system

Abstract

The system according to this embodiment aims to provide a realistic and immersive movie experience, similar to that of a movie theater, even at home. [Solution] The system according to the embodiment comprises an analysis unit, a generation unit, a control unit, and a sensory unit. The analysis unit analyzes video and audio. The generation unit generates vibrations and wind based on the information analyzed by the analysis unit. The control unit controls the vibrations and wind generated by the generation unit. The sensory unit experiences the vibrations and wind controlled by the control unit.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the prior art, there was a problem that it was difficult to obtain a real and immersive experience like a movie theater when watching a movie at home.

[0005] The system according to the embodiment aims to provide a real and immersive movie experience like a movie theater even at home.

Means for Solving the Problems

[0006] The system according to this embodiment comprises an analysis unit, a generation unit, a control unit, and a sensory experience unit. The analysis unit analyzes video and audio. The generation unit generates vibrations and wind based on the information analyzed by the analysis unit. The control unit controls the vibrations and wind generated by the generation unit. The sensory experience unit experiences the vibrations and wind controlled by the control unit. [Effects of the Invention]

[0007] The system according to this embodiment can provide a realistic and immersive movie experience, similar to that of a movie theater, even in the comfort of one's own home. [Brief explanation of the drawing]

[0008] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Modes for carrying out the invention]

[0009] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0010] First, let's explain the terminology used in the following explanation.

[0011] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), or TPU (Tensor Processing Unit).

[0012] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0013] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0014] In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor, an antenna, and the like. The communication I / F manages communication between a plurality of computers. Examples of communication standards applicable to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

[0016] [First Embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] As shown in FIG. 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. 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. Also, the database 24 and the communication I / F 26 are 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).

[0019] The smart device 14 comprises a computer 36, a receiving device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The receiving device 38, output device 40, and camera 42 are also connected to the bus 52.

[0020] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, and accepts user input. The touch panel 38A accepts user input via touch by detecting contact with an object (e.g., a pen or finger). The microphone 38B accepts user input via voice by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 (see Figure 2) acquires the data indicating the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user by outputting the data in a form perceptible to the user (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0023] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0025] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0026] In the smart device 14, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart device 14 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0027] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device having the data generation model 58. The data processing device 12 may also be a server device or a terminal device owned by a user (e.g., a mobile phone, robot, home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example of form 1) An immersive home theater system according to an embodiment of the present invention is a system that utilizes AI to realize an immersive home theater experience similar to that of a movie theater, even at home. This immersive home theater system makes movie viewing more realistic and immersive by having AI analyze video and audio and generate vibrations and wind. First, the immersive home theater system uses AI to recognize and analyze the video and audio of a movie. Based on the content of the video and audio, the AI ​​determines what kind of vibrations and wind to generate in which scenes. Next, the immersive home theater system controls devices such as bone conduction earphones and mini blowers based on the information analyzed by the AI. This allows the user to experience vibrations and wind in accordance with the scenes in the movie. Furthermore, by using AR glasses, the immersive home theater system allows users to enjoy movies in their own private space. This system also provides opportunities for people with visual or hearing impairments to enjoy movies. In addition, this system can provide new added value to video rental companies and movie / video streaming companies. For example, the immersive home theater system provides users with a sense of realism by generating vibrations and wind in accordance with the scenes in the movie. For example, the system can generate strong vibrations and wind during action scenes, and gentle vibrations and wind during quiet scenes. This allows users to enjoy a sensory experience that matches the movie scene. Furthermore, the immersive home theater system can estimate the user's emotions and adjust the vibration and wind generation method based on those emotions. For example, it can generate strong vibrations and wind when the user is excited, and gentle vibrations and wind when the user is relaxed. This allows users to enjoy a sensory experience that matches their emotions. In addition, the immersive home theater system can improve its analysis and generation accuracy by referring to past analysis and generation data. For example, it can refer to data from the same movie analyzed in the past to optimize the vibration and wind generation patterns for each scene. This ensures that the immersive home theater system always provides the optimal experience. As a result, the immersive home theater system can make movie watching more realistic and immersive.

