system

Abstract

Provide a system. [Solution] means for inputting scene data; means for receiving and storing said scene data; means for analyzing the scene data and recognizing a particular scene; means for generating appropriate sound effects based on the recognized scene; means for storing and providing the generated sound effects; A system including:

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] In the entertainment industry, generating scene-specific sound effects traditionally required specialized knowledge and expensive equipment and environments. This meant that generating sound effects was costly and time-consuming, placing a significant burden on small-scale projects and individual creators. Furthermore, it was difficult to prepare sound sources that could accommodate the diversity of scenes, making it difficult to maintain a sense of realism. This invention solves these problems by providing a method for generating high-quality sound effects efficiently and at low cost. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system including: means for inputting scene data; means for receiving and saving the scene data; means for analyzing the scene data and recognizing a specific scene; means for generating appropriate sound effects based on the recognized scene; and means for saving and providing the generated sound effects.

[0006] "Scene data" refers to image data and video data used within entertainment content.

[0007] "Means for inputting" refers to an interface through which a user provides scene data to the system.

[0008] "Means for receiving and storing" refers to a mechanism that has the function of receiving scene data and storing it in an appropriate storage.

[0009] "Means for analyzing" refers to algorithms and techniques for analyzing scene data and understanding its contents.

[0010] The "means for recognizing a scene" refers to a mechanism that has the function of identifying a specific scene from the analyzed scene data and labeling that scene.

[0011] "Means for generating sound effects" refers to a function that uses a generative AI model to create appropriate sound effects based on a recognized scene.

[0012] "Means for storing and providing" refers to a function for storing the generated sound effects and providing them so that users can access and download them.

[0013] "Generative AI Model" refers to the machine learning model used to generate sound effects.

[0014] These are the definitions of important words. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0023] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0036] The present invention relates to a system for inputting scene data, analyzing the data, and generating appropriate sound effects. This system is intended to generate sound effects to provide a realistic experience, primarily in entertainment content.

[0037] System configuration

[0038] The user provides scene data (image or video data) and uploads the data from their device to the server. The server receives the uploaded scene data, analyzes it, and recognizes specific scenes. The AI ​​model then generates sound effects based on the recognized scene and provides them to the user. Each part of the system is described in detail below.

[0039] Data upload

[0040] 1. The user selects scene data

[0041] The user uses the file browser on the device to select image data or video data of the scene for which they want to generate sound effects. For example, the user can select a video file called "Battle Scene.mp4."

[0042] 2. The user uploads the scene data.

[0043] The user sends the selected scene data to the server via an upload interface from the terminal to the system.

[0044] Receiving and saving scene data

[0045] 3. The server receives the scene data.

[0046] The server receives the scene data sent by the user and saves it in the data storage. For example, it saves "BattleScene.mp4" in the specified directory.

[0047] Scene Analysis and Recognition

[0048] 4. The server starts analyzing the scene

[0049] The server begins analyzing the uploaded scene data using the generative AI model. In this step, it extracts scene features and identifies specific scenes (e.g., sword swinging scenes, magic casting scenes, etc.).

[0050] 5. The server recognizes the scene

[0051] The generative AI model recognizes specific actions and events in the scene data and assigns scene tags (e.g., sword, magic, explosion, etc.) accordingly.

[0052] Sound effect generation and provision

[0053] 6. The server generates the sound effects

[0054] The server automatically generates optimal sound effects using a generative AI model based on the recognized scene tags, such as the sound of a sword swing or magic.

[0055] 7. The server saves the sound effect files

[0056] Save the generated sound effects as audio files and record the path to save them. For example, save "sword swinging sound.wav" and "magic sound.wav" in the appropriate directory.

[0057] 8. The server generates the download link

[0058] Based on the path of the saved sound effect file, a link is generated that allows the user to easily download it.

[0059] Download sound effects

[0060] 9. The server provides the download link to the user

[0061] The server provides the user with a download link for the generated sound effect, and the user can download the generated sound effect to their device by clicking the provided link.

[0062] Specific examples

[0063] For example, if a user wants to generate sound effects to be used in a battle scene in a game, the process would be as follows:

[0064] 1. The user uploads a video of a battle scene, "BattleScene.mp4," from their device to the server.

[0065] 2. The server receives the video and stores it in the system.

[0066] 3. The server analyzes the video and recognizes scenes where swords are swung or magic is cast.

[0067] 4. The server generates sword swinging and magic sound effects based on the recognized scene.

[0068] 5. The server saves the generated sound effect file and provides a download link to the user.

[0069] 6. The user clicks on the link to download the generated sound effect and apply it to the game.

[0070] The above is a detailed description of the embodiment of the present invention. This system makes it possible to generate high-quality sound effects simply and at low cost without requiring specialized knowledge or expensive equipment.

[0071] The processing flow will be explained below.

[0072] Step 1:

[0073] The user uses the file browser on the device to select image data or video data of the scene for which they want to generate sound effects. For example, the user selects a video file called "Battle Scene.mp4."

[0074] Step 2:

[0075] The user sends the selected scene data from the terminal to the server via the system's upload interface. The uploaded file is saved in the specified directory on the server.

[0076] Step 3:

[0077] The server receives the scene data sent by the user and saves it in the data storage. The path of the saved file is recorded and used for subsequent processing.

[0078] Step 4:

[0079] The server inputs the saved file into the generative AI model to begin analyzing the scene data. During this process, the server extracts features from the scene data.

[0080] Step 5:

[0081] The server uses the generated AI model to recognize specific scenes within the scene data, such as a sword swing or a magic cast, and assigns a scene tag to the recognized scene.

[0082] Step 6:

[0083] The server automatically generates appropriate sound effects using a generative AI model based on the recognized scene tags. The generated sound effects correspond to the scene tags, such as "sword swinging sounds" or "magic sounds."

[0084] Step 7:

[0085] The server saves the generated sound effects as audio files, and records the path of each audio file to provide to the user.

[0086] Step 8:

[0087] The server generates a link based on the path of the saved sound effect file, which the user can use to easily download it. This link is generated for each user and managed together with their authentication information.

[0088] Step 9:

[0089] The server provides the user with a download link for the generated sound effect, which is sent to the user via email or a web portal.

[0090] Step 10:

[0091] The user clicks on the provided download link to download the generated sound effect to their device, and the downloaded file can be applied to the user's entertainment content.

[0092] This is the specific flow of processing in this system. Taking into account the details of the operations at each step, we aim to generate sound effects efficiently and with high quality.

[0093] Example 1

[0094] 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."

[0095] Conventional systems have the problem that they require specialized knowledge and expensive equipment to generate high-quality sound effects for entertainment content. Furthermore, manually creating appropriate sound effects for each scene takes a great deal of time and effort, so there is a demand for a system that can generate sound effects simply and efficiently.

[0096] 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.

[0097] In this invention, the server includes means for a user to select scene data, means for a user to upload scene data, means for the server to receive and store the scene data, means for the server to analyze the scene data using a generative AI model and recognize a specific scene, means for the server to generate sound effects using the generative AI model based on the recognized scene, and means for storing and providing the generated sound effect files. This makes it possible to generate high-quality sound effects easily and at low cost without requiring specialized knowledge or expensive equipment.

[0098] The "means for the user to select scene data" refers to an interface that allows the user to select image or video data for which sound effects are to be generated via a file browser on the terminal or the like.

[0099] The "means for the user to upload scene data" refers to an interface that provides a function for the user to send scene data selected by the user to a server via the Internet.

[0100] "Means for the server to receive and store scene data" refers to software or hardware that has the function of allowing the server to receive scene data sent by a user and store it for a certain period of time or in a certain directory.

[0101] "Means for the server to analyze scene data using a generative AI model and recognize specific scenes" refers to the process by which the server utilizes a machine learning model (generative AI model) to analyze received scene data and identify specific features or events.

[0102] "Means for the server to generate sound effects using a generative AI model based on the recognized scene" refers to algorithms or software that enable the generative AI model to automatically generate appropriate sound effects based on the results of scene recognition.

[0103] "Means for storing and providing generated sound effect files" refers to the function of storing sound effect files generated by a generative AI model on a server and providing a link or interface that allows users to easily download or use the files.

[0104] The present invention relates to a system for inputting scene data, analyzing the data, and generating appropriate sound effects. This system is primarily intended to generate sound effects to provide a realistic experience in entertainment content.

[0105] System configuration

[0106] The user provides scene data (image or video data) and uploads the data from their device to the server. The server receives the uploaded scene data, analyzes it, and recognizes specific scenes. Then, a generative AI model generates sound effects based on the recognized scene and provides them to the user. Each part of the system is described in detail below.

[0107] Data upload

[0108] The user selects scene data

[0109] The user uses the file browser on the device to select image data or video data of the scene for which they want to generate sound effects. For example, the user can select a video file called "Battle Scene.mp4."

[0110] The user uploads scene data

[0111] The user sends the selected scene data to the server via an upload interface from the terminal to the system.

[0112] Receiving and saving scene data

[0113] The server receives the scene data

[0114] The server receives the scene data sent by the user and saves it in the data storage. For example, it saves "BattleScene.mp4" in the specified directory.

[0115] Scene Analysis and Recognition

[0116] The server starts scene analysis

[0117] The server begins analyzing the uploaded scene data using the generative AI model. In this step, it extracts scene features and identifies specific scenes (e.g., sword swinging scenes, magic casting scenes, etc.).

[0118] The server recognizes the scene

[0119] The generative AI model recognizes specific actions and events in the scene data and assigns scene tags (e.g., sword, magic, explosion, etc.) accordingly.

[0120] Sound effect generation and provision

[0121] The server generates the sound effects

[0122] The server automatically generates optimal sound effects using a generative AI model based on the recognized scene tags, such as the sound of a sword swing or magic.

[0123] The server stores the sound effect files.

[0124] Save the generated sound effects as audio files and record the path to save them. For example, save "sword swinging sound.wav" and "magic sound.wav" in the appropriate directory.

[0125] The server generates the download link

[0126] Based on the path of the saved sound effect file, a link is generated that allows the user to easily download it.

[0127] Download sound effects

[0128] The server provides the download link to the user.

[0129] The server provides the user with a download link for the generated sound effect, and the user can download the generated sound effect to their device by clicking the provided link.

[0130] Specific examples

[0131] For example, if a user wants to generate sound effects to be used in a battle scene in a game, the process would be as follows:

[0132] 1. The user uploads a video of a battle scene, "BattleScene.mp4," from their device to the server.

[0133] 2. The server receives the video and stores it in the system.

[0134] 3. The server analyzes the video and recognizes scenes where swords are swung or magic is cast.

[0135] 4. The server generates sword swinging and magic sound effects based on the recognized scene.

[0136] 5. The server saves the generated sound effect file and provides a download link to the user.

[0137] 6. The user clicks on the link to download the generated sound effect and apply it to the game.

[0138] Examples of prompt statements

[0139] Examples of prompts that users can input into a generative AI model include:

[0140] "I want you to generate sound effects for sword-swinging battle scenes."

[0141] "Create sounds for scenes where magic is used."

[0142] This system makes it possible to generate high-quality sound effects easily and at low cost, without requiring specialized knowledge or expensive equipment.

[0143] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0144] Step 1:

[0145] The user selects scene data

[0146] Input: The user uses the device's file browser to select the image or video data of the scene for which they want to generate sound effects. For example, the user selects the video file "C:\Videos\BattleScene.mp4".

[0147] How it works: The user navigates through the file browser and clicks on the desired scene data file.

[0148] Output: The selected file path is retrieved.

[0149] Step 2:

[0150] The user uploads scene data

[0151] Input: The scene data file selected by the user in step 1.

[0152] How it works: A user drags and drops a file into the system's upload interface and clicks the upload button.

[0153] Output: The scene data is sent over the internet to the server. Progress is displayed and a notification is displayed when the upload is complete.

[0154] Step 3:

[0155] The server receives and stores the scene data.

[0156] Input: Scene data submitted by the user.

[0157] Operation: The server saves the received scene data in the specified directory. For example, it saves it as " / tmp / battlescene.mp4".

[0158] Output: Scene data is saved in a temporary folder on the server.

[0159] Step 4:

[0160] The server starts scene analysis

[0161] Input: Scene data saved in step 3.

[0162] Operation: The server initializes the generative AI model and inputs the saved scene data into the model. Video frames are extracted and preprocessed.

[0163] Output: The scene data is ready for analysis and key features are extracted.

[0164] Step 5:

[0165] The server recognizes the scene

[0166] Input: Scene data parsed by a generative AI model.

[0167] How it works: The generative AI model identifies key features in the scene data and assigns them specific tags (e.g., sword, magic).

[0168] Output: Recognized scene tags are generated.

[0169] Step 6:

[0170] The server generates the sound effects

[0171] Input: Scene tags recognized in step 5.

[0172] How it works: The server uses a generative AI model to generate appropriate sound effects based on the tag. For example, if the tag "sword" is recognized, the server inputs a prompt to the generative AI model saying, "I would like you to generate sound effects for a sword-swinging battle scene."

[0173] Output: The generated sound effect file is created.

[0174] Step 7:

[0175] The server stores the sound effect files.

[0176] Input: The sound effect file generated in step 6.

[0177] Behavior: The server saves the generated sound effect file in the specified directory, for example, as " / audio / sword-swinging-sound.wav". It also performs a checksum check.

[0178] Output: The sound effect file has been saved.

[0179] Step 8:

[0180] The server generates the download link

[0181] Input: The path to the saved sound effect file.

[0182] How it works: The server generates a link based on the path of the saved sound effect file so that the user can easily download it. For example, it generates a link like "https: / / server.com / download / swordswingingsound.wav".

[0183] Output: A download link will be generated.

[0184] Step 9:

[0185] The server provides the download link to the user.

[0186] Input: The download link generated in step 8.

[0187] How it works: The server provides the generated download link to the user, and notification can be via email, chat system, or in-system notification.

[0188] Output: The user receives a link that they can click to download the sound effect.

[0189] (Application example 1)

[0190] 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."

[0191] The present invention relates to a system that analyzes scene data and generates sound effects appropriate for a specific scene. Its purpose is to provide a realistic entertainment experience by analyzing scenes in real time using a smart device and instantly reproducing sound effects. However, conventional technologies require specialized knowledge and expensive equipment, making them too costly and time-consuming for general consumers.

[0192] 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.

[0193] In this invention, the server includes means for inputting scene data, means for receiving and saving the scene data, means for analyzing the scene data and recognizing specific scenes, means for generating appropriate sound effects based on the recognized scenes, means for saving and providing the generated sound effects, means for acquiring video in real time from a camera of a smart device and uploading the scene data, and means for playing the generated sound effects on a speaker of the smart device. This allows even general consumers to easily generate high-quality sound effects in real time and enjoy a realistic entertainment experience.

[0194] "Scene data" refers to visual information such as images and videos, and is data used to recognize specific scenes by analyzing this information.

[0195] "Means for inputting scene data" refers to a device or interface that allows a user to provide scene data such as images or videos to the system.

[0196] The "means for receiving and storing the scene data" refers to a device or software for transferring the input scene data to a server and storing it temporarily or permanently.

[0197] "Means for analyzing the scene data and recognizing a particular scene" refers to an algorithm or program for detecting and identifying a particular event or action within the scene data.

[0198] The "means for generating appropriate sound effects based on the recognized scene" refers to an algorithm or program for generating optimal sound effects according to a specific scene label or tag.

[0199] The "means for storing and providing the generated sound effects" refers to a system or device for storing the generated sound effect files and providing them so that users can download or play them.

[0200] "Means for acquiring video in real time from a smart device camera and uploading scene data" refers to a device or program that uses a camera such as smart glasses or a smartphone to capture video in real time and transmits the data to a server.

[0201] "Means for playing the generated sound effect on a speaker of the smart device" refers to a device for playing the generated sound effect using a speaker of smart glasses, a smartphone, or the like.

[0202] The present invention relates to a system for inputting scene data, analyzing it, and generating appropriate sound effects. This system aims to provide a realistic entertainment experience by analyzing scenes in real time using a smart device and instantly reproducing sound effects.

[0203] System configuration

[0204] A user wears a smart device (e.g., smart glasses) and captures scene data in real time. The scene data is captured as video and uploaded to a server. The server receives the uploaded scene data, analyzes it, and recognizes specific scenes. A generative AI model then generates sound effects based on the recognized scene, which are instantly played on the smart device's speaker. Each part of the system is described in detail below.

[0205] Data upload

[0206] 1. The smart device captures the scene data.

[0207] A user wears a smart device (e.g., smart glasses), and the device's camera captures video in real time. For example, the smart glasses camera takes pictures while the user is walking around a store.

[0208] 2. The smart device uploads the scene data to the server.

[0209] The captured video data is uploaded from the smart device to a server in real time.

[0210] Receiving and saving scene data

[0211] 3. The server receives the scene data.

[0212] The server receives the video data sent from the user's smart device and temporarily stores it in a data storage. For example, the video data is continuously received.

[0213] Scene Analysis and Recognition

[0214] 4. The server starts analyzing the scene

[0215] The server uses the generative AI model to analyze the uploaded video data, extracting scene features and identifying specific scenes (e.g., product shelves, product displays, etc.).

[0216] 5. The server recognizes the scene

[0217] The generative AI model recognizes specific actions and events in the scene data and assigns scene tags (e.g., product descriptions, sale information, etc.) based on them.

[0218] Sound effect generation and provision

[0219] 6. The server generates the sound effects

[0220] The server automatically generates optimal sound effects using a generative AI model based on the recognized scene tags, such as product explanations or sales information.

[0221] 7. Smart devices play sound effects

[0222] The generated sound effects are played in real time through the smart device's speaker, allowing users to enjoy a realistic audio guide.

[0223] Specific examples

[0224] For example, if a user is walking around taking pictures of product shelves in a virtual store, the process will be as follows:

[0225] 1. The user wears smart glasses, and the camera captures real-time images of the product shelves.

[0226] 2. The smart device uploads the video data to the server.

[0227] 3. The server receives the video data, analyzes it, and recognizes the product shelf scene.

[0228] 4. The server generates a voice description of the product based on the recognized scene.

[0229] 5. The smart device will play the generated audio in real time, allowing the user to listen to the product description.

[0230] Prompt Sentence Examples

[0231] "Analyze this image (or video) and generate the appropriate sound effect."

[0232] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0233] System processing steps

[0234] Step 1:

[0235] The camera on the smart device captures the footage in real time.

[0236] Input: Video captured in real time by a smart device (e.g., smart glasses).

[0237] Processing: The smart device continuously captures the scene around the user.

[0238] Output: Captured video data.

[0239] Step 2:

[0240] The captured video data is uploaded to the server.

[0241] Input: Captured real-time video data.

[0242] Processing: The video data acquired by the smart device is compressed and encoded, and then uploaded to the server via the network.

[0243] Output: Video data sent to the server.

[0244] Step 3:

[0245] The server receives the video data and stores it in data storage.

[0246] Input: Video data sent from smart device.

[0247] Processing: The server receives the video data through the network and stores it in the appropriate format in the data storage.

[0248] Output: Saved video data.

[0249] Step 4:

[0250] The server uses a generative AI model to analyze the video data and recognize specific scenes.

[0251] Input: Stored video data.

[0252] Processing: The server uses the generated AI model and the prompt "Analyze this image (or video) and generate appropriate sound effects." to analyze the scene characteristics in the video data and identify specific scene labels and tags.

[0253] Output: Recognized scene tags (e.g. product descriptions, sale information, etc.).

[0254] Step 5:

[0255] The server generates sound effects using a generative AI model based on the recognized scene tags.

[0256] Input: Recognized scene tags.

[0257] Processing: The generative AI model generates appropriate sound effects corresponding to the scene tags, synthesizing the sounds based on pre-trained data.

[0258] Output: The generated sound effect file.

[0259] Step 6:

[0260] The server sends the generated sound effect file to the smart device.

[0261] Input: The generated sound effect file.

[0262] Processing: The server sends the path and data of the sound effect file to the smart device, where the sound effect file is encoded in the appropriate format.

[0263] Output: Sound effect data sent to smart device.

[0264] Step 7:

[0265] The smart device plays a sound effect.

[0266] Input: Sound effect data sent from the server.

[0267] Processing: The smart device decodes the received sound effect data and plays it through the built-in speaker.

[0268] Output: The sound effect that the user can hear.

[0269] 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.

[0270] The present invention is a system that inputs scene data, analyzes it, and generates appropriate sound effects, and also includes a function that recognizes the user's emotions and adjusts the sound effects based on those emotions. This system aims to provide a more realistic and emotional experience in entertainment content.

[0271] System configuration

[0272] The user provides scene data (image or video data) and uploads the data from their device to the server. The server receives the uploaded scene data, analyzes it, and recognizes specific scenes. An AI model then generates sound effects based on the recognized scene and provides them to the user. The system also incorporates an emotion engine that recognizes the user's emotions and adjusts the generated sound effects based on the user's emotions. Each part of the system is described in detail below.

[0273] Data upload

[0274] 1. The user selects scene data

[0275] The user uses the file browser on the device to select image data or video data of the scene for which they want to generate sound effects. For example, the user can select a video file called "Battle Scene.mp4."

[0276] 2. The user uploads the scene data.

[0277] The user sends the selected scene data to the server via an upload interface from the terminal to the system.

[0278] Receiving and saving scene data

[0279] 3. The server receives the scene data.

[0280] The server receives the scene data sent by the user and saves it in the data storage. For example, it saves "BattleScene.mp4" in the specified directory.

