System

Abstract

A system is provided.SOLUTION: The system includes an input means for inputting the generated content, a transmission means for transmitting the input content to a server, a determination means for analyzing the content in the server and collating it with a trademark right and copyright database, and a notification means for returning a determination result to a terminal of the user and displaying it to the 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] There is an increasing possibility that names, catchphrases, music lyrics, etc. created using generative AI models may infringe on existing trademarks or copyrights. This problem can lead to legal trouble and the risk of compensation for damages if the generated content accidentally overlaps with existing rights. For this reason, there is a need for a system that can check for overlaps with existing rights and avoid risks before users use the content they generate. [Means for solving the problem]

[0005] To solve this problem, the present invention provides the following means. First, an input means is provided for inputting content generated by a user, followed by a transmission means for transmitting the input content to a server. The server also provides a determination means for analyzing the content received and comparing it with a database of trademark and copyright protection. Finally, the server provides a notification means for returning the determination result to the user's terminal and notifying the user of the result. This allows the user to check in advance whether the content they have generated infringes any existing rights, allowing them to use the generated content with peace of mind.

[0006] The "input means" is an interface for inputting the content generated by the user, and is a means for acquiring the generated content using a text box or form.

[0007] The "transmission means" is a means for transmitting the content input by the user to the server, and has the function of sending data to the server via Internet communication.

[0008] The "determination means" is a means for analyzing the content received by the server and comparing it with the trademark database and copyright database to determine whether there is a possibility of overlapping or infringement of rights.

[0009] The "notification means" is a means for displaying the judgment result returned from the server on the user's terminal and notifying the user of the result.

[0010] A "trademark database" is a database that records information about existing trademarks and is used to check whether the content being generated overlaps with existing trademarks.

[0011] "Copyright database" means a database that records information about existing copyrights and is used to check whether the content being created overlaps with existing copyrights.

[0012] "Query means" refers to means for querying trademark and copyright databases to check the similarity of the generated content with existing rights.

[0013] The "display means" is a means for displaying the judgment results and warning messages on the user's terminal, and functions as a user interface. [Brief explanation of the drawings]

[0014] [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

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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."

[0035] This invention is a system that determines whether names, catchphrases, music lyrics, etc. obtained from a generative AI model infringe on existing trademarks or copyrights. Below, we will explain each component of this system and how it works.

[0036] 1. User Input

[0037] The user uses a terminal to input the generated content. The terminal is equipped with text boxes and forms, providing an interface for the user to input the name, catchphrase, lyrics, etc. obtained from the generative AI model. Once the input is complete, the user clicks the send button, and the content is sent to the server.

[0038] 2. Submit your input

[0039] The terminal plays a role in transmitting the content entered by the user to the server. The transmission means includes a function to transmit data to the server via the Internet, which allows the entered content to be quickly delivered to the server.

[0040] 3. Analysis processing on the server

[0041] The server receives the content sent from the terminal, and then analyzes the content, which includes splitting the text of the content and preparing it for matching with trademark and copyright databases.

[0042] 4. Trademark and copyright database matching

[0043] The server queries a trademark and copyright database to see if the entry overlaps with existing rights: the trademark database stores information about existing trademark rights, and the copyright database stores information about existing copyrights.

[0044] 5. Return and notification of the results

[0045] After obtaining the matching results, the server sends them back to the device. The device receives the results and notifies the user. The notification is in the form of a display of the results, and a warning is issued based on the judgment result. If there is an overlap with an existing trademark or copyright, the user is notified of this.

[0046] Specific examples

[0047] Example 1:

[0048] The user generates the name "Tech Innovation" using a generative AI model, enters "Tech Innovation" into the input form on their device, and then clicks the submit button.

[0049] The device sends the content "tech innovation" to the server. The server receives this content and begins to analyze the text "tech innovation." The analysis results are obtained by running queries against trademark and copyright databases.

[0050] A trademark database reveals that the existing name "Tech Innovation" is registered as a trademark, while a copyright database reveals that it is not registered as a name associated with any particular copyrighted work.

[0051] The server then sends these results back to the user's device, informing them that the name "Tech Innovation" may infringe on an existing trademark, allowing them to reconsider the new name.

[0052] In this way, the system of the present invention provides an effective means for proactively checking user-generated content and preventing legal trouble.

[0053] The processing flow will be explained below.

[0054] Step 1:

[0055] The user inputs the content to be generated. The user inputs the name, catchphrase, lyrics, etc. obtained from the generative AI model into the input form provided on the device. Once input is complete, the user clicks the send button.

[0056] Step 2:

[0057] The terminal transmits the input contents to the server. The input data is transmitted to the server via the Internet using the transmission means. This transmission process is performed in real time, and the data is quickly delivered to the server.

[0058] Step 3:

[0059] The server analyzes the received content. The server analyzes the received data in text format and prepares it for matching against trademark and copyright databases. This analysis includes segmenting the text and extracting specific keywords.

[0060] Step 4:

[0061] The server queries the trademark database. The server searches the received text data against the trademark database to see if there are any matches or similarities with existing trademarks. The results are obtained as a hypothesis-based similarity score.

[0062] Step 5:

[0063] The server also queries a copyright database: the server searches the received text data against the copyright database to see if there is a match or similarity to existing copyrighted content, and the results are also collected as a similarity score.

[0064] Step 6:

[0065] The server combines the results of the trademark and copyright databases, determines the degree of similarity or match based on the results from each database, and organizes this information into a data format that can be sent back to the user.

[0066] Step 7:

[0067] The server returns the judgment result to the terminal, which then sends the integrated data to the user's terminal and prepares to notify the result.

[0068] Step 8:

[0069] The device receives the determination result and displays it to the user. The device receives the determination result and displays it on the user interface. The result includes a similarity score and specific matching content, and a warning message is displayed to the user.

[0070] Step 9:

[0071] The user can check the results and take action as necessary. The user can check the displayed results and take action such as reconsidering the content to be generated or considering a different name.

[0072] This series of processes allows users to check in advance whether the generated content infringes existing trademark rights and copyrights, thereby preventing legal troubles.

[0073] Example 1

[0074] 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."

[0075] Until now, manually checking whether names, catchphrases, lyrics, and other content derived from generative AI models infringe on existing trademarks or copyrights has been extremely difficult for ordinary end users, as it is time-consuming, costly, and requires specialized knowledge. For this reason, an effective means of preventing legal troubles has been sought.

[0076] 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.

[0077] In this invention, the server includes an input means for inputting content generated by an end user, a transmission means for transmitting the input content via a network, a preprocessing means for receiving the input content and performing text analysis, a determination means for comparing the preprocessed content with a trademark database and a copyright database, a notification means for returning and notifying the end user of the comparison result, a query means for executing a comparison query, and a display means for displaying a warning message to the end user based on the comparison result. This makes it possible to quickly and easily determine the risk of infringement of trademark and copyright in content generated by the end user and prevent legal trouble before it occurs.

[0078] "Input means" refers to a device or interface for an end user to input generated content.

[0079] "Transmission means" refers to the technology and functions for transmitting the input content to a server via a network.

[0080] "Preprocessing means" refers to the technology or process used by the server to process the input received into a form that is easy to analyze.

[0081] "Determination means" refers to the technology or process for cross-checking the pre-processed content with a trademark database and a copyright database to make a determination.

[0082] "Notification means" refers to the technology and functions that allow the server to return and display the matching results to the end user's terminal.

[0083] "Query Instrument" means the technology or process for executing matching queries against trademark and copyright databases.

[0084] "Display means" refers to a technology or device for displaying a warning message to the end user based on the matching result.

[0085] This invention is a system that determines whether names, catchphrases, music lyrics, etc. obtained from a generative AI model infringe on existing trademarks or copyrights. Below, we will explain each component of this system and its operation.

[0086] User input

[0087] The user uses a terminal to input the generated content. The terminal is equipped with text boxes and forms, providing an interface for the user to input the name, catchphrase, lyrics, etc. obtained from the generative AI model. Once the user has completed the input, they click the send button to send the content to the server.

[0088] Sending input

[0089] The terminal is responsible for transmitting the information entered by the user to the server. This transmission is mainly carried out via the Internet, so the data reaches the server quickly.

[0090] Analysis processing on the server

[0091] The server receives the content sent from the device and then analyzes it, including tokenizing and morphological analysis of the text, in preparation for matching against trademark and copyright databases.

[0092] Trademark and copyright database matching

[0093] The server queries a trademark and copyright database to see if the entry overlaps with existing rights: the trademark database stores information about existing trademarks, and the copyright database stores information about existing copyrighted works.

[0094] Return and notification of judgment results

[0095] After obtaining the matching results, the server sends them back to the device. The device receives the results and notifies the user. The notification is in the form of a display of the results, and a warning is issued based on the judgment result. If there is an overlap with an existing trademark or copyright, the user is notified of this.

[0096] Specific examples

[0097] A user generates the name "Tech Innovation" using a generative AI model and enters "Tech Innovation" into an input form on their device. They then click the submit button. The device sends the content "Tech Innovation" to the server. The server receives this content and begins analyzing the text "Tech Innovation." The analysis results are obtained by running queries against trademark and copyright databases.

[0098] A trademark database reveals that the existing name "Tech Innovation" is registered as a trademark, while a copyright database reveals that it is not registered as a name associated with any particular copyrighted work.

[0099] The server then sends these results back to the device, informing the user that the name "Tech Innovation" may infringe on an existing trademark, allowing the user to reconsider the new name.

[0100] In this way, the system of the present invention provides an effective means for proactively checking user-generated content and preventing legal trouble.

[0101] Prompt Sentence Examples

[0102] Here are some example prompts to input to a generative AI model:

[0103] "Generate names for new technology companies."

[0104] The name, catchphrase, lyrics, etc. generated based on this prompt text are input into the system to determine trademark and copyright infringement.

[0105] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0106] Step 1:

[0107] The user uses the input form on the device to input the content obtained from the generative AI model (e.g., "Tech Innovation") and clicks the send button. This inputs the text data into the device. After input, the device prepares to send this text data to the server.

[0108] Specific behavior:

[0109] The user enters "Tech Innovation" into the text box on the terminal and clicks the send button. The input data is ready to be sent to the server in text format.

[0110] Step 2:

[0111] The terminal sends the text data entered by the user to the server using a network protocol such as an HTTP POST request. The input data, which is the text "Tech Innovation," reaches the server.

[0112] Specific behavior:

[0113] The device sends the text data "Tech Innovation" to the server via an HTTP POST request.

[0114] Step 3:

[0115] The server receives the text data sent from the device and preprocesses the received data ("Tech Innovation") into a format that is easy to analyze. This preprocessing includes tokenizing the text and performing morphological analysis.

[0116] Specific behavior:

[0117] The server receives the text "tech innovation," divides it into words (tokenizes it), and performs preprocessing for analysis.

[0118] Step 4:

[0119] The server uses the preprocessed text data to query the trademark database and the copyright database. For example, if the input data is "tech innovation," the server creates and executes a corresponding query against the trademark database and the copyright database. The results obtained from the databases are analyzed to see if the input overlaps with existing rights.

[0120] Specific behavior:

[0121] The server queries the trademark and copyright databases for "tech innovation" and retrieves results from each database.

[0122] Step 5:

[0123] The server generates a judgment result based on the data obtained from the trademark database and copyright database, and returns the result to the end user's terminal, preparing to notify them.

[0124] Specific behavior:

[0125] The server checks the trademark database to see that "Tech Innovation" is registered as an existing trademark, and similarly checks the copyright database to see that it is not registered as a related copyrighted work.

[0126] Step 6:

[0127] The server returns the results of the assessment to the device, which then notifies the user of the results and issues a warning based on the results.

[0128] Specific behavior:

[0129] The server sends a result to the device indicating that "Tech Innovation" may infringe on an existing trademark, and the device displays this and notifies the user to come up with a new name.

[0130] (Application example 1)

[0131] 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."

[0132] There is a need for a reliable system that can check in real time whether names, catchphrases, lyrics, etc. created using generative AI models infringe on existing trademarks or copyrights. However, current systems do not have a method for instantly checking this, making it difficult to prevent the risk of user-generated content infringing on rights in advance. The present invention aims to solve this problem.

[0133] 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.

[0134] In this invention, the server includes an input means for inputting generated content, a transmission means for transmitting the input content to the server, a determination means for analyzing the content on the server and comparing it with a trademark database and a copyright database, and a real-time analysis means for checking in real time whether content created using the generative AI model infringes trademarks or copyrights. This makes it possible to instantly check content created by users and prevent infringement of rights before it occurs.

[0135] A "generative AI model" is a model that uses artificial intelligence to generate new content such as text and designs.

[0136] An "input means" is a device or mechanism that provides an interface for a user to input generated content.

[0137] The "transmission means" refers to a device or mechanism for transmitting the inputted content to the server as data.

[0138] The "determination means" is a device or mechanism that analyzes the content on the server side and compares it with the trademark database and copyright database.

[0139] The "notification means" is a device or mechanism for returning the determination result to the user's terminal and notifying the user.

[0140] "Real-time analysis means" refers to devices or mechanisms that instantly check whether content created using a generative AI model infringes trademark rights or copyrights.

[0141] A "query means" is a device or mechanism for executing queries against trademark and copyright databases.

[0142] The "display means" is a device or mechanism for visually presenting a warning message to the user based on the determination result.

[0143] This invention is a system that checks whether catchphrases and names created using generative AI models infringe on existing trademarks or copyrights. Below, we will explain how this system is implemented in concrete terms.

[0144] System Configuration

[0145] The system consists of the following main components:

[0146] Input means: An interface for the user to input the generated content.

[0147] Transmission means: A mechanism for transmitting the input content to the server.

[0148] Determination means: A mechanism for analyzing the content on the server side and comparing it with a trademark database and a copyright database.

[0149] Notification means: A mechanism for returning the judgment result to the user's terminal and notifying the user.

[0150] Real-time analysis means: A mechanism for instantly checking content created using generative AI models (performing real-time processing).

[0151] Query facility: A mechanism for performing queries against trademark and copyright databases.

[0152] Display means: A mechanism for displaying a warning message based on the determination result.

[0153] What the program does

[0154] The server program has the following features:

[0155] Receiving and sending input data: Receives user input and processes it.

[0156] Data Analysis: Analyzes input text data and queries trademark and copyright databases.

[0157] Real-time detection: Determine whether there is any trademark or copyright infringement based on the query results in real time.

[0158] Notification and display of results: The judgment results are returned to the user's device and the results are displayed to notify the user.

[0159] Hardware and software used

[0160] Flask: Used as a server-side application framework.

[0161] Requests library: Used to execute HTTP requests on the server.

[0162] Smartphone: A device that handles user input and displays results.

[0163] Generative AI model: Used to generate new catchphrases and names.

[0164] Specific examples

[0165] For example:

[0166] Prompt Sentence Examples

[0167] "Generate the name 'Tech Brain' for a new startup product."

[0168] Processing flow

[0169] 1. User input: The user enters "Tech Brain" into the text box on the smartphone app and sends the content to the server.

[0170] 2. Server processing: The server analyzes the received content and sends queries to trademark and copyright databases.

[0171] 3. Return of results: Based on the results obtained, a real-time determination is made as to whether the entered "Tech Brain" infringes on existing trademarks or copyrights.

[0172] 4. Notification and display: The judgement result will be sent immediately to the smartphone and the user will be notified. If the judgement result indicates infringement, the user can reconsider the new name.

[0173] Through this specific process, the system of the present invention can immediately verify that the content generated by the user does not infringe trademark rights or copyrights, thereby preventing legal troubles.

[0174] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0175] Step 1:

[0176] The user inputs the content generated by the generative AI model into a smartphone application. Specifically, the user enters the newly generated catchphrase or name into a text box and clicks the application's send button to send the content to the server. The input data includes the generated name, such as "Tech Brain."

[0177] Step 2:

[0178] The device sends the entered content to the server. In this case, the smartphone app sends text data such as "Tech Brain" to the server as an HTTP request. The input data includes the content entered in the text box ("Tech Brain"), and after it is sent, it is received by the server.

[0179] Step 3:

[0180] The server analyzes the received text data and sends a query to the trademark and copyright database. Specifically, the server analyzes the text "Techbrain," generates an appropriate query, and searches the trademark and copyright database to verify whether the input data infringes any existing trademarks or copyrights.

[0181] Step 4:

[0182] The server receives query results from the database and performs real-time analysis. Specifically, it determines whether TechBrain is infringing on existing rights based on the results obtained from the trademark and copyright databases. Based on the results received (the status of existing trademarks and copyrights), the server then processes and calculates the data to confirm whether there is an infringement.

[0183] Step 5:

[0184] The server returns the result of the judgment to the user's device. Specifically, the server sends the judgment result (e.g., whether "Techbrain" infringes on existing trademark rights) back to the smartphone app. As a result, the user receives a notification indicating whether the content they entered infringes on existing rights.

[0185] Step 6:

[0186] The device will then display the results of the judgment to the user. Specifically, the smartphone app will visually display the results of the judgment received to the user. The user will be able to check whether there is an infringement, for example, as a pop-up message or a notification message, and if there is an infringement, they will be able to take action, such as coming up with a new name.

[0187] 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.

[0188] This invention combines an emotion engine with a system that determines whether names, catchphrases, music lyrics, etc. obtained from a generative AI model infringe on existing trademarks or copyrights. Below, we will explain each component of this system and how it works.

[0189] 1. User Input

[0190] The user uses a terminal to input the generated content. The terminal provides text boxes and forms, and has an interface function for the user to input the name, catchphrase, lyrics, etc. obtained from the generative AI model. Once the input is complete, the user clicks the send button, and the content is sent to the server.