[0029] The immersive home theater system according to this embodiment comprises an analysis unit, a generation unit, a control unit, and an immersive unit. The analysis unit analyzes video and audio. For example, the analysis unit recognizes and analyzes the video and audio of a movie. The analysis unit can use AI to analyze the content of the video and audio. For example, the analysis unit uses a speech recognition algorithm to analyze the audio of a movie. The analysis unit can also use an image recognition algorithm to analyze the video of a movie. The generation unit generates vibrations and wind based on the information analyzed by the analysis unit. For example, the generation unit generates vibrations and wind using a vibration motor or a blower. The generation unit can use AI to adjust the method of generating vibrations and wind. For example, the generation unit adjusts the method of generating vibration patterns based on information analyzed by the AI. The generation unit can also set the wind intensity and direction based on information analyzed by the AI. The control unit controls the vibrations and wind generated by the generation unit. For example, the control unit controls vibrations and wind using feedback control or PID control. The control unit can use AI to adjust the method of controlling vibrations and wind. For example, the control unit performs real-time control based on information analyzed by the AI. The control unit can also adjust the intensity and duration of vibrations and wind based on the information analyzed by the AI. The sensory unit experiences the vibrations and wind controlled by the control unit. The sensory unit experiences the vibrations and wind using, for example, bone conduction earphones or a mini fan. The sensory unit can adjust the way it experiences the vibrations using the AI. For example, the sensory unit adjusts the intensity and duration of vibrations and wind based on the information analyzed by the AI. The sensory unit can also enjoy movies using AR glasses. The sensory unit provides people with visual or hearing impairments with the opportunity to enjoy movies. As a result, the sensory home theater system according to this embodiment can make movie viewing more realistic and immersive.

[0030] The analysis unit analyzes video and audio. For example, the analysis unit recognizes and analyzes the video and audio of a movie. The analysis unit can use AI to analyze the content of video and audio. Specifically, the analysis unit uses a speech recognition algorithm to analyze the audio of a movie. The speech recognition algorithm converts the audio data into text data and identifies the dialogue and sound effects in the movie. This allows for accurate understanding of audio information corresponding to the movie scene. The analysis unit can also analyze the video of a movie using an image recognition algorithm. The image recognition algorithm analyzes the video data frame by frame and identifies movie scenes, characters, backgrounds, etc. This allows for accurate understanding of video information corresponding to the movie scene. Furthermore, the analysis unit can use AI to analyze the content of video and audio in real time. For example, in an action scene in a movie, the AI ​​quickly detects changes in audio and video and sends the analysis results to the generation unit. This allows the analysis unit to quickly and accurately generate vibrations and wind according to the movie scene.

[0031] The generation unit generates vibrations and wind based on information analyzed by the analysis unit. The generation unit generates vibrations and wind using, for example, a vibration motor or a blower. Specifically, the vibration motor generates vibrations in action scenes and explosion scenes in movies, providing users with a sense of realism. The blower generates wind in landscape scenes and storm scenes in movies, providing users with a realistic experience. The generation unit can adjust the method of generating vibrations and wind using AI. For example, the generation unit adjusts the method of generating vibration patterns based on information analyzed by the AI. The AI ​​generates the optimal vibration pattern according to the movie scene, providing users with a realistic experience. The generation unit can also set the intensity and direction of wind based on information analyzed by the AI. The AI ​​sets the optimal wind intensity and direction according to the movie scene, providing users with a realistic experience. Furthermore, the generation unit can generate vibrations and wind in real time. This allows the generation unit to quickly and accurately generate vibrations and wind according to movie scenes.

[0032] The control unit controls the vibrations and wind generated by the generation unit. The control unit controls the vibrations and wind using methods such as feedback control and PID control. Specifically, feedback control monitors the intensity and direction of the generated vibrations and wind in real time and adjusts them as needed. PID control predicts the intensity and direction of the generated vibrations and wind and performs optimal control. The control unit can use AI to adjust the vibration and wind control methods. For example, the control unit performs real-time control based on information analyzed by the AI. The AI ​​generates the optimal control method according to the movie scene, providing the user with a realistic experience. Furthermore, the control unit can adjust the intensity and duration of the vibrations and wind based on information analyzed by the AI. The AI ​​sets the optimal intensity and duration according to the movie scene, providing the user with a realistic experience. In addition, the control unit can control the vibrations and wind in real time. This allows the control unit to quickly and accurately control the vibrations and wind according to the movie scene.

[0033] The sensory unit experiences vibrations and wind controlled by the control unit. For example, the sensory unit uses bone conduction earphones or a mini fan to simulate vibrations and wind. Specifically, bone conduction earphones transmit movie audio as vibrations to the user, providing a realistic experience. The mini fan generates wind during landscape or storm scenes in movies, providing a realistic experience. The sensory unit can adjust the sensory experience using AI. For example, the sensory unit adjusts the intensity and duration of vibrations and wind based on information analyzed by the AI. The AI ​​sets the optimal intensity and duration according to the movie scene, providing a realistic experience. Furthermore, the sensory unit can also enjoy movies using AR glasses. AR glasses provide the user with movie footage as augmented reality, offering a realistic experience. In addition, the sensory unit provides opportunities for people with visual or hearing impairments to enjoy movies. For example, bone conduction earphones transmit movie audio as vibrations to people with hearing impairments, providing them with the opportunity to enjoy movies. This allows the sensory experience to make movie viewing more realistic and immersive.

[0034] The analysis unit can recognize and analyze video and audio. For example, the analysis unit can recognize and analyze the audio of a movie using a speech recognition algorithm. For example, the analysis unit can recognize and analyze the dialogue and sound effects of a movie. The analysis unit can also recognize and analyze the video of a movie using an image recognition algorithm. For example, the analysis unit can recognize and analyze scenes and characters in a movie. As a result, the analysis unit can obtain the information necessary for generating vibrations and wind by recognizing and analyzing video and audio. Some or all of the above processing in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input the video and audio of a movie into a generation AI, which can then recognize and analyze the video and audio.

[0035] The generation unit can generate vibrations and wind based on the analyzed information. For example, the generation unit can generate vibrations using a vibration motor. For example, the generation unit can change the intensity of the vibrations by adjusting the rotation speed of the vibration motor. The generation unit can also generate wind using a blower. For example, the generation unit can change the intensity of the wind by adjusting the airflow of the blower. Furthermore, the generation unit can adjust the direction of the wind. For example, the generation unit can change the direction of the wind by changing the angle of the blower. In this way, the generation unit can provide a tactile experience that matches the movie scene by generating vibrations and wind based on the analyzed information. Some or all of the above processing in the generation unit may be performed using AI, for example, or without AI. For example, the generation unit can input the analyzed information into a generation AI, which can then determine how to generate vibrations and wind.

[0036] The control unit can control the generated vibrations and wind. The control unit controls the vibrations and wind, for example, using feedback control. For example, the control unit can control the intensity of vibrations by adjusting the rotation speed of the vibration motor in real time. The control unit can also control the intensity of wind by adjusting the airflow of the fan in real time. Furthermore, the control unit can control the direction of wind by adjusting the angle of the fan in real time. In this way, the control unit can optimize the user's experience by controlling the generated vibrations and wind. Some or all of the above processing in the control unit may be performed using AI, for example, or without AI. For example, the control unit can input the generated vibration and wind data into a generating AI, which can then determine how to control the vibrations and wind.

[0037] The sensory unit can experience controlled vibrations and wind. For example, the sensory unit can experience vibrations using bone conduction earphones. For example, by wearing bone conduction earphones, the sensory unit can transmit vibrations directly to the bones. The sensory unit can also experience wind using a mini fan. For example, the sensory unit can use a mini fan to blow wind onto its face or body. In this way, the sensory unit can enjoy watching movies more realistically by experiencing controlled vibrations and wind. Some or all of the above processing in the sensory unit may be performed using AI, for example, or without AI. For example, the sensory unit can input data on controlled vibrations and wind into a generating AI, which can then determine how to experience them.

[0038] The sensory unit may include bone conduction earphones or a mini fan. The sensory unit can, for example, experience vibrations using bone conduction earphones. For example, the sensory unit can wear bone conduction earphones in its ears and transmit vibrations directly to the bone. The sensory unit can also experience wind using a mini fan. For example, the sensory unit can use a mini fan to blow wind onto its face or body. Thus, the sensory unit can effectively experience vibrations and wind by using bone conduction earphones or a mini fan. Some or all of the above processing in the sensory unit may be performed using AI, for example, or without AI. For example, the sensory unit can input data from bone conduction earphones or a mini fan into a generating AI, which can then determine the method of sensory experience.

[0039] The immersive unit can enjoy movies using AR glasses. The immersive unit can, for example, enjoy movies in its own private space by wearing AR glasses. For example, the immersive unit can display movie footage in front of the user's eyes using AR glasses. This allows the immersive unit to enjoy movies in its own private space by using AR glasses. Some or all of the above processing in the immersive unit may be performed using AI, for example, or without AI. For example, the immersive unit can input data from the AR glasses into a generating AI, which can then determine the method of experience.

[0040] The sensory experience unit can provide people with visual or hearing impairments with the opportunity to enjoy movies. For example, the sensory experience unit can provide visually impaired people with the opportunity to enjoy movies by providing audio guides. For example, the sensory experience unit can generate audio guides in accordance with movie scenes and provide them to visually impaired people. The sensory experience unit can also provide hearing impaired people with the opportunity to enjoy movies by providing subtitles and vibrations. For example, the sensory experience unit can display movie dialogue as subtitles and provide them to hearing impaired people. In this way, the sensory experience unit can provide people with visual or hearing impairments with the opportunity to enjoy movies. Some or all of the above processing in the sensory experience unit may be performed using AI, for example, or without AI. For example, the sensory experience unit can input data of people with visual or hearing impairments into a generating AI, and the generating AI can determine the method of experience.

[0041] The analysis unit can improve analysis accuracy by referring to past analysis data when analyzing video and audio. For example, the analysis unit can refer to data from the same movie that has been analyzed in the past to optimize the vibration and wind generation patterns for each scene. For example, the analysis unit can adjust the vibration and wind generation method based on past data. The analysis unit can also refer to the user's past viewing history and apply an analysis method tailored to their preferences. For example, the analysis unit can adjust the analysis method based on the genre of movies the user has watched in the past. In this way, the analysis unit improves analysis accuracy by referring to past analysis data. Some or all of the above processing in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input past analysis data into a generation AI, which can then improve the analysis accuracy.

[0042] The analysis unit can adjust the level of detail in its analysis of video and audio based on the importance of each scene. For example, in climactic scenes, the analysis unit can perform a detailed analysis to precisely control the generation of vibrations and wind. For instance, the analysis unit can analyze the video and audio of a climactic scene in detail and adjust the method of generating vibrations and wind. Conversely, in everyday scenes, the analysis unit can perform a simplified analysis to reduce the generation of vibrations and wind. For example, the analysis unit can simplify the analysis of video and audio in everyday scenes and adjust the method of generating vibrations and wind. This allows the analysis unit to generate more appropriate vibrations and wind by adjusting the level of detail in its analysis based on the importance of each scene. Some or all of the above processing in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input scene importance data into a generation AI, which can then adjust the level of detail in its analysis.

[0043] The analysis unit can customize its analysis method when analyzing video and audio, taking into account the user's viewing history. For example, the analysis unit can adjust its analysis method based on the genre of movies the user has watched in the past. For example, the analysis unit can refer to the user's viewing history and apply an analysis method tailored to their preferences. The analysis unit can also customize its analysis method based on the type of scenes the user prefers. For example, the analysis unit can analyze the type of scenes the user prefers and adjust the vibration and wind generation method. This allows the analysis unit to generate more appropriate vibrations and wind by customizing its analysis method while considering the user's viewing history. Some or all of the above processing in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input the user's viewing history data into a generation AI, which can then customize the analysis method.

[0044] The analysis unit can select the optimal analysis method when analyzing video and audio, taking into account the user's device information. For example, the analysis unit can adjust the analysis method based on the performance of the device the user is using. For example, the analysis unit can refer to the user's device information and select an analysis method based on the device's performance. The analysis unit can also customize the analysis method based on the screen size of the device the user is using. For example, the analysis unit can adjust the video and audio analysis method based on the device's screen size. This allows the analysis unit to select the optimal analysis method while considering the user's device information, enabling the generation of more appropriate vibrations and wind. Some or all of the above processing in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input the user's device information into a generation AI, which can then select the optimal analysis method.

[0045] The generation unit can improve generation accuracy by referring to past generation data when generating vibrations and wind. For example, the generation unit can refer to previously generated vibration and wind data and apply the optimal generation method. For example, the generation unit can adjust the vibration and wind generation method based on past data. The generation unit can also refer to the user's past sensory history and apply a generation method tailored to their preferences. For example, the generation unit can refer to the user's past sensory history and adjust the vibration and wind generation method. As a result, the generation unit improves generation accuracy by referring to past generation data. Some or all of the above processing in the generation unit may be performed using AI, for example, or without AI. For example, the generation unit can input past generation data into a generation AI, which can then improve generation accuracy.

[0046] The generation unit can adjust the level of detail in generating vibrations and wind based on the importance of the scene. For example, in climax scenes, the generation unit performs detailed generation and precisely controls the intensity of vibrations and wind. For example, the generation unit can analyze the video and audio of climax scenes in detail and adjust the method of generating vibrations and wind. Conversely, in everyday scenes, the generation unit can perform simplified generation and reduce the intensity of vibrations and wind. For example, the generation unit can analyze the video and audio of everyday scenes in a simplified manner and adjust the method of generating vibrations and wind. This allows the generation unit to adjust the level of detail in generation based on the importance of the scene, enabling a more appropriate experience. Some or all of the above processing in the generation unit may be performed using AI, for example, or without AI. For example, the generation unit can input scene importance data into a generation AI, which can then adjust the level of detail in generation.

[0047] The generation unit can customize the generation method for vibrations and wind by taking into account the user's viewing history. For example, the generation unit can adjust the generation method based on the genre of movies the user has watched in the past. For example, the generation unit can refer to the user's viewing history and apply a generation method tailored to their preferences. The generation unit can also customize the generation method based on the type of scenes the user prefers. For example, the generation unit can analyze the type of scenes the user prefers and adjust the vibration and wind generation method. In this way, the generation unit can customize the generation method by taking the user's viewing history into account, enabling a more appropriate experience. Some or all of the above processing in the generation unit may be performed using AI, for example, or without AI. For example, the generation unit can input the user's viewing history data into a generation AI, which can then customize the generation method.

[0048] The generation unit can select the optimal generation method for vibrations and wind by considering the user's device information. For example, the generation unit can adjust the generation method based on the performance of the device the user is using. For example, the generation unit can refer to the user's device information and select a generation method based on the device's performance. The generation unit can also customize the generation method based on the screen size of the device the user is using. For example, the generation unit can adjust the vibration and wind generation method based on the device's screen size. This allows the generation unit to select the optimal generation method by considering the user's device information, resulting in a more appropriate user experience. Some or all of the above-described processes in the generation unit may be performed using AI, for example, or without AI. For example, the generation unit can input the user's device information into a generation AI, which can then select the optimal generation method.

[0049] The control unit can improve control accuracy by referring to past control data when controlling vibration and wind. For example, the control unit can refer to past control data for vibration and wind and apply the optimal control method. For example, the control unit can adjust the vibration and wind control method based on past data. The control unit can also refer to the user's past sensory history and apply a control method tailored to their preferences. For example, the control unit can refer to the user's past sensory history and adjust the vibration and wind control method. As a result, the control unit improves control accuracy by referring to past control data. Some or all of the above processing in the control unit may be performed using AI, for example, or without AI. For example, the control unit can input past control data into a generating AI, which can then improve control accuracy.

[0050] The control unit can adjust the level of detail in vibration and wind control based on the importance of the scene. For example, in climactic scenes, the control unit can perform detailed control, precisely controlling the intensity of vibration and wind. For instance, the control unit can analyze the video and audio of climactic scenes in detail and adjust the vibration and wind control methods. Conversely, in everyday scenes, the control unit can perform simplified control, reducing the intensity of vibration and wind. For example, the control unit can analyze the video and audio of everyday scenes in a simplified manner and adjust the vibration and wind control methods. This allows the control unit to adjust the level of detail in control based on the importance of the scene, enabling a more appropriate sensory experience. Some or all of the above-described processes in the control unit may be performed using AI, for example, or without AI. For example, the control unit can input scene importance data into a generating AI, which can then adjust the level of detail in control.

[0051] The control unit can customize the control method for vibration and wind by taking into account the user's viewing history. For example, the control unit can adjust the control method based on the genre of movies the user has watched in the past. For example, the control unit can refer to the user's viewing history and apply a control method tailored to their preferences. The control unit can also customize the control method based on the type of scenes the user prefers. For example, the control unit can analyze the type of scenes the user prefers and adjust the vibration and wind control methods. This allows the control unit to customize the control method by taking into account the user's viewing history, enabling a more appropriate experience. Some or all of the above processing in the control unit may be performed using AI, for example, or without AI. For example, the control unit can input the user's viewing history data into a generating AI, which can then customize the control method.

[0052] The control unit can select the optimal control method when controlling vibration and wind, taking into account the user's device information. For example, the control unit can adjust the control method based on the performance of the device the user is using. For example, the control unit can refer to the user's device information and select a control method based on the device's performance. The control unit can also customize the control method based on the screen size of the device the user is using. For example, the control unit can adjust the vibration and wind control method based on the device's screen size. This allows the control unit to select the optimal control method by taking the user's device information into account, resulting in a more appropriate user experience. Some or all of the above processing in the control unit may be performed using AI, for example, or without AI. For example, the control unit can input the user's device information into a generating AI, which can then select the optimal control method.

[0053] The sensory unit can improve the accuracy of sensory perception by referring to past sensory perception data during sensory perception. For example, the sensory unit can refer to data on vibrations and wind experienced in the past and apply the optimal sensory perception method. For example, the sensory unit can adjust the way vibrations and wind are perceived based on past data. The sensory unit can also refer to the user's past sensory perception history and apply a sensory perception method tailored to their preferences. For example, the sensory unit can refer to the user's past sensory perception history and adjust the way vibrations and wind are perceived. As a result, the sensory unit improves the accuracy of sensory perception by referring to past sensory perception data. Some or all of the above processing in the sensory unit may be performed using AI, for example, or without AI. For example, the sensory unit can input past sensory perception data into a generating AI, which can then improve the accuracy of sensory perception.

[0054] The sensory unit can adjust the level of detail of the sensory experience based on the importance of the scene during the experience. For example, in a climax scene, the sensory unit can provide a detailed sensory experience, precisely controlling the intensity of vibrations and wind. For example, the sensory unit can analyze the video and audio of a climax scene in detail and adjust how vibrations and wind are perceived. Conversely, in everyday scenes, the sensory unit can provide a simplified sensory experience, reducing the intensity of vibrations and wind. For example, the sensory unit can analyze the video and audio of an everyday scene in a simplified manner and adjust how vibrations and wind are perceived. In this way, the sensory unit can provide a more appropriate sensory experience by adjusting the level of detail of the sensory experience based on the importance of the scene. Some or all of the above processing in the sensory unit may be performed using AI, for example, or without AI. For example, the sensory unit can input scene importance data into a generating AI, which can then adjust the level of detail of the sensory experience.

[0055] The sensory unit can customize the sensory experience by considering the user's viewing history during the experience. For example, the sensory unit can adjust the sensory experience based on the genre of movies the user has watched in the past. For example, the sensory unit can refer to the user's viewing history and apply a sensory experience tailored to their preferences. The sensory unit can also customize the sensory experience based on the type of scenes the user prefers. For example, the sensory unit can analyze the type of scenes the user prefers and adjust the vibration and wind sensations. In this way, the sensory unit can customize the sensory experience by considering the user's viewing history, enabling a more appropriate experience. Some or all of the above processing in the sensory unit may be performed using AI, for example, or without AI. For example, the sensory unit can input the user's viewing history data into a generating AI, which can then customize the sensory experience.

[0056] The sensory unit can select the optimal sensory experience method while considering the user's device information. For example, the sensory unit can adjust the sensory experience method based on the performance of the device the user is using. For example, the sensory unit can refer to the user's device information and select a sensory experience method based on the device's performance. The sensory unit can also customize the sensory experience method based on the screen size of the device the user is using. For example, the sensory unit can adjust the vibration and wind sensations based on the device's screen size. This allows the sensory unit to select the optimal sensory experience method while considering the user's device information, enabling a more appropriate experience. Some or all of the above processing in the sensory unit may be performed using AI, for example, or without AI. For example, the sensory unit can input the user's device information into a generating AI, which can then select the optimal sensory experience method.

[0057] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0058] An immersive home theater system can generate scents tailored to movie scenes based on the user's preferences and viewing history. For example, it can generate a spicy scent during action scenes and a lavender scent during relaxing scenes. This allows users to enjoy scents that match the movie scenes, providing a more immersive experience. Furthermore, scent generation can be optimized by referencing past viewing history and preference data. For instance, it can learn scents a user has liked in the past and generate the same scent in similar scenes. In addition, scent generation can be combined with other sensory elements (such as vibration or wind). This allows users to enjoy multiple senses simultaneously, providing a more realistic experience.

[0059] Immersive home theater systems can detect the user's seat position and posture, and adjust the generation of vibrations and wind based on seat movements. For example, if the user is leaning forward, the system can generate strong vibrations and wind, while if the user is sitting relaxed, it can generate gentler vibrations and wind. This allows for a more appropriate experience based on the user's posture. Furthermore, seat movement data can be compared with past data to improve analysis accuracy. For example, by referring to past seat movement data and learning the user's posture patterns, it becomes possible to generate more appropriate vibrations and wind. In addition, seat movement data can be analyzed in combination with other data (e.g., heart rate and gaze data). This allows for a more accurate estimation of the user's emotions and state, and optimizes the experience.

[0060] Immersive home theater systems can analyze the tone and volume of the user's voice and adjust the generation of vibrations and wind based on changes in the voice. For example, if the user is excited and speaking loudly, the system can generate strong vibrations and wind, while if the user is speaking quietly, it can generate gentler vibrations and wind. This allows for a more realistic experience based on changes in the user's voice. Furthermore, voice data can be compared with past data to improve analysis accuracy. For example, by referring to past voice data and learning the user's voice patterns, it becomes possible to generate more appropriate vibrations and wind. In addition, voice data can be analyzed in combination with other data (e.g., heart rate and eye gaze data). This allows for a more accurate estimation of the user's emotions and state, and optimizes the immersive experience.

[0061] An immersive home theater system can monitor changes in the user's weight and adjust the generation of vibrations and wind based on those changes. For example, if the user is sitting with weight on the device, the system can generate strong vibrations and wind, while if the user is sitting without weight on the device, it can generate gentler vibrations and wind. This allows for a more appropriate experience based on the user's weight changes. Furthermore, weight data can be compared with past data to improve analysis accuracy. For example, by referring to past weight data and learning the user's weight change patterns, it becomes possible to generate more appropriate vibrations and wind. In addition, weight data can be analyzed in combination with other data (e.g., heart rate and gaze data). This allows for a more accurate estimation of the user's emotions and state, and optimizes the experience.

[0062] An immersive home theater system can analyze ambient sounds around the user and adjust the generation of vibrations and wind based on changes in those sounds. For example, in a quiet environment, the system can generate gentle vibrations and wind, while in a noisy environment, it can generate stronger vibrations and wind. This allows for a more appropriate sensory experience based on the user's surroundings. Furthermore, the accuracy of the analysis can be improved by comparing the ambient sound data with past data. For instance, by referencing past ambient sound data and learning the user's ambient sound patterns, more appropriate vibrations and wind can be generated. In addition, ambient sound data can be analyzed in combination with other data (such as heart rate and gaze data). This allows for a more accurate estimation of the user's emotions and state, and optimizes the sensory experience.

[0063] The following briefly describes the processing flow for example form 1.

[0064] Step 1: The analysis unit analyzes the video and audio. For example, the analysis unit recognizes and analyzes the video and audio of a movie. The analysis unit can use AI to analyze the content of the video and audio. For example, the analysis unit can use a speech recognition algorithm to analyze the audio of a movie. The analysis unit can also use an image recognition algorithm to analyze the video of a movie. Step 2: The generation unit generates vibrations and wind based on the information analyzed by the analysis unit. The generation unit generates vibrations and wind using, for example, a vibration motor or a blower. The generation unit can adjust the method of generating vibrations and wind using AI. For example, the generation unit adjusts the method of generating vibration patterns based on the information analyzed by the AI. The generation unit can also set the wind intensity and direction based on the information analyzed by the AI. Step 3: The control unit controls the vibrations and wind generated by the generation unit. The control unit controls the vibrations and wind using, for example, feedback control or PID control. The control unit can use AI to adjust the control method for vibrations and wind. For example, the control unit performs real-time control based on information analyzed by the AI. The control unit can also adjust the intensity and duration of vibrations and wind based on information analyzed by the AI. Step 4: The sensory unit experiences vibrations and wind controlled by the control unit. The sensory unit experiences vibrations and wind using, for example, bone conduction earphones or a mini fan. The sensory unit can adjust the way it experiences vibrations using AI. For example, the sensory unit adjusts the intensity and duration of vibrations and wind based on information analyzed by the AI. The sensory unit can also enjoy movies using AR glasses. The sensory unit provides people with visual or hearing impairments with the opportunity to enjoy movies.

[0065] (Example of form 2) An immersive home theater system according to an embodiment of the present invention is a system that utilizes AI to realize an immersive home theater experience similar to that of a movie theater, even at home. This immersive home theater system makes movie viewing more realistic and immersive by having AI analyze video and audio and generate vibrations and wind. First, the immersive home theater system uses AI to recognize and analyze the video and audio of a movie. Based on the content of the video and audio, the AI ​​determines what kind of vibrations and wind to generate in which scenes. Next, the immersive home theater system controls devices such as bone conduction earphones and mini blowers based on the information analyzed by the AI. This allows the user to experience vibrations and wind in accordance with the scenes in the movie. Furthermore, by using AR glasses, the immersive home theater system allows users to enjoy movies in their own private space. This system also provides opportunities for people with visual or hearing impairments to enjoy movies. In addition, this system can provide new added value to video rental companies and movie / video streaming companies. For example, the immersive home theater system provides users with a sense of realism by generating vibrations and wind in accordance with the scenes in the movie. For example, the system can generate strong vibrations and wind during action scenes, and gentle vibrations and wind during quiet scenes. This allows users to enjoy a sensory experience that matches the movie scene. Furthermore, the immersive home theater system can estimate the user's emotions and adjust the vibration and wind generation method based on those emotions. For example, it can generate strong vibrations and wind when the user is excited, and gentle vibrations and wind when the user is relaxed. This allows users to enjoy a sensory experience that matches their emotions. In addition, the immersive home theater system can improve its analysis and generation accuracy by referring to past analysis and generation data. For example, it can refer to data from the same movie analyzed in the past to optimize the vibration and wind generation patterns for each scene. This ensures that the immersive home theater system always provides the optimal experience. As a result, the immersive home theater system can make movie watching more realistic and immersive.

[0066] The immersive home theater system according to this embodiment comprises an analysis unit, a generation unit, a control unit, and an immersive unit. The analysis unit analyzes video and audio. For example, the analysis unit recognizes and analyzes the video and audio of a movie. The analysis unit can use AI to analyze the content of the video and audio. For example, the analysis unit uses a speech recognition algorithm to analyze the audio of a movie. The analysis unit can also use an image recognition algorithm to analyze the video of a movie. The generation unit generates vibrations and wind based on the information analyzed by the analysis unit. For example, the generation unit generates vibrations and wind using a vibration motor or a blower. The generation unit can use AI to adjust the method of generating vibrations and wind. For example, the generation unit adjusts the method of generating vibration patterns based on information analyzed by the AI. The generation unit can also set the wind intensity and direction based on information analyzed by the AI. The control unit controls the vibrations and wind generated by the generation unit. For example, the control unit controls vibrations and wind using feedback control or PID control. The control unit can use AI to adjust the method of controlling vibrations and wind. For example, the control unit performs real-time control based on information analyzed by the AI. The control unit can also adjust the intensity and duration of vibrations and wind based on the information analyzed by the AI. The sensory unit experiences the vibrations and wind controlled by the control unit. The sensory unit experiences the vibrations and wind using, for example, bone conduction earphones or a mini fan. The sensory unit can adjust the way it experiences the vibrations using the AI. For example, the sensory unit adjusts the intensity and duration of vibrations and wind based on the information analyzed by the AI. The sensory unit can also enjoy movies using AR glasses. The sensory unit provides people with visual or hearing impairments with the opportunity to enjoy movies. As a result, the sensory home theater system according to this embodiment can make movie viewing more realistic and immersive.

[0067] The analysis unit analyzes video and audio. For example, the analysis unit recognizes and analyzes the video and audio of a movie. The analysis unit can use AI to analyze the content of video and audio. Specifically, the analysis unit uses a speech recognition algorithm to analyze the audio of a movie. The speech recognition algorithm converts the audio data into text data and identifies the dialogue and sound effects in the movie. This allows for accurate understanding of audio information corresponding to the movie scene. The analysis unit can also analyze the video of a movie using an image recognition algorithm. The image recognition algorithm analyzes the video data frame by frame and identifies movie scenes, characters, backgrounds, etc. This allows for accurate understanding of video information corresponding to the movie scene. Furthermore, the analysis unit can use AI to analyze the content of video and audio in real time. For example, in an action scene in a movie, the AI ​​quickly detects changes in audio and video and sends the analysis results to the generation unit. This allows the analysis unit to quickly and accurately generate vibrations and wind according to the movie scene.

[0068] The generation unit generates vibrations and wind based on information analyzed by the analysis unit. The generation unit generates vibrations and wind using, for example, a vibration motor or a blower. Specifically, the vibration motor generates vibrations in action scenes and explosion scenes in movies, providing users with a sense of realism. The blower generates wind in landscape scenes and storm scenes in movies, providing users with a realistic experience. The generation unit can adjust the method of generating vibrations and wind using AI. For example, the generation unit adjusts the method of generating vibration patterns based on information analyzed by the AI. The AI ​​generates the optimal vibration pattern according to the movie scene, providing users with a realistic experience. The generation unit can also set the intensity and direction of wind based on information analyzed by the AI. The AI ​​sets the optimal wind intensity and direction according to the movie scene, providing users with a realistic experience. Furthermore, the generation unit can generate vibrations and wind in real time. This allows the generation unit to quickly and accurately generate vibrations and wind according to movie scenes.

[0069] The control unit controls the vibrations and wind generated by the generation unit. The control unit controls the vibrations and wind using methods such as feedback control and PID control. Specifically, feedback control monitors the intensity and direction of the generated vibrations and wind in real time and adjusts them as needed. PID control predicts the intensity and direction of the generated vibrations and wind and performs optimal control. The control unit can use AI to adjust the vibration and wind control methods. For example, the control unit performs real-time control based on information analyzed by the AI. The AI ​​generates the optimal control method according to the movie scene, providing the user with a realistic experience. Furthermore, the control unit can adjust the intensity and duration of the vibrations and wind based on information analyzed by the AI. The AI ​​sets the optimal intensity and duration according to the movie scene, providing the user with a realistic experience. In addition, the control unit can control the vibrations and wind in real time. This allows the control unit to quickly and accurately control the vibrations and wind according to the movie scene.

[0070] The sensory unit experiences vibrations and wind controlled by the control unit. For example, the sensory unit uses bone conduction earphones or a mini fan to simulate vibrations and wind. Specifically, bone conduction earphones transmit movie audio as vibrations to the user, providing a realistic experience. The mini fan generates wind during landscape or storm scenes in movies, providing a realistic experience. The sensory unit can adjust the sensory experience using AI. For example, the sensory unit adjusts the intensity and duration of vibrations and wind based on information analyzed by the AI. The AI ​​sets the optimal intensity and duration according to the movie scene, providing a realistic experience. Furthermore, the sensory unit can also enjoy movies using AR glasses. AR glasses provide the user with movie footage as augmented reality, offering a realistic experience. In addition, the sensory unit provides opportunities for people with visual or hearing impairments to enjoy movies. For example, bone conduction earphones transmit movie audio as vibrations to people with hearing impairments, providing them with the opportunity to enjoy movies. This allows the sensory experience to make movie viewing more realistic and immersive.

[0071] The analysis unit can recognize and analyze video and audio. For example, the analysis unit can recognize and analyze the audio of a movie using a speech recognition algorithm. For example, the analysis unit can recognize and analyze the dialogue and sound effects of a movie. The analysis unit can also recognize and analyze the video of a movie using an image recognition algorithm. For example, the analysis unit can recognize and analyze scenes and characters in a movie. As a result, the analysis unit can obtain the information necessary for generating vibrations and wind by recognizing and analyzing video and audio. Some or all of the above processing in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input the video and audio of a movie into a generation AI, which can then recognize and analyze the video and audio.

[0072] The generation unit can generate vibrations and wind based on the analyzed information. For example, the generation unit can generate vibrations using a vibration motor. For example, the generation unit can change the intensity of the vibrations by adjusting the rotation speed of the vibration motor. The generation unit can also generate wind using a blower. For example, the generation unit can change the intensity of the wind by adjusting the airflow of the blower. Furthermore, the generation unit can adjust the direction of the wind. For example, the generation unit can change the direction of the wind by changing the angle of the blower. In this way, the generation unit can provide a tactile experience that matches the movie scene by generating vibrations and wind based on the analyzed information. Some or all of the above processing in the generation unit may be performed using AI, for example, or without AI. For example, the generation unit can input the analyzed information into a generation AI, which can then determine how to generate vibrations and wind.

[0073] The control unit can control the generated vibrations and wind. The control unit controls the vibrations and wind, for example, using feedback control. For example, the control unit can control the intensity of vibrations by adjusting the rotation speed of the vibration motor in real time. The control unit can also control the intensity of wind by adjusting the airflow of the fan in real time. