual elements into a single video file.

[1226] Step 7:

[1227] Server Operations

[1228] The newly generated digital content is moved to a long-term storage directory, the database metadata is updated, and a download link is generated and provided to users to notify them.

[1229] Step 8:

[1230] User operations

[1231] The user clicks the link provided on the device to download the new digital content from the server. The downloaded video contains the latest updated information, so it can be provided to customers immediately.

[1232] Example 1

[1233] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1234] Digital content often becomes outdated after it is created, which can lead to misunderstandings among viewers. For example, price and model information in product introduction videos changes very quickly. However, manually updating this information is time-consuming, costly, and inefficient. Therefore, there is a need to provide a method for automatically updating outdated information and generating new digital content.

[1235] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1236] In this invention, the server includes uploading means for uploading digital content including old information from a device used by a user, analysis means for inputting the digital content into a generative AI model to analyze the content and extract specific old information, information acquisition means for acquiring latest information corresponding to the old information based on the analysis results, replacement means for replacing the old information with the acquired latest information, generation means for generating new digital content based on the information replaced by the replacement means, and storage and provision means for saving the generated new digital content and making it accessible to users. This makes it possible to automatically update old information included in digital content with the latest information.

[1237] The "uploading means" is a means by which a user uses a terminal to send digital content including old information to a server.

[1238] "Analysis means" means a means for analyzing uploaded digital content using a generative AI model to extract certain outdated information.

[1239] The "information acquisition means" is a means for acquiring the latest information from an internal database or an external information source based on the old information identified by the analysis means.

[1240] The "replacement means" is a means for updating the old information identified by the analysis means using the latest information obtained by the acquisition means.

[1241] The "generating means" is a means for generating new digital content based on the data replaced with the latest information by the replacing means.

[1242] The "storage and provision means" is a means for storing new digital content generated by the generation means in a database for long-term storage and making it accessible to users.

[1243] System Overview

[1244] The present invention provides a system for automatically updating digital content containing outdated information with the latest information and generating new digital content. The system includes an uploading unit, an analyzing unit, an information acquiring unit, a replacing unit, a generating unit, and a storing and providing unit. The following description describes the specific operation of each unit.

[1245] Upload method

[1246] Users upload digital content, including old information, using a web browser or dedicated application on their device (e.g., personal computer, tablet, or smartphone). The user clicks the upload button on the web interface or application to send the selected file to the server. For example, this is the operation of uploading a company's product introduction video.

[1247] Analysis means

[1248] The server receives the uploaded digital content and stores it in a temporary storage area. The server then analyzes the content using a generative AI model. The generative AI model analyzes the video frame by frame and converts the audio data into text. From the analysis results, "old information" is extracted. For example, information such as "latest model ABC" and "price $1,000" is extracted.

[1249] Information acquisition means

[1250] The server retrieves the latest information from an internal database or an external source (e.g., API) based on the old information extracted from the analysis. It uses a database query or API request to get the latest information, such as "New Model ABC" and "Price: $1200."

[1251] replacement means

[1252] The server replaces the outdated information identified by the analytical means with the latest information retrieved. This includes not only text data, but also audio data and visual elements. For example, "latest model ABC" could be replaced with "new model ABC" and "price $1,000" could be replaced with "price $1,200."

[1253] generation means

[1254] The server generates new digital content based on the new information, using synthetic speech technology and video editing tools to generate a naturally updated video, resulting in a new introductory video in which the old information is replaced with the latest information.

[1255] Storage and provision means

[1256] The server stores the new digital content in a database for long-term storage, and then generates and notifies the user of the new content with a link to access it, for example, via an email notification.

[1257] Specific examples

[1258] As a concrete example, consider a company's product introduction video. For example, a video introducing the latest model ABC at a price of $1,000 is uploaded one year later. In this example, the video is updated to include the latest information, "New Model ABC" and "Price: $1,200."

[1259] Example of input prompt for generative AI model

[1260] Here are some examples of prompts to input to a generative AI model:

[1261] Please analyze your old introduction video and update it with the latest model name and price information based on the information below:

[1262] New model name: New model ABC

[1263] New price: $1,200

[1264] This prompt ensures that the generative AI model generates digital content that is updated with the latest information.

[1265] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1266] Step 1:

[1267] Users upload content

[1268] The user uses a terminal to upload digital content including old information. The user clicks the upload button in the web interface or dedicated application to send the selected file to the server. The input is the digital content file specified by the user (e.g., "Old Product Introduction Video.mp4"), and the output is the file uploaded to the server.