[0191] 2. Submit your input

[0192] The terminal serves to transmit the content entered by the user to the server. This transmission means has a function to transmit data via the Internet, and the content is passed to the server in real time.

[0193] 3. Analysis processing on the server

[0194] The server receives the content sent from the device, analyzes the text of the content, and prepares it for matching with trademark and copyright databases. This analysis includes segmenting the text and extracting specific keywords.

[0195] 4. Trademark and copyright database matching

[0196] The server queries a trademark database and a copyright database to see if the entry overlaps with existing rights. The trademark database stores information about existing trademark rights, and the copyright database stores information about existing copyrights.

[0197] 5. Return and notification of the results

[0198] After obtaining the matching results, the server sends them back to the user's device. The device receives the results and notifies the user. The notification is in the form of a display of the results, and a warning is issued based on the judgment result. If there is an overlap with an existing trademark or copyright, the user is notified of this.

[0199] 6. Incorporating an Emotional Engine

[0200] One of the features of the invention is the incorporation of an emotion engine, which recognizes and analyzes the user's emotions when they are input and when the judgment results are displayed.

[0201] 1. Emotion recognition during input:

[0202] While the user is entering information into the device, the emotion engine analyzes the user's facial image and facial expressions to recognize their emotional state. Based on this analysis, the engine provides appropriate feedback to the user.

[0203] 2. Emotion analysis when displaying judgment results:

[0204] The judgment results are displayed on the user's device, and at the same time, the emotion engine analyzes the user's reaction and understands their emotional state. Based on the analysis results, the displayed warning messages and feedback content are adjusted. For example, if the user is confused, a support message appropriate to their emotion is displayed.

[0205] Specific examples

[0206] Example 1:

[0207] The user generates the name "Tech Innovation" using the generative AI model and enters it into the device's input form. The emotion engine then analyzes the user's facial expressions and recognizes that the user is enjoying themselves. When the user clicks the send button, the content is sent to the server.

[0208] The server receives the content "Tech Innovation" and begins analyzing it, querying trademark and copyright databases to see if it overlaps with existing trademarks or copyrights.

[0209] As a result, it is discovered in the trademark database that the name "Tech Innovation" is registered as an existing trademark. The server sends this result back to the user's device. The device receives the result and displays a warning message to the user stating, "This name may infringe on an existing trademark." The emotion engine also analyzes the user's reaction at the time of display and recognizes that the user is confused. Based on this, it provides further specific improvement suggestions and support messages.

[0210] In this way, the system of the present invention, which combines an emotion engine, can provide feedback on the content created by the user and support the user according to their emotions, allowing the user to use the content with peace of mind and preventing legal troubles.

[0211] The processing flow will be explained below.

[0212] Step 1:

[0213] The user inputs the content to be generated. The user inputs the name, catchphrase, and lyrics obtained from the generative AI model into the input form provided on the device. Once input is complete, the user clicks the send button.

[0214] Step 2:

[0215] The terminal transmits the input contents to the server. The input data is transmitted to the server via the Internet using the transmission means. This transmission process is performed in real time, and the data is quickly delivered to the server.

[0216] Step 3:

[0217] The device recognizes the user's emotions while they are typing. While they are typing, the device's built-in emotion engine analyzes the user's facial image and facial expressions to recognize their emotional state. The analysis results are used in a later step to provide appropriate feedback to the user.

[0218] Step 4:

[0219] The server analyzes the received content. The server analyzes the received data in text format and prepares it for matching against trademark and copyright databases. This analysis includes segmenting the text and extracting specific keywords.

[0220] Step 5:

[0221] The server queries the trademark database. The server searches the received text data against the trademark database to see if there are any matches or similarities with existing trademarks. The result is a similarity score.

[0222] Step 6:

[0223] The server also queries a copyright database: the server searches the received text data against the copyright database to see if there is a match or similarity to existing copyrighted content, and the results are also collected as a similarity score.

[0224] Step 7:

[0225] The server combines the results of the trademark and copyright databases, determines the degree of similarity or match based on the results from each database, and organizes this information into a data format that can be sent back to the user.

[0226] Step 8:

[0227] The server returns the judgment result to the terminal, which then sends the integrated data to the user's terminal and prepares to notify the result.

[0228] Step 9:

[0229] The device receives the determination result and displays it to the user. The device receives the determination result and displays it on the user interface. The result includes a similarity score and specific matching content, and a warning message is displayed to the user.

[0230] Step 10:

[0231] The device analyzes the user's emotions when displaying the judgment result. When the judgment result is displayed, the emotion engine analyzes the user's reaction and understands their emotional state. Based on the analysis results, the warning message and feedback content displayed are adjusted.

[0232] Step 11:

[0233] The user can check the results and take action if necessary. The user can check the displayed results and take action such as reconsidering the generated content or considering a different name. By displaying feedback according to their emotions, the user can make an appropriate decision.

[0234] This process allows users to check in advance whether the generated content infringes existing trademarks or copyrights, preventing legal troubles. In addition, the incorporation of an emotion engine provides more personalized support to users.

[0235] Example 2

[0236] 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."

[0237] Systems that determine whether names, catchphrases, lyrics, etc. generated by conventional generative AI models infringe on existing trademarks or copyrights lack a feedback function that takes into account the user's emotional state. This can lead to users feeling confused or anxious about the provided judgment results. The lack of a user-friendly feedback system can reduce user satisfaction and impair the system's usability.

[0238] 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.

[0239] In this invention, the server includes an input means for inputting the generated content, a transmission means for transmitting the input content to the server, a determination means for analyzing the content in the server and comparing it with a trademark and copyright database, a notification means for returning the determination result to the user's terminal and displaying it to the user, and an emotion analysis means for analyzing the user's emotional state and providing feedback based on the result. This allows the user to receive appropriate feedback on the provided determination result, making it possible to improve user satisfaction and convenience.

[0240] The "input means" is a device that provides an interface for a user to input generated content.

[0241] The "transmission means" is a device that has the function of transmitting the input contents to a server via the Internet.

[0242] The "determination means" is a processing device that analyzes the content received on the server and compares it with a trademark and copyright database.

[0243] The "notification means" is a device that returns the determination result from the server to the user's terminal and displays it to the user.

[0244] The "emotion analysis means" is a device that analyzes the user's facial image and facial expressions to recognize the user's emotional state, and provides appropriate feedback based on the results.

[0245] A "trademark database" is a database that stores information about existing trademarks.

[0246] A "copyright database" is a database that stores information about existing copyrights.

[0247] The "query means" is a device that has the function of executing a query to the trademark database and copyright database and obtaining the matching results.

[0248] The "display means" is a device that displays a warning message to the user based on the determination result.

[0249] This invention combines an emotion engine with a system that determines whether names, catchphrases, music lyrics, etc. obtained from a generative AI model infringe on existing trademarks or copyrights. This system is realized by integrating the following functions: user input, terminal-server communication, data analysis, notification of judgment results, and emotion analysis. Each component of the system and its operation are described below.

[0250] User input

[0251] The user uses the device to input content such as names, catchphrases, and lyrics generated by the generative AI model. The device provides text boxes and forms, and has an interface function for inputting the content generated by the user. As a concrete example, the name "Tech Innovation" is entered into the device's input form.

[0252] Sending input

[0253] When the user clicks the send button, the device transmits the user's input to the server in real time over the Internet using a transmission method designed to reliably deliver data to the server.

[0254] Analysis processing on the server

[0255] After receiving the content sent from the device, the server analyzes it. Specifically, it segments the text of the content and extracts specific keywords. This analysis process is used to prepare queries against trademark and copyright databases. For example, the content "tech innovation" can be split into "tech" and "innovation" and then analyzed for each keyword.

[0256] Trademark and copyright database matching

[0257] The server queries the parsed content against a trademark database and a copyright database to check for overlaps with existing rights. The trademark database stores information about existing trademarks, and the copyright database stores information about existing copyrights.

[0258] Return and notification of judgment results

[0259] The server sends the matching results back to the user's device, which receives the results and notifies the user, for example by displaying a warning message saying, "This name may infringe on an existing trademark."

[0260] Incorporating an emotion engine

[0261] The emotion engine analyzes the user's emotions while the user is entering input content into the device and when the judgment result is displayed. While the user is entering content, the emotion engine analyzes the user's facial image and facial expressions through the device's camera to recognize their emotional state. When the judgment result is displayed, it analyzes the user's reaction and provides appropriate feedback based on their emotional state. For example, if the user is confused, a support message appropriate to their emotion is displayed.

[0262] Specific examples

[0263] Example 1:

[0264] The user generates the name "Tech Innovation" using the generative AI model and enters it into the device's input form. The emotion engine then analyzes the user's facial expressions and recognizes that the user is enjoying themselves. When the user clicks the send button, the content is sent to the server.

[0265] The server receives the content "Tech Innovation" and begins analyzing it, querying trademark and copyright databases to see if it overlaps with existing trademarks or copyrights.

[0266] As a result, it is discovered that the name "Tech Innovation" is registered as an existing trademark in the trademark database. The server sends this result back to the user's device. The device receives the result and displays a warning message to the user stating, "This name may infringe on an existing trademark." The emotion engine also analyzes the user's reaction to this message and recognizes that they are confused. Based on this, it displays supplementary support messages such as "Please consider another name" or "If you need support, please contact us."

[0267] Example prompt sentence:

[0268] "Please explain how to ensure that the generated names and taglines do not infringe on trademarks or copyrights."

[0269] "Please provide a concrete example of a feedback system that uses an emotion engine."

[0270] The above is an embodiment of the present invention.

[0271] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0272] Step 1:

[0273] The user enters the generated content into the input form on the device. Specifically, the user enters a name or catchphrase, such as "Tech Innovation," generated by the generative AI model. Once the input is complete, the device receives the data. The input data is text data. The output is the text data entered by the user.

[0274] Step 2:

[0275] The terminal transmits the text data entered by the user to the server using a transmission means. The transmission means is the Internet, and the data is passed to the server in real time. The input data is the text data entered by the user, and the output is the text data sent to the server.

[0276] Step 3:

[0277] The server receives text data sent from the device. To analyze the received data, it divides the text and extracts specific keywords. For example, "tech innovation" is divided into "tech" and "innovation." This analysis uses text processing programs and algorithms. The input data is the text data received by the server, and the output is the analyzed keyword data.

[0278] Step 4:

[0279] The server queries the parsed keyword data against the trademark and copyright databases. Specifically, the server matches the keywords against the databases to see if they overlap with existing rights. The input data is the parsed keyword data, and the output is the match result data.

[0280] Step 5:

[0281] The server returns the matching result data to the user's terminal. The terminal receives this matching result data and notifies the user. For example, it displays a warning message such as "This name may infringe on an existing trademark." The input data is the matching result data, and the output is a warning message that is displayed to the user.

[0282] Step 6:

[0283] While the user is entering input content into the device, the emotion engine analyzes the user's facial image and facial expressions via the device's camera. Based on the results of this analysis, the user's emotional state is recognized. For example, it identifies emotions such as whether the user is enjoying themselves or feeling confused. The input data is the user's facial image and facial expression data, and the output is analyzed emotional data.

[0284] Step 7:

[0285] At the same time as the judgment result is displayed, the emotion engine analyzes the user's reaction via the device's camera. The feedback message and support message are adjusted based on the analysis results. For example, if the user is confused, a support message such as "Please consider a different name" is displayed. The input data is the emotion data at the time the judgment result is displayed, and the output is the adjusted feedback message.

[0286] (Application example 2)

[0287] 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."

[0288] Systems that determine whether names, catchphrases, lyrics, etc. obtained from generative AI models infringe on existing trademarks and copyrights have the problem of being unable to take users' emotions into consideration and provide appropriate feedback. Another issue is the lack of systems that can understand users' emotional reactions to the results of the determination and provide appropriate support accordingly.

[0289] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an input means for inputting generated content, a transmission means for transmitting the input content to the server, a determination means for analyzing the content in the server and comparing it with a trademark and copyright database, a notification means for returning the determination result to the user's terminal and displaying it to the user, an emotion recognition means for recognizing and analyzing the user's emotions, and a feedback means for providing feedback based on the emotion analysis result. This makes it possible to determine whether the content obtained from the generative AI model infringes existing trademarks and copyrights, and at the same time provide appropriate support according to the user's emotions.

[0290] "Input means for inputting generated content" refers to a means for providing an interface for users to input names, catchphrases, lyrics, etc. obtained from the generative AI model.

[0291] The "transmission means for transmitting the input contents to the server" is a communication means for transmitting the contents input by the user to the server, and is a means having the function of transferring data via a network such as the Internet.

[0292] The "determination means for analyzing the content on the server and comparing it with the trademark and copyright database" refers to a means for analyzing the content entered on the server, comparing it with the trademark and copyright databases, and checking whether it overlaps with existing rights.

[0293] The "notification means for returning the judgment results to the user's terminal and displaying them to the user" refers to a means for returning the judgment results of trademark right and copyright to the user's terminal and displaying them on the screen.

[0294] The "emotion recognition means for recognizing and analyzing the user's emotions" is a means for analyzing the facial expressions and actions of the user when the user performs an input operation or displays a judgment result, and recognizing the user's emotional state.

[0295] The "feedback means for providing feedback based on the emotion analysis result" is a means for providing appropriate feedback or a support message to the user based on the emotion analysis result obtained by the emotion recognition means.

[0296] This section describes an embodiment of the present invention. This system determines whether names, catchphrases, lyrics, etc. generated by a generative AI model infringe on existing trademarks or copyrights, and recognizes the user's emotional state and provides appropriate feedback. Each component and its operation are described in detail below.

[0297] 1. User Input

[0298] Users install the ad creation support app on their smartphone and input the name and catchphrase obtained from the generative AI model. This input is done via an input means that provides an interface. Specifically, users enter their information into a text box and click the send button.

[0299] 2. Submit your input

[0300] The information entered by the user is sent to the server via the Internet. The transmission means has the function of transferring data in real time using the HTTP protocol. This allows the information entered by the user to be delivered to the server quickly.

[0301] 3. Analysis processing on the server

[0302] The server analyzes the received content. Specifically, it uses a server-side program (e.g., Node.js) to split the text and extract keywords. Based on the results of this analysis, it prepares to match the data with trademark and copyright databases.

[0303] 4. Trademark and copyright database matching

[0304] The server queries a trademark database and a copyright database to see if the entry overlaps with existing rights. The trademark database stores information about existing trademark rights, and the copyright database stores information about existing copyrights.

[0305] 5. Return and notification of the results

[0306] After obtaining the matching result, the server sends the result back to the user's device. The device receives the result and notifies the user. The result is displayed on the screen and a warning message is provided based on the judgment result.

[0307] 6. Incorporating an Emotional Engine

[0308] While the user is entering input content into the device, the emotion engine operates and analyzes the user's facial expressions. It uses libraries such as EmotionRecognition to recognize the user's emotional state from facial images and expressions. Based on the analysis results, it provides appropriate feedback to the user.

[0309] The judgment results are displayed on the user's device, and at the same time, the emotion engine analyzes the user's reaction and understands their emotional state. Based on the analysis results, the displayed warning messages and feedback content can be adjusted. For example, if the user is confused, a support message appropriate to their emotion will be displayed.

[0310] Specific examples

[0311] For example, suppose a user generates the name "Cool Tech" and enters it into an input form. At this time, the emotion engine recognizes the user's smile and analyzes it as a state of enjoyment. The input is sent to the server and compared with the trademark database. As a result, it is confirmed that the name "Cool Tech" does not match any existing trademark rights, and the user is notified that it is valid. In addition, to maintain the user's enjoyment, positive feedback based on the emotion analysis results is displayed.

[0312] Prompt Sentence Examples

[0313] "Generate a new name for creating ads"

[0314] In this way, by implementing the invention, users can use the generated content with peace of mind, prevent legal troubles, and receive appropriate support according to their emotions.

[0315] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0316] Step 1:

[0317] The user launches the ad creation support app and inputs the name and catchphrase obtained from the generative AI model. Using the input means (text box), the user inputs the content following the prompt "Generate a new name for ad creation." The user enters "Cool Tech" as the input content and clicks the send button. The input content is obtained in text format.

[0318] Step 2:

[0319] The terminal sends the user's input to the server via the Internet. The transmission method uses the HTTP protocol, and the user's text data is sent to the server in JSON format. The input is the text entered by the user, and the output is the text data received by the server.

[0320] Step 3:

[0321] The content received by the server is analyzed. Specifically, a server-side program (Node.js) is used to split the text and extract keywords. The input text is analyzed and keywords are identified. This analyzed data becomes the preparation data for subsequent database matching. The input is the received text data, and the output is the analyzed keyword data.

[0322] Step 4:

[0323] The server queries trademark and copyright databases to ensure that the input does not overlap with existing rights. It uses a query mechanism to match identified keywords against the database. The input is the analyzed keyword data, and the output is the match result data.

[0324] Step 5:

[0325] The server returns the matching results to the user's device. The result data is encoded in JSON format and sent to the device via the HTTP protocol. The input is the matching result data, and the output is the result data received on the device.

[0326] Step 6:

[0327] The terminal displays the received matching result on the screen and notifies the user. Specifically, the result is displayed in text format using a notification means. For example, a message such as "Cool Tech is available for use" is displayed. The input is the received result data, and the output is the text displayed on the screen.

[0328] Step 7:

[0329] At the same time, the emotion engine analyzes the user's facial expression. Using the EmotionRecognition library, it analyzes the user's facial image during input and when the results are displayed to identify the emotion. The emotional state is identified and obtained as analysis data. The input is the user's facial image, and the output is emotion analysis data.

[0330] Step 8:

[0331] The device provides the user with appropriate feedback based on the emotion analysis results. The feedback means is used to display positive feedback or supportive messages on the screen. For example, a message such as "Great idea! This name is available." is displayed. The input is emotion analysis data, and the output is a feedback message.