[0281] Scene Analysis and Recognition

[0282] 4. The server starts analyzing the scene

[0283] The server starts analyzing the uploaded scene data using the generative AI model. In this step, it extracts scene features.

[0284] 5. The server recognizes the scene

[0285] The generative AI model recognizes specific scenes within the scene data and assigns scene tags (e.g., sword, magic, explosion, etc.) accordingly.

[0286] User Emotion Recognition

[0287] 1. Obtain user emotion data

[0288] The device sends the user's voice data or facial expression data to the emotion engine, which analyzes it and recognizes the user's emotions.

[0289] 2. Analyze user sentiment

[0290] The server uses an emotion engine to analyze the user's emotion, and the analyzed emotion data corresponds to the scene tag.

[0291] Sound effect generation and adjustment

[0292] 1. The server generates the sound effects

[0293] The server automatically generates appropriate sound effects using a generative AI model based on the recognized scene tags, such as the sound of a sword swing or magic.

[0294] 2. The server adjusts the sound effects

[0295] The server adjusts the generated sound effects based on the user's emotions. For example, if the user is nervous, the server increases the volume of the sound effects or speeds up the tempo.

[0296] Saving and providing sound effects

[0297] 1. The server saves the sound effect files

[0298] Save the generated sound effects as audio files and record the path to save them. For example, save "sword swinging sound.wav" and "magic sound.wav" in the appropriate directory.

[0299] 2. The server generates a download link

[0300] Based on the path of the saved sound effect file, a link is generated that allows the user to easily download it. This link is generated individually for each user and managed together with authentication information.

[0301] Download sound effects

[0302] 1. The server provides the download link to the user.

[0303] The server provides the user with a download link for the generated sound effect, which is sent to the user via email or a web portal.

[0304] 2. The user downloads the sound effect

[0305] The user clicks on the provided download link to download the generated sound effect to their device, and the downloaded file can be applied to the user's entertainment content.

[0306] Specific examples

[0307] For example, if a user wants to generate sound effects to be used in a battle scene in a game, the process would be as follows:

[0308] 1. The user uploads a video of a battle scene, "BattleScene.mp4," from their device to the server.

[0309] 2. The server receives the video and stores it in the system.

[0310] 3. The server analyzes the video and recognizes scenes where swords are swung or magic is cast.

[0311] 4. The emotion engine analyzes the user's voice and facial expression data to recognize emotions such as tension and excitement.

[0312] 5. The server generates sword swinging and magic sound effects based on the recognized scene.

[0313] 6. The server adjusts the generated sound effects based on the user's emotions.

[0314] 7. The server saves the generated sound effect file and provides a download link to the user.

[0315] 8. The user clicks on the link to download the generated sound effect and apply it to the game.

[0316] The above is a detailed description of an embodiment of the present invention. This system makes it possible to generate high-quality sound effects and sound effects corresponding to emotions simply and at low cost, without requiring specialized knowledge or expensive equipment.

[0317] The processing flow will be explained below.

[0318] Step 1:

[0319] The user uses the file browser on the device to select image data or video data of the scene for which they want to generate sound effects. For example, the user selects a video file called "Battle Scene.mp4."

[0320] Step 2:

[0321] The user sends the selected scene data from the terminal to the server via the upload interface of the system.

[0322] Step 3:

[0323] The server receives the scene data sent by the user and saves it in the data storage. For example, it saves "BattleScene.mp4" in the specified directory.

[0324] Step 4:

[0325] The server then inputs the saved file into the generative AI model to begin analyzing the scene data, extracting the features of the scene data during this process.

[0326] Step 5:

[0327] The server uses the generated AI model to recognize specific scenes within the scene data, such as a sword swing or a magic cast, and assigns a scene tag.

[0328] Step 6:

[0329] The device sends the user's voice data or facial expression data to the emotion engine, which analyzes it and recognizes the user's emotions.

[0330] Step 7:

[0331] The server uses an emotion engine to analyze the voice and facial expression data to identify the user's emotions, such as nervousness, excitement, and joy.

[0332] Step 8:

[0333] The server automatically generates appropriate sound effects using a generative AI model based on the recognized scene tags and user emotion data, such as the sound of a sword swing or magic.

[0334] Step 9:

[0335] The server adjusts the generated sound effects based on the user's emotions. For example, if the user is excited, the server may increase the volume of the sound effects or speed up the tempo.

[0336] Step 10:

[0337] The server saves the generated sound effects as audio files, and records the path of each audio file to provide to the user.

[0338] Step 11:

[0339] The server generates a link based on the path of the saved sound effect file, which the user can use to easily download it. This link is generated for each user and managed together with their authentication information.

[0340] Step 12:

[0341] The server provides the user with a download link for the generated sound effect, which is sent to the user via email or a web portal.

[0342] Step 13:

[0343] The user clicks on the provided download link to download the generated sound effect to their device, and the downloaded file can be applied to the user's entertainment content.

[0344] The above is the specific processing flow of this system. Taking into account the details of the operation at each step, sound effects are generated efficiently and with high quality, and sound effects can be flexibly adjusted according to the user's emotions.

[0345] Example 2

[0346] 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."

[0347] Conventional sound effect generation systems for entertainment content mainly generate simple sound effects based on scene data, making it difficult to provide high-quality sound effects that reflect the user's emotions. For this reason, there has been a demand for systems that can appropriately adjust sound effects based on the user's actual emotions to provide a more realistic entertainment experience.

[0348] 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.

[0349] In this invention, the server includes means for inputting scene data, means for receiving and saving the scene data, means for analyzing the scene data and recognizing a specific scene, means for acquiring user emotion data, means for analyzing the user emotion data, means for generating appropriate sound effects using a generative AI model based on the recognized scene and the user emotion data, means for adjusting the generated sound effects based on the user emotion data, and means for saving and providing the generated and adjusted sound effects. This makes it possible to generate and provide high-quality sound effects that reflect the user's emotions.

[0350] "Scene data" is data that is provided in the form of image data or video data and is the subject of sound effect generation.

[0351] The "receiving and storing means" is a means for transmitting scene data to the server and storing the data in the data storage.

[0352] The "analysis means" is a means for extracting the characteristics of the scene data and recognizing a particular scene based on the extracted characteristics.

[0353] "Emotion data" is data that indicates the emotional state of the user, and is acquired based on the user's facial expressions, voice, and the like.

[0354] A "generative AI model" is a model that uses artificial intelligence technology to generate sound effects based on recognized scene and user emotional data.

[0355] The "adjustment means" is a means for changing and optimizing the generated sound effect based on the user's emotional data.

[0356] The "storing and providing means" refers to a means for storing the generated and adjusted sound effect files in a data storage and providing the files so that the users can download them.

[0357] The present invention is a system that inputs scene data, analyzes it, and generates appropriate sound effects, and also includes a function that recognizes the user's emotions and adjusts the sound effects based on those emotions. This system aims to provide a more realistic and emotional experience in entertainment content.

[0358] System configuration

[0359] First, the user provides scene data (image or video data) and uploads the data from the device to the server. Specifically, the user uses the device's file browser to select the video file of the scene for which they want to generate sound effects (e.g., "battle scene.mp4") and then sends it to the server via the upload interface.

[0360] The server receives the scene data and saves it in the data storage. For example, it saves "battlescene.mp4" in the specified directory (e.g., / storage / uploads / battlescene.mp4).

[0361] Next, the server uses the generative AI model to begin analyzing the uploaded scene data. In this step, it extracts scene features and recognizes specific scenes. Specifically, it breaks down the scene data into frames, extracts the features of each frame, and assigns tags such as "sword swinging scene" or "magic casting scene."

[0362] In parallel, the device collects the user's voice and facial expression data using a built-in camera and microphone, and sends them to the emotion engine. The server uses the emotion engine to analyze the user's emotions. For example, it can analyze whether the user is nervous or excited from the voice data.

[0363] The server uses a generative AI model to generate appropriate sound effects based on the recognized scene tags and analyzed emotional data. For example, for a sword-swinging scene, it generates a "sword-swinging sound.wav" file. It also adjusts the sound effects based on the user's emotional data. For example, if the user is nervous, it will increase the volume of the sound effects or speed up the tempo.

[0364] The generated sound effect files are saved in data storage, and the path to the saved location is recorded. For example, "sword swinging sound.wav" and "magic sound.wav" are stored in the save directory. Based on the path of the saved sound effect file, the server generates a link that users can easily download and provides it to them via email or a web portal.

[0365] The user clicks on the provided download link to download the generated sound effect to their device, and the downloaded file is applied to the user's entertainment content.

[0366] Examples and prompts

[0367] For example, if a user wants to generate sound effects to be used in a battle scene in a game, the process would be as follows:

[0368] 1. The user selects "BattleScene.mp4" on the device and clicks the upload button to send it to the server.

[0369] 2. The server receives the scene data and saves it to / storage / uploads / battlescene.mp4.

[0370] 3. The server begins analyzing the video, extracting features from each frame and recognizing tags such as "swinging a sword" and "casting magic."

[0371] 4. The device captures the user's facial expressions and voice data and sends it to the emotion engine.

[0372] 5. The server uses an emotion engine to analyze the user's emotions and detect, for example, "tension."

[0373] 6. The server generates an appropriate sound effect (e.g., "sword swinging sound.wav") and adjusts the volume based on the user's emotional data.

[0374] 7. The server saves the generated sound effect to / storage / sounds / swordswingingsound.wav and generates a download link.

[0375] 8. The server emails the generated link to the user.

[0376] 9. The user clicks on the link in the email, downloads the "Sword Swinging Sound.wav" file, and applies it to the game.

[0377] Prompt Sentence Examples

[0378] "Users can upload videos of battle scenes, and the app will generate sound effects that match the recognized scenes from the video. The app will also adjust the sound effects based on the user's emotions, and provide a download link."

[0379] The above is a specific embodiment of the invention, which makes it possible to generate high-quality sound effects and sound effects that correspond to emotions easily and at low cost without requiring specialized knowledge or expensive equipment.

[0380] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0381] System program processing flow

[0382] Step 1:

[0383] Selecting scene data

[0384] Input: The user uses the device's file browser to select image or video data for the scene for which they want to generate sound effects.

[0385] Specific behavior: The user clicks the "Choose File" button and selects "BattleScene.mp4" from the file dialog.

[0386] Output: The selected scene data file path is obtained.

[0387] Step 2:

[0388] Uploading scene data

[0389] Input: User selected scene data file path.

[0390] Specific operation: The user clicks the "Upload" button through the upload interface of the terminal, and the selected scene data is sent to the server as an HTTP request.

[0391] Output: Scene data is uploaded to the server.

[0392] Step 3:

[0393] Receiving and saving scene data

[0394] Input: The server receives the scene data as an HTTP request.

[0395] Specific operation: The server saves the received scene data to data storage, for example, / storage / uploads / battlescene.mp4.

[0396] Output: The scene data is saved to the specified directory.

[0397] Step 4:

[0398] Starting Scene Analysis

[0399] Input: Saved scene data file path.

[0400] Specific operation: The server uses the generative AI model to begin analyzing the uploaded scene data, breaking it down into frames and extracting the features of each frame.

[0401] Output: Feature data for each frame.

[0402] Step 5:

[0403] Scene Recognition

[0404] Input: Extracted frame-by-frame feature data.

[0405] Specific actions: The generative AI model analyzes feature data and recognizes specific scenes. Each scene is tagged with a tag such as "swinging a sword" or "casting magic."

[0406] Output: Tagged scene data.

[0407] Step 6:

[0408] Acquiring emotion data

[0409] Input: User's facial expression data and voice data.

[0410] Specific operation: The device uses the built-in camera and microphone to capture the user's facial expressions and voice data and transmits them to the emotion engine.

[0411] Output: Captured facial expression and voice data of the user.

[0412] Step 7:

[0413] Emotion Analysis

[0414] Input: Captured user facial expression and voice data.

[0415] Specific operation: The server uses the emotion engine to analyze the user's emotions. For example, emotions such as "tension" or "excitement" are determined from voice and facial expressions.

[0416] Output: Parsed user emotion data.

[0417] Step 8:

[0418] Sound effect generation

[0419] Input: Tagged scene data and parsed user emotion data.

[0420] How it works: The server uses the generative AI model to generate appropriate sound effects based on the recognized scene tags, for example, generating "sword swinging sound.wav" for a sword swinging scene.

[0421] Output: The generated sound effect file.

[0422] Step 9:

[0423] Sound effect adjustments

[0424] Input: Generated sound effect files and analyzed user emotion data.

[0425] Specific operation: The server adjusts the volume and tempo of the generated sound effects based on the user's emotional data. For example, if the user is nervous, the volume of the sound effects is increased.

[0426] Output: Adjusted sound effect file.

[0427] Step 10:

[0428] Saving sound effect files

[0429] Input: The adjusted sound effect file.

[0430] Specific operation: The server saves the adjusted sound effect file to data storage and records the path to save it, for example, / storage / sounds / swordswingingsound.wav.

[0431] Output: The path of the saved sound effect file.

[0432] Step 11:

[0433] Generate a download link

[0434] Input: The path to the saved sound effect file.

[0435] Specific operation: The server generates a link based on the path of the saved sound effect file, allowing the user to easily download it.

[0436] Output: The generated download link.

[0437] Step 12:

[0438] Providing a download link

[0439] Input: The generated download link.

[0440] What happens: The server provides the generated download link to the user, which can be provided via email or a web portal.

[0441] Output: The download link provided to the user.

[0442] Step 13:

[0443] Download sound effects

[0444] Input: The download link provided by the server.

[0445] Specific operation: The user clicks on the provided download link and the generated sound effect is downloaded to the device.

[0446] Output: Downloaded sound effect file.

[0447] The above are the specific processing steps of the program of this system.

[0448] (Application example 2)

[0449] 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."

[0450] In conventional entertainment content, sound effects are mostly preset, making it difficult to generate and adjust appropriate sound effects in real time according to the viewer's emotions. This has required more complex systems and a large number of human resources to improve the quality of the user experience. Therefore, there is a demand for a system that can generate and adjust sound effects in real time according to the user's emotions.

[0451] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0452] In this invention, the server includes means for inputting scene data, means for receiving and saving the scene data, means for analyzing the scene data and recognizing a specific scene, means for generating appropriate sound effects based on the recognized scene, means for acquiring and analyzing user emotion data, means for adjusting the generated sound effects based on the acquired and analyzed emotion data, and means for saving and providing the generated and adjusted sound effects, thereby making it possible to generate and adjust appropriate sound effects in real time based on the user's emotions.

[0453] "Scene data" refers to visual information expressed as image data or video data.

[0454] The "means for inputting scene data" refers to an interface or device that allows a user to provide scene data to the system.

[0455] The "means for receiving and saving scene data" refers to a mechanism for uploading scene data to a server and saving the data in storage.

[0456] The "means for analyzing scene data and recognizing a specific scene" refers to an analysis algorithm or software used to analyze the scene data and identify a specific scene therein.

[0457] "Means for generating appropriate sound effects" refers to generative AI models or sound generation software for generating sound effects based on a recognized scene.

[0458] "Means for acquiring and analyzing user emotional data" refers to software or equipment for acquiring the user's facial expressions and voice data, analyzing them, and recognizing the user's emotional state.

[0459] "Means for adjusting sound effects generated based on acquired and analyzed emotional data" refers to algorithms or software for adjusting the volume, tempo, tone, etc. of generated sound effects based on acquired and analyzed emotional data of the user.

[0460] The "means for storing and providing the generated and adjusted sound effects" refers to a mechanism for storing the finally generated sound effects and providing them so that the user can download or play them.

[0461] The present invention is a system that inputs and analyzes scene data and generates sound effects using a generative AI model based on the input data. It also has the ability to acquire and analyze user emotion data and adjust the generated sound effects based on the emotion. This invention is particularly intended for application in content distribution services.

[0462] System configuration

[0463] Data upload

[0464] 1. Input of scene data: The user inputs scene data (image data or video data) into the system by selecting the data using a file browser on their smartphone or PC and uploading it to the system.

[0465] 2. Receiving and storing scene data: The server receives the scene data uploaded by the user and stores it in data storage. This storage is done using a common cloud storage service (e.g., Amazon S3).

[0466] Scene analysis and sound effect generation

[0467] 3. Scene data analysis: The server analyzes specific scenes in the scene data. For scene analysis, it uses image recognition and video analysis libraries (e.g., TENSORFLOW (registered trademark), OpenCV).

[0468] 4. Sound Effect Generation: The server uses a generative AI model (e.g. WaveNet, JukeBox) to generate sound effects appropriate for a specific scene, using pre-trained AI models.

[0469] User Emotion Recognition

[0470] 5. Acquisition of emotion data: The user's device (smartphone or PC with webcam) acquires the user's voice data or facial expression data, and sends this data to the server in real time.

[0471] 6. Emotion data analysis: The server uses an emotion analysis AI engine (e.g., Microsoft® Azure® Face API) to analyze the acquired user emotion data and save the results.

[0472] Adjusting and providing sound effects

[0473] 7. Sound effect adjustment: The server adjusts the volume, tempo, and tone of the generated sound effects based on the recognized user emotion data. This adjustment is performed using algorithms (e.g., audio signal processing algorithms).

[0474] 8. Saving and providing sound effects: The adjusted sound effects will be saved again and a link will be generated for users to easily download them. The link will be provided via email or web portal.

[0475] Specific examples

[0476] For example, consider the case where a user uploads a video of a fight scene, "fightscene.mp4," to the system. In this case, the following process occurs:

[0477] 1. The user uploads "Battle Scene.mp4".

[0478] 2. The server receives the video and stores it in data storage.

[0479] 3. The server analyzes the video and recognizes scenes where swords are swung or magic is cast.

[0480] 4. Acquire the user's voice or facial expression data in real time and perform emotion analysis.

[0481] 5. The server generates sword swinging and magic sound effects based on the recognized scene.

[0482] 6. The server adjusts the volume and tempo of the sound effects based on the user's emotional data.

[0483] 7. Save the adjusted sound effect and generate a download link for the user.

[0484] 8. The user obtains the sound effect via the download link and applies it to their content.

[0485] Prompt Sentence Examples

[0486] For example, here's a sample prompt for a generative AI model to generate a sound effect:

[0487] "Please provide an example of how to adjust sound effects programmatically. For example, please implement a method in Python to change the volume of a sound depending on the user's emotions."

[0488] As described above, the system of the present invention is capable of generating and adjusting appropriate sound effects in real time based on the user's emotions, thereby improving the quality of the user's experience with entertainment content.

[0489] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0490] Step 1:

[0491] User enters scene data

[0492] The user selects scene data (image data or video data) from the terminal and uploads it to the system.

[0493] Input: A scene data file selected by the user (e.g. "BattleScene.mp4").

[0494] How it works: The user selects a file using the device's file browser and sends it to the server through the system's upload interface.

[0495] Output: The server receives the scene data.

[0496] Step 2:

[0497] The server receives and stores the scene data

[0498] The server receives the scene data sent by the user and stores it in a data storage.

[0499] Input: Scene data submitted by the user.

[0500] What it does: The server saves the file to a data storage (e.g. Amazon S3) and records the directory path where it was saved.

[0501] Output: The file path of the saved scene data.

[0502] Step 3:

[0503] The server analyzes the scene data and recognizes the specific scene.

[0504] The server analyzes the received scene data and performs scene analysis to recognize specific scenes.

[0505] Input: The file path of the saved scene data.

[0506] How it works: The server uses a scene analysis library (e.g. TensorFlow, OpenCV) to parse the scene data frame by frame and extract specific scene tags (e.g. sword, explosion, magic).

[0507] Output: Extracted scene tags.

[0508] Step 4:

[0509] Server generates sound effects

[0510] Based on the recognized scene tags, the server generates appropriate sound effects using a generative AI model.

[0511] Input: Extracted scene tags.

[0512] How it works: The server inputs the scene tag as a prompt into a generative AI model (e.g. WaveNet, JukeBox) and generates the corresponding sound effect.

[0513] Output: The generated sound effect file.

[0514] Step 5:

[0515] The device acquires the user's emotional data

[0516] The terminal acquires the user's voice data or facial expression data and transmits it to the server.

[0517] Input: User's voice or facial expression data.

[0518] How it works: The device uses a microphone and camera to capture the user's voice and facial expression data in real time and transmits it to a server.

[0519] Output: Emotion data sent to the server.

[0520] Step 6:

[0521] The server analyzes the emotional data

[0522] The server analyzes the acquired emotion data and recognizes the user's emotional state.

[0523] Input: Emotion data sent to the server.

[0524] How it works: The server uses an emotion analysis AI engine (e.g., Microsoft Azure Face API) to analyze the emotion data and determine the user's emotional state (e.g., nervous, excited, relaxed).

[0525] Output: User's emotional state data.

[0526] Step 7:

[0527] Adjusted server-generated sound effects

[0528] The server adjusts the generated sound effects based on the recognized emotional state data of the user.

[0529] Input: Generated sound effect files and user emotional state data.

[0530] How it works: The server uses audio signal processing algorithms to adjust the volume, tempo, and tone of sound effects based on the user's emotions.

[0531] Output: Adjusted sound effect file.

[0532] Step 8:

[0533] The server stores and provides the adjusted sound effects.

[0534] The server stores the adjusted sound effects and generates a link for users to download them.

[0535] Input: The adjusted sound effect file.

[0536] How it works: The server saves the adjusted sound effect file to data storage and generates a download link to provide to the user. The link is provided to the user via email or a web portal.

[0537] Output: A download link to the user.

[0538] The above are the specific processing steps of the system that realizes the application example. In this way, it becomes possible to generate and adjust appropriate sound effects in real time based on the user's emotions.