[1269] Step 2:

[1270] The server analyzes the digital content

[1271] The server receives the uploaded digital content and stores it in a temporary storage area. The server inputs the video file into a generative AI model, which analyzes the content frame by frame. It converts the audio data into text and extracts old information from the analysis results. The input is the uploaded digital content file, and the output is the analyzed text data (e.g., "Latest Model ABC" and "Price: $1,000").

[1272] Step 3:

[1273] The server retrieves the latest information

[1274] Based on the analysis results, the server sends a query to obtain the latest information from an internal database or an external information source. The input is the analyzed text data, and the output is the obtained latest information data (e.g., "New model ABC" and "New price $1,200"). This is done using a database query or an API request.

[1275] Step 4:

[1276] The server replaces the old information with the latest information.

[1277] The server uses the acquired latest information to replace the old information identified by the analysis means. This includes text data, audio data, and visual elements. The input is the acquired latest information data and analyzed text data, and the output is the data replaced with the new information (e.g., updated text to "New Model ABC" and "New Price $1,200"). Specifically, the replacement operation is performed using a generative AI model.

[1278] Step 5:

[1279] The server generates new digital content.

[1280] The server generates new digital content based on the replaced information. Using synthetic voice technology and video editing tools, it generates a new introductory video and saves it in a temporary storage area. The input is the data replaced with the new information, and the output is the generated new digital content (e.g., a new video introducing "New Model ABC").

[1281] Step 6:

[1282] Servers store and serve new digital content

[1283] The server stores the generated new digital content in a database for long-term storage. It then generates a download link and notifies the user to make it accessible to the user. The input is the generated new digital content, and the output is the stored content and a notification message to the user (e.g., sending a link via email notification).

[1284] (Application example 1)

[1285] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1286] In the food service industry, menu information, prices, campaign information, and other information change frequently, making it important to keep this information up to date. However, traditional methods often require these updates to be done manually, which not only takes time and effort but also carries the risk of providing customers with incorrect information. To solve this problem, an automatic system for updating menu and price information is needed.

[1287] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1288] In this invention, the server includes an uploading means for uploading digital content including old information, an analyzing means for inputting the digital content into a generative AI model and analyzing the content, an information acquiring means for identifying old information based on the analysis results of the digital content and acquiring the latest information, a replacing means for replacing the old information with the acquired latest information, a generating means for generating new digital content based on the information updated by the replacing means, a storing and providing means for storing the generated new digital content and providing it to users, and a function for always keeping menu information and prices in food service up to date, thereby enabling the food service industry to always provide the latest information quickly and accurately.

[1289] "Uploading means" refers to the function by which a user sends digital content, including old information, to a server.

[1290] "Analysis means" refers to the function of using a generative AI model to analyze uploaded digital content and understand its contents.

[1291] "Information acquisition means" refers to the function of acquiring the latest information from external or internal information sources based on the analysis results.

[1292] The "replacement means" refers to a function that uses the acquired latest information to replace old information in the digital content with new information.

[1293] "Generation means" refers to the function of creating new digital content based on updated information.

[1294] "Storage and provision means" refers to the function of storing the newly generated digital content and providing it to users.

[1295] "Food service" refers to the general industry that provides food and beverages, including restaurants and food delivery services.

[1296] The present invention relates to a system for automatically keeping menu and pricing information up to date in the food service industry. The system includes the following major components:

[1297] Upload method

[1298] Users use their devices to upload digital content (e.g., menu images) containing outdated information to the server. This operation is performed through a dedicated application or a web interface.

[1299] Analysis means

[1300] The server then feeds the uploaded digital content into a generative AI model to analyze its contents. This involves using optical character recognition (OCR) technology to extract text from images and identify outdated information. For this purpose, the pytesseract and opencv libraries are used.

[1301] Information acquisition means

[1302] The server retrieves the latest menu information and prices from external or internal sources, typically by using the requests library to retrieve data from a remote API.

[1303] replacement means

[1304] The server uses the retrieved updated information to replace the old information identified by the analysis means with new information. This process is performed by text replacement, and the new menu information and prices are reflected in the digital content.

[1305] generation means

[1306] The server generates new digital content based on the updated information, and uses the OpenCV library to draw new text information on the image and generate a new menu image.

[1307] Storage and provision means

[1308] The server stores the newly generated digital content in a database and makes it accessible to users, so a download link for the new digital content is generated and notified to the user.