[0332] In this way, throughout the process, the user's input is checked for legal compliance and feedback is provided according to the user's emotional state.

[0333] 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.

[0334] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (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.

[0335] 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.

[0336] [Second embodiment]

[0337] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0338] 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.

[0339] 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).

[0340] 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.

[0341] 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.

[0342] 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).

[0343] 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.

[0344] 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.

[0345] 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.

[0346] 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.

[0347] 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.

[0348] 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."

[0349] This invention is a system that determines whether names, catchphrases, music lyrics, etc. obtained from a generative AI model infringe on existing trademarks or copyrights. Below, we will explain each component of this system and how it works.

[0350] 1. User Input

[0351] The user uses a terminal to input the generated content. The terminal is equipped with text boxes and forms, providing an interface for the user to input the name, catchphrase, lyrics, etc. obtained from the generative AI model. Once the input is complete, the user clicks the send button, and the content is sent to the server.

[0352] 2. Submit your input

[0353] The terminal plays a role in transmitting the content entered by the user to the server. The transmission means includes a function to transmit data to the server via the Internet, which allows the entered content to be quickly delivered to the server.

[0354] 3. Analysis processing on the server

[0355] The server receives the content sent from the terminal, and then analyzes the content, which includes splitting the text of the content and preparing it for matching with trademark and copyright databases.

[0356] 4. Trademark and copyright database matching

[0357] The server queries a trademark and copyright database to see if the entry overlaps with existing rights: the trademark database stores information about existing trademark rights, and the copyright database stores information about existing copyrights.

[0358] 5. Return and notification of the results

[0359] After obtaining the matching results, the server sends them back to the device. The device receives the results and notifies the user. The notification is in the form of a display of the results, and a warning is issued based on the judgment result. If there is an overlap with an existing trademark or copyright, the user is notified of this.

[0360] Specific examples

[0361] Example 1:

[0362] The user generates the name "Tech Innovation" using a generative AI model, enters "Tech Innovation" into the input form on their device, and then clicks the submit button.

[0363] The device sends the content "tech innovation" to the server. The server receives this content and begins to analyze the text "tech innovation." The analysis results are obtained by running queries against trademark and copyright databases.

[0364] A trademark database reveals that the existing name "Tech Innovation" is registered as a trademark, while a copyright database reveals that it is not registered as a name associated with any particular copyrighted work.

[0365] The server then sends these results back to the user's device, informing them that the name "Tech Innovation" may infringe on an existing trademark, allowing them to reconsider the new name.

[0366] In this way, the system of the present invention provides an effective means for proactively checking user-generated content and preventing legal trouble.

[0367] The processing flow will be explained below.

[0368] Step 1:

[0369] The user inputs the content to be generated. The user inputs the name, catchphrase, lyrics, etc. obtained from the generative AI model into the input form provided on the device. Once input is complete, the user clicks the send button.

[0370] Step 2:

[0371] The terminal transmits the input contents to the server. The input data is transmitted to the server via the Internet using the transmission means. This transmission process is performed in real time, and the data is quickly delivered to the server.

[0372] Step 3:

[0373] The server analyzes the received content. The server analyzes the received data in text format and prepares it for matching against trademark and copyright databases. This analysis includes segmenting the text and extracting specific keywords.

[0374] Step 4:

[0375] The server queries the trademark database. The server searches the received text data against the trademark database to see if there are any matches or similarities with existing trademarks. The results are obtained as a hypothesis-based similarity score.

[0376] Step 5:

[0377] The server also queries a copyright database: the server searches the received text data against the copyright database to see if there is a match or similarity to existing copyrighted content, and the results are also collected as a similarity score.

[0378] Step 6:

[0379] The server combines the results of the trademark and copyright databases, determines the degree of similarity or match based on the results from each database, and organizes this information into a data format that can be sent back to the user.

[0380] Step 7:

[0381] The server returns the judgment result to the terminal, which then sends the integrated data to the user's terminal and prepares to notify the result.

[0382] Step 8:

[0383] The device receives the determination result and displays it to the user. The device receives the determination result and displays it on the user interface. The result includes a similarity score and specific matching content, and a warning message is displayed to the user.

[0384] Step 9:

[0385] The user can check the results and take action as necessary. The user can check the displayed results and take action such as reconsidering the content to be generated or considering a different name.

[0386] This series of processes allows users to check in advance whether the generated content infringes existing trademark rights and copyrights, thereby preventing legal troubles.

[0387] Example 1

[0388] 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."

[0389] Until now, manually checking whether names, catchphrases, lyrics, and other content derived from generative AI models infringe on existing trademarks or copyrights has been extremely difficult for ordinary end users, as it is time-consuming, costly, and requires specialized knowledge. For this reason, an effective means of preventing legal troubles has been sought.

[0390] 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.

[0391] In this invention, the server includes an input means for inputting content generated by an end user, a transmission means for transmitting the input content via a network, a preprocessing means for receiving the input content and performing text analysis, a determination means for comparing the preprocessed content with a trademark database and a copyright database, a notification means for returning and notifying the end user of the comparison result, a query means for executing a comparison query, and a display means for displaying a warning message to the end user based on the comparison result. This makes it possible to quickly and easily determine the risk of infringement of trademark and copyright in content generated by the end user and prevent legal trouble before it occurs.

[0392] "Input means" refers to a device or interface for an end user to input generated content.

[0393] "Transmission means" refers to the technology and functions for transmitting the input content to a server via a network.

[0394] "Preprocessing means" refers to the technology or process used by the server to process the input received into a form that is easy to analyze.

[0395] "Determination means" refers to the technology or process for cross-checking the pre-processed content with a trademark database and a copyright database to make a determination.

[0396] "Notification means" refers to the technology and functions that allow the server to return and display the matching results to the end user's terminal.

[0397] "Query Instrument" means the technology or process for executing matching queries against trademark and copyright databases.

[0398] "Display means" refers to a technology or device for displaying a warning message to the end user based on the matching result.

[0399] This invention is a system that determines whether names, catchphrases, music lyrics, etc. obtained from a generative AI model infringe on existing trademarks or copyrights. Below, we will explain each component of this system and its operation.

[0400] User input

[0401] The user uses a terminal to input the generated content. The terminal is equipped with text boxes and forms, providing an interface for the user to input the name, catchphrase, lyrics, etc. obtained from the generative AI model. Once the user has completed the input, they click the send button to send the content to the server.

[0402] Sending input

[0403] The terminal is responsible for transmitting the information entered by the user to the server. This transmission is mainly carried out via the Internet, so the data reaches the server quickly.

[0404] Analysis processing on the server

[0405] The server receives the content sent from the device and then analyzes it, including tokenizing and morphological analysis of the text, in preparation for matching against trademark and copyright databases.

[0406] Trademark and copyright database matching

[0407] The server queries a trademark and copyright database to see if the entry overlaps with existing rights: the trademark database stores information about existing trademarks, and the copyright database stores information about existing copyrighted works.

[0408] Return and notification of judgment results

[0409] After obtaining the matching results, the server sends them back to the device. The device receives the results and notifies the user. The notification is in the form of a display of the results, and a warning is issued based on the judgment result. If there is an overlap with an existing trademark or copyright, the user is notified of this.

[0410] Specific examples

[0411] A user generates the name "Tech Innovation" using a generative AI model and enters "Tech Innovation" into an input form on their device. They then click the submit button. The device sends the content "Tech Innovation" to the server. The server receives this content and begins analyzing the text "Tech Innovation." The analysis results are obtained by running queries against trademark and copyright databases.

[0412] A trademark database reveals that the existing name "Tech Innovation" is registered as a trademark, while a copyright database reveals that it is not registered as a name associated with any particular copyrighted work.

[0413] The server then sends these results back to the device, informing the user that the name "Tech Innovation" may infringe on an existing trademark, allowing the user to reconsider the new name.

[0414] In this way, the system of the present invention provides an effective means for proactively checking user-generated content and preventing legal trouble.

[0415] Prompt Sentence Examples

[0416] Here are some example prompts to input to a generative AI model:

[0417] "Generate names for new technology companies."

[0418] The name, catchphrase, lyrics, etc. generated based on this prompt text are input into the system to determine trademark and copyright infringement.

[0419] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0420] Step 1:

[0421] The user uses the input form on the device to input the content obtained from the generative AI model (e.g., "Tech Innovation") and clicks the send button. This inputs the text data into the device. After input, the device prepares to send this text data to the server.

[0422] Specific behavior:

[0423] The user enters "Tech Innovation" into the text box on the terminal and clicks the send button. The input data is ready to be sent to the server in text format.

[0424] Step 2:

[0425] The terminal sends the text data entered by the user to the server using a network protocol such as an HTTP POST request. The input data, which is the text "Tech Innovation," reaches the server.

[0426] Specific behavior:

[0427] The device sends the text data "Tech Innovation" to the server via an HTTP POST request.

[0428] Step 3:

[0429] The server receives the text data sent from the device and preprocesses the received data ("Tech Innovation") into a format that is easy to analyze. This preprocessing includes tokenizing the text and performing morphological analysis.

[0430] Specific behavior:

[0431] The server receives the text "tech innovation," divides it into words (tokenizes it), and performs preprocessing for analysis.

[0432] Step 4:

[0433] The server uses the preprocessed text data to query the trademark database and the copyright database. For example, if the input data is "tech innovation," the server creates and executes a corresponding query against the trademark database and the copyright database. The results obtained from the databases are analyzed to see if the input overlaps with existing rights.

[0434] Specific behavior:

[0435] The server queries the trademark and copyright databases for "tech innovation" and retrieves results from each database.

[0436] Step 5:

[0437] The server generates a judgment result based on the data obtained from the trademark database and copyright database, and returns the result to the end user's terminal, preparing to notify them.

[0438] Specific behavior:

[0439] The server checks the trademark database to see that "Tech Innovation" is registered as an existing trademark, and similarly checks the copyright database to see that it is not registered as a related copyrighted work.

[0440] Step 6:

[0441] The server returns the results of the assessment to the device, which then notifies the user of the results and issues a warning based on the results.

[0442] Specific behavior:

[0443] The server sends a result to the device indicating that "Tech Innovation" may infringe on an existing trademark, and the device displays this and notifies the user to come up with a new name.

[0444] (Application example 1)

[0445] 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."

[0446] There is a need for a reliable system that can check in real time whether names, catchphrases, lyrics, etc. created using generative AI models infringe on existing trademarks or copyrights. However, current systems do not have a method for instantly checking this, making it difficult to prevent the risk of user-generated content infringing on rights in advance. The present invention aims to solve this problem.

[0447] 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.

[0448] In this invention, the server includes an input means for inputting generated content, a transmission means for transmitting the input content to the server, a determination means for analyzing the content on the server and comparing it with a trademark database and a copyright database, and a real-time analysis means for checking in real time whether content created using the generative AI model infringes trademarks or copyrights. This makes it possible to instantly check content created by users and prevent infringement of rights before it occurs.

[0449] A "generative AI model" is a model that uses artificial intelligence to generate new content such as text and designs.

[0450] An "input means" is a device or mechanism that provides an interface for a user to input generated content.

[0451] The "transmission means" refers to a device or mechanism for transmitting the inputted content to the server as data.

[0452] The "determination means" is a device or mechanism that analyzes the content on the server side and compares it with the trademark database and copyright database.

[0453] The "notification means" is a device or mechanism for returning the determination result to the user's terminal and notifying the user.

[0454] "Real-time analysis means" refers to devices or mechanisms that instantly check whether content created using a generative AI model infringes trademark rights or copyrights.

[0455] A "query means" is a device or mechanism for executing queries against trademark and copyright databases.

[0456] The "display means" is a device or mechanism for visually presenting a warning message to the user based on the determination result.

[0457] This invention is a system that checks whether catchphrases and names created using generative AI models infringe on existing trademarks or copyrights. Below, we will explain how this system is implemented in concrete terms.

[0458] System Configuration

[0459] The system consists of the following main components:

[0460] Input means: An interface for the user to input the generated content.

[0461] Transmission means: A mechanism for transmitting the input content to the server.

[0462] Determination means: A mechanism for analyzing the content on the server side and comparing it with a trademark database and a copyright database.

[0463] Notification means: A mechanism for returning the judgment result to the user's terminal and notifying the user.

[0464] Real-time analysis means: A mechanism for instantly checking content created using generative AI models (performing real-time processing).

[0465] Query facility: A mechanism for performing queries against trademark and copyright databases.

[0466] Display means: A mechanism for displaying a warning message based on the determination result.

[0467] What the program does

[0468] The server program has the following features:

[0469] Receiving and sending input data: Receives user input and processes it.

[0470] Data Analysis: Analyzes input text data and queries trademark and copyright databases.

[0471] Real-time detection: Determine whether there is any trademark or copyright infringement based on the query results in real time.

[0472] Notification and display of results: The judgment results are returned to the user's device and the results are displayed to notify the user.

[0473] Hardware and software used

[0474] Flask: Used as a server-side application framework.

[0475] Requests library: Used to execute HTTP requests on the server.

[0476] Smartphone: A device that handles user input and displays results.

[0477] Generative AI model: Used to generate new catchphrases and names.

[0478] Specific examples

[0479] For example:

[0480] Prompt Sentence Examples

[0481] "Generate the name 'Tech Brain' for a new startup product."

[0482] Processing flow

[0483] 1. User input: The user enters "Tech Brain" into the text box on the smartphone app and sends the content to the server.

[0484] 2. Server processing: The server analyzes the received content and sends queries to trademark and copyright databases.

[0485] 3. Return of results: Based on the results obtained, a real-time determination is made as to whether the entered "Tech Brain" infringes on existing trademarks or copyrights.

[0486] 4. Notification and display: The judgement result will be sent immediately to the smartphone and the user will be notified. If the judgement result indicates infringement, the user can reconsider the new name.

[0487] Through this specific process, the system of the present invention can immediately verify that the content generated by the user does not infringe trademark rights or copyrights, thereby preventing legal troubles.

[0488] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0489] Step 1:

[0490] The user inputs the content generated by the generative AI model into a smartphone application. Specifically, the user enters the newly generated catchphrase or name into a text box and clicks the application's send button to send the content to the server. The input data includes the generated name, such as "Tech Brain."

[0491] Step 2:

[0492] The device sends the entered content to the server. In this case, the smartphone app sends text data such as "Tech Brain" to the server as an HTTP request. The input data includes the content entered in the text box ("Tech Brain"), and after it is sent, it is received by the server.

[0493] Step 3:

[0494] The server analyzes the received text data and sends a query to the trademark and copyright database. Specifically, the server analyzes the text "Techbrain," generates an appropriate query, and searches the trademark and copyright database to verify whether the input data infringes any existing trademarks or copyrights.

[0495] Step 4:

[0496] The server receives query results from the database and performs real-time analysis. Specifically, it determines whether TechBrain is infringing on existing rights based on the results obtained from the trademark and copyright databases. Based on the results received (the status of existing trademarks and copyrights), the server then processes and calculates the data to confirm whether there is an infringement.

[0497] Step 5:

[0498] The server returns the result of the judgment to the user's device. Specifically, the server sends the judgment result (e.g., whether "Techbrain" infringes on existing trademark rights) back to the smartphone app. As a result, the user receives a notification indicating whether the content they entered infringes on existing rights.

[0499] Step 6:

[0500] The device will then display the results of the judgment to the user. Specifically, the smartphone app will visually display the results of the judgment received to the user. The user will be able to check whether there is an infringement, for example, as a pop-up message or a notification message, and if there is an infringement, they will be able to take action, such as coming up with a new name.

[0501] 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.

[0502] This invention combines an emotion engine with a system that determines whether names, catchphrases, music lyrics, etc. obtained from a generative AI model infringe on existing trademarks or copyrights. Below, we will explain each component of this system and how it works.

[0503] 1. User Input

[0504] The user uses a terminal to input the generated content. The terminal provides text boxes and forms, and has an interface function for the user to input the name, catchphrase, lyrics, etc. obtained from the generative AI model. Once the input is complete, the user clicks the send button, and the content is sent to the server.

[0505] 2. Submit your input

[0506] The terminal serves to transmit the content entered by the user to the server. This transmission means has a function to transmit data via the Internet, and the content is passed to the server in real time.

[0507] 3. Analysis processing on the server

[0508] The server receives the content sent from the device, analyzes the text of the content, and prepares it for matching with trademark and copyright databases. This analysis includes segmenting the text and extracting specific keywords.

[0509] 4. Trademark and copyright database matching

[0510] The server queries a trademark database and a copyright database to see if the entry overlaps with existing rights. The trademark database stores information about existing trademark rights, and the copyright database stores information about existing copyrights.

[0511] 5. Return and notification of the results

[0512] After obtaining the matching results, the server sends them back to the user's device. The device receives the results and notifies the user. The notification is in the form of a display of the results, and a warning is issued based on the judgment result. If there is an overlap with an existing trademark or copyright, the user is notified of this.

[0513] 6. Incorporating an Emotional Engine

[0514] One of the features of the invention is the incorporation of an emotion engine, which recognizes and analyzes the user's emotions when they are input and when the judgment results are displayed.

[0515] 1. Emotion recognition during input:

[0516] While the user is entering information into the device, the emotion engine analyzes the user's facial image and facial expressions to recognize their emotional state. Based on this analysis, the engine provides appropriate feedback to the user.

[0517] 2. Emotion analysis when displaying judgment results:

[0518] The judgment results are displayed on the user's device, and at the same time, the emotion engine analyzes the user's reaction and understands their emotional state. Based on the analysis results, the displayed warning messages and feedback content are adjusted. For example, if the user is confused, a support message appropriate to their emotion is displayed.