[0539] 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.

[0540] 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.

[0541] 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.

[0542] [Second embodiment]

[0543] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0544] 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.

[0545] 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).

[0546] 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.

[0547] 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.

[0548] 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).

[0549] 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.

[0550] 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.

[0551] 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.

[0552] 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.

[0553] 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.

[0554] 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."

[0555] The present invention relates to a system for inputting scene data, analyzing the data, and generating appropriate sound effects. This system is intended to generate sound effects to provide a realistic experience, primarily in entertainment content.

[0556] System configuration

[0557] The user provides scene data (image or video data) and uploads the data from their device to the server. The server receives the uploaded scene data, analyzes it, and recognizes specific scenes. The AI ​​model then generates sound effects based on the recognized scene and provides them to the user. Each part of the system is described in detail below.

[0558] Data upload

[0559] 1. The user selects scene data

[0560] The user uses the file browser on the device to select image data or video data of the scene for which they want to generate sound effects. For example, the user can select a video file called "Battle Scene.mp4."

[0561] 2. The user uploads the scene data.

[0562] The user sends the selected scene data to the server via an upload interface from the terminal to the system.

[0563] Receiving and saving scene data

[0564] 3. The server receives the scene data.

[0565] The server receives the scene data sent by the user and saves it in the data storage. For example, it saves "BattleScene.mp4" in the specified directory.

[0566] Scene Analysis and Recognition

[0567] 4. The server starts analyzing the scene

[0568] The server begins analyzing the uploaded scene data using the generative AI model. In this step, it extracts scene features and identifies specific scenes (e.g., sword swinging scenes, magic casting scenes, etc.).

[0569] 5. The server recognizes the scene

[0570] The generative AI model recognizes specific actions and events in the scene data and assigns scene tags (e.g., sword, magic, explosion, etc.) accordingly.

[0571] Sound effect generation and provision

[0572] 6. The server generates the sound effects

[0573] The server automatically generates optimal sound effects using a generative AI model based on the recognized scene tags, such as the sound of a sword swing or magic.

[0574] 7. The server saves the sound effect files

[0575] Save the generated sound effects as audio files and record the path to save them. For example, save "sword swinging sound.wav" and "magic sound.wav" in the appropriate directory.

[0576] 8. The server generates the download link

[0577] Based on the path of the saved sound effect file, a link is generated that allows the user to easily download it.

[0578] Download sound effects

[0579] 9. The server provides the download link to the user

[0580] The server provides the user with a download link for the generated sound effect, and the user can download the generated sound effect to their device by clicking the provided link.

[0581] Specific examples

[0582] For example, if a user wants to generate sound effects to be used in a battle scene in a game, the process would be as follows:

[0583] 1. The user uploads a video of a battle scene, "BattleScene.mp4," from their device to the server.

[0584] 2. The server receives the video and stores it in the system.

[0585] 3. The server analyzes the video and recognizes scenes where swords are swung or magic is cast.

[0586] 4. The server generates sword swinging and magic sound effects based on the recognized scene.

[0587] 5. The server saves the generated sound effect file and provides a download link to the user.

[0588] 6. The user clicks on the link to download the generated sound effect and apply it to the game.

[0589] The above is a detailed description of the embodiment of the present invention. This system makes it possible to generate high-quality sound effects simply and at low cost without requiring specialized knowledge or expensive equipment.

[0590] The processing flow will be explained below.

[0591] Step 1:

[0592] The user uses the file browser on the device to select image data or video data of the scene for which they want to generate sound effects. For example, the user selects a video file called "Battle Scene.mp4."

[0593] Step 2:

[0594] The user sends the selected scene data from the terminal to the server via the system's upload interface. The uploaded file is saved in the specified directory on the server.

[0595] Step 3:

[0596] The server receives the scene data sent by the user and saves it in the data storage. The path of the saved file is recorded and used for subsequent processing.

[0597] Step 4:

[0598] The server inputs the saved file into the generative AI model to begin analyzing the scene data. During this process, the server extracts features from the scene data.

[0599] Step 5:

[0600] The server uses the generated AI model to recognize specific scenes within the scene data, such as a sword swing or a magic cast, and assigns a scene tag to the recognized scene.

[0601] Step 6:

[0602] The server automatically generates appropriate sound effects using a generative AI model based on the recognized scene tags. The generated sound effects correspond to the scene tags, such as "sword swinging sounds" or "magic sounds."

[0603] Step 7:

[0604] The server saves the generated sound effects as audio files, and records the path of each audio file to provide to the user.

[0605] Step 8:

[0606] The server generates a link based on the path of the saved sound effect file, which the user can use to easily download it. This link is generated for each user and managed together with their authentication information.

[0607] Step 9:

[0608] The server provides the user with a download link for the generated sound effect, which is sent to the user via email or a web portal.

[0609] Step 10:

[0610] The user clicks on the provided download link to download the generated sound effect to their device, and the downloaded file can be applied to the user's entertainment content.

[0611] This is the specific flow of processing in this system. Taking into account the details of the operations at each step, we aim to generate sound effects efficiently and with high quality.

[0612] Example 1

[0613] 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."

[0614] Conventional systems have the problem that they require specialized knowledge and expensive equipment to generate high-quality sound effects for entertainment content. Furthermore, manually creating appropriate sound effects for each scene takes a great deal of time and effort, so there is a demand for a system that can generate sound effects simply and efficiently.

[0615] 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.

[0616] In this invention, the server includes means for a user to select scene data, means for a user to upload scene data, means for the server to receive and store the scene data, means for the server to analyze the scene data using a generative AI model and recognize a specific scene, means for the server to generate sound effects using the generative AI model based on the recognized scene, and means for storing and providing the generated sound effect files. This makes it possible to generate high-quality sound effects easily and at low cost without requiring specialized knowledge or expensive equipment.

[0617] The "means for the user to select scene data" refers to an interface that allows the user to select image or video data for which sound effects are to be generated via a file browser on the terminal or the like.

[0618] The "means for the user to upload scene data" refers to an interface that provides a function for the user to send scene data selected by the user to a server via the Internet.

[0619] "Means for the server to receive and store scene data" refers to software or hardware that has the function of allowing the server to receive scene data sent by a user and store it for a certain period of time or in a certain directory.

[0620] "Means for the server to analyze scene data using a generative AI model and recognize specific scenes" refers to the process by which the server utilizes a machine learning model (generative AI model) to analyze received scene data and identify specific features or events.

[0621] "Means for the server to generate sound effects using a generative AI model based on the recognized scene" refers to algorithms or software that enable the generative AI model to automatically generate appropriate sound effects based on the results of scene recognition.

[0622] "Means for storing and providing generated sound effect files" refers to the function of storing sound effect files generated by a generative AI model on a server and providing a link or interface that allows users to easily download or use the files.

[0623] The present invention relates to a system for inputting scene data, analyzing the data, and generating appropriate sound effects. This system is primarily intended to generate sound effects to provide a realistic experience in entertainment content.

[0624] System configuration

[0625] The user provides scene data (image or video data) and uploads the data from their device to the server. The server receives the uploaded scene data, analyzes it, and recognizes specific scenes. Then, a generative AI model generates sound effects based on the recognized scene and provides them to the user. Each part of the system is described in detail below.

[0626] Data upload

[0627] The user selects scene data

[0628] The user uses the file browser on the device to select image data or video data of the scene for which they want to generate sound effects. For example, the user can select a video file called "Battle Scene.mp4."

[0629] The user uploads scene data

[0630] The user sends the selected scene data to the server via an upload interface from the terminal to the system.

[0631] Receiving and saving scene data

[0632] The server receives the scene data

[0633] The server receives the scene data sent by the user and saves it in the data storage. For example, it saves "BattleScene.mp4" in the specified directory.

[0634] Scene Analysis and Recognition

[0635] The server starts scene analysis

[0636] The server begins analyzing the uploaded scene data using the generative AI model. In this step, it extracts scene features and identifies specific scenes (e.g., sword swinging scenes, magic casting scenes, etc.).

[0637] The server recognizes the scene

[0638] The generative AI model recognizes specific actions and events in the scene data and assigns scene tags (e.g., sword, magic, explosion, etc.) accordingly.

[0639] Sound effect generation and provision

[0640] The server generates the sound effects

[0641] The server automatically generates optimal sound effects using a generative AI model based on the recognized scene tags, such as the sound of a sword swing or magic.

[0642] The server stores the sound effect files.

[0643] Save the generated sound effects as audio files and record the path to save them. For example, save "sword swinging sound.wav" and "magic sound.wav" in the appropriate directory.

[0644] The server generates the download link

[0645] Based on the path of the saved sound effect file, a link is generated that allows the user to easily download it.

[0646] Download sound effects

[0647] The server provides the download link to the user.

[0648] The server provides the user with a download link for the generated sound effect, and the user can download the generated sound effect to their device by clicking the provided link.

[0649] Specific examples

[0650] For example, if a user wants to generate sound effects to be used in a battle scene in a game, the process would be as follows:

[0651] 1. The user uploads a video of a battle scene, "BattleScene.mp4," from their device to the server.

[0652] 2. The server receives the video and stores it in the system.

[0653] 3. The server analyzes the video and recognizes scenes where swords are swung or magic is cast.

[0654] 4. The server generates sword swinging and magic sound effects based on the recognized scene.

[0655] 5. The server saves the generated sound effect file and provides a download link to the user.

[0656] 6. The user clicks on the link to download the generated sound effect and apply it to the game.

[0657] Examples of prompt statements

[0658] Examples of prompts that users can input into a generative AI model include:

[0659] "I want you to generate sound effects for sword-swinging battle scenes."

[0660] "Create sounds for scenes where magic is used."

[0661] This system makes it possible to generate high-quality sound effects easily and at low cost, without requiring specialized knowledge or expensive equipment.

[0662] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0663] Step 1:

[0664] The user selects scene data

[0665] Input: The user uses the device's file browser to select the image or video data of the scene for which they want to generate sound effects. For example, the user selects the video file "C:\Videos\BattleScene.mp4".

[0666] How it works: The user navigates through the file browser and clicks on the desired scene data file.

[0667] Output: The selected file path is retrieved.

[0668] Step 2:

[0669] The user uploads scene data

[0670] Input: The scene data file selected by the user in step 1.

[0671] How it works: A user drags and drops a file into the system's upload interface and clicks the upload button.

[0672] Output: The scene data is sent over the internet to the server. Progress is displayed and a notification is displayed when the upload is complete.

[0673] Step 3:

[0674] The server receives and stores the scene data.

[0675] Input: Scene data submitted by the user.

[0676] Operation: The server saves the received scene data in the specified directory. For example, it saves it as " / tmp / battlescene.mp4".

[0677] Output: Scene data is saved in a temporary folder on the server.

[0678] Step 4:

[0679] The server starts scene analysis

[0680] Input: Scene data saved in step 3.

[0681] Operation: The server initializes the generative AI model and inputs the saved scene data into the model. Video frames are extracted and preprocessed.

[0682] Output: The scene data is ready for analysis and key features are extracted.

[0683] Step 5:

[0684] The server recognizes the scene

[0685] Input: Scene data parsed by a generative AI model.

[0686] How it works: The generative AI model identifies key features in the scene data and assigns them specific tags (e.g., sword, magic).

[0687] Output: Recognized scene tags are generated.

[0688] Step 6:

[0689] The server generates the sound effects

[0690] Input: Scene tags recognized in step 5.

[0691] How it works: The server uses a generative AI model to generate appropriate sound effects based on the tag. For example, if the tag "sword" is recognized, the server inputs a prompt to the generative AI model saying, "I would like you to generate sound effects for a sword-swinging battle scene."

[0692] Output: The generated sound effect file is created.

[0693] Step 7:

[0694] The server stores the sound effect files.

[0695] Input: The sound effect file generated in step 6.

[0696] Behavior: The server saves the generated sound effect file in the specified directory, for example, as " / audio / sword-swinging-sound.wav". It also performs a checksum check.

[0697] Output: The sound effect file has been saved.

[0698] Step 8:

[0699] The server generates the download link

[0700] Input: The path to the saved sound effect file.

[0701] How it works: The server generates a link based on the path of the saved sound effect file so that the user can easily download it. For example, it generates a link like "https: / / server.com / download / swordswingingsound.wav".

[0702] Output: A download link will be generated.

[0703] Step 9:

[0704] The server provides the download link to the user.

[0705] Input: The download link generated in step 8.

[0706] How it works: The server provides the generated download link to the user, and notification can be via email, chat system, or in-system notification.

[0707] Output: The user receives a link that they can click to download the sound effect.

[0708] (Application example 1)

[0709] 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."

[0710] The present invention relates to a system that analyzes scene data and generates sound effects appropriate for a specific scene. Its purpose is to provide a realistic entertainment experience by analyzing scenes in real time using a smart device and instantly reproducing sound effects. However, conventional technologies require specialized knowledge and expensive equipment, making them too costly and time-consuming for general consumers.

[0711] 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.

[0712] In this invention, the server includes means for inputting scene data, means for receiving and saving the scene data, means for analyzing the scene data and recognizing specific scenes, means for generating appropriate sound effects based on the recognized scenes, means for saving and providing the generated sound effects, means for acquiring video in real time from a camera of a smart device and uploading the scene data, and means for playing the generated sound effects on a speaker of the smart device. This allows even general consumers to easily generate high-quality sound effects in real time and enjoy a realistic entertainment experience.

[0713] "Scene data" refers to visual information such as images and videos, and is data used to recognize specific scenes by analyzing this information.

[0714] "Means for inputting scene data" refers to a device or interface that allows a user to provide scene data such as images or videos to the system.

[0715] The "means for receiving and storing the scene data" refers to a device or software for transferring the input scene data to a server and storing it temporarily or permanently.

[0716] "Means for analyzing the scene data and recognizing a particular scene" refers to an algorithm or program for detecting and identifying a particular event or action within the scene data.

[0717] The "means for generating appropriate sound effects based on the recognized scene" refers to an algorithm or program for generating optimal sound effects according to a specific scene label or tag.

[0718] The "means for storing and providing the generated sound effects" refers to a system or device for storing the generated sound effect files and providing them so that users can download or play them.

[0719] "Means for acquiring video in real time from a smart device camera and uploading scene data" refers to a device or program that uses a camera such as smart glasses or a smartphone to capture video in real time and transmits the data to a server.

[0720] "Means for playing the generated sound effect on a speaker of the smart device" refers to a device for playing the generated sound effect using a speaker of smart glasses, a smartphone, or the like.

[0721] The present invention relates to a system for inputting scene data, analyzing it, and generating appropriate sound effects. This system aims to provide a realistic entertainment experience by analyzing scenes in real time using a smart device and instantly reproducing sound effects.

[0722] System configuration

[0723] A user wears a smart device (e.g., smart glasses) and captures scene data in real time. The scene data is captured as video and uploaded to a server. The server receives the uploaded scene data, analyzes it, and recognizes specific scenes. A generative AI model then generates sound effects based on the recognized scene, which are instantly played on the smart device's speaker. Each part of the system is described in detail below.

[0724] Data upload

[0725] 1. The smart device captures the scene data.

[0726] A user wears a smart device (e.g., smart glasses), and the device's camera captures video in real time. For example, the smart glasses camera takes pictures while the user is walking around a store.

[0727] 2. The smart device uploads the scene data to the server.

[0728] The captured video data is uploaded from the smart device to a server in real time.

[0729] Receiving and saving scene data

[0730] 3. The server receives the scene data.

[0731] The server receives the video data sent from the user's smart device and temporarily stores it in a data storage. For example, the video data is continuously received.

[0732] Scene Analysis and Recognition

[0733] 4. The server starts analyzing the scene

[0734] The server uses the generative AI model to analyze the uploaded video data, extracting scene features and identifying specific scenes (e.g., product shelves, product displays, etc.).

[0735] 5. The server recognizes the scene

[0736] The generative AI model recognizes specific actions and events in the scene data and assigns scene tags (e.g., product descriptions, sale information, etc.) based on them.

[0737] Sound effect generation and provision

[0738] 6. The server generates the sound effects

[0739] The server automatically generates optimal sound effects using a generative AI model based on the recognized scene tags, such as product explanations or sales information.

[0740] 7. Smart devices play sound effects

[0741] The generated sound effects are played in real time through the smart device's speaker, allowing users to enjoy a realistic audio guide.

[0742] Specific examples

[0743] For example, if a user is walking around taking pictures of product shelves in a virtual store, the process will be as follows:

[0744] 1. The user wears smart glasses, and the camera captures real-time images of the product shelves.

[0745] 2. The smart device uploads the video data to the server.

[0746] 3. The server receives the video data, analyzes it, and recognizes the product shelf scene.

[0747] 4. The server generates a voice description of the product based on the recognized scene.

[0748] 5. The smart device will play the generated audio in real time, allowing the user to listen to the product description.

[0749] Prompt Sentence Examples

[0750] "Analyze this image (or video) and generate the appropriate sound effect."

[0751] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0752] System processing steps

[0753] Step 1:

[0754] The camera on the smart device captures the footage in real time.

[0755] Input: Video captured in real time by a smart device (e.g., smart glasses).

[0756] Processing: The smart device continuously captures the scene around the user.

[0757] Output: Captured video data.

[0758] Step 2:

[0759] The captured video data is uploaded to the server.

[0760] Input: Captured real-time video data.

[0761] Processing: The video data acquired by the smart device is compressed and encoded, and then uploaded to the server via the network.

[0762] Output: Video data sent to the server.

[0763] Step 3:

[0764] The server receives the video data and stores it in data storage.

[0765] Input: Video data sent from smart device.

[0766] Processing: The server receives the video data through the network and stores it in the appropriate format in the data storage.

[0767] Output: Saved video data.

[0768] Step 4:

[0769] The server uses a generative AI model to analyze the video data and recognize specific scenes.

[0770] Input: Stored video data.

[0771] Processing: The server uses the generated AI model and the prompt "Analyze this image (or video) and generate appropriate sound effects." to analyze the scene characteristics in the video data and identify specific scene labels and tags.

[0772] Output: Recognized scene tags (e.g. product descriptions, sale information, etc.).

[0773] Step 5:

[0774] The server generates sound effects using a generative AI model based on the recognized scene tags.

[0775] Input: Recognized scene tags.

[0776] Processing: The generative AI model generates appropriate sound effects corresponding to the scene tags, synthesizing the sounds based on pre-trained data.

[0777] Output: The generated sound effect file.

[0778] Step 6:

[0779] The server sends the generated sound effect file to the smart device.

[0780] Input: The generated sound effect file.

[0781] Processing: The server sends the path and data of the sound effect file to the smart device, where the sound effect file is encoded in the appropriate format.

[0782] Output: Sound effect data sent to smart device.

[0783] Step 7:

[0784] The smart device plays a sound effect.

[0785] Input: Sound effect data sent from the server.

[0786] Processing: The smart device decodes the received sound effect data and plays it through the built-in speaker.

[0787] Output: The sound effect that the user can hear.

[0788] 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.

[0789] The present invention is a system that inputs scene data, analyzes it, and generates appropriate sound effects, and also includes a function that recognizes the user's emotions and adjusts the sound effects based on those emotions. This system aims to provide a more realistic and emotional experience in entertainment content.

[0790] System configuration

[0791] The user provides scene data (image or video data) and uploads the data from their device to the server. The server receives the uploaded scene data, analyzes it, and recognizes specific scenes. An AI model then generates sound effects based on the recognized scene and provides them to the user. The system also incorporates an emotion engine that recognizes the user's emotions and adjusts the generated sound effects based on the user's emotions. Each part of the system is described in detail below.

[0792] Data upload

[0793] 1. The user selects scene data

[0794] The user uses the file browser on the device to select image data or video data of the scene for which they want to generate sound effects. For example, the user can select a video file called "Battle Scene.mp4."

[0795] 2. The user uploads the scene data.

[0796] The user sends the selected scene data to the server via an upload interface from the terminal to the system.

[0797] Receiving and saving scene data

[0798] 3. The server receives the scene data.

[0799] The server receives the scene data sent by the user and saves it in the data storage. For example, it saves "BattleScene.mp4" in the specified directory.

[0800] Scene Analysis and Recognition

[0801] 4. The server starts analyzing the scene

[0802] The server starts analyzing the uploaded scene data using the generative AI model. In this step, it extracts scene features.

[0803] 5. The server recognizes the scene

[0804] The generative AI model recognizes specific scenes within the scene data and assigns scene tags (e.g., sword, magic, explosion, etc.) accordingly.

[0805] User Emotion Recognition

[0806] 1. Obtain user emotion data

[0807] The device sends the user's voice data or facial expression data to the emotion engine, which analyzes it and recognizes the user's emotions.

[0808] 2. Analyze user sentiment

[0809] The server uses an emotion engine to analyze the user's emotion, and the analyzed emotion data corresponds to the scene tag.

[0810] Sound effect generation and adjustment

[0811] 1. The server generates the sound effects

[0812] The server automatically generates appropriate sound effects using a generative AI model based on the recognized scene tags, such as the sound of a sword swing or magic.

[0813] 2. The server adjusts the sound effects

[0814] The server adjusts the generated sound effects based on the user's emotions. For example, if the user is nervous, the server increases the volume of the sound effects or speeds up the tempo.

[0815] Saving and providing sound effects

[0816] 1. The server saves the sound effect files

[0817] Save the generated sound effects as audio files and record the path to save them. For example, save "sword swinging sound.wav" and "magic sound.wav" in the appropriate directory.

[0818] 2. The server generates a download link

[0819] Based on the path of the saved sound effect file, a link is generated that allows the user to easily download it. This link is generated individually for each user and managed together with authentication information.

[0820] Download sound effects

[0821] 1. The server provides the download link to the user.

[0822] The server provides the user with a download link for the generated sound effect, which is sent to the user via email or a web portal.

[0823] 2. The user downloads the sound effect

[0824] The user clicks on the provided download link to download the generated sound effect to their device, and the downloaded file can be applied to the user's entertainment content.

[0825] Specific examples

[0826] For example, if a user wants to generate sound effects to be used in a battle scene in a game, the process would be as follows:

[0827] 1. The user uploads a video of a battle scene, "BattleScene.mp4," from their device to the server.

[0828] 2. The server receives the video and stores it in the system.

[0829] 3. The server analyzes the video and recognizes scenes where swords are swung or magic is cast.

[0830] 4. The emotion engine analyzes the user's voice and facial expression data to recognize emotions such as tension and excitement.

[0831] 5. The server generates sword swinging and magic sound effects based on the recognized scene.

[0832] 6. The server adjusts the generated sound effects based on the user's emotions.

[0833] 7. The server saves the generated sound effect file and provides a download link to the user.

[0834] 8. The user clicks on the link to download the generated sound effect and apply it to the game.

[0835] The above is a detailed description of an embodiment of the present invention. This system makes it possible to generate high-quality sound effects and sound effects corresponding to emotions simply and at low cost, without requiring specialized knowledge or expensive equipment.

[0836] The processing flow will be explained below.

[0837] Step 1:

[0838] The user uses the file browser on the device to select image data or video data of the scene for which they want to generate sound effects. For example, the user selects a video file called "Battle Scene.mp4."

[0839] Step 2:

[0840] The user sends the selected scene data from the terminal to the server via the upload interface of the system.

[0841] Step 3:

[0842] The server receives the scene data sent by the user and saves it in the data storage. For example, it saves "BattleScene.mp4" in the specified directory.

[0843] Step 4:

[0844] The server then inputs the saved file into the generative AI model to begin analyzing the scene data, extracting the features of the scene data during this process.

[0845] Step 5:

[0846] The server uses the generated AI model to recognize specific scenes within the scene data, such as a sword swing or a magic cast, and assigns a scene tag.

[0847] Step 6:

[0848] The device sends the user's voice data or facial expression data to the emotion engine, which analyzes it and recognizes the user's emotions.

[0849] Step 7:

[0850] The server uses an emotion engine to analyze the voice and facial expression data to identify the user's emotions, such as nervousness, excitement, and joy.

[0851] Step 8:

[0852] The server automatically generates appropriate sound effects using a generative AI model based on the recognized scene tags and user emotion data, such as the sound of a sword swing or magic.

[0853] Step 9:

[0854] The server adjusts the generated sound effects based on the user's emotions. For example, if the user is excited, the server may increase the volume of the sound effects or speed up the tempo.

[0855] Step 10:

[0856] The server saves the generated sound effects as audio files, and records the path of each audio file to provide to the user.

[0857] Step 11:

[0858] The server generates a link based on the path of the saved sound effect file, which the user can use to easily download it. This link is generated for each user and managed together with their authentication information.

[0859] Step 12:

[0860] The server provides the user with a download link for the generated sound effect, which is sent to the user via email or a web portal.

[0861] Step 13:

[0862] The user clicks on the provided download link to download the generated sound effect to their device, and the downloaded file can be applied to the user's entertainment content.

[0863] The above is the specific processing flow of this system. Taking into account the details of the operation at each step, sound effects are generated efficiently and with high quality, and sound effects can be flexibly adjusted according to the user's emotions.

[0864] Example 2

[0865] 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."

[0866] Conventional sound effect generation systems for entertainment content mainly generate simple sound effects based on scene data, making it difficult to provide high-quality sound effects that reflect the user's emotions. For this reason, there has been a demand for systems that can appropriately adjust sound effects based on the user's actual emotions to provide a more realistic entertainment experience.

[0867] 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.

[0868] In this invention, the server includes means for inputting scene data, means for receiving and saving the scene data, means for analyzing the scene data and recognizing a specific scene, means for acquiring user emotion data, means for analyzing the user emotion data, means for generating appropriate sound effects using a generative AI model based on the recognized scene and the user emotion data, means for adjusting the generated sound effects based on the user emotion data, and means for saving and providing the generated and adjusted sound effects. This makes it possible to generate and provide high-quality sound effects that reflect the user's emotions.

[0869] "Scene data" is data that is provided in the form of image data or video data and is the subject of sound effect generation.

[0870] The "receiving and storing means" is a means for transmitting scene data to the server and storing the data in the data storage.

[0871] The "analysis means" is a means for extracting the characteristics of the scene data and recognizing a particular scene based on the extracted characteristics.

[0872] "Emotion data" is data that indicates the emotional state of the user, and is acquired based on the user's facial expressions, voice, and the like.

[0873] A "generative AI model" is a model that uses artificial intelligence technology to generate sound effects based on recognized scene and user emotional data.

[0874] The "adjustment means" is a means for changing and optimizing the generated sound effect based on the user's emotional data.

[0875] The "storing and providing means" refers to a means for storing the generated and adjusted sound effect files in a data storage and providing the files so that the users can download them.

[0876] The present invention is a system that inputs scene data, analyzes it, and generates appropriate sound effects, and also includes a function that recognizes the user's emotions and adjusts the sound effects based on those emotions. This system aims to provide a more realistic and emotional experience in entertainment content.

[0877] System configuration

[0878] First, the user provides scene data (image or video data) and uploads the data from the device to the server. Specifically, the user uses the device's file browser to select the video file of the scene for which they want to generate sound effects (e.g., "battle scene.mp4") and then sends it to the server via the upload interface.

[0879] The server receives the scene data and saves it in the data storage. For example, it saves "battlescene.mp4" in the specified directory (e.g., / storage / uploads / battlescene.mp4).

[0880] Next, the server uses the generative AI model to begin analyzing the uploaded scene data. In this step, it extracts scene features and recognizes specific scenes. Specifically, it breaks down the scene data into frames, extracts the features of each frame, and assigns tags such as "sword swinging scene" or "magic casting scene."

[0881] In parallel, the device collects the user's voice and facial expression data using a built-in camera and microphone, and sends them to the emotion engine. The server uses the emotion engine to analyze the user's emotions. For example, it can analyze whether the user is nervous or excited from the voice data.

[0882] The server uses a generative AI model to generate appropriate sound effects based on the recognized scene tags and analyzed emotional data. For example, for a sword-swinging scene, it generates a "sword-swinging sound.wav" file. It also adjusts the sound effects based on the user's emotional data. For example, if the user is nervous, it will increase the volume of the sound effects or speed up the tempo.

[0883] The generated sound effect files are saved in data storage, and the path to the saved location is recorded. For example, "sword swinging sound.wav" and "magic sound.wav" are stored in the save directory. Based on the path of the saved sound effect file, the server generates a link that users can easily download and provides it to them via email or a web portal.

[0884] The user clicks on the provided download link to download the generated sound effect to their device, and the downloaded file is applied to the user's entertainment content.

[0885] Examples and prompts

[0886] For example, if a user wants to generate sound effects to be used in a battle scene in a game, the process would be as follows:

[0887] 1. The user selects "BattleScene.mp4" on the device and clicks the upload button to send it to the server.

[0888] 2. The server receives the scene data and saves it to / storage / uploads / battlescene.mp4.

[0889] 3. The server begins analyzing the video, extracting features from each frame and recognizing tags such as "swinging a sword" and "casting magic."

[0890] 4. The device captures the user's facial expressions and voice data and sends it to the emotion engine.

[0891] 5. The server uses an emotion engine to analyze the user's emotions and detect, for example, "tension."

[0892] 6. The server generates an appropriate sound effect (e.g., "sword swinging sound.wav") and adjusts the volume based on the user's emotional data.

[0893] 7. The server saves the generated sound effect to / storage / sounds / swordswingingsound.wav and generates a download link.

[0894] 8. The server emails the generated link to the user.

[0895] 9. The user clicks on the link in the email, downloads the "Sword Swinging Sound.wav" file, and applies it to the game.

[0896] Prompt Sentence Examples

[0897] "Users can upload videos of battle scenes, and the app will generate sound effects that match the recognized scenes from the video. The app will also adjust the sound effects based on the user's emotions, and provide a download link."

[0898] The above is a specific embodiment of the invention, which makes it possible to generate high-quality sound effects and sound effects that correspond to emotions easily and at low cost without requiring specialized knowledge or expensive equipment.

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

[0900] System program processing flow

[0901] Step 1:

[0902] Selecting scene data

[0903] Input: The user uses the device's file browser to select image or video data for the scene for which they want to generate sound effects.

[0904] Specific behavior: The user clicks the "Choose File" button and selects "BattleScene.mp4" from the file dialog.

[0905] Output: The selected scene data file path is obtained.

[0906] Step 2:

[0907] Uploading scene data

[0908] Input: User selected scene data file path.

[0909] Specific operation: The user clicks the "Upload" button through the upload interface of the terminal, and the selected scene data is sent to the server as an HTTP request.

[0910] Output: Scene data is uploaded to the server.

[0911] Step 3:

[0912] Receiving and saving scene data

[0913] Input: The server receives the scene data as an HTTP request.

[0914] Specific operation: The server saves the received scene data to data storage, for example, / storage / uploads / battlescene.mp4.

[0915] Output: The scene data is saved to the specified directory.

[0916] Step 4:

[0917] Starting Scene Analysis

[0918] Input: Saved scene data file path.

[0919] Specific operation: The server uses the generative AI model to begin analyzing the uploaded scene data, breaking it down into frames and extracting the features of each frame.

[0920] Output: Feature data for each frame.

[0921] Step 5:

[0922] Scene Recognition

[0923] Input: Extracted frame-by-frame feature data.

[0924] Specific actions: The generative AI model analyzes feature data and recognizes specific scenes. Each scene is tagged with a tag such as "swinging a sword" or "casting magic."

[0925] Output: Tagged scene data.

[0926] Step 6:

[0927] Acquiring emotion data

[0928] Input: User's facial expression data and voice data.

[0929] Specific operation: The device uses the built-in camera and microphone to capture the user's facial expressions and voice data and transmits them to the emotion engine.

[0930] Output: Captured facial expression and voice data of the user.

[0931] Step 7:

[0932] Emotion Analysis

[0933] Input: Captured user facial expression and voice data.

[0934] Specific operation: The server uses the emotion engine to analyze the user's emotions. For example, emotions such as "tension" or "excitement" are determined from voice and facial expressions.

[0935] Output: Parsed user emotion data.

[0936] Step 8:

[0937] Sound effect generation

[0938] Input: Tagged scene data and parsed user emotion data.

[0939] How it works: The server uses the generative AI model to generate appropriate sound effects based on the recognized scene tags, for example, generating "sword swinging sound.wav" for a sword swinging scene.

[0940] Output: The generated sound effect file.

[0941] Step 9:

[0942] Sound effect adjustments

[0943] Input: Generated sound effect files and analyzed user emotion data.

[0944] Specific operation: The server adjusts the volume and tempo of the generated sound effects based on the user's emotional data. For example, if the user is nervous, the volume of the sound effects is increased.

[0945] Output: Adjusted sound effect file.

[0946] Step 10:

[0947] Saving sound effect files

[0948] Input: The adjusted sound effect file.

[0949] Specific operation: The server saves the adjusted sound effect file to data storage and records the path to save it, for example, / storage / sounds / swordswingingsound.wav.

[0950] Output: The path of the saved sound effect file.

[0951] Step 11:

[0952] Generate a download link

[0953] Input: The path to the saved sound effect file.

[0954] Specific operation: The server generates a link based on the path of the saved sound effect file, allowing the user to easily download it.

[0955] Output: The generated download link.

[0956] Step 12:

[0957] Providing a download link

[0958] Input: The generated download link.

[0959] What happens: The server provides the generated download link to the user, which can be provided via email or a web portal.

[0960] Output: The download link provided to the user.

[0961] Step 13:

[0962] Download sound effects

[0963] Input: The download link provided by the server.

[0964] Specific operation: The user clicks on the provided download link and the generated sound effect is downloaded to the device.

[0965] Output: Downloaded sound effect file.

[0966] The above are the specific processing steps of the program of this system.

[0967] (Application example 2)

[0968] 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."

[0969] In conventional entertainment content, sound effects are mostly preset, making it difficult to generate and adjust appropriate sound effects in real time according to the viewer's emotions. This has required more complex systems and a large number of human resources to improve the quality of the user experience. Therefore, there is a demand for a system that can generate and adjust sound effects in real time according to the user's emotions.

[0970] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0971] In this invention, the server includes means for inputting scene data, means for receiving and saving the scene data, means for analyzing the scene data and recognizing a specific scene, means for generating appropriate sound effects based on the recognized scene, means for acquiring and analyzing user emotion data, means for adjusting the generated sound effects based on the acquired and analyzed emotion data, and means for saving and providing the generated and adjusted sound effects, thereby making it possible to generate and adjust appropriate sound effects in real time based on the user's emotions.

[0972] "Scene data" refers to visual information expressed as image data or video data.

[0973] The "means for inputting scene data" refers to an interface or device that allows a user to provide scene data to the system.

[0974] The "means for receiving and saving scene data" refers to a mechanism for uploading scene data to a server and saving the data in storage.

[0975] The "means for analyzing scene data and recognizing a specific scene" refers to an analysis algorithm or software used to analyze the scene data and identify a specific scene therein.

[0976] "Means for generating appropriate sound effects" refers to generative AI models or sound generation software for generating sound effects based on a recognized scene.

[0977] "Means for acquiring and analyzing user emotional data" refers to software or equipment for acquiring the user's facial expressions and voice data, analyzing them, and recognizing the user's emotional state.

[0978] "Means for adjusting sound effects generated based on acquired and analyzed emotional data" refers to algorithms or software for adjusting the volume, tempo, tone, etc. of generated sound effects based on acquired and analyzed emotional data of the user.

[0979] The "means for storing and providing the generated and adjusted sound effects" refers to a mechanism for storing the finally generated sound effects and providing them so that the user can download or play them.

[0980] The present invention is a system that inputs and analyzes scene data and generates sound effects using a generative AI model based on the input data. It also has the ability to acquire and analyze user emotion data and adjust the generated sound effects based on the emotion. This invention is particularly intended for application in content distribution services.

[0981] System configuration

[0982] Data upload

[0983] 1. Input of scene data: The user inputs scene data (image data or video data) into the system by selecting the data using a file browser on their smartphone or PC and uploading it to the system.

[0984] 2. Receiving and storing scene data: The server receives the scene data uploaded by the user and stores it in data storage. This storage is done using a common cloud storage service (e.g., Amazon S3).

[0985] Scene analysis and sound effect generation

[0986] 3. Scene data analysis: The server analyzes specific scenes in the scene data using image recognition and video analysis libraries (e.g., TensorFlow, OpenCV).

[0987] 4. Sound Effect Generation: The server uses a generative AI model (e.g. WaveNet, JukeBox) to generate sound effects appropriate for a specific scene, using pre-trained AI models.

[0988] User Emotion Recognition

[0989] 5. Acquisition of emotion data: The user's device (smartphone or PC with webcam) acquires the user's voice data or facial expression data, and sends this data to the server in real time.

[0990] 6. Emotion data analysis: The server uses an emotion analysis AI engine (e.g., Microsoft Azure Face API) to analyze the acquired user emotion data and save the results.

[0991] Adjusting and providing sound effects

[0992] 7. Sound effect adjustment: The server adjusts the volume, tempo, and tone of the generated sound effects based on the recognized user emotion data. This adjustment is performed using algorithms (e.g., audio signal processing algorithms).

[0993] 8. Saving and providing sound effects: The adjusted sound effects will be saved again and a link will be generated for users to easily download them. The link will be provided via email or web portal.

[0994] Specific examples

[0995] For example, consider the case where a user uploads a video of a fight scene, "fightscene.mp4," to the system. In this case, the following process occurs:

[0996] 1. The user uploads "Battle Scene.mp4".

[0997] 2. The server receives the video and stores it in data storage.

[0998] 3. The server analyzes the video and recognizes scenes where swords are swung or magic is cast.

[0999] 4. Acquire the user's voice or facial expression data in real time and perform emotion analysis.

[1000] 5. The server generates sword swinging and magic sound effects based on the recognized scene.

[1001] 6. The server adjusts the volume and tempo of the sound effects based on the user's emotional data.

[1002] 7. Save the adjusted sound effect and generate a download link for the user.

[1003] 8. The user obtains the sound effect via the download link and applies it to their content.

[1004] Prompt Sentence Examples

[1005] For example, here's a sample prompt for a generative AI model to generate a sound effect:

[1006] "Please provide an example of how to adjust sound effects programmatically. For example, please implement a method in Python to change the volume of a sound depending on the user's emotions."

[1007] As described above, the system of the present invention is capable of generating and adjusting appropriate sound effects in real time based on the user's emotions, thereby improving the quality of the user's experience with entertainment content.

[1008] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1009] Step 1:

[1010] User enters scene data

[1011] The user selects scene data (image data or video data) from the terminal and uploads it to the system.

[1012] Input: A scene data file selected by the user (e.g. "BattleScene.mp4").

[1013] How it works: The user selects a file using the device's file browser and sends it to the server through the system's upload interface.

[1014] Output: The server receives the scene data.

[1015] Step 2:

[1016] The server receives and stores the scene data

[1017] The server receives the scene data sent by the user and stores it in a data storage.

[1018] Input: Scene data submitted by the user.

[1019] What it does: The server saves the file to a data storage (e.g. Amazon S3) and records the directory path where it was saved.

[1020] Output: The file path of the saved scene data.

[1021] Step 3:

[1022] The server analyzes the scene data and recognizes the specific scene.

[1023] The server analyzes the received scene data and performs scene analysis to recognize specific scenes.

[1024] Input: The file path of the saved scene data.

[1025] How it works: The server uses a scene analysis library (e.g. TensorFlow, OpenCV) to parse the scene data frame by frame and extract specific scene tags (e.g. sword, explosion, magic).

[1026] Output: Extracted scene tags.

[1027] Step 4:

[1028] Server generates sound effects

[1029] Based on the recognized scene tags, the server generates appropriate sound effects using a generative AI model.

[1030] Input: Extracted scene tags.

[1031] How it works: The server inputs the scene tag as a prompt into a generative AI model (e.g. WaveNet, JukeBox) and generates the corresponding sound effect.

[1032] Output: The generated sound effect file.

[1033] Step 5:

[1034] The device acquires the user's emotional data

[1035] The terminal acquires the user's voice data or facial expression data and transmits it to the server.

[1036] Input: User's voice or facial expression data.

[1037] How it works: The device uses a microphone and camera to capture the user's voice and facial expression data in real time and transmits it to a server.

[1038] Output: Emotion data sent to the server.

[1039] Step 6:

[1040] The server analyzes the emotional data

[1041] The server analyzes the acquired emotion data and recognizes the user's emotional state.

[1042] Input: Emotion data sent to the server.

[1043] How it works: The server uses an emotion analysis AI engine (e.g., Microsoft Azure Face API) to analyze the emotion data and determine the user's emotional state (e.g., nervous, excited, relaxed).

[1044] Output: User's emotional state data.

[1045] Step 7:

[1046] Adjusted server-generated sound effects

[1047] The server adjusts the generated sound effects based on the recognized emotional state data of the user.

[1048] Input: Generated sound effect files and user emotional state data.

[1049] How it works: The server uses audio signal processing algorithms to adjust the volume, tempo, and tone of sound effects based on the user's emotions.

[1050] Output: Adjusted sound effect file.

[1051] Step 8:

[1052] The server stores and provides the adjusted sound effects.

[1053] The server stores the adjusted sound effects and generates a link for users to download them.

[1054] Input: The adjusted sound effect file.

[1055] How it works: The server saves the adjusted sound effect file to data storage and generates a download link to provide to the user. The link is provided to the user via email or a web portal.

[1056] Output: A download link to the user.

[1057] The above are the specific processing steps of the system that realizes the application example. In this way, it becomes possible to generate and adjust appropriate sound effects in real time based on the user's emotions.

[1058] 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.

[1059] 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.

[1060] 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.

[1061] [Third embodiment]

[1062] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1063] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1064] 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).

[1065] 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.

[1066] 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.

[1067] 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).

[1068] 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.

[1069] 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.

[1070] 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.

[1071] 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.

[1072] 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.

[1073] 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."

[1074] The present invention relates to a system for inputting scene data, analyzing the data, and generating appropriate sound effects. This system is intended to generate sound effects to provide a realistic experience, primarily in entertainment content.

[1075] System configuration

[1076] The user provides scene data (image or video data) and uploads the data from their device to the server. The server receives the uploaded scene data, analyzes it, and recognizes specific scenes. The AI ​​model then generates sound effects based on the recognized scene and provides them to the user. Each part of the system is described in detail below.

[1077] Data upload

[1078] 1. The user selects scene data

[1079] The user uses the file browser on the device to select image data or video data of the scene for which they want to generate sound effects. For example, the user can select a video file called "Battle Scene.mp4."

[1080] 2. The user uploads the scene data.

[1081] The user sends the selected scene data to the server via an upload interface from the terminal to the system.

[1082] Receiving and saving scene data

[1083] 3. The server receives the scene data.

[1084] The server receives the scene data sent by the user and saves it in the data storage. For example, it saves "BattleScene.mp4" in the specified directory.

[1085] Scene Analysis and Recognition

[1086] 4. The server starts analyzing the scene

[1087] The server begins analyzing the uploaded scene data using the generative AI model. In this step, it extracts scene features and identifies specific scenes (e.g., sword swinging scenes, magic casting scenes, etc.).

[1088] 5. The server recognizes the scene

[1089] The generative AI model recognizes specific actions and events in the scene data and assigns scene tags (e.g., sword, magic, explosion, etc.) accordingly.

[1090] Sound effect generation and provision

[1091] 6. The server generates the sound effects

[1092] The server automatically generates optimal sound effects using a generative AI model based on the recognized scene tags, such as the sound of a sword swing or magic.

[1093] 7. The server saves the sound effect files

[1094] Save the generated sound effects as audio files and record the path to save them. For example, save "sword swinging sound.wav" and "magic sound.wav" in the appropriate directory.

[1095] 8. The server generates the download link

[1096] Based on the path of the saved sound effect file, a link is generated that allows the user to easily download it.

[1097] Download sound effects

[1098] 9. The server provides the download link to the user

[1099] The server provides the user with a download link for the generated sound effect, and the user can download the generated sound effect to their device by clicking the provided link.

[1100] Specific examples

[1101] For example, if a user wants to generate sound effects to be used in a battle scene in a game, the process would be as follows:

[1102] 1. The user uploads a video of a battle scene, "BattleScene.mp4," from their device to the server.

[1103] 2. The server receives the video and stores it in the system.

[1104] 3. The server analyzes the video and recognizes scenes where swords are swung or magic is cast.

[1105] 4. The server generates sword swinging and magic sound effects based on the recognized scene.

[1106] 5. The server saves the generated sound effect file and provides a download link to the user.

[1107] 6. The user clicks on the link to download the generated sound effect and apply it to the game.

[1108] The above is a detailed description of the embodiment of the present invention. This system makes it possible to generate high-quality sound effects simply and at low cost without requiring specialized knowledge or expensive equipment.

[1109] The processing flow will be explained below.

[1110] Step 1:

[1111] The user uses the file browser on the device to select image data or video data of the scene for which they want to generate sound effects. For example, the user selects a video file called "Battle Scene.mp4."

[1112] Step 2:

[1113] The user sends the selected scene data from the terminal to the server via the system's upload interface. The uploaded file is saved in the specified directory on the server.

[1114] Step 3:

[1115] The server receives the scene data sent by the user and saves it in the data storage. The path of the saved file is recorded and used for subsequent processing.

[1116] Step 4:

[1117] The server inputs the saved file into the generative AI model to begin analyzing the scene data. During this process, the server extracts features from the scene data.

[1118] Step 5:

[1119] The server uses the generated AI model to recognize specific scenes within the scene data, such as a sword swing or a magic cast, and assigns a scene tag to the recognized scene.

[1120] Step 6:

[1121] The server automatically generates appropriate sound effects using a generative AI model based on the recognized scene tags. The generated sound effects correspond to the scene tags, such as "sword swinging sounds" or "magic sounds."

[1122] Step 7:

[1123] The server saves the generated sound effects as audio files, and records the path of each audio file to provide to the user.

[1124] Step 8:

[1125] The server generates a link based on the path of the saved sound effect file, which the user can use to easily download it. This link is generated for each user and managed together with their authentication information.

[1126] Step 9:

[1127] The server provides the user with a download link for the generated sound effect, which is sent to the user via email or a web portal.

[1128] Step 10:

[1129] The user clicks on the provided download link to download the generated sound effect to their device, and the downloaded file can be applied to the user's entertainment content.

[1130] This is the specific flow of processing in this system. Taking into account the details of the operations at each step, we aim to generate sound effects efficiently and with high quality.

[1131] Example 1

[1132] 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."

[1133] Conventional systems have the problem that they require specialized knowledge and expensive equipment to generate high-quality sound effects for entertainment content. Furthermore, manually creating appropriate sound effects for each scene takes a great deal of time and effort, so there is a demand for a system that can generate sound effects simply and efficiently.

[1134] 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.

[1135] In this invention, the server includes means for a user to select scene data, means for a user to upload scene data, means for the server to receive and store the scene data, means for the server to analyze the scene data using a generative AI model and recognize a specific scene, means for the server to generate sound effects using the generative AI model based on the recognized scene, and means for storing and providing the generated sound effect files. This makes it possible to generate high-quality sound effects easily and at low cost without requiring specialized knowledge or expensive equipment.

[1136] The "means for the user to select scene data" refers to an interface that allows the user to select image or video data for which sound effects are to be generated via a file browser on the terminal or the like.

[1137] The "means for the user to upload scene data" refers to an interface that provides a function for the user to send scene data selected by the user to a server via the Internet.

[1138] "Means for the server to receive and store scene data" refers to software or hardware that has the function of allowing the server to receive scene data sent by a user and store it for a certain period of time or in a certain directory.

[1139] "Means for the server to analyze scene data using a generative AI model and recognize specific scenes" refers to the process by which the server utilizes a machine learning model (generative AI model) to analyze received scene data and identify specific features or events.

[1140] "Means for the server to generate sound effects using a generative AI model based on the recognized scene" refers to algorithms or software that enable the generative AI model to automatically generate appropriate sound effects based on the results of scene recognition.

[1141] "Means for storing and providing generated sound effect files" refers to the function of storing sound effect files generated by a generative AI model on a server and providing a link or interface that allows users to easily download or use the files.

[1142] The present invention relates to a system for inputting scene data, analyzing the data, and generating appropriate sound effects. This system is primarily intended to generate sound effects to provide a realistic experience in entertainment content.

[1143] System configuration

[1144] The user provides scene data (image or video data) and uploads the data from their device to the server. The server receives the uploaded scene data, analyzes it, and recognizes specific scenes. Then, a generative AI model generates sound effects based on the recognized scene and provides them to the user. Each part of the system is described in detail below.

[1145] Data upload

[1146] The user selects scene data

[1147] The user uses the file browser on the device to select image data or video data of the scene for which they want to generate sound effects. For example, the user can select a video file called "Battle Scene.mp4."

[1148] The user uploads scene data

[1149] The user sends the selected scene data to the server via an upload interface from the terminal to the system.

[1150] Receiving and saving scene data

[1151] The server receives the scene data

[1152] The server receives the scene data sent by the user and saves it in the data storage. For example, it saves "BattleScene.mp4" in the specified directory.

[1153] Scene Analysis and Recognition

[1154] The server starts scene analysis

[1155] The server begins analyzing the uploaded scene data using the generative AI model. In this step, it extracts scene features and identifies specific scenes (e.g., sword swinging scenes, magic casting scenes, etc.).

[1156] The server recognizes the scene

[1157] The generative AI model recognizes specific actions and events in the scene data and assigns scene tags (e.g., sword, magic, explosion, etc.) accordingly.

[1158] Sound effect generation and provision

[1159] The server generates the sound effects

[1160] The server automatically generates optimal sound effects using a generative AI model based on the recognized scene tags, such as the sound of a sword swing or magic.

[1161] The server stores the sound effect files.

[1162] Save the generated sound effects as audio files and record the path to save them. For example, save "sword swinging sound.wav" and "magic sound.wav" in the appropriate directory.

[1163] The server generates the download link

[1164] Based on the path of the saved sound effect file, a link is generated that allows the user to easily download it.

[1165] Download sound effects

[1166] The server provides the download link to the user.

[1167] The server provides the user with a download link for the generated sound effect, and the user can download the generated sound effect to their device by clicking the provided link.

[1168] Specific examples

[1169] For example, if a user wants to generate sound effects to be used in a battle scene in a game, the process would be as follows:

[1170] 1. The user uploads a video of a battle scene, "BattleScene.mp4," from their device to the server.

[1171] 2. The server receives the video and stores it in the system.

[1172] 3. The server analyzes the video and recognizes scenes where swords are swung or magic is cast.

[1173] 4. The server generates sword swinging and magic sound effects based on the recognized scene.

[1174] 5. The server saves the generated sound effect file and provides a download link to the user.

[1175] 6. The user clicks on the link to download the generated sound effect and apply it to the game.

[1176] Examples of prompt statements

[1177] Examples of prompts that users can input into a generative AI model include:

[1178] "I want you to generate sound effects for sword-swinging battle scenes."

[1179] "Create sounds for scenes where magic is used."

[1180] This system makes it possible to generate high-quality sound effects easily and at low cost, without requiring specialized knowledge or expensive equipment.

[1181] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1182] Step 1:

[1183] The user selects scene data

[1184] Input: The user uses the device's file browser to select the image or video data of the scene for which they want to generate sound effects. For example, the user selects the video file "C:\Videos\BattleScene.mp4".

[1185] How it works: The user navigates through the file browser and clicks on the desired scene data file.

[1186] Output: The selected file path is retrieved.

[1187] Step 2:

[1188] The user uploads scene data

[1189] Input: The scene data file selected by the user in step 1.

[1190] How it works: A user drags and drops a file into the system's upload interface and clicks the upload button.

[1191] Output: The scene data is sent over the internet to the server. Progress is displayed and a notification is displayed when the upload is complete.

[1192] Step 3:

[1193] The server receives and stores the scene data.

[1194] Input: Scene data submitted by the user.

[1195] Operation: The server saves the received scene data in the specified directory. For example, it saves it as " / tmp / battlescene.mp4".

[1196] Output: Scene data is saved in a temporary folder on the server.

[1197] Step 4:

[1198] The server starts scene analysis

[1199] Input: Scene data saved in step 3.

[1200] Operation: The server initializes the generative AI model and inputs the saved scene data into the model. Video frames are extracted and preprocessed.

[1201] Output: The scene data is ready for analysis and key features are extracted.

[1202] Step 5:

[1203] The server recognizes the scene

[1204] Input: Scene data parsed by a generative AI model.

[1205] How it works: The generative AI model identifies key features in the scene data and assigns them specific tags (e.g., sword, magic).

[1206] Output: Recognized scene tags are generated.

[1207] Step 6:

[1208] The server generates the sound effects

[1209] Input: Scene tags recognized in step 5.

[1210] How it works: The server uses a generative AI model to generate appropriate sound effects based on the tag. For example, if the tag "sword" is recognized, the server inputs a prompt to the generative AI model saying, "I would like you to generate sound effects for a sword-swinging battle scene."

[1211] Output: The generated sound effect file is created.

[1212] Step 7:

[1213] The server stores the sound effect files.

[1214] Input: The sound effect file generated in step 6.

[1215] Behavior: The server saves the generated sound effect file in the specified directory, for example, as " / audio / sword-swinging-sound.wav". It also performs a checksum check.

[1216] Output: The sound effect file has been saved.

[1217] Step 8:

[1218] The server generates the download link

[1219] Input: The path to the saved sound effect file.

[1220] How it works: The server generates a link based on the path of the saved sound effect file so that the user can easily download it. For example, it generates a link like "https: / / server.com / download / swordswingingsound.wav".

[1221] Output: A download link will be generated.

[1222] Step 9:

[1223] The server provides the download link to the user.

[1224] Input: The download link generated in step 8.

[1225] How it works: The server provides the generated download link to the user, and notification can be via email, chat system, or in-system notification.

[1226] Output: The user receives a link that they can click to download the sound effect.

[1227] (Application example 1)

[1228] 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."

[1229] The present invention relates to a system that analyzes scene data and generates sound effects appropriate for a specific scene. Its purpose is to provide a realistic entertainment experience by analyzing scenes in real time using a smart device and instantly reproducing sound effects. However, conventional technologies require specialized knowledge and expensive equipment, making them too costly and time-consuming for general consumers.

[1230] 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.

[1231] In this invention, the server includes means for inputting scene data, means for receiving and saving the scene data, means for analyzing the scene data and recognizing specific scenes, means for generating appropriate sound effects based on the recognized scenes, means for saving and providing the generated sound effects, means for acquiring video in real time from a camera of a smart device and uploading the scene data, and means for playing the generated sound effects on a speaker of the smart device. This allows even general consumers to easily generate high-quality sound effects in real time and enjoy a realistic entertainment experience.

[1232] "Scene data" refers to visual information such as images and videos, and is data used to recognize specific scenes by analyzing this information.

[1233] "Means for inputting scene data" refers to a device or interface that allows a user to provide scene data such as images or videos to the system.

[1234] The "means for receiving and storing the scene data" refers to a device or software for transferring the input scene data to a server and storing it temporarily or permanently.

[1235] "Means for analyzing the scene data and recognizing a particular scene" refers to an algorithm or program for detecting and identifying a particular event or action within the scene data.

[1236] The "means for generating appropriate sound effects based on the recognized scene" refers to an algorithm or program for generating optimal sound effects according to a specific scene label or tag.

[1237] The "means for storing and providing the generated sound effects" refers to a system or device for storing the generated sound effect files and providing them so that users can download or play them.

[1238] "Means for acquiring video in real time from a smart device camera and uploading scene data" refers to a device or program that uses a camera such as smart glasses or a smartphone to capture video in real time and transmits the data to a server.

[1239] "Means for playing the generated sound effect on a speaker of the smart device" refers to a device for playing the generated sound effect using a speaker of smart glasses, a smartphone, or the like.

[1240] The present invention relates to a system for inputting scene data, analyzing it, and generating appropriate sound effects. This system aims to provide a realistic entertainment experience by analyzing scenes in real time using a smart device and instantly reproducing sound effects.

[1241] System configuration

[1242] A user wears a smart device (e.g., smart glasses) and captures scene data in real time. The scene data is captured as video and uploaded to a server. The server receives the uploaded scene data, analyzes it, and recognizes specific scenes. A generative AI model then generates sound effects based on the recognized scene, which are instantly played on the smart device's speaker. Each part of the system is described in detail below.

[1243] Data upload

[1244] 1. The smart device captures the scene data.

[1245] A user wears a smart device (e.g., smart glasses), and the device's camera captures video in real time. For example, the smart glasses camera takes pictures while the user is walking around a store.

[1246] 2. The smart device uploads the scene data to the server.

[1247] The captured video data is uploaded from the smart device to a server in real time.

[1248] Receiving and saving scene data

[1249] 3. The server receives the scene data.

[1250] The server receives the video data sent from the user's smart device and temporarily stores it in a data storage. For example, the video data is continuously received.

[1251] Scene Analysis and Recognition

[1252] 4. The server starts analyzing the scene

[1253] The server uses the generative AI model to analyze the uploaded video data, extracting scene features and identifying specific scenes (e.g., product shelves, product displays, etc.).

[1254] 5. The server recognizes the scene

[1255] The generative AI model recognizes specific actions and events in the scene data and assigns scene tags (e.g., product descriptions, sale information, etc.) based on them.

[1256] Sound effect generation and provision

[1257] 6. The server generates the sound effects

[1258] The server automatically generates optimal sound effects using a generative AI model based on the recognized scene tags, such as product explanations or sales information.

[1259] 7. Smart devices play sound effects

[1260] The generated sound effects are played in real time through the smart device's speaker, allowing users to enjoy a realistic audio guide.

[1261] Specific examples

[1262] For example, if a user is walking around taking pictures of product shelves in a virtual store, the process will be as follows:

[1263] 1. The user wears smart glasses, and the camera captures real-time images of the product shelves.

[1264] 2. The smart device uploads the video data to the server.

[1265] 3. The server receives the video data, analyzes it, and recognizes the product shelf scene.

[1266] 4. The server generates a voice description of the product based on the recognized scene.

[1267] 5. The smart device will play the generated audio in real time, allowing the user to listen to the product description.

[1268] Prompt Sentence Examples

[1269] "Analyze this image (or video) and generate the appropriate sound effect."

[1270] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1271] System processing steps

[1272] Step 1:

[1273] The camera on the smart device captures the footage in real time.

[1274] Input: Video captured in real time by a smart device (e.g., smart glasses).

[1275] Processing: The smart device continuously captures the scene around the user.

[1276] Output: Captured video data.

[1277] Step 2:

[1278] The captured video data is uploaded to the server.

[1279] Input: Captured real-time video data.

[1280] Processing: The video data acquired by the smart device is compressed and encoded, and then uploaded to the server via the network.

[1281] Output: Video data sent to the server.

[1282] Step 3:

[1283] The server receives the video data and stores it in data storage.

[1284] Input: Video data sent from smart device.

[1285] Processing: The server receives the video data through the network and stores it in the appropriate format in the data storage.

[1286] Output: Saved video data.

[1287] Step 4:

[1288] The server uses a generative AI model to analyze the video data and recognize specific scenes.

[1289] Input: Stored video data.

[1290] Processing: The server uses the generated AI model and the prompt "Analyze this image (or video) and generate appropriate sound effects." to analyze the scene characteristics in the video data and identify specific scene labels and tags.

[1291] Output: Recognized scene tags (e.g. product descriptions, sale information, etc.).

[1292] Step 5:

[1293] The server generates sound effects using a generative AI model based on the recognized scene tags.

[1294] Input: Recognized scene tags.

[1295] Processing: The generative AI model generates appropriate sound effects corresponding to the scene tags, synthesizing the sounds based on pre-trained data.

[1296] Output: The generated sound effect file.

[1297] Step 6:

[1298] The server sends the generated sound effect file to the smart device.

[1299] Input: The generated sound effect file.

[1300] Processing: The server sends the path and data of the sound effect file to the smart device, where the sound effect file is encoded in the appropriate format.

[1301] Output: Sound effect data sent to smart device.

[1302] Step 7:

[1303] The smart device plays a sound effect.

[1304] Input: Sound effect data sent from the server.

[1305] Processing: The smart device decodes the received sound effect data and plays it through the built-in speaker.

[1306] Output: The sound effect that the user can hear.

[1307] 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.

[1308] The present invention is a system that inputs scene data, analyzes it, and generates appropriate sound effects, and also includes a function that recognizes the user's emotions and adjusts the sound effects based on those emotions. This system aims to provide a more realistic and emotional experience in entertainment content.

[1309] System configuration

[1310] The user provides scene data (image or video data) and uploads the data from their device to the server. The server receives the uploaded scene data, analyzes it, and recognizes specific scenes. An AI model then generates sound effects based on the recognized scene and provides them to the user. The system also incorporates an emotion engine that recognizes the user's emotions and adjusts the generated sound effects based on the user's emotions. Each part of the system is described in detail below.

[1311] Data upload

[1312] 1. The user selects scene data

[1313] The user uses the file browser on the device to select image data or video data of the scene for which they want to generate sound effects. For example, the user can select a video file called "Battle Scene.mp4."

[1314] 2. The user uploads the scene data.

[1315] The user sends the selected scene data to the server via an upload interface from the terminal to the system.

[1316] Receiving and saving scene data

[1317] 3. The server receives the scene data.

[1318] The server receives the scene data sent by the user and saves it in the data storage. For example, it saves "BattleScene.mp4" in the specified directory.

[1319] Scene Analysis and Recognition

[1320] 4. The server starts analyzing the scene

[1321] The server starts analyzing the uploaded scene data using the generative AI model. In this step, it extracts scene features.

[1322] 5. The server recognizes the scene

[1323] The generative AI model recognizes specific scenes within the scene data and assigns scene tags (e.g., sword, magic, explosion, etc.) accordingly.

[1324] User Emotion Recognition

[1325] 1. Obtain user emotion data

[1326] The device sends the user's voice data or facial expression data to the emotion engine, which analyzes it and recognizes the user's emotions.

[1327] 2. Analyze user sentiment

[1328] The server uses an emotion engine to analyze the user's emotion, and the analyzed emotion data corresponds to the scene tag.

[1329] Sound effect generation and adjustment

[1330] 1. The server generates the sound effects

[1331] The server automatically generates appropriate sound effects using a generative AI model based on the recognized scene tags, such as the sound of a sword swing or magic.

[1332] 2. The server adjusts the sound effects

[1333] The server adjusts the generated sound effects based on the user's emotions. For example, if the user is nervous, the server increases the volume of the sound effects or speeds up the tempo.

[1334] Saving and providing sound effects

[1335] 1. The server saves the sound effect files

[1336] Save the generated sound effects as audio files and record the path to save them. For example, save "sword swinging sound.wav" and "magic sound.wav" in the appropriate directory.

[1337] 2. The server generates a download link

[1338] Based on the path of the saved sound effect file, a link is generated that allows the user to easily download it. This link is generated individually for each user and managed together with authentication information.

[1339] Download sound effects

[1340] 1. The server provides the download link to the user.

[1341] The server provides the user with a download link for the generated sound effect, which is sent to the user via email or a web portal.

[1342] 2. The user downloads the sound effect

[1343] The user clicks on the provided download link to download the generated sound effect to their device, and the downloaded file can be applied to the user's entertainment content.

[1344] Specific examples

[1345] For example, if a user wants to generate sound effects to be used in a battle scene in a game, the process would be as follows:

[1346] 1. The user uploads a video of a battle scene, "BattleScene.mp4," from their device to the server.

[1347] 2. The server receives the video and stores it in the system.

[1348] 3. The server analyzes the video and recognizes scenes where swords are swung or magic is cast.

[1349] 4. The emotion engine analyzes the user's voice and facial expression data to recognize emotions such as tension and excitement.

[1350] 5. The server generates sword swinging and magic sound effects based on the recognized scene.

[1351] 6. The server adjusts the generated sound effects based on the user's emotions.

[1352] 7. The server saves the generated sound effect file and provides a download link to the user.

[1353] 8. The user clicks on the link to download the generated sound effect and apply it to the game.

[1354] The above is a detailed description of an embodiment of the present invention. This system makes it possible to generate high-quality sound effects and sound effects corresponding to emotions simply and at low cost, without requiring specialized knowledge or expensive equipment.

[1355] The processing flow will be explained below.

[1356] Step 1:

[1357] The user uses the file browser on the device to select image data or video data of the scene for which they want to generate sound effects. For example, the user selects a video file called "Battle Scene.mp4."

[1358] Step 2:

[1359] The user sends the selected scene data from the terminal to the server via the upload interface of the system.

[1360] Step 3:

[1361] The server receives the scene data sent by the user and saves it in the data storage. For example, it saves "BattleScene.mp4" in the specified directory.

[1362] Step 4:

[1363] The server then inputs the saved file into the generative AI model to begin analyzing the scene data, extracting the features of the scene data during this process.

[1364] Step 5:

[1365] The server uses the generated AI model to recognize specific scenes within the scene data, such as a sword swing or a magic cast, and assigns a scene tag.

[1366] Step 6:

[1367] The device sends the user's voice data or facial expression data to the emotion engine, which analyzes it and recognizes the user's emotions.

[1368] Step 7:

[1369] The server uses an emotion engine to analyze the voice and facial expression data to identify the user's emotions, such as nervousness, excitement, and joy.

[1370] Step 8:

[1371] The server automatically generates appropriate sound effects using a generative AI model based on the recognized scene tags and user emotion data, such as the sound of a sword swing or magic.

[1372] Step 9:

[1373] The server adjusts the generated sound effects based on the user's emotions. For example, if the user is excited, the server may increase the volume of the sound effects or speed up the tempo.

[1374] Step 10:

[1375] The server saves the generated sound effects as audio files, and records the path of each audio file to provide to the user.

[1376] Step 11:

[1377] The server generates a link based on the path of the saved sound effect file, which the user can use to easily download it. This link is generated for each user and managed together with their authentication information.

[1378] Step 12:

[1379] The server provides the user with a download link for the generated sound effect, which is sent to the user via email or a web portal.

[1380] Step 13:

[1381] The user clicks on the provided download link to download the generated sound effect to their device, and the downloaded file can be applied to the user's entertainment content.

[1382] The above is the specific processing flow of this system. Taking into account the details of the operation at each step, sound effects are generated efficiently and with high quality, and sound effects can be flexibly adjusted according to the user's emotions.

[1383] Example 2

[1384] 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."

[1385] Conventional sound effect generation systems for entertainment content mainly generate simple sound effects based on scene data, making it difficult to provide high-quality sound effects that reflect the user's emotions. For this reason, there has been a demand for systems that can appropriately adjust sound effects based on the user's actual emotions to provide a more realistic entertainment experience.

[1386] 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.

[1387] In this invention, the server includes means for inputting scene data, means for receiving and saving the scene data, means for analyzing the scene data and recognizing a specific scene, means for acquiring user emotion data, means for analyzing the user emotion data, means for generating appropriate sound effects using a generative AI model based on the recognized scene and the user emotion data, means for adjusting the generated sound effects based on the user emotion data, and means for saving and providing the generated and adjusted sound effects. This makes it possible to generate and provide high-quality sound effects that reflect the user's emotions.

[1388] "Scene data" is data that is provided in the form of image data or video data and is the subject of sound effect generation.

[1389] The "receiving and storing means" is a means for transmitting scene data to the server and storing the data in the data storage.

[1390] The "analysis means" is a means for extracting the characteristics of the scene data and recognizing a particular scene based on the extracted characteristics.

[1391] "Emotion data" is data that indicates the emotional state of the user, and is acquired based on the user's facial expressions, voice, and the like.

[1392] A "generative AI model" is a model that uses artificial intelligence technology to generate sound effects based on recognized scene and user emotional data.

[1393] The "adjustment means" is a means for changing and optimizing the generated sound effect based on the user's emotional data.

[1394] The "storing and providing means" refers to a means for storing the generated and adjusted sound effect files in a data storage and providing the files so that the users can download them.

[1395] The present invention is a system that inputs scene data, analyzes it, and generates appropriate sound effects, and also includes a function that recognizes the user's emotions and adjusts the sound effects based on those emotions. This system aims to provide a more realistic and emotional experience in entertainment content.

[1396] System configuration

[1397] First, the user provides scene data (image or video data) and uploads the data from the device to the server. Specifically, the user uses the device's file browser to select the video file of the scene for which they want to generate sound effects (e.g., "battle scene.mp4") and then sends it to the server via the upload interface.

[1398] The server receives the scene data and saves it in the data storage. For example, it saves "battlescene.mp4" in the specified directory (e.g., / storage / uploads / battlescene.mp4).

[1399] Next, the server uses the generative AI model to begin analyzing the uploaded scene data. In this step, it extracts scene features and recognizes specific scenes. Specifically, it breaks down the scene data into frames, extracts the features of each frame, and assigns tags such as "sword swinging scene" or "magic casting scene."

[1400] In parallel, the device collects the user's voice and facial expression data using a built-in camera and microphone, and sends them to the emotion engine. The server uses the emotion engine to analyze the user's emotions. For example, it can analyze whether the user is nervous or excited from the voice data.

[1401] The server uses a generative AI model to generate appropriate sound effects based on the recognized scene tags and analyzed emotional data. For example, for a sword-swinging scene, it generates a "sword-swinging sound.wav" file. It also adjusts the sound effects based on the user's emotional data. For example, if the user is nervous, it will increase the volume of the sound effects or speed up the tempo.

[1402] The generated sound effect files are saved in data storage, and the path to the saved location is recorded. For example, "sword swinging sound.wav" and "magic sound.wav" are stored in the save directory. Based on the path of the saved sound effect file, the server generates a link that users can easily download and provides it to them via email or a web portal.

[1403] The user clicks on the provided download link to download the generated sound effect to their device, and the downloaded file is applied to the user's entertainment content.

[1404] Examples and prompts

[1405] For example, if a user wants to generate sound effects to be used in a battle scene in a game, the process would be as follows:

[1406] 1. The user selects "BattleScene.mp4" on the device and clicks the upload button to send it to the server.

[1407] 2. The server receives the scene data and saves it to / storage / uploads / battlescene.mp4.

[1408] 3. The server begins analyzing the video, extracting features from each frame and recognizing tags such as "swinging a sword" and "casting magic."

[1409] 4. The device captures the user's facial expressions and voice data and sends it to the emotion engine.

[1410] 5. The server uses an emotion engine to analyze the user's emotions and detect, for example, "tension."

[1411] 6. The server generates an appropriate sound effect (e.g., "sword swinging sound.wav") and adjusts the volume based on the user's emotional data.

[1412] 7. The server saves the generated sound effect to / storage / sounds / swordswingingsound.wav and generates a download link.

[1413] 8. The server emails the generated link to the user.

[1414] 9. The user clicks on the link in the email, downloads the "Sword Swinging Sound.wav" file, and applies it to the game.

[1415] Prompt Sentence Examples

[1416] "Users can upload videos of battle scenes, and the app will generate sound effects that match the recognized scenes from the video. The app will also adjust the sound effects based on the user's emotions, and provide a download link."

[1417] The above is a specific embodiment of the invention, which makes it possible to generate high-quality sound effects and sound effects that correspond to emotions easily and at low cost without requiring specialized knowledge or expensive equipment.

[1418] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1419] System program processing flow

[1420] Step 1:

[1421] Selecting scene data

[1422] Input: The user uses the device's file browser to select image or video data for the scene for which they want to generate sound effects.

[1423] Specific behavior: The user clicks the "Choose File" button and selects "BattleScene.mp4" from the file dialog.

[1424] Output: The selected scene data file path is obtained.

[1425] Step 2:

[1426] Uploading scene data

[1427] Input: User selected scene data file path.

[1428] Specific operation: The user clicks the "Upload" button through the upload interface of the terminal, and the selected scene data is sent to the server as an HTTP request.

[1429] Output: Scene data is uploaded to the server.

[1430] Step 3:

[1431] Receiving and saving scene data

[1432] Input: The server receives the scene data as an HTTP request.

[1433] Specific operation: The server saves the received scene data to data storage, for example, / storage / uploads / battlescene.mp4.

[1434] Output: The scene data is saved to the specified directory.

[1435] Step 4:

[1436] Starting Scene Analysis

[1437] Input: Saved scene data file path.

[1438] Specific operation: The server uses the generative AI model to begin analyzing the uploaded scene data, breaking it down into frames and extracting the features of each frame.

[1439] Output: Feature data for each frame.

[1440] Step 5:

[1441] Scene Recognition

[1442] Input: Extracted frame-by-frame feature data.

[1443] Specific actions: The generative AI model analyzes feature data and recognizes specific scenes. Each scene is tagged with a tag such as "swinging a sword" or "casting magic."

[1444] Output: Tagged scene data.

[1445] Step 6:

[1446] Acquiring emotion data

[1447] Input: User's facial expression data and voice data.

[1448] Specific operation: The device uses the built-in camera and microphone to capture the user's facial expressions and voice data and transmits them to the emotion engine.

[1449] Output: Captured facial expression and voice data of the user.

[1450] Step 7:

[1451] Emotion Analysis

[1452] Input: Captured user facial expression and voice data.

[1453] Specific operation: The server uses the emotion engine to analyze the user's emotions. For example, emotions such as "tension" or "excitement" are determined from voice and facial expressions.

[1454] Output: Parsed user emotion data.

[1455] Step 8:

[1456] Sound effect generation

[1457] Input: Tagged scene data and parsed user emotion data.

[1458] How it works: The server uses the generative AI model to generate appropriate sound effects based on the recognized scene tags, for example, generating "sword swinging sound.wav" for a sword swinging scene.

[1459] Output: The generated sound effect file.

[1460] Step 9:

[1461] Sound effect adjustments

[1462] Input: Generated sound effect files and analyzed user emotion data.

[1463] Specific operation: The server adjusts the volume and tempo of the generated sound effects based on the user's emotional data. For example, if the user is nervous, the volume of the sound effects is increased.

[1464] Output: Adjusted sound effect file.

[1465] Step 10:

[1466] Saving sound effect files

[1467] Input: The adjusted sound effect file.

[1468] Specific operation: The server saves the adjusted sound effect file to data storage and records the path to save it, for example, / storage / sounds / swordswingingsound.wav.

[1469] Output: The path of the saved sound effect file.

[1470] Step 11:

[1471] Generate a download link

[1472] Input: The path to the saved sound effect file.

[1473] Specific operation: The server generates a link based on the path of the saved sound effect file, allowing the user to easily download it.

[1474] Output: The generated download link.

[1475] Step 12:

[1476] Providing a download link

[1477] Input: The generated download link.

[1478] What happens: The server provides the generated download link to the user, which can be provided via email or a web portal.

[1479] Output: The download link provided to the user.

[1480] Step 13:

[1481] Download sound effects

[1482] Input: The download link provided by the server.

[1483] Specific operation: The user clicks on the provided download link and the generated sound effect is downloaded to the device.

[1484] Output: Downloaded sound effect file.

[1485] The above are the specific processing steps of the program of this system.

[1486] (Application example 2)

[1487] 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."

[1488] In conventional entertainment content, sound effects are mostly preset, making it difficult to generate and adjust appropriate sound effects in real time according to the viewer's emotions. This has required more complex systems and a large number of human resources to improve the quality of the user experience. Therefore, there is a demand for a system that can generate and adjust sound effects in real time according to the user's emotions.

[1489] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1490] In this invention, the server includes means for inputting scene data, means for receiving and saving the scene data, means for analyzing the scene data and recognizing a specific scene, means for generating appropriate sound effects based on the recognized scene, means for acquiring and analyzing user emotion data, means for adjusting the generated sound effects based on the acquired and analyzed emotion data, and means for saving and providing the generated and adjusted sound effects, thereby making it possible to generate and adjust appropriate sound effects in real time based on the user's emotions.

[1491] "Scene data" refers to visual information expressed as image data or video data.

[1492] The "means for inputting scene data" refers to an interface or device that allows a user to provide scene data to the system.

[1493] The "means for receiving and saving scene data" refers to a mechanism for uploading scene data to a server and saving the data in storage.

[1494] The "means for analyzing scene data and recognizing a specific scene" refers to an analysis algorithm or software used to analyze the scene data and identify a specific scene therein.

[1495] "Means for generating appropriate sound effects" refers to generative AI models or sound generation software for generating sound effects based on a recognized scene.

[1496] "Means for acquiring and analyzing user emotional data" refers to software or equipment for acquiring the user's facial expressions and voice data, analyzing them, and recognizing the user's emotional state.

[1497] "Means for adjusting sound effects generated based on acquired and analyzed emotional data" refers to algorithms or software for adjusting the volume, tempo, tone, etc. of generated sound effects based on acquired and analyzed emotional data of the user.

[1498] The "means for storing and providing the generated and adjusted sound effects" refers to a mechanism for storing the finally generated sound effects and providing them so that the user can download or play them.

[1499] The present invention is a system that inputs and analyzes scene data and generates sound effects using a generative AI model based on the input data. It also has the ability to acquire and analyze user emotion data and adjust the generated sound effects based on the emotion. This invention is particularly intended for application in content distribution services.

[1500] System configuration

[1501] Data upload

[1502] 1. Input of scene data: The user inputs scene data (image data or video data) into the system by selecting the data using a file browser on their smartphone or PC and uploading it to the system.

[1503] 2. Receiving and storing scene data: The server receives the scene data uploaded by the user and stores it in data storage. This storage is done using a common cloud storage service (e.g., Amazon S3).

[1504] Scene analysis and sound effect generation

[1505] 3. Scene data analysis: The server analyzes specific scenes in the scene data using image recognition and video analysis libraries (e.g., TensorFlow, OpenCV).

[1506] 4. Sound Effect Generation: The server uses a generative AI model (e.g. WaveNet, JukeBox) to generate sound effects appropriate for a specific scene, using pre-trained AI models.

[1507] User Emotion Recognition

[1508] 5. Acquisition of emotion data: The user's device (smartphone or PC with webcam) acquires the user's voice data or facial expression data, and sends this data to the server in real time.

[1509] 6. Emotion data analysis: The server uses an emotion analysis AI engine (e.g., Microsoft Azure Face API) to analyze the acquired user emotion data and save the results.

[1510] Adjusting and providing sound effects

[1511] 7. Sound effect adjustment: The server adjusts the volume, tempo, and tone of the generated sound effects based on the recognized user emotion data. This adjustment is performed using algorithms (e.g., audio signal processing algorithms).

[1512] 8. Saving and providing sound effects: The adjusted sound effects will be saved again and a link will be generated for users to easily download them. The link will be provided via email or web portal.

[1513] Specific examples

[1514] For example, consider the case where a user uploads a video of a fight scene, "fightscene.mp4," to the system. In this case, the following process occurs:

[1515] 1. The user uploads "Battle Scene.mp4".

[1516] 2. The server receives the video and stores it in data storage.

[1517] 3. The server analyzes the video and recognizes scenes where swords are swung or magic is cast.

[1518] 4. Acquire the user's voice or facial expression data in real time and perform emotion analysis.

[1519] 5. The server generates sword swinging and magic sound effects based on the recognized scene.

[1520] 6. The server adjusts the volume and tempo of the sound effects based on the user's emotional data.

[1521] 7. Save the adjusted sound effect and generate a download link for the user.

[1522] 8. The user obtains the sound effect via the download link and applies it to their content.

[1523] Prompt Sentence Examples

[1524] For example, here's a sample prompt for a generative AI model to generate a sound effect:

[1525] "Please provide an example of how to adjust sound effects programmatically. For example, please implement a method in Python to change the volume of a sound depending on the user's emotions."

[1526] As described above, the system of the present invention is capable of generating and adjusting appropriate sound effects in real time based on the user's emotions, thereby improving the quality of the user's experience with entertainment content.

[1527] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1528] Step 1:

[1529] User enters scene data

[1530] The user selects scene data (image data or video data) from the terminal and uploads it to the system.

[1531] Input: A scene data file selected by the user (e.g. "BattleScene.mp4").

[1532] How it works: The user selects a file using the device's file browser and sends it to the server through the system's upload interface.

[1533] Output: The server receives the scene data.

[1534] Step 2:

[1535] The server receives and stores the scene data

[1536] The server receives the scene data sent by the user and stores it in a data storage.

[1537] Input: Scene data submitted by the user.

[1538] What it does: The server saves the file to a data storage (e.g. Amazon S3) and records the directory path where it was saved.

[1539] Output: The file path of the saved scene data.

[1540] Step 3:

[1541] The server analyzes the scene data and recognizes the specific scene.

[1542] The server analyzes the received scene data and performs scene analysis to recognize specific scenes.

[1543] Input: The file path of the saved scene data.

[1544] How it works: The server uses a scene analysis library (e.g. TensorFlow, OpenCV) to parse the scene data frame by frame and extract specific scene tags (e.g. sword, explosion, magic).

[1545] Output: Extracted scene tags.

[1546] Step 4:

[1547] Server generates sound effects

[1548] Based on the recognized scene tags, the server generates appropriate sound effects using a generative AI model.

[1549] Input: Extracted scene tags.

[1550] How it works: The server inputs the scene tag as a prompt into a generative AI model (e.g. WaveNet, JukeBox) and generates the corresponding sound effect.

[1551] Output: The generated sound effect file.

[1552] Step 5:

[1553] The device acquires the user's emotional data

[1554] The terminal acquires the user's voice data or facial expression data and transmits it to the server.

[1555] Input: User's voice or facial expression data.

[1556] How it works: The device uses a microphone and camera to capture the user's voice and facial expression data in real time and transmits it to a server.

[1557] Output: Emotion data sent to the server.

[1558] Step 6:

[1559] The server analyzes the emotional data

[1560] The server analyzes the acquired emotion data and recognizes the user's emotional state.

[1561] Input: Emotion data sent to the server.

[1562] How it works: The server uses an emotion analysis AI engine (e.g., Microsoft Azure Face API) to analyze the emotion data and determine the user's emotional state (e.g., nervous, excited, relaxed).

[1563] Output: User's emotional state data.

[1564] Step 7:

[1565] Adjusted server-generated sound effects

[1566] The server adjusts the generated sound effects based on the recognized emotional state data of the user.

[1567] Input: Generated sound effect files and user emotional state data.

[1568] How it works: The server uses audio signal processing algorithms to adjust the volume, tempo, and tone of sound effects based on the user's emotions.

[1569] Output: Adjusted sound effect file.

[1570] Step 8:

[1571] The server stores and provides the adjusted sound effects.

[1572] The server stores the adjusted sound effects and generates a link for users to download them.

[1573] Input: The adjusted sound effect file.

[1574] How it works: The server saves the adjusted sound effect file to data storage and generates a download link to provide to the user. The link is provided to the user via email or a web portal.

[1575] Output: A download link to the user.

[1576] The above are the specific processing steps of the system that realizes the application example. In this way, it becomes possible to generate and adjust appropriate sound effects in real time based on the user's emotions.

[1577] 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.

[1578] 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.

[1579] 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.

[1580] [Fourth embodiment]

[1581] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1582] 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.

[1583] 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).

[1584] 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.

[1585] 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.

[1586] 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).

[1587] 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.

[1588] 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.

[1589] 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.

[1590] 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.

[1591] 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.

[1592] 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.

[1593] 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."

[1594] The present invention relates to a system for inputting scene data, analyzing the data, and generating appropriate sound effects. This system is intended to generate sound effects to provide a realistic experience, primarily in entertainment content.

[1595] System configuration

[1596] The user provides scene data (image or video data) and uploads the data from their device to the server. The server receives the uploaded scene data, analyzes it, and recognizes specific scenes. The AI ​​model then generates sound effects based on the recognized scene and provides them to the user. Each part of the system is described in detail below.

[1597] Data upload

[1598] 1. The user selects scene data

[1599] The user uses the file browser on the device to select image data or video data of the scene for which they want to generate sound effects. For example, the user can select a video file called "Battle Scene.mp4."

[1600] 2. The user uploads the scene data.

[1601] The user sends the selected scene data to the server via an upload interface from the terminal to the system.

[1602] Receiving and saving scene data

[1603] 3. The server receives the scene data.

[1604] The server receives the scene data sent by the user and saves it in the data storage. For example, it saves "BattleScene.mp4" in the specified directory.

[1605] Scene Analysis and Recognition

[1606] 4. The server starts analyzing the scene

[1607] The server begins analyzing the uploaded scene data using the generative AI model. In this step, it extracts scene features and identifies specific scenes (e.g., sword swinging scenes, magic casting scenes, etc.).

[1608] 5. The server recognizes the scene

[1609] The generative AI model recognizes specific actions and events in the scene data and assigns scene tags (e.g., sword, magic, explosion, etc.) accordingly.

[1610] Sound effect generation and provision

[1611] 6. The server generates the sound effects

[1612] The server automatically generates optimal sound effects using a generative AI model based on the recognized scene tags, such as the sound of a sword swing or magic.

[1613] 7. The server saves the sound effect files

[1614] Save the generated sound effects as audio files and record the path to save them. For example, save "sword swinging sound.wav" and "magic sound.wav" in the appropriate directory.

[1615] 8. The server generates the download link

[1616] Based on the path of the saved sound effect file, a link is generated that allows the user to easily download it.

[1617] Download sound effects

[1618] 9. The server provides the download link to the user

[1619] The server provides the user with a download link for the generated sound effect, and the user can download the generated sound effect to their device by clicking the provided link.

[1620] Specific examples

[1621] For example, if a user wants to generate sound effects to be used in a battle scene in a game, the process would be as follows:

[1622] 1. The user uploads a video of a battle scene, "BattleScene.mp4," from their device to the server.

[1623] 2. The server receives the video and stores it in the system.

[1624] 3. The server analyzes the video and recognizes scenes where swords are swung or magic is cast.

[1625] 4. The server generates sword swinging and magic sound effects based on the recognized scene.

[1626] 5. The server saves the generated sound effect file and provides a download link to the user.

[1627] 6. The user clicks on the link to download the generated sound effect and apply it to the game.

[1628] The above is a detailed description of the embodiment of the present invention. This system makes it possible to generate high-quality sound effects simply and at low cost without requiring specialized knowledge or expensive equipment.

[1629] The processing flow will be explained below.

[1630] Step 1:

[1631] The user uses the file browser on the device to select image data or video data of the scene for which they want to generate sound effects. For example, the user selects a video file called "Battle Scene.mp4."

[1632] Step 2:

[1633] The user sends the selected scene data from the terminal to the server via the system's upload interface. The uploaded file is saved in the specified directory on the server.

[1634] Step 3:

[1635] The server receives the scene data sent by the user and saves it in the data storage. The path of the saved file is recorded and used for subsequent processing.

[1636] Step 4:

[1637] The server inputs the saved file into the generative AI model to begin analyzing the scene data. During this process, the server extracts features from the scene data.

[1638] Step 5:

[1639] The server uses the generated AI model to recognize specific scenes within the scene data, such as a sword swing or a magic cast, and assigns a scene tag to the recognized scene.

[1640] Step 6:

[1641] The server automatically generates appropriate sound effects using a generative AI model based on the recognized scene tags. The generated sound effects correspond to the scene tags, such as "sword swinging sounds" or "magic sounds."

[1642] Step 7:

[1643] The server saves the generated sound effects as audio files, and records the path of each audio file to provide to the user.

[1644] Step 8:

[1645] The server generates a link based on the path of the saved sound effect file, which the user can use to easily download it. This link is generated for each user and managed together with their authentication information.

[1646] Step 9:

[1647] The server provides the user with a download link for the generated sound effect, which is sent to the user via email or a web portal.

[1648] Step 10:

[1649] The user clicks on the provided download link to download the generated sound effect to their device, and the downloaded file can be applied to the user's entertainment content.

[1650] This is the specific flow of processing in this system. Taking into account the details of the operations at each step, we aim to generate sound effects efficiently and with high quality.

[1651] Example 1

[1652] 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."

[1653] Conventional systems have the problem that they require specialized knowledge and expensive equipment to generate high-quality sound effects for entertainment content. Furthermore, manually creating appropriate sound effects for each scene takes a great deal of time and effort, so there is a demand for a system that can generate sound effects simply and efficiently.

[1654] 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.

[1655] In this invention, the server includes means for a user to select scene data, means for a user to upload scene data, means for the server to receive and store the scene data, means for the server to analyze the scene data using a generative AI model and recognize a specific scene, means for the server to generate sound effects using the generative AI model based on the recognized scene, and means for storing and providing the generated sound effect files. This makes it possible to generate high-quality sound effects easily and at low cost without requiring specialized knowledge or expensive equipment.

[1656] The "means for the user to select scene data" refers to an interface that allows the user to select image or video data for which sound effects are to be generated via a file browser on the terminal or the like.

[1657] The "means for the user to upload scene data" refers to an interface that provides a function for the user to send scene data selected by the user to a server via the Internet.

[1658] "Means for the server to receive and store scene data" refers to software or hardware that has the function of allowing the server to receive scene data sent by a user and store it for a certain period of time or in a certain directory.

[1659] "Means for the server to analyze scene data using a generative AI model and recognize specific scenes" refers to the process by which the server utilizes a machine learning model (generative AI model) to analyze received scene data and identify specific features or events.

[1660] "Means for the server to generate sound effects using a generative AI model based on the recognized scene" refers to algorithms or software that enable the generative AI model to automatically generate appropriate sound effects based on the results of scene recognition.

[1661] "Means for storing and providing generated sound effect files" refers to the function of storing sound effect files generated by a generative AI model on a server and providing a link or interface that allows users to easily download or use the files.

[1662] The present invention relates to a system for inputting scene data, analyzing the data, and generating appropriate sound effects. This system is primarily intended to generate sound effects to provide a realistic experience in entertainment content.

[1663] System configuration

[1664] The user provides scene data (image or video data) and uploads the data from their device to the server. The server receives the uploaded scene data, analyzes it, and recognizes specific scenes. Then, a generative AI model generates sound effects based on the recognized scene and provides them to the user. Each part of the system is described in detail below.

[1665] Data upload

[1666] The user selects scene data

[1667] The user uses the file browser on the device to select image data or video data of the scene for which they want to generate sound effects. For example, the user can select a video file called "Battle Scene.mp4."

[1668] The user uploads scene data

[1669] The user sends the selected scene data to the server via an upload interface from the terminal to the system.

[1670] Receiving and saving scene data

[1671] The server receives the scene data

[1672] The server receives the scene data sent by the user and saves it in the data storage. For example, it saves "BattleScene.mp4" in the specified directory.

[1673] Scene Analysis and Recognition

[1674] The server starts scene analysis

[1675] The server begins analyzing the uploaded scene data using the generative AI model. In this step, it extracts scene features and identifies specific scenes (e.g., sword swinging scenes, magic casting scenes, etc.).

[1676] The server recognizes the scene

[1677] The generative AI model recognizes specific actions and events in the scene data and assigns scene tags (e.g., sword, magic, explosion, etc.) accordingly.

[1678] Sound effect generation and provision

[1679] The server generates the sound effects

[1680] The server automatically generates optimal sound effects using a generative AI model based on the recognized scene tags, such as the sound of a sword swing or magic.

[1681] The server stores the sound effect files.

[1682] Save the generated sound effects as audio files and record the path to save them. For example, save "sword swinging sound.wav" and "magic sound.wav" in the appropriate directory.

[1683] The server generates the download link

[1684] Based on the path of the saved sound effect file, a link is generated that allows the user to easily download it.

[1685] Download sound effects

[1686] The server provides the download link to the user.

[1687] The server provides the user with a download link for the generated sound effect, and the user can download the generated sound effect to their device by clicking the provided link.

[1688] Specific examples

[1689] For example, if a user wants to generate sound effects to be used in a battle scene in a game, the process would be as follows:

[1690] 1. The user uploads a video of a battle scene, "BattleScene.mp4," from their device to the server.

[1691] 2. The server receives the video and stores it in the system.

[1692] 3. The server analyzes the video and recognizes scenes where swords are swung or magic is cast.

[1693] 4. The server generates sword swinging and magic sound effects based on the recognized scene.

[1694] 5. The server saves the generated sound effect file and provides a download link to the user.

[1695] 6. The user clicks on the link to download the generated sound effect and apply it to the game.

[1696] Examples of prompt statements

[1697] Examples of prompts that users can input into a generative AI model include:

[1698] "I want you to generate sound effects for sword-swinging battle scenes."

[1699] "Create sounds for scenes where magic is used."

[1700] This system makes it possible to generate high-quality sound effects easily and at low cost, without requiring specialized knowledge or expensive equipment.

[1701] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1702] Step 1:

[1703] The user selects scene data

[1704] Input: The user uses the device's file browser to select the image or video data of the scene for which they want to generate sound effects. For example, the user selects the video file "C:\Videos\BattleScene.mp4".

[1705] How it works: The user navigates through the file browser and clicks on the desired scene data file.

[1706] Output: The selected file path is retrieved.

[1707] Step 2:

[1708] The user uploads scene data

[1709] Input: The scene data file selected by the user in step 1.

[1710] How it works: A user drags and drops a file into the system's upload interface and clicks the upload button.

[1711] Output: The scene data is sent over the internet to the server. Progress is displayed and a notification is displayed when the upload is complete.

[1712] Step 3:

[1713] The server receives and stores the scene data.

[1714] Input: Scene data submitted by the user.

[1715] Operation: The server saves the received scene data in the specified directory. For example, it saves it as " / tmp / battlescene.mp4".

[1716] Output: Scene data is saved in a temporary folder on the server.

[1717] Step 4:

[1718] The server starts scene analysis

[1719] Input: Scene data saved in step 3.

[1720] Operation: The server initializes the generative AI model and inputs the saved scene data into the model. Video frames are extracted and preprocessed.

[1721] Output: The scene data is ready for analysis and key features are extracted.

[1722] Step 5:

[1723] The server recognizes the scene

[1724] Input: Scene data parsed by a generative AI model.

[1725] How it works: The generative AI model identifies key features in the scene data and assigns them specific tags (e.g., sword, magic).

[1726] Output: Recognized scene tags are generated.

[1727] Step 6:

[1728] The server generates the sound effects

[1729] Input: Scene tags recognized in step 5.

[1730] How it works: The server uses a generative AI model to generate appropriate sound effects based on the tag. For example, if the tag "sword" is recognized, the server inputs a prompt to the generative AI model saying, "I would like you to generate sound effects for a sword-swinging battle scene."

[1731] Output: The generated sound effect file is created.

[1732] Step 7:

[1733] The server stores the sound effect files.

[1734] Input: The sound effect file generated in step 6.

[1735] Behavior: The server saves the generated sound effect file in the specified directory, for example, as " / audio / sword-swinging-sound.wav". It also performs a checksum check.

[1736] Output: The sound effect file has been saved.

[1737] Step 8:

[1738] The server generates the download link

[1739] Input: The path to the saved sound effect file.

[1740] How it works: The server generates a link based on the path of the saved sound effect file so that the user can easily download it. For example, it generates a link like "https: / / server.com / download / swordswingingsound.wav".

[1741] Output: A download link will be generated.

[1742] Step 9:

[1743] The server provides the download link to the user.

[1744] Input: The download link generated in step 8.

[1745] How it works: The server provides the generated download link to the user, and notification can be via email, chat system, or in-system notification.

[1746] Output: The user receives a link that they can click to download the sound effect.

[1747] (Application example 1)

[1748] 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."

[1749] The present invention relates to a system that analyzes scene data and generates sound effects appropriate for a specific scene. Its purpose is to provide a realistic entertainment experience by analyzing scenes in real time using a smart device and instantly reproducing sound effects. However, conventional technologies require specialized knowledge and expensive equipment, making them too costly and time-consuming for general consumers.

[1750] 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.

[1751] In this invention, the server includes means for inputting scene data, means for receiving and saving the scene data, means for analyzing the scene data and recognizing specific scenes, means for generating appropriate sound effects based on the recognized scenes, means for saving and providing the generated sound effects, means for acquiring video in real time from a camera of a smart device and uploading the scene data, and means for playing the generated sound effects on a speaker of the smart device. This allows even general consumers to easily generate high-quality sound effects in real time and enjoy a realistic entertainment experience.

[1752] "Scene data" refers to visual information such as images and videos, and is data used to recognize specific scenes by analyzing this information.

[1753] "Means for inputting scene data" refers to a device or interface that allows a user to provide scene data such as images or videos to the system.

[1754] The "means for receiving and storing the scene data" refers to a device or software for transferring the input scene data to a server and storing it temporarily or permanently.

[1755] "Means for analyzing the scene data and recognizing a particular scene" refers to an algorithm or program for detecting and identifying a particular event or action within the scene data.

[1756] The "means for generating appropriate sound effects based on the recognized scene" refers to an algorithm or program for generating optimal sound effects according to a specific scene label or tag.

[1757] The "means for storing and providing the generated sound effects" refers to a system or device for storing the generated sound effect files and providing them so that users can download or play them.

[1758] "Means for acquiring video in real time from a smart device camera and uploading scene data" refers to a device or program that uses a camera such as smart glasses or a smartphone to capture video in real time and transmits the data to a server.

[1759] "Means for playing the generated sound effect on a speaker of the smart device" refers to a device for playing the generated sound effect using a speaker of smart glasses, a smartphone, or the like.

[1760] The present invention relates to a system for inputting scene data, analyzing it, and generating appropriate sound effects. This system aims to provide a realistic entertainment experience by analyzing scenes in real time using a smart device and instantly reproducing sound effects.

[1761] System configuration

[1762] A user wears a smart device (e.g., smart glasses) and captures scene data in real time. The scene data is captured as video and uploaded to a server. The server receives the uploaded scene data, analyzes it, and recognizes specific scenes. A generative AI model then generates sound effects based on the recognized scene, which are instantly played on the smart device's speaker. Each part of the system is described in detail below.

[1763] Data upload

[1764] 1. The smart device captures the scene data.

[1765] A user wears a smart device (e.g., smart glasses), and the device's camera captures video in real time. For example, the smart glasses camera takes pictures while the user is walking around a store.

[1766] 2. The smart device uploads the scene data to the server.

[1767] The captured video data is uploaded from the smart device to a server in real time.

[1768] Receiving and saving scene data

[1769] 3. The server receives the scene data.

[1770] The server receives the video data sent from the user's smart device and temporarily stores it in a data storage. For example, the video data is continuously received.

[1771] Scene Analysis and Recognition

[1772] 4. The server starts analyzing the scene

[1773] The server uses the generative AI model to analyze the uploaded video data, extracting scene features and identifying specific scenes (e.g., product shelves, product displays, etc.).

[1774] 5. The server recognizes the scene

[1775] The generative AI model recognizes specific actions and events in the scene data and assigns scene tags (e.g., product descriptions, sale information, etc.) based on them.

[1776] Sound effect generation and provision

[1777] 6. The server generates the sound effects

[1778] The server automatically generates optimal sound effects using a generative AI model based on the recognized scene tags, such as product explanations or sales information.

[1779] 7. Smart devices play sound effects

[1780] The generated sound effects are played in real time through the smart device's speaker, allowing users to enjoy a realistic audio guide.

[1781] Specific examples

[1782] For example, if a user is walking around taking pictures of product shelves in a virtual store, the process will be as follows:

[1783] 1. The user wears smart glasses, and the camera captures real-time images of the product shelves.

[1784] 2. The smart device uploads the video data to the server.

[1785] 3. The server receives the video data, analyzes it, and recognizes the product shelf scene.

[1786] 4. The server generates a voice description of the product based on the recognized scene.

[1787] 5. The smart device will play the generated audio in real time, allowing the user to listen to the product description.

[1788] Prompt Sentence Examples

[1789] "Analyze this image (or video) and generate the appropriate sound effect."

[1790] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1791] System processing steps

[1792] Step 1:

[1793] The camera on the smart device captures the footage in real time.

[1794] Input: Video captured in real time by a smart device (e.g., smart glasses).

[1795] Processing: The smart device continuously captures the scene around the user.

[1796] Output: Captured video data.

[1797] Step 2:

[1798] The captured video data is uploaded to the server.

[1799] Input: Captured real-time video data.

[1800] Processing: The video data acquired by the smart device is compressed and encoded, and then uploaded to the server via the network.

[1801] Output: Video data sent to the server.

[1802] Step 3:

[1803] The server receives the video data and stores it in data storage.

[1804] Input: Video data sent from smart device.

[1805] Processing: The server receives the video data through the network and stores it in the appropriate format in the data storage.

[1806] Output: Saved video data.

[1807] Step 4:

[1808] The server uses a generative AI model to analyze the video data and recognize specific scenes.

[1809] Input: Stored video data.

[1810] Processing: The server uses the generated AI model and the prompt "Analyze this image (or video) and generate appropriate sound effects." to analyze the scene characteristics in the video data and identify specific scene labels and tags.

[1811] Output: Recognized scene tags (e.g. product descriptions, sale information, etc.).

[1812] Step 5:

[1813] The server generates sound effects using a generative AI model based on the recognized scene tags.

[1814] Input: Recognized scene tags.

[1815] Processing: The generative AI model generates appropriate sound effects corresponding to the scene tags, synthesizing the sounds based on pre-trained data.

[1816] Output: The generated sound effect file.

[1817] Step 6:

[1818] The server sends the generated sound effect file to the smart device.

[1819] Input: The generated sound effect file.

[1820] Processing: The server sends the path and data of the sound effect file to the smart device, where the sound effect file is encoded in the appropriate format.

[1821] Output: Sound effect data sent to smart device.

[1822] Step 7:

[1823] The smart device plays a sound effect.

[1824] Input: Sound effect data sent from the server.

[1825] Processing: The smart device decodes the received sound effect data and plays it through the built-in speaker.

[1826] Output: The sound effect that the user can hear.

[1827] 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.

[1828] The present invention is a system that inputs scene data, analyzes it, and generates appropriate sound effects, and also includes a function that recognizes the user's emotions and adjusts the sound effects based on those emotions. This system aims to provide a more realistic and emotional experience in entertainment content.

[1829] System configuration

[1830] The user provides scene data (image or video data) and uploads the data from their device to the server. The server receives the uploaded scene data, analyzes it, and recognizes specific scenes. An AI model then generates sound effects based on the recognized scene and provides them to the user. The system also incorporates an emotion engine that recognizes the user's emotions and adjusts the generated sound effects based on the user's emotions. Each part of the system is described in detail below.

[1831] Data upload

[1832] 1. The user selects scene data

[1833] The user uses the file browser on the device to select image data or video data of the scene for which they want to generate sound effects. For example, the user can select a video file called "Battle Scene.mp4."

[1834] 2. The user uploads the scene data.

[1835] The user sends the selected scene data to the server via an upload interface from the terminal to the system.

[1836] Receiving and saving scene data

[1837] 3. The server receives the scene data.

[1838] The server receives the scene data sent by the user and saves it in the data storage. For example, it saves "BattleScene.mp4" in the specified directory.

[1839] Scene Analysis and Recognition

[1840] 4. The server starts analyzing the scene

[1841] The server starts analyzing the uploaded scene data using the generative AI model. In this step, it extracts scene features.

[1842] 5. The server recognizes the scene

[1843] The generative AI model recognizes specific scenes within the scene data and assigns scene tags (e.g., sword, magic, explosion, etc.) accordingly.

[1844] User Emotion Recognition

[1845] 1. Obtain user emotion data

[1846] The device sends the user's voice data or facial expression data to the emotion engine, which analyzes it and recognizes the user's emotions.

[1847] 2. Analyze user sentiment

[1848] The server uses an emotion engine to analyze the user's emotion, and the analyzed emotion data corresponds to the scene tag.

[1849] Sound effect generation and adjustment

[1850] 1. The server generates the sound effects

[1851] The server automatically generates appropriate sound effects using a generative AI model based on the recognized scene tags, such as the sound of a sword swing or magic.

[1852] 2. The server adjusts the sound effects

[1853] The server adjusts the generated sound effects based on the user's emotions. For example, if the user is nervous, the server increases the volume of the sound effects or speeds up the tempo.

[1854] Saving and providing sound effects

[1855] 1. The server saves the sound effect files

[1856] Save the generated sound effects as audio files and record the path to save them. For example, save "sword swinging sound.wav" and "magic sound.wav" in the appropriate directory.

[1857] 2. The server generates a download link

[1858] Based on the path of the saved sound effect file, a link is generated that allows the user to easily download it. This link is generated individually for each user and managed together with authentication information.

[1859] Download sound effects

[1860] 1. The server provides the download link to the user.

[1861] The server provides the user with a download link for the generated sound effect, which is sent to the user via email or a web portal.

[1862] 2. The user downloads the sound effect

[1863] The user clicks on the provided download link to download the generated sound effect to their device, and the downloaded file can be applied to the user's entertainment content.

[1864] Specific examples

[1865] For example, if a user wants to generate sound effects to be used in a battle scene in a game, the process would be as follows:

[1866] 1. The user uploads a video of a battle scene, "BattleScene.mp4," from their device to the server.

[1867] 2. The server receives the video and stores it in the system.

[1868] 3. The server analyzes the video and recognizes scenes where swords are swung or magic is cast.

[1869] 4. The emotion engine analyzes the user's voice and facial expression data to recognize emotions such as tension and excitement.

[1870] 5. The server generates sword swinging and magic sound effects based on the recognized scene.

[1871] 6. The server adjusts the generated sound effects based on the user's emotions.

[1872] 7. The server saves the generated sound effect file and provides a download link to the user.

[1873] 8. The user clicks on the link to download the generated sound effect and apply it to the game.

[1874] The above is a detailed description of an embodiment of the present invention. This system makes it possible to generate high-quality sound effects and sound effects corresponding to emotions simply and at low cost, without requiring specialized knowledge or expensive equipment.

[1875] The processing flow will be explained below.

[1876] Step 1:

[1877] The user uses the file browser on the device to select image data or video data of the scene for which they want to generate sound effects. For example, the user selects a video file called "Battle Scene.mp4."

[1878] Step 2:

[1879] The user sends the selected scene data from the terminal to the server via the upload interface of the system.

[1880] Step 3:

[1881] The server receives the scene data sent by the user and saves it in the data storage. For example, it saves "BattleScene.mp4" in the specified directory.

[1882] Step 4:

[1883] The server then inputs the saved file into the generative AI model to begin analyzing the scene data, extracting the features of the scene data during this process.

[1884] Step 5:

[1885] The server uses the generated AI model to recognize specific scenes within the scene data, such as a sword swing or a magic cast, and assigns a scene tag.

[1886] Step 6:

[1887] The device sends the user's voice data or facial expression data to the emotion engine, which analyzes it and recognizes the user's emotions.

[1888] Step 7:

[1889] The server uses an emotion engine to analyze the voice and facial expression data to identify the user's emotions, such as nervousness, excitement, and joy.

[1890] Step 8:

[1891] The server automatically generates appropriate sound effects using a generative AI model based on the recognized scene tags and user emotion data, such as the sound of a sword swing or magic.

[1892] Step 9:

[1893] The server adjusts the generated sound effects based on the user's emotions. For example, if the user is excited, the server may increase the volume of the sound effects or speed up the tempo.

[1894] Step 10:

[1895] The server saves the generated sound effects as audio files, and records the path of each audio file to provide to the user.

[1896] Step 11:

[1897] The server generates a link based on the path of the saved sound effect file, which the user can use to easily download it. This link is generated for each user and managed together with their authentication information.

[1898] Step 12:

[1899] The server provides the user with a download link for the generated sound effect, which is sent to the user via email or a web portal.

[1900] Step 13:

[1901] The user clicks on the provided download link to download the generated sound effect to their device, and the downloaded file can be applied to the user's entertainment content.

[1902] The above is the specific processing flow of this system. Taking into account the details of the operation at each step, sound effects are generated efficiently and with high quality, and sound effects can be flexibly adjusted according to the user's emotions.

[1903] Example 2

[1904] 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."

[1905] Conventional sound effect generation systems for entertainment content mainly generate simple sound effects based on scene data, making it difficult to provide high-quality sound effects that reflect the user's emotions. For this reason, there has been a demand for systems that can appropriately adjust sound effects based on the user's actual emotions to provide a more realistic entertainment experience.

[1906] 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.

[1907] In this invention, the server includes means for inputting scene data, means for receiving and saving the scene data, means for analyzing the scene data and recognizing a specific scene, means for acquiring user emotion data, means for analyzing the user emotion data, means for generating appropriate sound effects using a generative AI model based on the recognized scene and the user emotion data, means for adjusting the generated sound effects based on the user emotion data, and means for saving and providing the generated and adjusted sound effects. This makes it possible to generate and provide high-quality sound effects that reflect the user's emotions.

[1908] "Scene data" is data that is provided in the form of image data or video data and is the subject of sound effect generation.

[1909] The "receiving and storing means" is a means for transmitting scene data to the server and storing the data in the data storage.

[1910] The "analysis means" is a means for extracting the characteristics of the scene data and recognizing a particular scene based on the extracted characteristics.

[1911] "Emotion data" is data that indicates the emotional state of the user, and is acquired based on the user's facial expressions, voice, and the like.

[1912] A "generative AI model" is a model that uses artificial intelligence technology to generate sound effects based on recognized scene and user emotional data.

[1913] The "adjustment means" is a means for changing and optimizing the generated sound effect based on the user's emotional data.

[1914] The "storing and providing means" refers to a means for storing the generated and adjusted sound effect files in a data storage and providing the files so that the users can download them.

[1915] The present invention is a system that inputs scene data, analyzes it, and generates appropriate sound effects, and also includes a function that recognizes the user's emotions and adjusts the sound effects based on those emotions. This system aims to provide a more realistic and emotional experience in entertainment content.

[1916] System configuration

[1917] First, the user provides scene data (image or video data) and uploads the data from the device to the server. Specifically, the user uses the device's file browser to select the video file of the scene for which they want to generate sound effects (e.g., "battle scene.mp4") and then sends it to the server via the upload interface.

[1918] The server receives the scene data and saves it in the data storage. For example, it saves "battlescene.mp4" in the specified directory (e.g., / storage / uploads / battlescene.mp4).

[1919] Next, the server uses the generative AI model to begin analyzing the uploaded scene data. In this step, it extracts scene features and recognizes specific scenes. Specifically, it breaks down the scene data into frames, extracts the features of each frame, and assigns tags such as "sword swinging scene" or "magic casting scene."

[1920] In parallel, the device collects the user's voice and facial expression data using a built-in camera and microphone, and sends them to the emotion engine. The server uses the emotion engine to analyze the user's emotions. For example, it can analyze whether the user is nervous or excited from the voice data.

[1921] The server uses a generative AI model to generate appropriate sound effects based on the recognized scene tags and analyzed emotional data. For example, for a sword-swinging scene, it generates a "sword-swinging sound.wav" file. It also adjusts the sound effects based on the user's emotional data. For example, if the user is nervous, it will increase the volume of the sound effects or speed up the tempo.

[1922] The generated sound effect files are saved in data storage, and the path to the saved location is recorded. For example, "sword swinging sound.wav" and "magic sound.wav" are stored in the save directory. Based on the path of the saved sound effect file, the server generates a link that users can easily download and provides it to them via email or a web portal.

[1923] The user clicks on the provided download link to download the generated sound effect to their device, and the downloaded file is applied to the user's entertainment content.

[1924] Examples and prompts

[1925] For example, if a user wants to generate sound effects to be used in a battle scene in a game, the process would be as follows:

[1926] 1. The user selects "BattleScene.mp4" on the device and clicks the upload button to send it to the server.

[1927] 2. The server receives the scene data and saves it to / storage / uploads / battlescene.mp4.

[1928] 3. The server begins analyzing the video, extracting features from each frame and recognizing tags such as "swinging a sword" and "casting magic."

[1929] 4. The device captures the user's facial expressions and voice data and sends it to the emotion engine.

[1930] 5. The server uses an emotion engine to analyze the user's emotions and detect, for example, "tension."

[1931] 6. The server generates an appropriate sound effect (e.g., "sword swinging sound.wav") and adjusts the volume based on the user's emotional data.

[1932] 7. The server saves the generated sound effect to / storage / sounds / swordswingingsound.wav and generates a download link.

[1933] 8. The server emails the generated link to the user.

[1934] 9. The user clicks on the link in the email, downloads the "Sword Swinging Sound.wav" file, and applies it to the game.

[1935] Prompt Sentence Examples

[1936] "Users can upload videos of battle scenes, and the app will generate sound effects that match the recognized scenes from the video. The app will also adjust the sound effects based on the user's emotions, and provide a download link."

[1937] The above is a specific embodiment of the invention, which makes it possible to generate high-quality sound effects and sound effects that correspond to emotions easily and at low cost without requiring specialized knowledge or expensive equipment.

[1938] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1939] System program processing flow

[1940] Step 1:

[1941] Selecting scene data

[1942] Input: The user uses the device's file browser to select image or video data for the scene for which they want to generate sound effects.

[1943] Specific behavior: The user clicks the "Choose File" button and selects "BattleScene.mp4" from the file dialog.

[1944] Output: The selected scene data file path is obtained.

[1945] Step 2:

[1946] Uploading scene data

[1947] Input: User selected scene data file path.

[1948] Specific operation: The user clicks the "Upload" button through the upload interface of the terminal, and the selected scene data is sent to the server as an HTTP request.

[1949] Output: Scene data is uploaded to the server.

[1950] Step 3:

[1951] Receiving and saving scene data

[1952] Input: The server receives the scene data as an HTTP request.

[1953] Specific operation: The server saves the received scene data to data storage, for example, / storage / uploads / battlescene.mp4.

[1954] Output: The scene data is saved to the specified directory.

[1955] Step 4:

[1956] Starting Scene Analysis

[1957] Input: Saved scene data file path.

[1958] Specific operation: The server uses the generative AI model to begin analyzing the uploaded scene data, breaking it down into frames and extracting the features of each frame.

[1959] Output: Feature data for each frame.

[1960] Step 5:

[1961] Scene Recognition

[1962] Input: Extracted frame-by-frame feature data.

[1963] Specific actions: The generative AI model analyzes feature data and recognizes specific scenes. Each scene is tagged with a tag such as "swinging a sword" or "casting magic."

[1964] Output: Tagged scene data.

[1965] Step 6:

[1966] Acquiring emotion data

[1967] Input: User's facial expression data and voice data.

[1968] Specific operation: The device uses the built-in camera and microphone to capture the user's facial expressions and voice data and transmits them to the emotion engine.

[1969] Output: Captured facial expression and voice data of the user.

[1970] Step 7:

[1971] Emotion Analysis

[1972] Input: Captured user facial expression and voice data.

[1973] Specific operation: The server uses the emotion engine to analyze the user's emotions. For example, emotions such as "tension" or "excitement" are determined from voice and facial expressions.

[1974] Output: Parsed user emotion data.

[1975] Step 8:

[1976] Sound effect generation

[1977] Input: Tagged scene data and parsed user emotion data.

[1978] How it works: The server uses the generative AI model to generate appropriate sound effects based on the recognized scene tags, for example, generating "sword swinging sound.wav" for a sword swinging scene.

[1979] Output: The generated sound effect file.

[1980] Step 9:

[1981] Sound effect adjustments

[1982] Input: Generated sound effect files and analyzed user emotion data.

[1983] Specific operation: The server adjusts the volume and tempo of the generated sound effects based on the user's emotional data. For example, if the user is nervous, the volume of the sound effects is increased.

[1984] Output: Adjusted sound effect file.

[1985] Step 10:

[1986] Saving sound effect files

[1987] Input: The adjusted sound effect file.

[1988] Specific operation: The server saves the adjusted sound effect file to data storage and records the path to save it, for example, / storage / sounds / swordswingingsound.wav.

[1989] Output: The path of the saved sound effect file.

[1990] Step 11:

[1991] Generate a download link

[1992] Input: The path to the saved sound effect file.

[1993] Specific operation: The server generates a link based on the path of the saved sound effect file, allowing the user to easily download it.

[1994] Output: The generated download link.

[1995] Step 12:

[1996] Providing a download link

[1997] Input: The generated download link.

[1998] What happens: The server provides the generated download link to the user, which can be provided via email or a web portal.

[1999] Output: The download link provided to the user.

[2000] Step 13:

[2001] Download sound effects

[2002] Input: The download link provided by the server.

[2003] Specific operation: The user clicks on the provided download link and the generated sound effect is downloaded to the device.

[2004] Output: Downloaded sound effect file.

[2005] The above are the specific processing steps of the program of this system.

[2006] (Application example 2)

[2007] 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."

[2008] In conventional entertainment content, sound effects are mostly preset, making it difficult to generate and adjust appropriate sound effects in real time according to the viewer's emotions. This has required more complex systems and a large number of human resources to improve the quality of the user experience. Therefore, there is a demand for a system that can generate and adjust sound effects in real time according to the user's emotions.

[2009] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2010] In this invention, the server includes means for inputting scene data, means for receiving and saving the scene data, means for analyzing the scene data and recognizing a specific scene, means for generating appropriate sound effects based on the recognized scene, means for acquiring and analyzing user emotion data, means for adjusting the generated sound effects based on the acquired and analyzed emotion data, and means for saving and providing the generated and adjusted sound effects, thereby making it possible to generate and adjust appropriate sound effects in real time based on the user's emotions.

[2011] "Scene data" refers to visual information expressed as image data or video data.

[2012] The "means for inputting scene data" refers to an interface or device that allows a user to provide scene data to the system.

[2013] The "means for receiving and saving scene data" refers to a mechanism for uploading scene data to a server and saving the data in storage.

[2014] The "means for analyzing scene data and recognizing a specific scene" refers to an analysis algorithm or software used to analyze the scene data and identify a specific scene therein.

[2015] "Means for generating appropriate sound effects" refers to generative AI models or sound generation software for generating sound effects based on a recognized scene.

[2016] "Means for acquiring and analyzing user emotional data" refers to software or equipment for acquiring the user's facial expressions and voice data, analyzing them, and recognizing the user's emotional state.

[2017] "Means for adjusting sound effects generated based on acquired and analyzed emotional data" refers to algorithms or software for adjusting the volume, tempo, tone, etc. of generated sound effects based on acquired and analyzed emotional data of the user.

[2018] The "means for storing and providing the generated and adjusted sound effects" refers to a mechanism for storing the finally generated sound effects and providing them so that the user can download or play them.

[2019] The present invention is a system that inputs and analyzes scene data and generates sound effects using a generative AI model based on the input data. It also has the ability to acquire and analyze user emotion data and adjust the generated sound effects based on the emotion. This invention is particularly intended for application in content distribution services.

[2020] System configuration

[2021] Data upload

[2022] 1. Input of scene data: The user inputs scene data (image data or video data) into the system by selecting the data using a file browser on their smartphone or PC and uploading it to the system.

[2023] 2. Receiving and storing scene data: The server receives the scene data uploaded by the user and stores it in data storage. This storage is done using a common cloud storage service (e.g., Amazon S3).

[2024] Scene analysis and sound effect generation

[2025] 3. Scene data analysis: The server analyzes specific scenes in the scene data using image recognition and video analysis libraries (e.g., TensorFlow, OpenCV).

[2026] 4. Sound Effect Generation: The server uses a generative AI model (e.g. WaveNet, JukeBox) to generate sound effects appropriate for a specific scene, using pre-trained AI models.

[2027] User Emotion Recognition

[2028] 5. Acquisition of emotion data: The user's device (smartphone or PC with webcam) acquires the user's voice data or facial expression data, and sends this data to the server in real time.

[2029] 6. Emotion data analysis: The server uses an emotion analysis AI engine (e.g., Microsoft Azure Face API) to analyze the acquired user emotion data and save the results.

[2030] Adjusting and providing sound effects

[2031] 7. Sound effect adjustment: The server adjusts the volume, tempo, and tone of the generated sound effects based on the recognized user emotion data. This adjustment is performed using algorithms (e.g., audio signal processing algorithms).

[2032] 8. Saving and providing sound effects: The adjusted sound effects will be saved again and a link will be generated for users to easily download them. The link will be provided via email or web portal.

[2033] Specific examples

[2034] For example, consider the case where a user uploads a video of a fight scene, "fightscene.mp4," to the system. In this case, the following process occurs:

[2035] 1. The user uploads "Battle Scene.mp4".

[2036] 2. The server receives the video and stores it in data storage.

[2037] 3. The server analyzes the video and recognizes scenes where swords are swung or magic is cast.

[2038] 4. Acquire the user's voice or facial expression data in real time and perform emotion analysis.

[2039] 5. The server generates sword swinging and magic sound effects based on the recognized scene.

[2040] 6. The server adjusts the volume and tempo of the sound effects based on the user's emotional data.

[2041] 7. Save the adjusted sound effect and generate a download link for the user.

[2042] 8. The user obtains the sound effect via the download link and applies it to their content.

[2043] Prompt Sentence Examples

[2044] For example, here's a sample prompt for a generative AI model to generate a sound effect:

[2045] "Please provide an example of how to adjust sound effects programmatically. For example, please implement a method in Python to change the volume of a sound depending on the user's emotions."

[2046] As described above, the system of the present invention is capable of generating and adjusting appropriate sound effects in real time based on the user's emotions, thereby improving the quality of the user's experience with entertainment content.

[2047] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2048] Step 1:

[2049] User enters scene data

[2050] The user selects scene data (image data or video data) from the terminal and uploads it to the system.

[2051] Input: A scene data file selected by the user (e.g. "BattleScene.mp4").

[2052] How it works: The user selects a file using the device's file browser and sends it to the server through the system's upload interface.

[2053] Output: The server receives the scene data.

[2054] Step 2:

[2055] The server receives and stores the scene data

[2056] The server receives the scene data sent by the user and stores it in a data storage.

[2057] Input: Scene data submitted by the user.

[2058] What it does: The server saves the file to a data storage (e.g. Amazon S3) and records the directory path where it was saved.

[2059] Output: The file path of the saved scene data.

[2060] Step 3:

[2061] The server analyzes the scene data and recognizes the specific scene.

[2062] The server analyzes the received scene data and performs scene analysis to recognize specific scenes.

[2063] Input: The file path of the saved scene data.

[2064] How it works: The server uses a scene analysis library (e.g. TensorFlow, OpenCV) to parse the scene data frame by frame and extract specific scene tags (e.g. sword, explosion, magic).

[2065] Output: Extracted scene tags.

[2066] Step 4:

[2067] Server generates sound effects

[2068] Based on the recognized scene tags, the server generates appropriate sound effects using a generative AI model.

[2069] Input: Extracted scene tags.

[2070] How it works: The server inputs the scene tag as a prompt into a generative AI model (e.g. WaveNet, JukeBox) and generates the corresponding sound effect.

[2071] Output: The generated sound effect file.

[2072] Step 5:

[2073] The device acquires the user's emotional data

[2074] The terminal acquires the user's voice data or facial expression data and transmits it to the server.

[2075] Input: User's voice or facial expression data.

[2076] How it works: The device uses a microphone and camera to capture the user's voice and facial expression data in real time and transmits it to a server.

[2077] Output: Emotion data sent to the server.

[2078] Step 6:

[2079] The server analyzes the emotional data

[2080] The server analyzes the acquired emotion data and recognizes the user's emotional state.

[2081] Input: Emotion data sent to the server.

[2082] How it works: The server uses an emotion analysis AI engine (e.g., Microsoft Azure Face API) to analyze the emotion data and determine the user's emotional state (e.g., nervous, excited, relaxed).

[2083] Output: User's emotional state data.

[2084] Step 7:

[2085] Adjusted server-generated sound effects

[2086] The server adjusts the generated sound effects based on the recognized emotional state data of the user.

[2087] Input: Generated sound effect files and user emotional state data.

[2088] How it works: The server uses audio signal processing algorithms to adjust the volume, tempo, and tone of sound effects based on the user's emotions.

[2089] Output: Adjusted sound effect file.

[2090] Step 8:

[2091] The server stores and provides the adjusted sound effects.

[2092] The server stores the adjusted sound effects and generates a link for users to download them.

[2093] Input: The adjusted sound effect file.

[2094] How it works: The server saves the adjusted sound effect file to data storage and generates a download link to provide to the user. The link is provided to the user via email or a web portal.

[2095] Output: A download link to the user.

[2096] The above are the specific processing steps of the system that realizes the application example. In this way, it becomes possible to generate and adjust appropriate sound effects in real time based on the user's emotions.

[2097] 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.

[2098] 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.

[2099] 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.

[2100] 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.

[2101] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2102] 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.

[2103] 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).

[2104] 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.

[2105] 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."

[2106] 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.

[2107] 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).

[2108] 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.

[2109] 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.

[2110] 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.

[2111] 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.

[2112] 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.

[2113] 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.

[2114] 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.

[2115] 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.

[2116] 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.

[2117] 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.

[2118] The following is further disclosed regarding the above embodiment.

[2119] (Claim 1)

[2120] means for inputting scene data;

[2121] means for receiving and storing said scene data;

[2122] means for analyzing the scene data and recognizing a particular scene;

[2123] means for generating appropriate sound effects based on the recognized scene;

[2124] means for storing and providing the generated sound effects;

[2125] A system including:

[2126] (Claim 2)

[2127] The system of claim 1 , wherein the scene data is image data or video data.

[2128] (Claim 3)

[2129] 10. The system of claim 1, wherein the means for generating the sound effects uses a generative AI model.

[2130] "Example 1"

[2131] (Claim 1)

[2132] means for a user to select scene data;

[2133] means for a user to upload scene data;

[2134] means for the server to receive and store scene data;

[2135] a means for the server to analyze the scene data using the generative AI model and recognize a particular scene;

[2136] a means for the server to generate sound effects using a generative AI model based on the recognized scene;

[2137] means for storing and providing the generated sound effect files;

[2138] A system including:

[2139] (Claim 2)

[2140] The system of claim 1 , wherein the scene data is image data or video data.

[2141] (Claim 3)

[2142] 10. The system of claim 1, wherein the means for generating the sound effect uses a prompt sentence to operate a generative AI model.

[2143] "Application Example 1"

[2144] (Claim 1)

[2145] means for inputting scene data;

[2146] means for receiving and storing said scene data;

[2147] means for analyzing the scene data and recognizing a particular scene;

[2148] means for generating appropriate sound effects based on the recognized scene;

[2149] means for storing and providing the generated sound effects;

[2150] A means to acquire video from the smart device camera in real time and upload scene data;

[2151] means for playing the generated sound effect on a speaker of the smart device;

[2152] A system including:

[2153] (Claim 2)

[2154] The system of claim 1 , wherein the scene data is image data or video data.

[2155] (Claim 3)

[2156] 10. The system of claim 1, wherein the means for generating the sound effects uses a generative AI model.

[2157] "Example 2: Combining Emotion Engines"

[2158] (Claim 1)

[2159] means for inputting scene data;

[2160] means for receiving and storing said scene data;

[2161] means for analyzing the scene data and recognizing a particular scene;

[2162] means for acquiring user emotion data;

[2163] means for analyzing emotion data of the user;

[2164] means for generating appropriate sound effects using a generative AI model based on the recognized scene and user emotion data;

[2165] means for adjusting the generated sound effect based on emotion data of a user;

[2166] means for storing and providing the generated and adjusted sound effects;

[2167] A system including:

[2168] (Claim 2)

[2169] The system of claim 1 , wherein the scene data is image data or video data.

[2170] (Claim 3)

[2171] 10. The system of claim 1, wherein the means for analyzing scene data and recognizing a particular scene and the means for generating sound effects use generative AI models.

[2172] "Application example 2 when combining emotion engines"

[2173] (Claim 1)

[2174] means for inputting scene data;

[2175] means for receiving and storing said scene data;

[2176] means for analyzing the scene data and recognizing a particular scene;

[2177] means for generating appropriate sound effects based on the recognized scene;

[2178] means for acquiring and analyzing user emotion data;

[2179] means for adjusting the generated sound effect based on the acquired and analyzed emotion data;

[2180] means for storing and providing the generated and adjusted sound effects;

[2181] A system including:

[2182] (Claim 2)

[2183] The system of claim 1 , wherein the scene data is image data or video data.

[2184] (Claim 3)

[2185] 10. The system of claim 1, wherein the means for generating the sound effects uses a generative AI model. [Explanation of symbols]

[2186] 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. means for inputting scene data; means for receiving and storing said scene data; means for analyzing the scene data and recognizing a particular scene; means for generating appropriate sound effects based on the recognized scene; means for storing and providing the generated sound effects; A system including:

2. The system of claim 1 , wherein the scene data is image data or video data.

3. The system of claim 1 , wherein the means for generating the sound effects uses a generative AI model.

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