[1309] Main hardware and software used

[1310] Hardware: PC or Server

[1311] Software: Python, pytesseract, opencv, requests

[1312] Specific examples

[1313] For example, consider a restaurant that updates its weekly lunch menu. Users can upload an image of the old menu, and the system automatically updates it to reflect the new lunch menu. The old information in the uploaded image, "Curry rice 800 yen," is replaced with the new information, "Beef curry 900 yen."

[1314] Example prompts for generative AI models

[1315] Analyze the old lunch menu in the image below and update it with the new information: menu name, price, and description. For example, if the old menu item was "Curry rice 800 yen," change it to "Beef curry 900 yen."

[1316] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1317] Step 1: Upload your old digital content

[1318] A user uses a terminal to upload digital content (e.g., menu images) containing old menu information for a food service to a server. This operation is performed through a dedicated application or a web interface, and the content file is sent to the server. The input is the old menu image selected by the user, and the output is the uploaded image file.

[1319] Step 2: Analyzing the digital content

[1320] The server inputs the uploaded digital content into a generative AI model to analyze its contents. The server first uses the pytesseract library to extract text from images using optical character recognition (OCR) technology, and then identifies outdated menu information from the extracted text. The input is the uploaded image file, and the output is the extracted text data.

[1321] Step 3: Stay up to date

[1322] Based on the analysis results, the server retrieves the latest menu information and prices from external or internal sources. During this process, it uses the requests library to retrieve the necessary data from a remote API. The input is the parsed text data, and the output is the retrieved latest menu information.

[1323] Step 4: Replace old information

[1324] The server uses the acquired latest information to replace the old information identified by the analysis means with new information. This process is performed by text replacement. Specifically, the extracted old menu information is replaced with new menu information. The input is text data containing the old information and the latest information, and the output is text data containing the new menu information.

[1325] Step 5: Generate new digital content

[1326] The server generates new digital content based on the updated information. Using the OpenCV library, it draws the new text information on the image and generates a new menu image. The input is text data containing the new menu information, and the output is the new menu image.

[1327] Step 6: Store and serve

[1328] The server saves the generated new digital content in a database and makes it accessible to users. A download link for the new digital content is generated and notified to the user. The input is a new menu image, and the output is the image file saved in the database and notification information.

[1329] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1330] System Overview

[1331] The present invention combines a system that automatically updates digital content containing outdated information with the latest information and generates new digital content, with an emotion engine that recognizes user emotions. This system includes an uploading means, an analyzing means, an information acquisition means, a replacement means, a generating means, a storage and provision means, and an emotion engine. The operation of each means will be described below.

[1332] How it works

[1333] Upload method

[1334] User operations

[1335] Users upload old digital content from their devices (PCs, tablets, smartphones, etc.) by clicking an upload button using a web interface or a dedicated application.

[1336] Analysis means

[1337] Server Operations

[1338] The server inputs the uploaded digital content into a generative AI model to analyze the content. The analysis method analyzes the video content frame by frame, converts audio and subtitle data into text, and extracts specific outdated information.

[1339] Information acquisition means

[1340] Server Operations

[1341] The server retrieves the latest information from an internal database or an external source, and retrieves the latest data corresponding to the outdated information identified by the analysis means.

[1342] replacement means

[1343] Server Operations

[1344] The analyzed information is replaced with the latest information. This applies not only to text data, but also to audio data and visual elements.

[1345] generation means

[1346] Server Operations

[1347] New digital content is generated based on the data replaced with the latest information. The generation method uses synthesized voice and video editing tools to generate videos that naturally update old information with the latest information.

[1348] Storage and provision means

[1349] Server Operations

[1350] The newly generated digital content is transferred to a database for long-term storage and made accessible to users. The server generates a download link for the new content and notifies the user.

[1351] Emotion Engine

[1352] Server Operations

[1353] The server activates an emotion engine that recognizes emotions from the user's facial expressions, tone of voice, language, etc. The emotion engine analyzes emotions while the user is viewing digital content and customizes the content in real time.

[1354] Specific examples

[1355] For example, consider a company's product introduction video. If a product introduction video shows that the "latest model ABC" is currently priced at $1,000, then one year from now, that information will change to the "new model ABC" with a price of $1,200. In this case, the process will be as follows:

[1356] 1. User Input

[1357] The user uses the terminal to upload the old "Introduction video for the latest model ABC" to the server via the web interface.

[1358] 2. Server Operation - Analysis

[1359] The server inputs the uploaded video file into the generative AI model and identifies the "latest model ABC" and "current price $1,000."

[1360] 3. Server Operation - Getting the Latest Information

[1361] Retrieve information about "New Model ABC" and "New Price $1200" from the database.