[0519] Specific examples

[0520] Example 1:

[0521] The user generates the name "Tech Innovation" using the generative AI model and enters it into the device's input form. The emotion engine then analyzes the user's facial expressions and recognizes that the user is enjoying themselves. When the user clicks the send button, the content is sent to the server.

[0522] The server receives the content "Tech Innovation" and begins analyzing it, querying trademark and copyright databases to see if it overlaps with existing trademarks or copyrights.

[0523] As a result, it is discovered in the trademark database that the name "Tech Innovation" is registered as an existing trademark. The server sends this result back to the user's device. The device receives the result and displays a warning message to the user stating, "This name may infringe on an existing trademark." The emotion engine also analyzes the user's reaction at the time of display and recognizes that the user is confused. Based on this, it provides further specific improvement suggestions and support messages.

[0524] In this way, the system of the present invention, which combines an emotion engine, can provide feedback on the content created by the user and support the user according to their emotions, allowing the user to use the content with peace of mind and preventing legal troubles.

[0525] The processing flow will be explained below.

[0526] Step 1:

[0527] The user inputs the content to be generated. The user inputs the name, catchphrase, and lyrics obtained from the generative AI model into the input form provided on the device. Once input is complete, the user clicks the send button.

[0528] Step 2:

[0529] The terminal transmits the input contents to the server. The input data is transmitted to the server via the Internet using the transmission means. This transmission process is performed in real time, and the data is quickly delivered to the server.

[0530] Step 3:

[0531] The device recognizes the user's emotions while they are typing. While they are typing, the device's built-in emotion engine analyzes the user's facial image and facial expressions to recognize their emotional state. The analysis results are used in a later step to provide appropriate feedback to the user.

[0532] Step 4:

[0533] The server analyzes the received content. The server analyzes the received data in text format and prepares it for matching against trademark and copyright databases. This analysis includes segmenting the text and extracting specific keywords.

[0534] Step 5:

[0535] The server queries the trademark database. The server searches the received text data against the trademark database to see if there are any matches or similarities with existing trademarks. The result is a similarity score.

[0536] Step 6:

[0537] The server also queries a copyright database: the server searches the received text data against the copyright database to see if there is a match or similarity to existing copyrighted content, and the results are also collected as a similarity score.

[0538] Step 7:

[0539] The server combines the results of the trademark and copyright databases, determines the degree of similarity or match based on the results from each database, and organizes this information into a data format that can be sent back to the user.

[0540] Step 8:

[0541] The server returns the judgment result to the terminal, which then sends the integrated data to the user's terminal and prepares to notify the result.

[0542] Step 9:

[0543] The device receives the determination result and displays it to the user. The device receives the determination result and displays it on the user interface. The result includes a similarity score and specific matching content, and a warning message is displayed to the user.

[0544] Step 10:

[0545] The device analyzes the user's emotions when displaying the judgment result. When the judgment result is displayed, the emotion engine analyzes the user's reaction and understands their emotional state. Based on the analysis results, the warning message and feedback content displayed are adjusted.

[0546] Step 11:

[0547] The user can check the results and take action if necessary. The user can check the displayed results and take action such as reconsidering the generated content or considering a different name. By displaying feedback according to their emotions, the user can make an appropriate decision.

[0548] This process allows users to check in advance whether the generated content infringes existing trademarks or copyrights, preventing legal troubles. In addition, the incorporation of an emotion engine provides more personalized support to users.

[0549] Example 2

[0550] 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."

[0551] Systems that determine whether names, catchphrases, lyrics, etc. generated by conventional generative AI models infringe on existing trademarks or copyrights lack a feedback function that takes into account the user's emotional state. This can lead to users feeling confused or anxious about the provided judgment results. The lack of a user-friendly feedback system can reduce user satisfaction and impair the system's usability.

[0552] 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.

[0553] In this invention, the server includes an input means for inputting the generated content, a transmission means for transmitting the input content to the server, a determination means for analyzing the content in the server and comparing it with a trademark and copyright database, a notification means for returning the determination result to the user's terminal and displaying it to the user, and an emotion analysis means for analyzing the user's emotional state and providing feedback based on the result. This allows the user to receive appropriate feedback on the provided determination result, making it possible to improve user satisfaction and convenience.

[0554] The "input means" is a device that provides an interface for a user to input generated content.

[0555] The "transmission means" is a device that has the function of transmitting the input contents to a server via the Internet.

[0556] The "determination means" is a processing device that analyzes the content received on the server and compares it with a trademark and copyright database.

[0557] The "notification means" is a device that returns the determination result from the server to the user's terminal and displays it to the user.

[0558] The "emotion analysis means" is a device that analyzes the user's facial image and facial expressions to recognize the user's emotional state, and provides appropriate feedback based on the results.

[0559] A "trademark database" is a database that stores information about existing trademarks.

[0560] A "copyright database" is a database that stores information about existing copyrights.

[0561] The "query means" is a device that has the function of executing a query to the trademark database and copyright database and obtaining the matching results.

[0562] The "display means" is a device that displays a warning message to the user based on the determination result.

[0563] This invention combines an emotion engine with a system that determines whether names, catchphrases, music lyrics, etc. obtained from a generative AI model infringe on existing trademarks or copyrights. This system is realized by integrating the following functions: user input, terminal-server communication, data analysis, notification of judgment results, and emotion analysis. Each component of the system and its operation are described below.

[0564] User input

[0565] The user uses the device to input content such as names, catchphrases, and lyrics generated by the generative AI model. The device provides text boxes and forms, and has an interface function for inputting the content generated by the user. As a concrete example, the name "Tech Innovation" is entered into the device's input form.

[0566] Sending input

[0567] When the user clicks the send button, the device transmits the user's input to the server in real time over the Internet using a transmission method designed to reliably deliver data to the server.

[0568] Analysis processing on the server

[0569] After receiving the content sent from the device, the server analyzes it. Specifically, it segments the text of the content and extracts specific keywords. This analysis process is used to prepare queries against trademark and copyright databases. For example, the content "tech innovation" can be split into "tech" and "innovation" and then analyzed for each keyword.

[0570] Trademark and copyright database matching

[0571] The server queries the parsed content against a trademark database and a copyright database to check for overlaps with existing rights. The trademark database stores information about existing trademarks, and the copyright database stores information about existing copyrights.

[0572] Return and notification of judgment results

[0573] The server sends the matching results back to the user's device, which receives the results and notifies the user, for example by displaying a warning message saying, "This name may infringe on an existing trademark."

[0574] Incorporating an emotion engine

[0575] The emotion engine analyzes the user's emotions while the user is entering input content into the device and when the judgment result is displayed. While the user is entering content, the emotion engine analyzes the user's facial image and facial expressions through the device's camera to recognize their emotional state. When the judgment result is displayed, it analyzes the user's reaction and provides appropriate feedback based on their emotional state. For example, if the user is confused, a support message appropriate to their emotion is displayed.

[0576] Specific examples

[0577] Example 1:

[0578] The user generates the name "Tech Innovation" using the generative AI model and enters it into the device's input form. The emotion engine then analyzes the user's facial expressions and recognizes that the user is enjoying themselves. When the user clicks the send button, the content is sent to the server.

[0579] The server receives the content "Tech Innovation" and begins analyzing it, querying trademark and copyright databases to see if it overlaps with existing trademarks or copyrights.

[0580] As a result, it is discovered that the name "Tech Innovation" is registered as an existing trademark in the trademark database. The server sends this result back to the user's device. The device receives the result and displays a warning message to the user stating, "This name may infringe on an existing trademark." The emotion engine also analyzes the user's reaction to this message and recognizes that they are confused. Based on this, it displays supplementary support messages such as "Please consider another name" or "If you need support, please contact us."

[0581] Example prompt sentence:

[0582] "Please explain how to ensure that the generated names and taglines do not infringe on trademarks or copyrights."

[0583] "Please provide a concrete example of a feedback system that uses an emotion engine."

[0584] The above is an embodiment of the present invention.

[0585] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0586] Step 1:

[0587] The user enters the generated content into the input form on the device. Specifically, the user enters a name or catchphrase, such as "Tech Innovation," generated by the generative AI model. Once the input is complete, the device receives the data. The input data is text data. The output is the text data entered by the user.

[0588] Step 2:

[0589] The terminal transmits the text data entered by the user to the server using a transmission means. The transmission means is the Internet, and the data is passed to the server in real time. The input data is the text data entered by the user, and the output is the text data sent to the server.

[0590] Step 3:

[0591] The server receives text data sent from the device. To analyze the received data, it divides the text and extracts specific keywords. For example, "tech innovation" is divided into "tech" and "innovation." This analysis uses text processing programs and algorithms. The input data is the text data received by the server, and the output is the analyzed keyword data.

[0592] Step 4:

[0593] The server queries the parsed keyword data against the trademark and copyright databases. Specifically, the server matches the keywords against the databases to see if they overlap with existing rights. The input data is the parsed keyword data, and the output is the match result data.

[0594] Step 5:

[0595] The server returns the matching result data to the user's terminal. The terminal receives this matching result data and notifies the user. For example, it displays a warning message such as "This name may infringe on an existing trademark." The input data is the matching result data, and the output is a warning message that is displayed to the user.

[0596] Step 6:

[0597] While the user is entering input content into the device, the emotion engine analyzes the user's facial image and facial expressions via the device's camera. Based on the results of this analysis, the user's emotional state is recognized. For example, it identifies emotions such as whether the user is enjoying themselves or feeling confused. The input data is the user's facial image and facial expression data, and the output is analyzed emotional data.

[0598] Step 7:

[0599] At the same time as the judgment result is displayed, the emotion engine analyzes the user's reaction via the device's camera. The feedback message and support message are adjusted based on the analysis results. For example, if the user is confused, a support message such as "Please consider a different name" is displayed. The input data is the emotion data at the time the judgment result is displayed, and the output is the adjusted feedback message.

[0600] (Application example 2)

[0601] 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."

[0602] Systems that determine whether names, catchphrases, lyrics, etc. obtained from generative AI models infringe on existing trademarks and copyrights have the problem of being unable to take users' emotions into consideration and provide appropriate feedback. Another issue is the lack of systems that can understand users' emotional reactions to the results of the determination and provide appropriate support accordingly.

[0603] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an input means for inputting generated content, a transmission means for transmitting the input content to the server, a determination means for analyzing the content in the server and comparing it with a trademark and copyright database, a notification means for returning the determination result to the user's terminal and displaying it to the user, an emotion recognition means for recognizing and analyzing the user's emotions, and a feedback means for providing feedback based on the emotion analysis result. This makes it possible to determine whether the content obtained from the generative AI model infringes existing trademarks and copyrights, and at the same time provide appropriate support according to the user's emotions.

[0604] "Input means for inputting generated content" refers to a means for providing an interface for users to input names, catchphrases, lyrics, etc. obtained from the generative AI model.

[0605] The "transmission means for transmitting the input contents to the server" is a communication means for transmitting the contents input by the user to the server, and is a means having the function of transferring data via a network such as the Internet.

[0606] The "determination means for analyzing the content on the server and comparing it with the trademark and copyright database" refers to a means for analyzing the content entered on the server, comparing it with the trademark and copyright databases, and checking whether it overlaps with existing rights.

[0607] The "notification means for returning the judgment results to the user's terminal and displaying them to the user" refers to a means for returning the judgment results of trademark right and copyright to the user's terminal and displaying them on the screen.

[0608] The "emotion recognition means for recognizing and analyzing the user's emotions" is a means for analyzing the facial expressions and actions of the user when the user performs an input operation or displays a judgment result, and recognizing the user's emotional state.

[0609] The "feedback means for providing feedback based on the emotion analysis result" is a means for providing appropriate feedback or a support message to the user based on the emotion analysis result obtained by the emotion recognition means.

[0610] This section describes an embodiment of the present invention. This system determines whether names, catchphrases, lyrics, etc. generated by a generative AI model infringe on existing trademarks or copyrights, and recognizes the user's emotional state and provides appropriate feedback. Each component and its operation are described in detail below.

[0611] 1. User Input

[0612] Users install the ad creation support app on their smartphone and input the name and catchphrase obtained from the generative AI model. This input is done via an input means that provides an interface. Specifically, users enter their information into a text box and click the send button.

[0613] 2. Submit your input

[0614] The information entered by the user is sent to the server via the Internet. The transmission means has the function of transferring data in real time using the HTTP protocol. This allows the information entered by the user to be delivered to the server quickly.

[0615] 3. Analysis processing on the server

[0616] The server analyzes the received content. Specifically, it uses a server-side program (e.g., Node.js) to split the text and extract keywords. Based on the results of this analysis, it prepares to match the data with trademark and copyright databases.

[0617] 4. Trademark and copyright database matching

[0618] The server queries a trademark database and a copyright database to see if the entry overlaps with existing rights. The trademark database stores information about existing trademark rights, and the copyright database stores information about existing copyrights.

[0619] 5. Return and notification of the results

[0620] After obtaining the matching result, the server sends the result back to the user's device. The device receives the result and notifies the user. The result is displayed on the screen and a warning message is provided based on the judgment result.

[0621] 6. Incorporating an Emotional Engine

[0622] While the user is entering input content into the device, the emotion engine operates and analyzes the user's facial expressions. It uses libraries such as EmotionRecognition to recognize the user's emotional state from facial images and expressions. Based on the analysis results, it provides appropriate feedback to the user.

[0623] The judgment results are displayed on the user's device, and at the same time, the emotion engine analyzes the user's reaction and understands their emotional state. Based on the analysis results, the displayed warning messages and feedback content can be adjusted. For example, if the user is confused, a support message appropriate to their emotion will be displayed.

[0624] Specific examples

[0625] For example, suppose a user generates the name "Cool Tech" and enters it into an input form. At this time, the emotion engine recognizes the user's smile and analyzes it as a state of enjoyment. The input is sent to the server and compared with the trademark database. As a result, it is confirmed that the name "Cool Tech" does not match any existing trademark rights, and the user is notified that it is valid. In addition, to maintain the user's enjoyment, positive feedback based on the emotion analysis results is displayed.

[0626] Prompt Sentence Examples

[0627] "Generate a new name for creating ads"

[0628] In this way, by implementing the invention, users can use the generated content with peace of mind, prevent legal troubles, and receive appropriate support according to their emotions.

[0629] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0630] Step 1:

[0631] The user launches the ad creation support app and inputs the name and catchphrase obtained from the generative AI model. Using the input means (text box), the user inputs the content following the prompt "Generate a new name for ad creation." The user enters "Cool Tech" as the input content and clicks the send button. The input content is obtained in text format.

[0632] Step 2:

[0633] The terminal sends the user's input to the server via the Internet. The transmission method uses the HTTP protocol, and the user's text data is sent to the server in JSON format. The input is the text entered by the user, and the output is the text data received by the server.

[0634] Step 3:

[0635] The content received by the server is analyzed. Specifically, a server-side program (Node.js) is used to split the text and extract keywords. The input text is analyzed and keywords are identified. This analyzed data becomes the preparation data for subsequent database matching. The input is the received text data, and the output is the analyzed keyword data.

[0636] Step 4:

[0637] The server queries trademark and copyright databases to ensure that the input does not overlap with existing rights. It uses a query mechanism to match identified keywords against the database. The input is the analyzed keyword data, and the output is the match result data.

[0638] Step 5:

[0639] The server returns the matching results to the user's device. The result data is encoded in JSON format and sent to the device via the HTTP protocol. The input is the matching result data, and the output is the result data received on the device.

[0640] Step 6:

[0641] The terminal displays the received matching result on the screen and notifies the user. Specifically, the result is displayed in text format using a notification means. For example, a message such as "Cool Tech is available for use" is displayed. The input is the received result data, and the output is the text displayed on the screen.

[0642] Step 7:

[0643] At the same time, the emotion engine analyzes the user's facial expression. Using the EmotionRecognition library, it analyzes the user's facial image during input and when the results are displayed to identify the emotion. The emotional state is identified and obtained as analysis data. The input is the user's facial image, and the output is emotion analysis data.

[0644] Step 8:

[0645] The device provides the user with appropriate feedback based on the emotion analysis results. The feedback means is used to display positive feedback or supportive messages on the screen. For example, a message such as "Great idea! This name is available." is displayed. The input is emotion analysis data, and the output is a feedback message.

[0646] In this way, throughout the process, the user's input is checked for legal compliance and feedback is provided according to the user's emotional state.

[0647] 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.

[0648] 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.

[0649] 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.

[0650] [Third embodiment]

[0651] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0652] 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.

[0653] 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).

[0654] 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.

[0655] 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.

[0656] 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).

[0657] 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.

[0658] 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.

[0659] 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.

[0660] 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.

[0661] 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.

[0662] 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."

[0663] This invention is a system that determines whether names, catchphrases, music lyrics, etc. obtained from a generative AI model infringe on existing trademarks or copyrights. Below, we will explain each component of this system and how it works.

[0664] 1. User Input

[0665] The user uses a terminal to input the generated content. The terminal is equipped with text boxes and forms, providing an interface for the user to input the name, catchphrase, lyrics, etc. obtained from the generative AI model. Once the input is complete, the user clicks the send button, and the content is sent to the server.

[0666] 2. Submit your input

[0667] The terminal plays a role in transmitting the content entered by the user to the server. The transmission means includes a function to transmit data to the server via the Internet, which allows the entered content to be quickly delivered to the server.

[0668] 3. Analysis processing on the server

[0669] The server receives the content sent from the terminal, and then analyzes the content, which includes splitting the text of the content and preparing it for matching with trademark and copyright databases.

[0670] 4. Trademark and copyright database matching

[0671] The server queries a trademark and copyright database to see if the entry overlaps with existing rights: the trademark database stores information about existing trademark rights, and the copyright database stores information about existing copyrights.

[0672] 5. Return and notification of the results

[0673] After obtaining the matching results, the server sends them back to the device. The device receives the results and notifies the user. The notification is in the form of a display of the results, and a warning is issued based on the judgment result. If there is an overlap with an existing trademark or copyright, the user is notified of this.

[0674] Specific examples

[0675] Example 1:

[0676] The user generates the name "Tech Innovation" using a generative AI model, enters "Tech Innovation" into the input form on their device, and then clicks the submit button.

[0677] The device sends the content "tech innovation" to the server. The server receives this content and begins to analyze the text "tech innovation." The analysis results are obtained by running queries against trademark and copyright databases.

[0678] A trademark database reveals that the existing name "Tech Innovation" is registered as a trademark, while a copyright database reveals that it is not registered as a name associated with any particular copyrighted work.

[0679] The server then sends these results back to the user's device, informing them that the name "Tech Innovation" may infringe on an existing trademark, allowing them to reconsider the new name.

[0680] In this way, the system of the present invention provides an effective means for proactively checking user-generated content and preventing legal trouble.

[0681] The processing flow will be explained below.

[0682] Step 1:

[0683] The user inputs the content to be generated. The user inputs the name, catchphrase, lyrics, etc. obtained from the generative AI model into the input form provided on the device. Once input is complete, the user clicks the send button.

[0684] Step 2:

[0685] The terminal transmits the input contents to the server. The input data is transmitted to the server via the Internet using the transmission means. This transmission process is performed in real time, and the data is quickly delivered to the server.

[0686] Step 3:

[0687] The server analyzes the received content. The server analyzes the received data in text format and prepares it for matching against trademark and copyright databases. This analysis includes segmenting the text and extracting specific keywords.

[0688] Step 4:

[0689] The server queries the trademark database. The server searches the received text data against the trademark database to see if there are any matches or similarities with existing trademarks. The results are obtained as a hypothesis-based similarity score.

[0690] Step 5:

[0691] The server also queries a copyright database: the server searches the received text data against the copyright database to see if there is a match or similarity to existing copyrighted content, and the results are also collected as a similarity score.

[0692] Step 6:

[0693] The server combines the results of the trademark and copyright databases, determines the degree of similarity or match based on the results from each database, and organizes this information into a data format that can be sent back to the user.

[0694] Step 7:

[0695] The server returns the judgment result to the terminal, which then sends the integrated data to the user's terminal and prepares to notify the result.

[0696] Step 8:

[0697] The device receives the determination result and displays it to the user. The device receives the determination result and displays it on the user interface. The result includes a similarity score and specific matching content, and a warning message is displayed to the user.

[0698] Step 9:

[0699] The user can check the results and take action as necessary. The user can check the displayed results and take action such as reconsidering the content to be generated or considering a different name.

[0700] This series of processes allows users to check in advance whether the generated content infringes existing trademark rights and copyrights, thereby preventing legal troubles.

[0701] Example 1

[0702] 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."

[0703] Until now, manually checking whether names, catchphrases, lyrics, and other content derived from generative AI models infringe on existing trademarks or copyrights has been extremely difficult for ordinary end users, as it is time-consuming, costly, and requires specialized knowledge. For this reason, an effective means of preventing legal troubles has been sought.

[0704] 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.

[0705] In this invention, the server includes an input means for inputting content generated by an end user, a transmission means for transmitting the input content via a network, a preprocessing means for receiving the input content and performing text analysis, a determination means for comparing the preprocessed content with a trademark database and a copyright database, a notification means for returning and notifying the end user of the comparison result, a query means for executing a comparison query, and a display means for displaying a warning message to the end user based on the comparison result. This makes it possible to quickly and easily determine the risk of infringement of trademark and copyright in content generated by the end user and prevent legal trouble before it occurs.

[0706] "Input means" refers to a device or interface for an end user to input generated content.

[0707] "Transmission means" refers to the technology and functions for transmitting the input content to a server via a network.

[0708] "Preprocessing means" refers to the technology or process used by the server to process the input received into a form that is easy to analyze.

[0709] "Determination means" refers to the technology or process for cross-checking the pre-processed content with a trademark database and a copyright database to make a determination.

[0710] "Notification means" refers to the technology and functions that allow the server to return and display the matching results to the end user's terminal.

[0711] "Query Instrument" means the technology or process for executing matching queries against trademark and copyright databases.

[0712] "Display means" refers to a technology or device for displaying a warning message to the end user based on the matching result.

[0713] This invention is a system that determines whether names, catchphrases, music lyrics, etc. obtained from a generative AI model infringe on existing trademarks or copyrights. Below, we will explain each component of this system and its operation.

[0714] User input

[0715] The user uses a terminal to input the generated content. The terminal is equipped with text boxes and forms, providing an interface for the user to input the name, catchphrase, lyrics, etc. obtained from the generative AI model. Once the user has completed the input, they click the send button to send the content to the server.

[0716] Sending input

[0717] The terminal is responsible for transmitting the information entered by the user to the server. This transmission is mainly carried out via the Internet, so the data reaches the server quickly.

[0718] Analysis processing on the server

[0719] The server receives the content sent from the device and then analyzes it, including tokenizing and morphological analysis of the text, in preparation for matching against trademark and copyright databases.

[0720] Trademark and copyright database matching

[0721] The server queries a trademark and copyright database to see if the entry overlaps with existing rights: the trademark database stores information about existing trademarks, and the copyright database stores information about existing copyrighted works.

[0722] Return and notification of judgment results

[0723] After obtaining the matching results, the server sends them back to the device. The device receives the results and notifies the user. The notification is in the form of a display of the results, and a warning is issued based on the judgment result. If there is an overlap with an existing trademark or copyright, the user is notified of this.

[0724] Specific examples

[0725] A user generates the name "Tech Innovation" using a generative AI model and enters "Tech Innovation" into an input form on their device. They then click the submit button. The device sends the content "Tech Innovation" to the server. The server receives this content and begins analyzing the text "Tech Innovation." The analysis results are obtained by running queries against trademark and copyright databases.

[0726] A trademark database reveals that the existing name "Tech Innovation" is registered as a trademark, while a copyright database reveals that it is not registered as a name associated with any particular copyrighted work.

[0727] The server then sends these results back to the device, informing the user that the name "Tech Innovation" may infringe on an existing trademark, allowing the user to reconsider the new name.

[0728] In this way, the system of the present invention provides an effective means for proactively checking user-generated content and preventing legal trouble.

[0729] Prompt Sentence Examples

[0730] Here are some example prompts to input to a generative AI model:

[0731] "Generate names for new technology companies."

[0732] The name, catchphrase, lyrics, etc. generated based on this prompt text are input into the system to determine trademark and copyright infringement.

[0733] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0734] Step 1:

[0735] The user uses the input form on the device to input the content obtained from the generative AI model (e.g., "Tech Innovation") and clicks the send button. This inputs the text data into the device. After input, the device prepares to send this text data to the server.

[0736] Specific behavior:

[0737] The user enters "Tech Innovation" into the text box on the terminal and clicks the send button. The input data is ready to be sent to the server in text format.

[0738] Step 2:

[0739] The terminal sends the text data entered by the user to the server using a network protocol such as an HTTP POST request. The input data, which is the text "Tech Innovation," reaches the server.

[0740] Specific behavior:

[0741] The device sends the text data "Tech Innovation" to the server via an HTTP POST request.

[0742] Step 3:

[0743] The server receives the text data sent from the device and preprocesses the received data ("Tech Innovation") into a format that is easy to analyze. This preprocessing includes tokenizing the text and performing morphological analysis.

[0744] Specific behavior:

[0745] The server receives the text "tech innovation," divides it into words (tokenizes it), and performs preprocessing for analysis.

[0746] Step 4:

[0747] The server uses the preprocessed text data to query the trademark database and the copyright database. For example, if the input data is "tech innovation," the server creates and executes a corresponding query against the trademark database and the copyright database. The results obtained from the databases are analyzed to see if the input overlaps with existing rights.

[0748] Specific behavior:

[0749] The server queries the trademark and copyright databases for "tech innovation" and retrieves results from each database.

[0750] Step 5:

[0751] The server generates a judgment result based on the data obtained from the trademark database and copyright database, and returns the result to the end user's terminal, preparing to notify them.

[0752] Specific behavior:

[0753] The server checks the trademark database to see that "Tech Innovation" is registered as an existing trademark, and similarly checks the copyright database to see that it is not registered as a related copyrighted work.

[0754] Step 6:

[0755] The server returns the results of the assessment to the device, which then notifies the user of the results and issues a warning based on the results.

[0756] Specific behavior:

[0757] The server sends a result to the device indicating that "Tech Innovation" may infringe on an existing trademark, and the device displays this and notifies the user to come up with a new name.

[0758] (Application example 1)

[0759] 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."

[0760] There is a need for a reliable system that can check in real time whether names, catchphrases, lyrics, etc. created using generative AI models infringe on existing trademarks or copyrights. However, current systems do not have a method for instantly checking this, making it difficult to prevent the risk of user-generated content infringing on rights in advance. The present invention aims to solve this problem.

[0761] 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.

[0762] In this invention, the server includes an input means for inputting generated content, a transmission means for transmitting the input content to the server, a determination means for analyzing the content on the server and comparing it with a trademark database and a copyright database, and a real-time analysis means for checking in real time whether content created using the generative AI model infringes trademarks or copyrights. This makes it possible to instantly check content created by users and prevent infringement of rights before it occurs.

[0763] A "generative AI model" is a model that uses artificial intelligence to generate new content such as text and designs.

[0764] An "input means" is a device or mechanism that provides an interface for a user to input generated content.

[0765] The "transmission means" refers to a device or mechanism for transmitting the inputted content to the server as data.

[0766] The "determination means" is a device or mechanism that analyzes the content on the server side and compares it with the trademark database and copyright database.

[0767] The "notification means" is a device or mechanism for returning the determination result to the user's terminal and notifying the user.

[0768] "Real-time analysis means" refers to devices or mechanisms that instantly check whether content created using a generative AI model infringes trademark rights or copyrights.

[0769] A "query means" is a device or mechanism for executing queries against trademark and copyright databases.

[0770] The "display means" is a device or mechanism for visually presenting a warning message to the user based on the determination result.

[0771] This invention is a system that checks whether catchphrases and names created using generative AI models infringe on existing trademarks or copyrights. Below, we will explain how this system is implemented in concrete terms.

[0772] System Configuration

[0773] The system consists of the following main components:

[0774] Input means: An interface for the user to input the generated content.

[0775] Transmission means: A mechanism for transmitting the input content to the server.

[0776] Determination means: A mechanism for analyzing the content on the server side and comparing it with a trademark database and a copyright database.

[0777] Notification means: A mechanism for returning the judgment result to the user's terminal and notifying the user.

[0778] Real-time analysis means: A mechanism for instantly checking content created using generative AI models (performing real-time processing).

[0779] Query facility: A mechanism for performing queries against trademark and copyright databases.

[0780] Display means: A mechanism for displaying a warning message based on the determination result.

[0781] What the program does

[0782] The server program has the following features:

[0783] Receiving and sending input data: Receives user input and processes it.

[0784] Data Analysis: Analyzes input text data and queries trademark and copyright databases.

[0785] Real-time detection: Determine whether there is any trademark or copyright infringement based on the query results in real time.

[0786] Notification and display of results: The judgment results are returned to the user's device and the results are displayed to notify the user.

[0787] Hardware and software used

[0788] Flask: Used as a server-side application framework.

[0789] Requests library: Used to execute HTTP requests on the server.

[0790] Smartphone: A device that handles user input and displays results.

[0791] Generative AI model: Used to generate new catchphrases and names.

[0792] Specific examples

[0793] For example:

[0794] Prompt Sentence Examples

[0795] "Generate the name 'Tech Brain' for a new startup product."

[0796] Processing flow

[0797] 1. User input: The user enters "Tech Brain" into the text box on the smartphone app and sends the content to the server.

[0798] 2. Server processing: The server analyzes the received content and sends queries to trademark and copyright databases.

[0799] 3. Return of results: Based on the results obtained, a real-time determination is made as to whether the entered "Tech Brain" infringes on existing trademarks or copyrights.

[0800] 4. Notification and display: The judgement result will be sent immediately to the smartphone and the user will be notified. If the judgement result indicates infringement, the user can reconsider the new name.

[0801] Through this specific process, the system of the present invention can immediately verify that the content generated by the user does not infringe trademark rights or copyrights, thereby preventing legal troubles.

[0802] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0803] Step 1:

[0804] The user inputs the content generated by the generative AI model into a smartphone application. Specifically, the user enters the newly generated catchphrase or name into a text box and clicks the application's send button to send the content to the server. The input data includes the generated name, such as "Tech Brain."

[0805] Step 2:

[0806] The device sends the entered content to the server. In this case, the smartphone app sends text data such as "Tech Brain" to the server as an HTTP request. The input data includes the content entered in the text box ("Tech Brain"), and after it is sent, it is received by the server.

[0807] Step 3:

[0808] The server analyzes the received text data and sends a query to the trademark and copyright database. Specifically, the server analyzes the text "Techbrain," generates an appropriate query, and searches the trademark and copyright database to verify whether the input data infringes any existing trademarks or copyrights.

[0809] Step 4:

[0810] The server receives query results from the database and performs real-time analysis. Specifically, it determines whether TechBrain is infringing on existing rights based on the results obtained from the trademark and copyright databases. Based on the results received (the status of existing trademarks and copyrights), the server then processes and calculates the data to confirm whether there is an infringement.

[0811] Step 5:

[0812] The server returns the result of the judgment to the user's device. Specifically, the server sends the judgment result (e.g., whether "Techbrain" infringes on existing trademark rights) back to the smartphone app. As a result, the user receives a notification indicating whether the content they entered infringes on existing rights.

[0813] Step 6:

[0814] The device will then display the results of the judgment to the user. Specifically, the smartphone app will visually display the results of the judgment received to the user. The user will be able to check whether there is an infringement, for example, as a pop-up message or a notification message, and if there is an infringement, they will be able to take action, such as coming up with a new name.

[0815] 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.

[0816] This invention combines an emotion engine with a system that determines whether names, catchphrases, music lyrics, etc. obtained from a generative AI model infringe on existing trademarks or copyrights. Below, we will explain each component of this system and how it works.

[0817] 1. User Input

[0818] The user uses a terminal to input the generated content. The terminal provides text boxes and forms, and has an interface function for the user to input the name, catchphrase, lyrics, etc. obtained from the generative AI model. Once the input is complete, the user clicks the send button, and the content is sent to the server.

[0819] 2. Submit your input

[0820] The terminal serves to transmit the content entered by the user to the server. This transmission means has a function to transmit data via the Internet, and the content is passed to the server in real time.

[0821] 3. Analysis processing on the server

[0822] The server receives the content sent from the device, analyzes the text of the content, and prepares it for matching with trademark and copyright databases. This analysis includes segmenting the text and extracting specific keywords.

[0823] 4. Trademark and copyright database matching

[0824] The server queries a trademark database and a copyright database to see if the entry overlaps with existing rights. The trademark database stores information about existing trademark rights, and the copyright database stores information about existing copyrights.

[0825] 5. Return and notification of the results

[0826] After obtaining the matching results, the server sends them back to the user's device. The device receives the results and notifies the user. The notification is in the form of a display of the results, and a warning is issued based on the judgment result. If there is an overlap with an existing trademark or copyright, the user is notified of this.

[0827] 6. Incorporating an Emotional Engine

[0828] One of the features of the invention is the incorporation of an emotion engine, which recognizes and analyzes the user's emotions when they are input and when the judgment results are displayed.

[0829] 1. Emotion recognition during input:

[0830] While the user is entering information into the device, the emotion engine analyzes the user's facial image and facial expressions to recognize their emotional state. Based on this analysis, the engine provides appropriate feedback to the user.

[0831] 2. Emotion analysis when displaying judgment results:

[0832] The judgment results are displayed on the user's device, and at the same time, the emotion engine analyzes the user's reaction and understands their emotional state. Based on the analysis results, the displayed warning messages and feedback content are adjusted. For example, if the user is confused, a support message appropriate to their emotion is displayed.

[0833] Specific examples

[0834] Example 1:

[0835] The user generates the name "Tech Innovation" using the generative AI model and enters it into the device's input form. The emotion engine then analyzes the user's facial expressions and recognizes that the user is enjoying themselves. When the user clicks the send button, the content is sent to the server.

[0836] The server receives the content "Tech Innovation" and begins analyzing it, querying trademark and copyright databases to see if it overlaps with existing trademarks or copyrights.

[0837] As a result, it is discovered in the trademark database that the name "Tech Innovation" is registered as an existing trademark. The server sends this result back to the user's device. The device receives the result and displays a warning message to the user stating, "This name may infringe on an existing trademark." The emotion engine also analyzes the user's reaction at the time of display and recognizes that the user is confused. Based on this, it provides further specific improvement suggestions and support messages.

[0838] In this way, the system of the present invention, which combines an emotion engine, can provide feedback on the content created by the user and support the user according to their emotions, allowing the user to use the content with peace of mind and preventing legal troubles.

[0839] The processing flow will be explained below.

[0840] Step 1:

[0841] The user inputs the content to be generated. The user inputs the name, catchphrase, and lyrics obtained from the generative AI model into the input form provided on the device. Once input is complete, the user clicks the send button.

[0842] Step 2:

[0843] The terminal transmits the input contents to the server. The input data is transmitted to the server via the Internet using the transmission means. This transmission process is performed in real time, and the data is quickly delivered to the server.

[0844] Step 3:

[0845] The device recognizes the user's emotions while they are typing. While they are typing, the device's built-in emotion engine analyzes the user's facial image and facial expressions to recognize their emotional state. The analysis results are used in a later step to provide appropriate feedback to the user.