[1362] 4. Server Operations - Information Replacement

[1363] Using a generative AI model, "Latest Model ABC" is replaced with "New Model ABC" and "Current Price $1,000" is replaced with "New Price $1,200."

[1364] 5. Server Operation - Creating a New Video

[1365] Generate a new introductory video based on new information.

[1366] 6. Server Operation - Storage and Serving

[1367] The new introductory video is saved in the database, a new download link is generated and notified to the user.

[1368] 7. Manipulating the Emotion Engine

[1369] As users watch new videos, the emotion engine analyzes their emotions and customizes the content in real time.

[1370] This allows users to quickly obtain digital content that always reflects the latest information without any hassle, and provides an optimal viewing experience that suits each individual's emotions.

[1371] The processing flow will be explained below.

[1372] Step 1:

[1373] User operations

[1374] Users select the old brand video file from their device and click the upload button using the web interface or a dedicated application, which sends the video file to the server.

[1375] Step 2:

[1376] Server Operations

[1377] The server receives the video file sent by the user and saves it in a temporary directory in the file system, while recording the video file path and metadata in a database.

[1378] Step 3:

[1379] Server Operations

[1380] The server passes the video file to a generative AI model and activates an analytical method. The generative AI model analyzes the video content frame by frame, converts audio to text, and extracts subtitle data, thereby identifying outdated information in the video.

[1381] Step 4:

[1382] Server Operations

[1383] The server accesses a database or external information source to retrieve up-to-date information that corresponds to outdated information identified by the analytical means, and retrieves up-to-date product and pricing information using database queries or API requests.

[1384] Step 5:

[1385] Server Operations

[1386] The server then uses the latest information to replace the old analyzed information. This includes not only text data, but also audio data and visual elements. The replacement process is automated, using voice synthesis and video editing techniques.

[1387] Step 6:

[1388] Server Operations

[1389] The server generates new digital content based on the data replaced with the latest information. The generation means integrates preprocessed text, audio data, and visual elements into a single video file.

[1390] Step 7:

[1391] Server Operations

[1392] The newly generated digital content is moved to a long-term storage directory, the database metadata is updated, and a download link is generated and provided to users to notify them.

[1393] Step 8:

[1394] User operations

[1395] The user clicks the link provided on the device to download the new digital content from the server. The downloaded video contains the latest updated information, so it can be provided to customers immediately.

[1396] Step 9:

[1397] Server Operations

[1398] The server activates an emotion engine to recognize emotions from the user's facial expressions, tone of voice, language, etc. While the user is viewing digital content, the emotion engine analyzes the user's emotions in real time.

[1399] Step 10:

[1400] Server Operations

[1401] The server changes the presentation order and content of digital content in real time based on the user's emotions recognized by the emotion engine, providing a viewing experience optimized for each user's emotional state.

[1402] Example 2

[1403] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1404] Modern digital content faces the challenge of becoming outdated quickly and requiring a great deal of time and effort to update. It is also difficult to customize digital content in real time to reflect the emotions and interests of each user. This leads to a homogenous user experience that fails to address individual needs.

[1405] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1406] In this invention, the server includes an uploading means for uploading digital content including old information, an analyzing means for inputting the digital content into a generative AI model and analyzing the content, an information acquiring means for identifying old information based on the analysis results of the digital content and acquiring the latest information, a replacing means for replacing the old information with the acquired latest information, a generating means for generating new digital content based on the information updated by the replacing means, a storing and providing means for storing the generated new digital content and providing it to the user, and an emotion engine for recognizing the user's emotions and customizing the digital content in real time, thereby enabling rapid updating of digital content and an optimized viewing experience for each user.

[1407] An "uploading mechanism" is a mechanism by which a user transfers digital content, including old information, to the system.

[1408] "Analysis means" refers to the means for inputting uploaded digital content into a generative AI model and analyzing its contents to identify outdated information.

[1409] The "information acquisition means" is a means for acquiring the latest information corresponding to the old information identified by the analysis means from an internal database or an external information source.

[1410] The "replacement means" is a means for replacing old information with new information using the acquired latest information.

[1411] The "generation means" is a means for generating new digital content based on data replaced with the latest information.

[1412] The "storage and provision means" refers to a means for storing the newly generated digital content and providing it in a form accessible to users.

[1413] An "emotion engine" is a means of analyzing a user's facial expressions, tone of voice, and language, and customizing digital content in real time according to the user's emotions.

[1414] A "generative AI model" is an artificial intelligence model used to analyze uploaded digital content and identify and replace outdated information.

[1415] To implement this invention, a system involving three main elements is used: a server, a terminal, and a user. This system automatically updates digital content, including old information, with the latest information, generates new digital content, and also incorporates an emotion engine that recognizes the user's emotions. Each means of this system is described in detail below.

[1416] Upload method

[1417] Users upload old digital content using a device (PC, tablet, smartphone, etc.). Specifically, users operate a web interface or dedicated application, click the upload button, and select the desired digital content file. This transfers the digital content to the server.

[1418] Analysis means

[1419] The server inputs the uploaded digital content into a generative AI model and analyzes its contents. During this process, the analysis means analyzes each frame of the video and converts the audio and subtitle data into text. From the analyzed text data, outdated information is identified. The generative AI model uses natural language processing and machine learning techniques.

[1420] Information acquisition means

[1421] The server retrieves the latest information from an internal database or an external source (such as an API). It searches for and retrieves the latest data corresponding to outdated information identified by the analysis method. For example, if a specific product name or price is outdated, it retrieves the corresponding latest product name and price information from the database.

[1422] replacement means

[1423] The server then uses the latest information to replace the old information it has analyzed. This replacement process involves not only text data, but also audio and visual elements. For example, the old product name is replaced with the new product name, and audio data is also replaced with the new information using synthesized speech technology.

[1424] generation means

[1425] The server generates new digital content based on the data replaced with the latest information. This generation method uses video editing tools (e.g., FFmpeg) and synthetic voice technology to create new, natural-looking, and consistent digital content.

[1426] Storage and provision means

[1427] The server then transfers the newly generated digital content to a long-term storage database, makes it accessible to users, generates a download link for the new digital content, and notifies the user via email or in-app notification.

[1428] Emotion Engine

[1429] While the user is viewing new digital content, the server activates an emotion engine that analyzes the user's facial expressions, tone of voice, and language data. This emotion engine analyzes the user's emotions in real time and customizes the digital content accordingly. For example, it adapts by displaying detailed information related to parts that the user is interested in and reducing the amount of information in parts that the user is not interested in.

[1430] Specific examples

[1431] For example, if a company has a product introduction video that includes the product name "old model XYZ" and the price "$100," the following steps would be taken:

[1432] 1. The user uses a terminal to upload an old product introduction video to the server via a web interface.

[1433] 2. The server inputs the video file into the generative AI model and identifies "old model XYZ" and "$100."

[1434] 3. Retrieve the new product name "New Model XYZ" and new price "$120" from the internal database.

[1435] 4. Use a generative AI model to replace "Old Model XYZ" with "New Model XYZ" and "$100" with "$120."

[1436] 5. Generate new digital content using video editing tools.

[1437] 6. Save the new video to the database, generate a download link and notify the user.

[1438] 7. As users watch new videos, the emotion engine analyzes their emotions and customizes their viewing experience in real time.

[1439] Prompt Sentence Examples

[1440] "Program the system to update the content of the video and customize it based on the user's emotions. For example, replace the old model name in a product introduction video with the new model name, and adjust the content in real time based on the user's emotions while watching."

[1441] This allows users to quickly obtain digital content that always reflects the latest information, and to have the optimal viewing experience that suits their individual emotions.

[1442] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1443] Step 1: Upload

[1444] Specific operation: Users use a device (PC, tablet, smartphone, etc.) to upload old digital content via a web interface or dedicated application.

[1445] Input: Digital content file (e.g. product introduction video)

[1446] Output: Digital content files uploaded to the server

[1447] Step 2: Analysis

[1448] How it works: The server feeds uploaded digital content into a generative AI model that analyzes its content, parsing each frame of video, converting audio and subtitle data into text, and identifying outdated information.

[1449] Input: Uploaded digital content file

[1450] Output: Text data containing outdated information (e.g., "Old Model XYZ", "$100")

[1451] Step 3: Information Acquisition

[1452] Specific operation: The server retrieves the latest information from an internal database or external information source (e.g., API). It searches for and retrieves the latest data corresponding to the old information identified by the analysis method.

[1453] Input: Text data containing outdated information (e.g., "Old Model XYZ," "$100")

[1454] Output: Data containing the latest information (e.g., "New Model XYZ," "$120")

[1455] Step 4: Substitution

[1456] What it does: The server replaces the old parsed information with the latest information it has retrieved. This replacement process involves not only replacing text data, but also synthesizing audio data and changing visual elements.

[1457] Input: Text data containing old information, data containing the latest information

[1458] Output: Data replaced with the latest information

[1459] Step 5: Generate

[1460] Specific operation: The server generates new digital content based on the data replaced with the latest information. The generation method uses video editing tools (e.g., FFmpeg) and synthetic voice technology to create new, natural, and consistent digital content.

[1461] Input: Data replaced with the latest information

[1462] Output: The new digital content file generated

[1463] Step 6: Store and serve

[1464] Specific operations: The server migrates the generated new digital content to a database for long-term storage and makes it accessible to users. It also generates a download link for the new digital content and notifies the user.

[1465] Input: The new digital content file that was generated

[1466] Output: Content stored in database and download link notification to user

[1467] Step 7: Launching the Emotion Engine and Customizing It in Real Time

[1468] Specific operation: The server activates the emotion engine while the user is viewing new digital content. The emotion engine analyzes the user's facial expressions, tone of voice, language data, etc., and customizes the digital content in real time. For example, it displays detailed related information in areas that the user is interested in, and reduces the amount of information in areas that the user is not interested in.

[1469] Input: User viewing data (e.g., facial expressions, tone of voice, language data) and digital content files

[1470] Output: Real-time customized digital content

[1471] This allows users to quickly obtain digital content that always reflects the latest information, and to have the optimal viewing experience that suits their individual emotions.

[1472] (Application example 2)

[1473] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1474] Modern digital content requires rapid updates, and the presence of outdated product information, especially on online shopping sites, can detract from the customer experience. In addition, a lack of real-time customization based on user preferences can also impact customer satisfaction. However, manual updates and customization require significant time and effort, creating a growing need for automated systems. The present invention aims to address these issues and provide an optimal digital experience that reflects the latest information while responding to user preferences.

[1475] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1476] In this invention, the server includes an uploading means for uploading digital content including old information, an analyzing means for inputting the digital content into a generating artificial intelligence model and analyzing the content, an information acquiring means for identifying old information based on the analysis result of the digital content and acquiring the latest information, a replacing means for replacing the old information with the acquired latest information, a generating means for generating new digital content based on the information updated by the replacing means, a storing and providing means for storing the generated new digital content and providing it to the user, a sentiment analyzing means for analyzing the user's sentiment and customizing the viewing experience in real time, and a prompt generating means for uploading information about specific products and generating new product introductions and reviews based on the latest information. This allows the latest information to be always reflected and enables the provision of an optimal shopping experience tailored to the user's sentiment.

[1477] "Outdated information" refers to information contained in digital content created in the past that is no longer accurate today.

[1478] "Digital content" means information or media represented or stored in electronic form.

[1479] "Uploading means" refers to a means by which a user transmits digital content, including old information, to a server.

[1480] A "generative artificial intelligence model" refers to an algorithm or entire system that uses machine learning and deep learning to analyze digital content and generate new content.

[1481] "Analysis means" means a means for inputting uploaded digital content into a generative artificial intelligence model to analyze the content and extract information.

[1482] The "information acquisition means" refers to a means for acquiring the latest information corresponding to the old information identified by the analysis means.

[1483] The "replacement means" refers to a means for replacing old information in the digital content with new information using the acquired latest information.

[1484] The "generation means" refers to a means for creating new digital content based on the information updated by the replacement means.

[1485] "Storage and provision means" refers to the means for storing the newly generated digital content and providing it in a form that allows users to access it.

[1486] An "emotion analysis means" is a means for analyzing emotions from a user's facial expressions, voice, etc., and using that information to customize the viewing experience in real time.

[1487] A "prompt generation means" is a means for uploading specific product information and generating new product introductions and reviews based on the latest information.

[1488] The present invention provides a system for automatically updating digital content, including outdated information, on an online shopping site to provide a customized shopping experience based on user emotions. The system includes an uploading unit, an analyzing unit, an information acquiring unit, a replacing unit, a generating unit, a storing and providing unit, an emotion analyzing unit, and a prompt generating unit.

[1489] Hardware and software used

[1490] Hardware: Smartphone (with camera and microphone)

[1491] software:

[1492] Generative AI models (e.g., GPT-4)

[1493] Synthetic speech tools (e.g., Amazon Polly)

[1494] Video editing software (e.g. Adobe Premiere Pro)

[1495] Emotion recognition engines (e.g., Affectiva, Emotion AI)

[1496] How it works

[1497] Upload method

[1498] Users first upload old product introduction videos and reviews using their smartphones, then use a dedicated application to click the upload button, which sends the data to the server.

[1499] Analysis means

[1500] The server then analyzes the uploaded digital content by feeding it into a generative AI model (e.g., GPT-4), which identifies outdated information in the content, such as "current price: $1,000."

[1501] Information acquisition means

[1502] The server collects the latest information from an internal database or external sources, for example, the latest product information and pricing data.

[1503] replacement means

[1504] The old parsed information is replaced with the latest information retrieved. For example, "Current price $1000" is replaced with "New price $1200."

[1505] generation means

[1506] Based on the replaced information, new product introduction videos and reviews are generated using synthetic voice tools and video editing software, creating new digital content that is natural to the eye and ear.

[1507] Storage and provision means

[1508] The new content generated is stored in a long-term database and made available on the server for user access, who receives a download link for the new content.

[1509] Emotion analysis means

[1510] While a user is viewing new content, an emotion recognition engine (e.g., Affectiva) uses the smartphone's camera and microphone to analyze emotions in real time, providing a customized viewing experience, such as displaying positive product reviews if the user is happy.

[1511] Specific examples

[1512] For example, if a user wants to update the "Product Description with Current Price of $1000," they would enter the following prompt text:

[1513] "Please update the product description from its current price of $1000 to $1200."

[1514] Based on this, the server generates new digital content based on the latest price information and provides it to users at the appropriate time using sentiment analysis.

[1515] This allows the system of the present invention to always reflect the latest information and provide the optimal shopping experience according to the user's emotions.

[1516] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1517] Step 1:

[1518] Users upload old product videos and reviews using their own devices by clicking the upload button within a specific application. The input of this step is the old digital content, and the output is the data sent to the server.

[1519] Step 2:

[1520] The server inputs the uploaded digital content into a generative AI model (e.g., GPT-4). This starts the analysis of the digital content. The input of this step is the digital content sent by the user, and the output is the analysis results. The specific operation of the analysis is to analyze the text and audio in the digital content and identify outdated information.

[1521] Step 3:

[1522] The server identifies outdated information based on the analysis results and retrieves the latest information from an internal database or external information source. The input to this step is the outdated information identified as a result of the analysis, and the output is the latest information. Specifically, the latest price information and product specifications are retrieved from the database using an API.

[1523] Step 4:

[1524] The server replaces the identified outdated information with the latest information. The inputs to this step are the identified outdated information and the acquired latest information, and the output is the replaced new information. The specific operation is to edit the text data, audio data, and visual data to reflect the latest information.

[1525] Step 5:

[1526] The server generates new product introduction videos and reviews based on the replaced information. The input of this step is the replaced information, and the output is new digital content. Specifically, the new digital content is generated using a synthetic voice tool (e.g., Amazon Polly) or video editing software (e.g., Adobe Premiere Pro).

[1527] Step 6:

[1528] The server stores the generated new digital content and provides it to the user. The input of this step is the new digital content, and the output is data stored in a long-term storage database and information provided to the user. Specific operations include storing the digital content in the database, generating a sharing link, and notifying the user.

[1529] Step 7:

[1530] While a user is viewing new digital content, emotion analysis is performed using the smartphone's built-in camera and microphone. The input for this step is the user's facial and voice data, and the output is analyzed emotional information. Specifically, an emotion recognition engine (e.g., Affectiva, Emotion AI) is used to monitor the user's emotions in real time.

[1531] Step 8:

[1532] Based on the results of the emotion analysis, the server uses a prompt generation means to display customized product introductions and reviews according to the user's emotions. The input of this step is the analyzed emotion information, and the output is customized viewing content. Specifically, the server generates prompts to provide new product introductions and reviews to the user in real time.

[1533] 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 control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1534] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1535] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1536] The emotion identification model 59 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 an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1537] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1538] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1539] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1540] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1541] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs 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 a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1542] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1543] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1544] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1545] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1546] 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.

[1547] It is not necessary to store all 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 all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1548] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1549] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific processing may be a single processor.

[1550] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1551] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1552] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1553] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1554] The following is further disclosed regarding the above embodiment.

[1555] (Claim 1)

[1556] uploading means for uploading digital content including outdated information;

[1557] analysis means for inputting the digital content into a generative artificial intelligence model to analyze the content;

[1558] an information acquisition means for identifying old information based on the analysis result of the digital content and acquiring the latest information;

[1559] a replacement means for replacing the old information with the obtained latest information;

[1560] a generating means for generating new digital content based on the information updated by the replacing means;

[1561] The system includes a storage and provision means for storing the generated new digital content and providing it to a user.

[1562] (Claim 2)

[1563] 2. The system of claim 1, wherein the generative artificial intelligence model automatically detects outdated information by analyzing subtitles and audio.

[1564] (Claim 3)

[1565] 2. The system of claim 1, wherein the information acquisition means acquires up-to-date information from an internal database or an external information source.

[1566] "Example 1"

[1567] (Claim 1)

[1568] uploading means for uploading digital content including old information from a device used by a user;

[1569] analysis means for inputting the digital content into a generative AI model to analyze the content and extract specific outdated information;

[1570] information acquisition means for acquiring the latest information corresponding to the old information based on the analysis result;

[1571] a replacement means for replacing the old information with the obtained latest information;

[1572] a generating means for generating new digital content based on the information replaced by the replacing means;

[1573] The system includes a storage and provision means for storing the generated new digital content and making it accessible to users.

[1574] (Claim 2)

[1575] 2. The system of claim 1, wherein the generative AI model automatically detects outdated information by analyzing subtitles and audio within a video.

[1576] (Claim 3)

[1577] 2. The system of claim 1, wherein the information acquisition means acquires up-to-date information from an internal database or an external information source.

[1578] "Application Example 1"

[1579] (Claim 1)

[1580] uploading means for uploading digital content including outdated information;

[1581] analysis means for inputting the digital content into a generative AI model to analyze the content;

[1582] an information acquisition means for identifying old information based on the analysis result of the digital content and acquiring the latest information;

[1583] a replacement means for replacing the old information with the obtained latest information;

[1584] a generating means for generating new digital content based on the information updated by the replacing means;

[1585] a storage and provision means for storing the generated new digital content and providing it to a user;

[1586] A system that includes functionality to keep food service menu information and prices up to date.

[1587] (Claim 2)

[1588] 10. The system of claim 1, wherein the generative AI model automatically detects outdated information by analyzing text, images, and text using optical character recognition technology.

[1589] (Claim 3)

[1590] 10. The system of claim 1, wherein said information obtaining means obtains new menu information and prices from external or internal sources.

[1591] "Example 2: Combining Emotion Engines"

[1592] (Claim 1)

[1593] uploading means for uploading digital content including outdated information;

[1594] analysis means for inputting the digital content into a generative AI model to analyze the content;

[1595] an information acquisition means for identifying old information based on the analysis result of the digital content and acquiring the latest information;

[1596] a replacement means for replacing the old information with the obtained latest information;

[1597] a generating means for generating new digital content based on the information updated by the replacing means;

[1598] a storage and provision means for storing the generated new digital content and providing it to a user;

[1599] A system including an emotion engine for recognizing user emotions and customizing digital content in real time.

[1600] (Claim 2)

[1601] 10. The system of claim 1, wherein the generative AI model analyzes subtitles and audio to automatically detect outdated information.

[1602] (Claim 3)

[1603] 2. The system of claim 1, wherein the information acquisition means acquires up-to-date information from an internal database or an external information source.

[1604] "Application example 2 when combining emotion engines"

[1605] (Claim 1)

[1606] uploading means for uploading digital content including outdated information;

[1607] analysis means for inputting the digital content into a generative artificial intelligence model to analyze the content;

[1608] an information acquisition means for identifying old information based on the analysis result of the digital content and acquiring the latest information;

[1609] a replacement means for replacing the old information with the obtained latest information;

[1610] a generating means for generating new digital content based on the information updated by the replacing means;

[1611] a storage and provision means for storing the generated new digital content and providing it to a user;

[1612] a sentiment analysis means for analyzing user sentiment and customizing the viewing experience in real time;

[1613] The system includes a prompt generation means for uploading information about specific products and generating new product introductions and reviews based on the latest information.

[1614] (Claim 2)

[1615] 2. The system of claim 1, wherein the generative artificial intelligence model automatically detects outdated information by analyzing subtitles and audio.

[1616] (Claim 3)

[1617] 2. The system of claim 1, wherein the information acquisition means acquires up-to-date information from an internal database or an external information source. [Explanation of symbols]

[1618] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. uploading means for uploading digital content including outdated information; analysis means for inputting the digital content into a generative artificial intelligence model to analyze the content; an information acquisition means for identifying old information based on the analysis result of the digital content and acquiring the latest information; a replacement means for replacing the old information with the obtained latest information; a generating means for generating new digital content based on the information updated by the replacing means; The system includes a storage and provision means for storing the generated new digital content and providing it to a user.

2. The system of claim 1 , wherein the generative artificial intelligence model automatically detects outdated information by analyzing subtitles and audio.

3. 2. The system of claim 1, wherein said information acquisition means acquires up-to-date information from an internal database or an external information source.

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