[0846] Step 4:

[0847] The server analyzes the received content. The server analyzes the received data in text format and prepares it for matching against trademark and copyright databases. This analysis includes segmenting the text and extracting specific keywords.

[0848] Step 5:

[0849] The server queries the trademark database. The server searches the received text data against the trademark database to see if there are any matches or similarities with existing trademarks. The result is a similarity score.

[0850] Step 6:

[0851] The server also queries a copyright database: the server searches the received text data against the copyright database to see if there is a match or similarity to existing copyrighted content, and the results are also collected as a similarity score.

[0852] Step 7:

[0853] The server combines the results of the trademark and copyright databases, determines the degree of similarity or match based on the results from each database, and organizes this information into a data format that can be sent back to the user.

[0854] Step 8:

[0855] The server returns the judgment result to the terminal, which then sends the integrated data to the user's terminal and prepares to notify the result.

[0856] Step 9:

[0857] The device receives the determination result and displays it to the user. The device receives the determination result and displays it on the user interface. The result includes a similarity score and specific matching content, and a warning message is displayed to the user.

[0858] Step 10:

[0859] The device analyzes the user's emotions when displaying the judgment result. When the judgment result is displayed, the emotion engine analyzes the user's reaction and understands their emotional state. Based on the analysis results, the warning message and feedback content displayed are adjusted.

[0860] Step 11:

[0861] The user can check the results and take action if necessary. The user can check the displayed results and take action such as reconsidering the generated content or considering a different name. By displaying feedback according to their emotions, the user can make an appropriate decision.

[0862] This process allows users to check in advance whether the generated content infringes existing trademarks or copyrights, preventing legal troubles. In addition, the incorporation of an emotion engine provides more personalized support to users.

[0863] Example 2

[0864] 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."

[0865] Systems that determine whether names, catchphrases, lyrics, etc. generated by conventional generative AI models infringe on existing trademarks or copyrights lack a feedback function that takes into account the user's emotional state. This can lead to users feeling confused or anxious about the provided judgment results. The lack of a user-friendly feedback system can reduce user satisfaction and impair the system's usability.

[0866] 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.

[0867] In this invention, the server includes an input means for inputting the generated content, a transmission means for transmitting the input content to the server, a determination means for analyzing the content in the server and comparing it with a trademark and copyright database, a notification means for returning the determination result to the user's terminal and displaying it to the user, and an emotion analysis means for analyzing the user's emotional state and providing feedback based on the result. This allows the user to receive appropriate feedback on the provided determination result, making it possible to improve user satisfaction and convenience.

[0868] The "input means" is a device that provides an interface for a user to input generated content.

[0869] The "transmission means" is a device that has the function of transmitting the input contents to a server via the Internet.

[0870] The "determination means" is a processing device that analyzes the content received on the server and compares it with a trademark and copyright database.

[0871] The "notification means" is a device that returns the determination result from the server to the user's terminal and displays it to the user.

[0872] The "emotion analysis means" is a device that analyzes the user's facial image and facial expressions to recognize the user's emotional state, and provides appropriate feedback based on the results.

[0873] A "trademark database" is a database that stores information about existing trademarks.

[0874] A "copyright database" is a database that stores information about existing copyrights.

[0875] The "query means" is a device that has the function of executing a query to the trademark database and copyright database and obtaining the matching results.

[0876] The "display means" is a device that displays a warning message to the user based on the determination result.

[0877] This invention combines an emotion engine with a system that determines whether names, catchphrases, music lyrics, etc. obtained from a generative AI model infringe on existing trademarks or copyrights. This system is realized by integrating the following functions: user input, terminal-server communication, data analysis, notification of judgment results, and emotion analysis. Each component of the system and its operation are described below.

[0878] User input

[0879] The user uses the device to input content such as names, catchphrases, and lyrics generated by the generative AI model. The device provides text boxes and forms, and has an interface function for inputting the content generated by the user. As a concrete example, the name "Tech Innovation" is entered into the device's input form.

[0880] Sending input

[0881] When the user clicks the send button, the device transmits the user's input to the server in real time over the Internet using a transmission method designed to reliably deliver data to the server.

[0882] Analysis processing on the server

[0883] After receiving the content sent from the device, the server analyzes it. Specifically, it segments the text of the content and extracts specific keywords. This analysis process is used to prepare queries against trademark and copyright databases. For example, the content "tech innovation" can be split into "tech" and "innovation" and then analyzed for each keyword.

[0884] Trademark and copyright database matching

[0885] The server queries the parsed content against a trademark database and a copyright database to check for overlaps with existing rights. The trademark database stores information about existing trademarks, and the copyright database stores information about existing copyrights.

[0886] Return and notification of judgment results

[0887] The server sends the matching results back to the user's device, which receives the results and notifies the user, for example by displaying a warning message saying, "This name may infringe on an existing trademark."

[0888] Incorporating an emotion engine

[0889] The emotion engine analyzes the user's emotions while the user is entering input content into the device and when the judgment result is displayed. While the user is entering content, the emotion engine analyzes the user's facial image and facial expressions through the device's camera to recognize their emotional state. When the judgment result is displayed, it analyzes the user's reaction and provides appropriate feedback based on their emotional state. For example, if the user is confused, a support message appropriate to their emotion is displayed.

[0890] Specific examples

[0891] Example 1:

[0892] The user generates the name "Tech Innovation" using the generative AI model and enters it into the device's input form. The emotion engine then analyzes the user's facial expressions and recognizes that the user is enjoying themselves. When the user clicks the send button, the content is sent to the server.

[0893] The server receives the content "Tech Innovation" and begins analyzing it, querying trademark and copyright databases to see if it overlaps with existing trademarks or copyrights.

[0894] As a result, it is discovered that the name "Tech Innovation" is registered as an existing trademark in the trademark database. The server sends this result back to the user's device. The device receives the result and displays a warning message to the user stating, "This name may infringe on an existing trademark." The emotion engine also analyzes the user's reaction to this message and recognizes that they are confused. Based on this, it displays supplementary support messages such as "Please consider another name" or "If you need support, please contact us."

[0895] Example prompt sentence:

[0896] "Please explain how to ensure that the generated names and taglines do not infringe on trademarks or copyrights."

[0897] "Please provide a concrete example of a feedback system that uses an emotion engine."

[0898] The above is an embodiment of the present invention.

[0899] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0900] Step 1:

[0901] The user enters the generated content into the input form on the device. Specifically, the user enters a name or catchphrase, such as "Tech Innovation," generated by the generative AI model. Once the input is complete, the device receives the data. The input data is text data. The output is the text data entered by the user.

[0902] Step 2:

[0903] The terminal transmits the text data entered by the user to the server using a transmission means. The transmission means is the Internet, and the data is passed to the server in real time. The input data is the text data entered by the user, and the output is the text data sent to the server.

[0904] Step 3:

[0905] The server receives text data sent from the device. To analyze the received data, it divides the text and extracts specific keywords. For example, "tech innovation" is divided into "tech" and "innovation." This analysis uses text processing programs and algorithms. The input data is the text data received by the server, and the output is the analyzed keyword data.

[0906] Step 4:

[0907] The server queries the parsed keyword data against the trademark and copyright databases. Specifically, the server matches the keywords against the databases to see if they overlap with existing rights. The input data is the parsed keyword data, and the output is the match result data.

[0908] Step 5:

[0909] The server returns the matching result data to the user's terminal. The terminal receives this matching result data and notifies the user. For example, it displays a warning message such as "This name may infringe on an existing trademark." The input data is the matching result data, and the output is a warning message that is displayed to the user.

[0910] Step 6:

[0911] While the user is entering input content into the device, the emotion engine analyzes the user's facial image and facial expressions via the device's camera. Based on the results of this analysis, the user's emotional state is recognized. For example, it identifies emotions such as whether the user is enjoying themselves or feeling confused. The input data is the user's facial image and facial expression data, and the output is analyzed emotional data.

[0912] Step 7:

[0913] At the same time as the judgment result is displayed, the emotion engine analyzes the user's reaction via the device's camera. The feedback message and support message are adjusted based on the analysis results. For example, if the user is confused, a support message such as "Please consider a different name" is displayed. The input data is the emotion data at the time the judgment result is displayed, and the output is the adjusted feedback message.

[0914] (Application example 2)

[0915] 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."

[0916] Systems that determine whether names, catchphrases, lyrics, etc. obtained from generative AI models infringe on existing trademarks and copyrights have the problem of being unable to take users' emotions into consideration and provide appropriate feedback. Another issue is the lack of systems that can understand users' emotional reactions to the results of the determination and provide appropriate support accordingly.

[0917] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an input means for inputting generated content, a transmission means for transmitting the input content to the server, a determination means for analyzing the content in the server and comparing it with a trademark and copyright database, a notification means for returning the determination result to the user's terminal and displaying it to the user, an emotion recognition means for recognizing and analyzing the user's emotions, and a feedback means for providing feedback based on the emotion analysis result. This makes it possible to determine whether the content obtained from the generative AI model infringes existing trademarks and copyrights, and at the same time provide appropriate support according to the user's emotions.

[0918] "Input means for inputting generated content" refers to a means for providing an interface for users to input names, catchphrases, lyrics, etc. obtained from the generative AI model.

[0919] The "transmission means for transmitting the input contents to the server" is a communication means for transmitting the contents input by the user to the server, and is a means having the function of transferring data via a network such as the Internet.

[0920] The "determination means for analyzing the content on the server and comparing it with the trademark and copyright database" refers to a means for analyzing the content entered on the server, comparing it with the trademark and copyright databases, and checking whether it overlaps with existing rights.

[0921] The "notification means for returning the judgment results to the user's terminal and displaying them to the user" refers to a means for returning the judgment results of trademark right and copyright to the user's terminal and displaying them on the screen.

[0922] The "emotion recognition means for recognizing and analyzing the user's emotions" is a means for analyzing the facial expressions and actions of the user when the user performs an input operation or displays a judgment result, and recognizing the user's emotional state.

[0923] The "feedback means for providing feedback based on the emotion analysis result" is a means for providing appropriate feedback or a support message to the user based on the emotion analysis result obtained by the emotion recognition means.

[0924] This section describes an embodiment of the present invention. This system determines whether names, catchphrases, lyrics, etc. generated by a generative AI model infringe on existing trademarks or copyrights, and recognizes the user's emotional state and provides appropriate feedback. Each component and its operation are described in detail below.

[0925] 1. User Input

[0926] Users install the ad creation support app on their smartphone and input the name and catchphrase obtained from the generative AI model. This input is done via an input means that provides an interface. Specifically, users enter their information into a text box and click the send button.

[0927] 2. Submit your input

[0928] The information entered by the user is sent to the server via the Internet. The transmission means has the function of transferring data in real time using the HTTP protocol. This allows the information entered by the user to be delivered to the server quickly.

[0929] 3. Analysis processing on the server

[0930] The server analyzes the received content. Specifically, it uses a server-side program (e.g., Node.js) to split the text and extract keywords. Based on the results of this analysis, it prepares to match the data with trademark and copyright databases.

[0931] 4. Trademark and copyright database matching

[0932] The server queries a trademark database and a copyright database to see if the entry overlaps with existing rights. The trademark database stores information about existing trademark rights, and the copyright database stores information about existing copyrights.

[0933] 5. Return and notification of the results

[0934] After obtaining the matching result, the server sends the result back to the user's device. The device receives the result and notifies the user. The result is displayed on the screen and a warning message is provided based on the judgment result.

[0935] 6. Incorporating an Emotional Engine

[0936] While the user is entering input content into the device, the emotion engine operates and analyzes the user's facial expressions. It uses libraries such as EmotionRecognition to recognize the user's emotional state from facial images and expressions. Based on the analysis results, it provides appropriate feedback to the user.

[0937] The judgment results are displayed on the user's device, and at the same time, the emotion engine analyzes the user's reaction and understands their emotional state. Based on the analysis results, the displayed warning messages and feedback content can be adjusted. For example, if the user is confused, a support message appropriate to their emotion will be displayed.

[0938] Specific examples

[0939] For example, suppose a user generates the name "Cool Tech" and enters it into an input form. At this time, the emotion engine recognizes the user's smile and analyzes it as a state of enjoyment. The input is sent to the server and compared with the trademark database. As a result, it is confirmed that the name "Cool Tech" does not match any existing trademark rights, and the user is notified that it is valid. In addition, to maintain the user's enjoyment, positive feedback based on the emotion analysis results is displayed.

[0940] Prompt Sentence Examples

[0941] "Generate a new name for creating ads"

[0942] In this way, by implementing the invention, users can use the generated content with peace of mind, prevent legal troubles, and receive appropriate support according to their emotions.

[0943] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0944] Step 1:

[0945] The user launches the ad creation support app and inputs the name and catchphrase obtained from the generative AI model. Using the input means (text box), the user inputs the content following the prompt "Generate a new name for ad creation." The user enters "Cool Tech" as the input content and clicks the send button. The input content is obtained in text format.

[0946] Step 2:

[0947] The terminal sends the user's input to the server via the Internet. The transmission method uses the HTTP protocol, and the user's text data is sent to the server in JSON format. The input is the text entered by the user, and the output is the text data received by the server.

[0948] Step 3:

[0949] The content received by the server is analyzed. Specifically, a server-side program (Node.js) is used to split the text and extract keywords. The input text is analyzed and keywords are identified. This analyzed data becomes the preparation data for subsequent database matching. The input is the received text data, and the output is the analyzed keyword data.

[0950] Step 4:

[0951] The server queries trademark and copyright databases to ensure that the input does not overlap with existing rights. It uses a query mechanism to match identified keywords against the database. The input is the analyzed keyword data, and the output is the match result data.

[0952] Step 5:

[0953] The server returns the matching results to the user's device. The result data is encoded in JSON format and sent to the device via the HTTP protocol. The input is the matching result data, and the output is the result data received on the device.

[0954] Step 6:

[0955] The terminal displays the received matching result on the screen and notifies the user. Specifically, the result is displayed in text format using a notification means. For example, a message such as "Cool Tech is available for use" is displayed. The input is the received result data, and the output is the text displayed on the screen.

[0956] Step 7:

[0957] At the same time, the emotion engine analyzes the user's facial expression. Using the EmotionRecognition library, it analyzes the user's facial image during input and when the results are displayed to identify the emotion. The emotional state is identified and obtained as analysis data. The input is the user's facial image, and the output is emotion analysis data.

[0958] Step 8:

[0959] The device provides the user with appropriate feedback based on the emotion analysis results. The feedback means is used to display positive feedback or supportive messages on the screen. For example, a message such as "Great idea! This name is available." is displayed. The input is emotion analysis data, and the output is a feedback message.

[0960] In this way, throughout the process, the user's input is checked for legal compliance and feedback is provided according to the user's emotional state.

[0961] 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.

[0962] 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.

[0963] 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.

[0964] [Fourth embodiment]

[0965] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0966] 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.

[0967] 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).

[0968] 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.

[0969] 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.

[0970] 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).

[0971] 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.

[0972] 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.

[0973] 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.

[0974] 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.

[0975] 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.

[0976] 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.

[0977] 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."

[0978] This invention is a system that determines whether names, catchphrases, music lyrics, etc. obtained from a generative AI model infringe on existing trademarks or copyrights. Below, we will explain each component of this system and how it works.

[0979] 1. User Input

[0980] The user uses a terminal to input the generated content. The terminal is equipped with text boxes and forms, providing an interface for the user to input the name, catchphrase, lyrics, etc. obtained from the generative AI model. Once the input is complete, the user clicks the send button, and the content is sent to the server.

[0981] 2. Submit your input

[0982] The terminal plays a role in transmitting the content entered by the user to the server. The transmission means includes a function to transmit data to the server via the Internet, which allows the entered content to be quickly delivered to the server.

[0983] 3. Analysis processing on the server

[0984] The server receives the content sent from the terminal, and then analyzes the content, which includes splitting the text of the content and preparing it for matching with trademark and copyright databases.

[0985] 4. Trademark and copyright database matching

[0986] The server queries a trademark and copyright database to see if the entry overlaps with existing rights: the trademark database stores information about existing trademark rights, and the copyright database stores information about existing copyrights.

[0987] 5. Return and notification of the results

[0988] After obtaining the matching results, the server sends them back to the device. The device receives the results and notifies the user. The notification is in the form of a display of the results, and a warning is issued based on the judgment result. If there is an overlap with an existing trademark or copyright, the user is notified of this.

[0989] Specific examples

[0990] Example 1:

[0991] The user generates the name "Tech Innovation" using a generative AI model, enters "Tech Innovation" into the input form on their device, and then clicks the submit button.

[0992] The device sends the content "tech innovation" to the server. The server receives this content and begins to analyze the text "tech innovation." The analysis results are obtained by running queries against trademark and copyright databases.

[0993] A trademark database reveals that the existing name "Tech Innovation" is registered as a trademark, while a copyright database reveals that it is not registered as a name associated with any particular copyrighted work.

[0994] The server then sends these results back to the user's device, informing them that the name "Tech Innovation" may infringe on an existing trademark, allowing them to reconsider the new name.

[0995] In this way, the system of the present invention provides an effective means for proactively checking user-generated content and preventing legal trouble.

[0996] The processing flow will be explained below.

[0997] Step 1:

[0998] The user inputs the content to be generated. The user inputs the name, catchphrase, lyrics, etc. obtained from the generative AI model into the input form provided on the device. Once input is complete, the user clicks the send button.

[0999] Step 2:

[1000] The terminal transmits the input contents to the server. The input data is transmitted to the server via the Internet using the transmission means. This transmission process is performed in real time, and the data is quickly delivered to the server.

[1001] Step 3:

[1002] The server analyzes the received content. The server analyzes the received data in text format and prepares it for matching against trademark and copyright databases. This analysis includes segmenting the text and extracting specific keywords.

[1003] Step 4:

[1004] The server queries the trademark database. The server searches the received text data against the trademark database to see if there are any matches or similarities with existing trademarks. The results are obtained as a hypothesis-based similarity score.

[1005] Step 5:

[1006] The server also queries a copyright database: the server searches the received text data against the copyright database to see if there is a match or similarity to existing copyrighted content, and the results are also collected as a similarity score.

[1007] Step 6:

[1008] The server combines the results of the trademark and copyright databases, determines the degree of similarity or match based on the results from each database, and organizes this information into a data format that can be sent back to the user.

[1009] Step 7:

[1010] The server returns the judgment result to the terminal, which then sends the integrated data to the user's terminal and prepares to notify the result.

[1011] Step 8:

[1012] The device receives the determination result and displays it to the user. The device receives the determination result and displays it on the user interface. The result includes a similarity score and specific matching content, and a warning message is displayed to the user.

[1013] Step 9:

[1014] The user can check the results and take action as necessary. The user can check the displayed results and take action such as reconsidering the content to be generated or considering a different name.

[1015] This series of processes allows users to check in advance whether the generated content infringes existing trademark rights and copyrights, thereby preventing legal troubles.

[1016] Example 1

[1017] 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."

[1018] Until now, manually checking whether names, catchphrases, lyrics, and other content derived from generative AI models infringe on existing trademarks or copyrights has been extremely difficult for ordinary end users, as it is time-consuming, costly, and requires specialized knowledge. For this reason, an effective means of preventing legal troubles has been sought.

[1019] 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.

[1020] In this invention, the server includes an input means for inputting content generated by an end user, a transmission means for transmitting the input content via a network, a preprocessing means for receiving the input content and performing text analysis, a determination means for comparing the preprocessed content with a trademark database and a copyright database, a notification means for returning and notifying the end user of the comparison result, a query means for executing a comparison query, and a display means for displaying a warning message to the end user based on the comparison result. This makes it possible to quickly and easily determine the risk of infringement of trademark and copyright in content generated by the end user and prevent legal trouble before it occurs.

[1021] "Input means" refers to a device or interface for an end user to input generated content.

[1022] "Transmission means" refers to the technology and functions for transmitting the input content to a server via a network.

[1023] "Preprocessing means" refers to the technology or process used by the server to process the input received into a form that is easy to analyze.

[1024] "Determination means" refers to the technology or process for cross-checking the pre-processed content with a trademark database and a copyright database to make a determination.

[1025] "Notification means" refers to the technology and functions that allow the server to return and display the matching results to the end user's terminal.

[1026] "Query Instrument" means the technology or process for executing matching queries against trademark and copyright databases.

[1027] "Display means" refers to a technology or device for displaying a warning message to the end user based on the matching result.

[1028] This invention is a system that determines whether names, catchphrases, music lyrics, etc. obtained from a generative AI model infringe on existing trademarks or copyrights. Below, we will explain each component of this system and its operation.

[1029] User input

[1030] The user uses a terminal to input the generated content. The terminal is equipped with text boxes and forms, providing an interface for the user to input the name, catchphrase, lyrics, etc. obtained from the generative AI model. Once the user has completed the input, they click the send button to send the content to the server.

[1031] Sending input

[1032] The terminal is responsible for transmitting the information entered by the user to the server. This transmission is mainly carried out via the Internet, so the data reaches the server quickly.

[1033] Analysis processing on the server

[1034] The server receives the content sent from the device and then analyzes it, including tokenizing and morphological analysis of the text, in preparation for matching against trademark and copyright databases.

[1035] Trademark and copyright database matching

[1036] The server queries a trademark and copyright database to see if the entry overlaps with existing rights: the trademark database stores information about existing trademarks, and the copyright database stores information about existing copyrighted works.

[1037] Return and notification of judgment results

[1038] After obtaining the matching results, the server sends them back to the device. The device receives the results and notifies the user. The notification is in the form of a display of the results, and a warning is issued based on the judgment result. If there is an overlap with an existing trademark or copyright, the user is notified of this.

[1039] Specific examples

[1040] A user generates the name "Tech Innovation" using a generative AI model and enters "Tech Innovation" into an input form on their device. They then click the submit button. The device sends the content "Tech Innovation" to the server. The server receives this content and begins analyzing the text "Tech Innovation." The analysis results are obtained by running queries against trademark and copyright databases.

[1041] A trademark database reveals that the existing name "Tech Innovation" is registered as a trademark, while a copyright database reveals that it is not registered as a name associated with any particular copyrighted work.

[1042] The server then sends these results back to the device, informing the user that the name "Tech Innovation" may infringe on an existing trademark, allowing the user to reconsider the new name.

[1043] In this way, the system of the present invention provides an effective means for proactively checking user-generated content and preventing legal trouble.

[1044] Prompt Sentence Examples

[1045] Here are some example prompts to input to a generative AI model:

[1046] "Generate names for new technology companies."

[1047] The name, catchphrase, lyrics, etc. generated based on this prompt text are input into the system to determine trademark and copyright infringement.

[1048] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1049] Step 1:

[1050] The user uses the input form on the device to input the content obtained from the generative AI model (e.g., "Tech Innovation") and clicks the send button. This inputs the text data into the device. After input, the device prepares to send this text data to the server.

[1051] Specific behavior:

[1052] The user enters "Tech Innovation" into the text box on the terminal and clicks the send button. The input data is ready to be sent to the server in text format.

[1053] Step 2:

[1054] The terminal sends the text data entered by the user to the server using a network protocol such as an HTTP POST request. The input data, which is the text "Tech Innovation," reaches the server.

[1055] Specific behavior:

[1056] The device sends the text data "Tech Innovation" to the server via an HTTP POST request.

[1057] Step 3:

[1058] The server receives the text data sent from the device and preprocesses the received data ("Tech Innovation") into a format that is easy to analyze. This preprocessing includes tokenizing the text and performing morphological analysis.

[1059] Specific behavior:

[1060] The server receives the text "tech innovation," divides it into words (tokenizes it), and performs preprocessing for analysis.

[1061] Step 4:

[1062] The server uses the preprocessed text data to query the trademark database and the copyright database. For example, if the input data is "tech innovation," the server creates and executes a corresponding query against the trademark database and the copyright database. The results obtained from the databases are analyzed to see if the input overlaps with existing rights.

[1063] Specific behavior:

[1064] The server queries the trademark and copyright databases for "tech innovation" and retrieves results from each database.

[1065] Step 5:

[1066] The server generates a judgment result based on the data obtained from the trademark database and copyright database, and returns the result to the end user's terminal, preparing to notify them.

[1067] Specific behavior:

[1068] The server checks the trademark database to see that "Tech Innovation" is registered as an existing trademark, and similarly checks the copyright database to see that it is not registered as a related copyrighted work.

[1069] Step 6:

[1070] The server returns the results of the assessment to the device, which then notifies the user of the results and issues a warning based on the results.

[1071] Specific behavior:

[1072] The server sends a result to the device indicating that "Tech Innovation" may infringe on an existing trademark, and the device displays this and notifies the user to come up with a new name.

[1073] (Application example 1)

[1074] 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."

[1075] There is a need for a reliable system that can check in real time whether names, catchphrases, lyrics, etc. created using generative AI models infringe on existing trademarks or copyrights. However, current systems do not have a method for instantly checking this, making it difficult to prevent the risk of user-generated content infringing on rights in advance. The present invention aims to solve this problem.

[1076] 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.

[1077] In this invention, the server includes an input means for inputting generated content, a transmission means for transmitting the input content to the server, a determination means for analyzing the content on the server and comparing it with a trademark database and a copyright database, and a real-time analysis means for checking in real time whether content created using the generative AI model infringes trademarks or copyrights. This makes it possible to instantly check content created by users and prevent infringement of rights before it occurs.

[1078] A "generative AI model" is a model that uses artificial intelligence to generate new content such as text and designs.

[1079] An "input means" is a device or mechanism that provides an interface for a user to input generated content.

[1080] The "transmission means" refers to a device or mechanism for transmitting the inputted content to the server as data.

[1081] The "determination means" is a device or mechanism that analyzes the content on the server side and compares it with the trademark database and copyright database.

[1082] The "notification means" is a device or mechanism for returning the determination result to the user's terminal and notifying the user.

[1083] "Real-time analysis means" refers to devices or mechanisms that instantly check whether content created using a generative AI model infringes trademark rights or copyrights.

[1084] A "query means" is a device or mechanism for executing queries against trademark and copyright databases.

[1085] The "display means" is a device or mechanism for visually presenting a warning message to the user based on the determination result.

[1086] This invention is a system that checks whether catchphrases and names created using generative AI models infringe on existing trademarks or copyrights. Below, we will explain how this system is implemented in concrete terms.

[1087] System Configuration

[1088] The system consists of the following main components:

[1089] Input means: An interface for the user to input the generated content.

[1090] Transmission means: A mechanism for transmitting the input content to the server.

[1091] Determination means: A mechanism for analyzing the content on the server side and comparing it with a trademark database and a copyright database.

[1092] Notification means: A mechanism for returning the judgment result to the user's terminal and notifying the user.

[1093] Real-time analysis means: A mechanism for instantly checking content created using generative AI models (performing real-time processing).

[1094] Query facility: A mechanism for performing queries against trademark and copyright databases.

[1095] Display means: A mechanism for displaying a warning message based on the determination result.

[1096] What the program does

[1097] The server program has the following features:

[1098] Receiving and sending input data: Receives user input and processes it.

[1099] Data Analysis: Analyzes input text data and queries trademark and copyright databases.

[1100] Real-time detection: Determine whether there is any trademark or copyright infringement based on the query results in real time.

[1101] Notification and display of results: The judgment results are returned to the user's device and the results are displayed to notify the user.

[1102] Hardware and software used

[1103] Flask: Used as a server-side application framework.

[1104] Requests library: Used to execute HTTP requests on the server.

[1105] Smartphone: A device that handles user input and displays results.

[1106] Generative AI model: Used to generate new catchphrases and names.

[1107] Specific examples

[1108] For example:

[1109] Prompt Sentence Examples

[1110] "Generate the name 'Tech Brain' for a new startup product."

[1111] Processing flow

[1112] 1. User input: The user enters "Tech Brain" into the text box on the smartphone app and sends the content to the server.

[1113] 2. Server processing: The server analyzes the received content and sends queries to trademark and copyright databases.

[1114] 3. Return of results: Based on the results obtained, a real-time determination is made as to whether the entered "Tech Brain" infringes on existing trademarks or copyrights.

[1115] 4. Notification and display: The judgement result will be sent immediately to the smartphone and the user will be notified. If the judgement result indicates infringement, the user can reconsider the new name.

[1116] Through this specific process, the system of the present invention can immediately verify that the content generated by the user does not infringe trademark rights or copyrights, thereby preventing legal troubles.

[1117] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1118] Step 1:

[1119] The user inputs the content generated by the generative AI model into a smartphone application. Specifically, the user enters the newly generated catchphrase or name into a text box and clicks the application's send button to send the content to the server. The input data includes the generated name, such as "Tech Brain."

[1120] Step 2:

[1121] The device sends the entered content to the server. In this case, the smartphone app sends text data such as "Tech Brain" to the server as an HTTP request. The input data includes the content entered in the text box ("Tech Brain"), and after it is sent, it is received by the server.

[1122] Step 3:

[1123] The server analyzes the received text data and sends a query to the trademark and copyright database. Specifically, the server analyzes the text "Techbrain," generates an appropriate query, and searches the trademark and copyright database to verify whether the input data infringes any existing trademarks or copyrights.

[1124] Step 4:

[1125] The server receives query results from the database and performs real-time analysis. Specifically, it determines whether TechBrain is infringing on existing rights based on the results obtained from the trademark and copyright databases. Based on the results received (the status of existing trademarks and copyrights), the server then processes and calculates the data to confirm whether there is an infringement.

[1126] Step 5:

[1127] The server returns the result of the judgment to the user's device. Specifically, the server sends the judgment result (e.g., whether "Techbrain" infringes on existing trademark rights) back to the smartphone app. As a result, the user receives a notification indicating whether the content they entered infringes on existing rights.

[1128] Step 6:

[1129] The device will then display the results of the judgment to the user. Specifically, the smartphone app will visually display the results of the judgment received to the user. The user will be able to check whether there is an infringement, for example, as a pop-up message or a notification message, and if there is an infringement, they will be able to take action, such as coming up with a new name.

[1130] 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.

[1131] This invention combines an emotion engine with a system that determines whether names, catchphrases, music lyrics, etc. obtained from a generative AI model infringe on existing trademarks or copyrights. Below, we will explain each component of this system and how it works.

[1132] 1. User Input

[1133] The user uses a terminal to input the generated content. The terminal provides text boxes and forms, and has an interface function for the user to input the name, catchphrase, lyrics, etc. obtained from the generative AI model. Once the input is complete, the user clicks the send button, and the content is sent to the server.

[1134] 2. Submit your input

[1135] The terminal serves to transmit the content entered by the user to the server. This transmission means has a function to transmit data via the Internet, and the content is passed to the server in real time.

[1136] 3. Analysis processing on the server

[1137] The server receives the content sent from the device, analyzes the text of the content, and prepares it for matching with trademark and copyright databases. This analysis includes segmenting the text and extracting specific keywords.

[1138] 4. Trademark and copyright database matching

[1139] The server queries a trademark database and a copyright database to see if the entry overlaps with existing rights. The trademark database stores information about existing trademark rights, and the copyright database stores information about existing copyrights.

[1140] 5. Return and notification of the results

[1141] After obtaining the matching results, the server sends them back to the user's device. The device receives the results and notifies the user. The notification is in the form of a display of the results, and a warning is issued based on the judgment result. If there is an overlap with an existing trademark or copyright, the user is notified of this.

[1142] 6. Incorporating an Emotional Engine

[1143] One of the features of the invention is the incorporation of an emotion engine, which recognizes and analyzes the user's emotions when they are input and when the judgment results are displayed.

[1144] 1. Emotion recognition during input:

[1145] While the user is entering information into the device, the emotion engine analyzes the user's facial image and facial expressions to recognize their emotional state. Based on this analysis, the engine provides appropriate feedback to the user.

[1146] 2. Emotion analysis when displaying judgment results:

[1147] The judgment results are displayed on the user's device, and at the same time, the emotion engine analyzes the user's reaction and understands their emotional state. Based on the analysis results, the displayed warning messages and feedback content are adjusted. For example, if the user is confused, a support message appropriate to their emotion is displayed.

[1148] Specific examples

[1149] Example 1:

[1150] The user generates the name "Tech Innovation" using the generative AI model and enters it into the device's input form. The emotion engine then analyzes the user's facial expressions and recognizes that the user is enjoying themselves. When the user clicks the send button, the content is sent to the server.

[1151] The server receives the content "Tech Innovation" and begins analyzing it, querying trademark and copyright databases to see if it overlaps with existing trademarks or copyrights.

[1152] As a result, it is discovered in the trademark database that the name "Tech Innovation" is registered as an existing trademark. The server sends this result back to the user's device. The device receives the result and displays a warning message to the user stating, "This name may infringe on an existing trademark." The emotion engine also analyzes the user's reaction at the time of display and recognizes that the user is confused. Based on this, it provides further specific improvement suggestions and support messages.

[1153] In this way, the system of the present invention, which combines an emotion engine, can provide feedback on the content created by the user and support the user according to their emotions, allowing the user to use the content with peace of mind and preventing legal troubles.

[1154] The processing flow will be explained below.

[1155] Step 1:

[1156] The user inputs the content to be generated. The user inputs the name, catchphrase, and lyrics obtained from the generative AI model into the input form provided on the device. Once input is complete, the user clicks the send button.

[1157] Step 2:

[1158] The terminal transmits the input contents to the server. The input data is transmitted to the server via the Internet using the transmission means. This transmission process is performed in real time, and the data is quickly delivered to the server.

[1159] Step 3:

[1160] The device recognizes the user's emotions while they are typing. While they are typing, the device's built-in emotion engine analyzes the user's facial image and facial expressions to recognize their emotional state. The analysis results are used in a later step to provide appropriate feedback to the user.

[1161] Step 4:

[1162] The server analyzes the received content. The server analyzes the received data in text format and prepares it for matching against trademark and copyright databases. This analysis includes segmenting the text and extracting specific keywords.

[1163] Step 5:

[1164] The server queries the trademark database. The server searches the received text data against the trademark database to see if there are any matches or similarities with existing trademarks. The result is a similarity score.

[1165] Step 6:

[1166] The server also queries a copyright database: the server searches the received text data against the copyright database to see if there is a match or similarity to existing copyrighted content, and the results are also collected as a similarity score.

[1167] Step 7:

[1168] The server combines the results of the trademark and copyright databases, determines the degree of similarity or match based on the results from each database, and organizes this information into a data format that can be sent back to the user.

[1169] Step 8:

[1170] The server returns the judgment result to the terminal, which then sends the integrated data to the user's terminal and prepares to notify the result.

[1171] Step 9:

[1172] The device receives the determination result and displays it to the user. The device receives the determination result and displays it on the user interface. The result includes a similarity score and specific matching content, and a warning message is displayed to the user.

[1173] Step 10:

[1174] The device analyzes the user's emotions when displaying the judgment result. When the judgment result is displayed, the emotion engine analyzes the user's reaction and understands their emotional state. Based on the analysis results, the warning message and feedback content displayed are adjusted.

[1175] Step 11:

[1176] The user can check the results and take action if necessary. The user can check the displayed results and take action such as reconsidering the generated content or considering a different name. By displaying feedback according to their emotions, the user can make an appropriate decision.

[1177] This process allows users to check in advance whether the generated content infringes existing trademarks or copyrights, preventing legal troubles. In addition, the incorporation of an emotion engine provides more personalized support to users.

[1178] Example 2

[1179] 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."

[1180] Systems that determine whether names, catchphrases, lyrics, etc. generated by conventional generative AI models infringe on existing trademarks or copyrights lack a feedback function that takes into account the user's emotional state. This can lead to users feeling confused or anxious about the provided judgment results. The lack of a user-friendly feedback system can reduce user satisfaction and impair the system's usability.

[1181] 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.

[1182] In this invention, the server includes an input means for inputting the generated content, a transmission means for transmitting the input content to the server, a determination means for analyzing the content in the server and comparing it with a trademark and copyright database, a notification means for returning the determination result to the user's terminal and displaying it to the user, and an emotion analysis means for analyzing the user's emotional state and providing feedback based on the result. This allows the user to receive appropriate feedback on the provided determination result, making it possible to improve user satisfaction and convenience.

[1183] The "input means" is a device that provides an interface for a user to input generated content.

[1184] The "transmission means" is a device that has the function of transmitting the input contents to a server via the Internet.

[1185] The "determination means" is a processing device that analyzes the content received on the server and compares it with a trademark and copyright database.

[1186] The "notification means" is a device that returns the determination result from the server to the user's terminal and displays it to the user.

[1187] The "emotion analysis means" is a device that analyzes the user's facial image and facial expressions to recognize the user's emotional state, and provides appropriate feedback based on the results.

[1188] A "trademark database" is a database that stores information about existing trademarks.

[1189] A "copyright database" is a database that stores information about existing copyrights.

[1190] The "query means" is a device that has the function of executing a query to the trademark database and copyright database and obtaining the matching results.

[1191] The "display means" is a device that displays a warning message to the user based on the determination result.

[1192] This invention combines an emotion engine with a system that determines whether names, catchphrases, music lyrics, etc. obtained from a generative AI model infringe on existing trademarks or copyrights. This system is realized by integrating the following functions: user input, terminal-server communication, data analysis, notification of judgment results, and emotion analysis. Each component of the system and its operation are described below.

[1193] User input

[1194] The user uses the device to input content such as names, catchphrases, and lyrics generated by the generative AI model. The device provides text boxes and forms, and has an interface function for inputting the content generated by the user. As a concrete example, the name "Tech Innovation" is entered into the device's input form.

[1195] Sending input

[1196] When the user clicks the send button, the device transmits the user's input to the server in real time over the Internet using a transmission method designed to reliably deliver data to the server.

[1197] Analysis processing on the server

[1198] After receiving the content sent from the device, the server analyzes it. Specifically, it segments the text of the content and extracts specific keywords. This analysis process is used to prepare queries against trademark and copyright databases. For example, the content "tech innovation" can be split into "tech" and "innovation" and then analyzed for each keyword.

[1199] Trademark and copyright database matching

[1200] The server queries the parsed content against a trademark database and a copyright database to check for overlaps with existing rights. The trademark database stores information about existing trademarks, and the copyright database stores information about existing copyrights.

[1201] Return and notification of judgment results

[1202] The server sends the matching results back to the user's device, which receives the results and notifies the user, for example by displaying a warning message saying, "This name may infringe on an existing trademark."

[1203] Incorporating an emotion engine

[1204] The emotion engine analyzes the user's emotions while the user is entering input content into the device and when the judgment result is displayed. While the user is entering content, the emotion engine analyzes the user's facial image and facial expressions through the device's camera to recognize their emotional state. When the judgment result is displayed, it analyzes the user's reaction and provides appropriate feedback based on their emotional state. For example, if the user is confused, a support message appropriate to their emotion is displayed.

[1205] Specific examples

[1206] Example 1:

[1207] The user generates the name "Tech Innovation" using the generative AI model and enters it into the device's input form. The emotion engine then analyzes the user's facial expressions and recognizes that the user is enjoying themselves. When the user clicks the send button, the content is sent to the server.

[1208] The server receives the content "Tech Innovation" and begins analyzing it, querying trademark and copyright databases to see if it overlaps with existing trademarks or copyrights.

[1209] As a result, it is discovered that the name "Tech Innovation" is registered as an existing trademark in the trademark database. The server sends this result back to the user's device. The device receives the result and displays a warning message to the user stating, "This name may infringe on an existing trademark." The emotion engine also analyzes the user's reaction to this message and recognizes that they are confused. Based on this, it displays supplementary support messages such as "Please consider another name" or "If you need support, please contact us."

[1210] Example prompt sentence:

[1211] "Please explain how to ensure that the generated names and taglines do not infringe on trademarks or copyrights."

[1212] "Please provide a concrete example of a feedback system that uses an emotion engine."

[1213] The above is an embodiment of the present invention.

[1214] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1215] Step 1:

[1216] The user enters the generated content into the input form on the device. Specifically, the user enters a name or catchphrase, such as "Tech Innovation," generated by the generative AI model. Once the input is complete, the device receives the data. The input data is text data. The output is the text data entered by the user.

[1217] Step 2:

[1218] The terminal transmits the text data entered by the user to the server using a transmission means. The transmission means is the Internet, and the data is passed to the server in real time. The input data is the text data entered by the user, and the output is the text data sent to the server.

[1219] Step 3:

[1220] The server receives text data sent from the device. To analyze the received data, it divides the text and extracts specific keywords. For example, "tech innovation" is divided into "tech" and "innovation." This analysis uses text processing programs and algorithms. The input data is the text data received by the server, and the output is the analyzed keyword data.

[1221] Step 4:

[1222] The server queries the parsed keyword data against the trademark and copyright databases. Specifically, the server matches the keywords against the databases to see if they overlap with existing rights. The input data is the parsed keyword data, and the output is the match result data.

[1223] Step 5:

[1224] The server returns the matching result data to the user's terminal. The terminal receives this matching result data and notifies the user. For example, it displays a warning message such as "This name may infringe on an existing trademark." The input data is the matching result data, and the output is a warning message that is displayed to the user.

[1225] Step 6:

[1226] While the user is entering input content into the device, the emotion engine analyzes the user's facial image and facial expressions via the device's camera. Based on the results of this analysis, the user's emotional state is recognized. For example, it identifies emotions such as whether the user is enjoying themselves or feeling confused. The input data is the user's facial image and facial expression data, and the output is analyzed emotional data.

[1227] Step 7:

[1228] At the same time as the judgment result is displayed, the emotion engine analyzes the user's reaction via the device's camera. The feedback message and support message are adjusted based on the analysis results. For example, if the user is confused, a support message such as "Please consider a different name" is displayed. The input data is the emotion data at the time the judgment result is displayed, and the output is the adjusted feedback message.

[1229] (Application example 2)

[1230] 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."

[1231] Systems that determine whether names, catchphrases, lyrics, etc. obtained from generative AI models infringe on existing trademarks and copyrights have the problem of being unable to take users' emotions into consideration and provide appropriate feedback. Another issue is the lack of systems that can understand users' emotional reactions to the results of the determination and provide appropriate support accordingly.

[1232] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an input means for inputting generated content, a transmission means for transmitting the input content to the server, a determination means for analyzing the content in the server and comparing it with a trademark and copyright database, a notification means for returning the determination result to the user's terminal and displaying it to the user, an emotion recognition means for recognizing and analyzing the user's emotions, and a feedback means for providing feedback based on the emotion analysis result. This makes it possible to determine whether the content obtained from the generative AI model infringes existing trademarks and copyrights, and at the same time provide appropriate support according to the user's emotions.

[1233] "Input means for inputting generated content" refers to a means for providing an interface for users to input names, catchphrases, lyrics, etc. obtained from the generative AI model.

[1234] The "transmission means for transmitting the input contents to the server" is a communication means for transmitting the contents input by the user to the server, and is a means having the function of transferring data via a network such as the Internet.

[1235] The "determination means for analyzing the content on the server and comparing it with the trademark and copyright database" refers to a means for analyzing the content entered on the server, comparing it with the trademark and copyright databases, and checking whether it overlaps with existing rights.

[1236] The "notification means for returning the judgment results to the user's terminal and displaying them to the user" refers to a means for returning the judgment results of trademark right and copyright to the user's terminal and displaying them on the screen.

[1237] The "emotion recognition means for recognizing and analyzing the user's emotions" is a means for analyzing the facial expressions and actions of the user when the user performs an input operation or displays a judgment result, and recognizing the user's emotional state.

[1238] The "feedback means for providing feedback based on the emotion analysis result" is a means for providing appropriate feedback or a support message to the user based on the emotion analysis result obtained by the emotion recognition means.

[1239] This section describes an embodiment of the present invention. This system determines whether names, catchphrases, lyrics, etc. generated by a generative AI model infringe on existing trademarks or copyrights, and recognizes the user's emotional state and provides appropriate feedback. Each component and its operation are described in detail below.

[1240] 1. User Input

[1241] Users install the ad creation support app on their smartphone and input the name and catchphrase obtained from the generative AI model. This input is done via an input means that provides an interface. Specifically, users enter their information into a text box and click the send button.

[1242] 2. Submit your input

[1243] The information entered by the user is sent to the server via the Internet. The transmission means has the function of transferring data in real time using the HTTP protocol. This allows the information entered by the user to be delivered to the server quickly.

[1244] 3. Analysis processing on the server

[1245] The server analyzes the received content. Specifically, it uses a server-side program (e.g., Node.js) to split the text and extract keywords. Based on the results of this analysis, it prepares to match the data with trademark and copyright databases.

[1246] 4. Trademark and copyright database matching

[1247] The server queries a trademark database and a copyright database to see if the entry overlaps with existing rights. The trademark database stores information about existing trademark rights, and the copyright database stores information about existing copyrights.

[1248] 5. Return and notification of the results

[1249] After obtaining the matching result, the server sends the result back to the user's device. The device receives the result and notifies the user. The result is displayed on the screen and a warning message is provided based on the judgment result.

[1250] 6. Incorporating an Emotional Engine

[1251] While the user is entering input content into the device, the emotion engine operates and analyzes the user's facial expressions. It uses libraries such as EmotionRecognition to recognize the user's emotional state from facial images and expressions. Based on the analysis results, it provides appropriate feedback to the user.

[1252] The judgment results are displayed on the user's device, and at the same time, the emotion engine analyzes the user's reaction and understands their emotional state. Based on the analysis results, the displayed warning messages and feedback content can be adjusted. For example, if the user is confused, a support message appropriate to their emotion will be displayed.

[1253] Specific examples

[1254] For example, suppose a user generates the name "Cool Tech" and enters it into an input form. At this time, the emotion engine recognizes the user's smile and analyzes it as a state of enjoyment. The input is sent to the server and compared with the trademark database. As a result, it is confirmed that the name "Cool Tech" does not match any existing trademark rights, and the user is notified that it is valid. In addition, to maintain the user's enjoyment, positive feedback based on the emotion analysis results is displayed.

[1255] Prompt Sentence Examples

[1256] "Generate a new name for creating ads"

[1257] In this way, by implementing the invention, users can use the generated content with peace of mind, prevent legal troubles, and receive appropriate support according to their emotions.

[1258] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1259] Step 1:

[1260] The user launches the ad creation support app and inputs the name and catchphrase obtained from the generative AI model. Using the input means (text box), the user inputs the content following the prompt "Generate a new name for ad creation." The user enters "Cool Tech" as the input content and clicks the send button. The input content is obtained in text format.

[1261] Step 2:

[1262] The terminal sends the user's input to the server via the Internet. The transmission method uses the HTTP protocol, and the user's text data is sent to the server in JSON format. The input is the text entered by the user, and the output is the text data received by the server.

[1263] Step 3:

[1264] The content received by the server is analyzed. Specifically, a server-side program (Node.js) is used to split the text and extract keywords. The input text is analyzed and keywords are identified. This analyzed data becomes the preparation data for subsequent database matching. The input is the received text data, and the output is the analyzed keyword data.

[1265] Step 4:

[1266] The server queries trademark and copyright databases to ensure that the input does not overlap with existing rights. It uses a query mechanism to match identified keywords against the database. The input is the analyzed keyword data, and the output is the match result data.

[1267] Step 5:

[1268] The server returns the matching results to the user's device. The result data is encoded in JSON format and sent to the device via the HTTP protocol. The input is the matching result data, and the output is the result data received on the device.

[1269] Step 6:

[1270] The terminal displays the received matching result on the screen and notifies the user. Specifically, the result is displayed in text format using a notification means. For example, a message such as "Cool Tech is available for use" is displayed. The input is the received result data, and the output is the text displayed on the screen.

[1271] Step 7:

[1272] At the same time, the emotion engine analyzes the user's facial expression. Using the EmotionRecognition library, it analyzes the user's facial image during input and when the results are displayed to identify the emotion. The emotional state is identified and obtained as analysis data. The input is the user's facial image, and the output is emotion analysis data.

[1273] Step 8:

[1274] The device provides the user with appropriate feedback based on the emotion analysis results. The feedback means is used to display positive feedback or supportive messages on the screen. For example, a message such as "Great idea! This name is available." is displayed. The input is emotion analysis data, and the output is a feedback message.

[1275] In this way, throughout the process, the user's input is checked for legal compliance and feedback is provided according to the user's emotional state.

[1276] 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.

[1277] 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.

[1278] 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.

[1279] 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.

[1280] FIG. 9 illustrates 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 behaviors 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.

[1281] 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.

[1282] 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).

[1283] 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.

[1284] 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."

[1285] 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.

[1286] 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).

[1287] 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.

[1288] 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.

[1289] 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.

[1290] 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.

[1291] 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.

[1292] 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.

[1293] 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.

[1294] 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.

[1295] 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.

[1296] 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.

[1297] The following is further disclosed regarding the above embodiment.

[1298] (Claim 1)

[1299] an input means for inputting the generated content;

[1300] a transmitting means for transmitting the input contents to a server;

[1301] A determination means for analyzing the content on the server and comparing it with a trademark and copyright database;

[1302] a notification means for returning the determination result to the user's terminal and displaying it to the user;

[1303] A system including:

[1304] (Claim 2)

[1305] 10. The system of claim 1, further comprising query means for matching the trademark database and the copyright database.

[1306] (Claim 3)

[1307] 2. The system according to claim 1, further comprising a display means for displaying a warning message based on the determination result.

[1308] "Example 1"

[1309] (Claim 1)

[1310] input means for inputting end-user generated content;

[1311] a transmitting means for transmitting the input contents to a server via a network;

[1312] a preprocessing means for receiving the input content at the server and performing text analysis;

[1313] a determining means for checking the preprocessed content against a trademark database and a copyright database;

[1314] a notification means for returning and notifying the matching result to the end user's terminal;

[1315] A system including:

[1316] (Claim 2)

[1317] 10. The system of claim 1, further comprising query means for performing matching queries on trademark and copyright databases.

[1318] (Claim 3)

[1319] 10. The system of claim 1, further comprising a display means for displaying a warning message to the end user based on the result of the matching.

[1320] "Application Example 1"

[1321] (Claim 1)

[1322] an input means for inputting the generated content;

[1323] a transmitting means for transmitting the input contents to a server;

[1324] A determination means for analyzing the content in the server and comparing it with a trademark database and a copyright database;

[1325] a notification means for returning the determination result to the user's terminal and displaying it to the user;

[1326] A real-time analytical method for checking whether content created using generative AI models infringes trademarks or copyrights in real time, and

[1327] A system including:

[1328] (Claim 2)

[1329] 10. The system of claim 1, further comprising query means for performing a query to match the trademark database and the copyright database.

[1330] (Claim 3)

[1331] 2. The system according to claim 1, further comprising a display means for displaying a warning message based on the determination result.

[1332] "Example 2: Combining Emotion Engines"

[1333] (Claim 1)

[1334] an input means for inputting the generated content;

[1335] a transmitting means for transmitting the input contents to a server;

[1336] A determination means for analyzing the content on the server and comparing it with a trademark and copyright database;

[1337] a notification means for returning the determination result to the user's terminal and displaying it to the user;

[1338] emotion analysis means for analyzing the user's emotional state and providing feedback based on the analysis result;

[1339] A system including:

[1340] (Claim 2)

[1341] 10. The system of claim 1, further comprising query means for matching the trademark database and the copyright database.

[1342] (Claim 3)

[1343] The system of claim 1, further comprising a display means for displaying a warning message based on the judgment result, and a means for analyzing the user's reaction when the judgment result is displayed and providing a support message according to the user's emotional state.

[1344] "Application example 2 when combining emotion engines"

[1345] (Claim 1)

[1346] an input means for inputting the generated content;

[1347] a transmitting means for transmitting the input contents to a server;

[1348] A determination means for analyzing the content on the server and comparing it with a trademark and copyright database;

[1349] a notification means for returning the determination result to the user's terminal and displaying it to the user;

[1350] emotion recognition means for recognizing and analyzing the emotions of a user;

[1351] a feedback means for providing feedback based on the emotion analysis result;

[1352] A system including:

[1353] (Claim 2)

[1354] 10. The system of claim 1, further comprising query means for matching the trademark database and the copyright database.

[1355] (Claim 3)

[1356] 2. The system according to claim 1, further comprising a display means for displaying a warning message based on the determination result. [Explanation of symbols]

[1357] 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. an input means for inputting the generated content; a transmitting means for transmitting the input contents to a server; A determination means for analyzing the content on the server and comparing it with a trademark and copyright database; a notification means for returning the determination result to the user's terminal and displaying it to the user; A system including:

2. 10. The system of claim 1, further comprising query means for matching the trademark database and the copyright database.

3. 2. The system according to claim 1, further comprising a display means for displaying a warning message based on the determination result.

Images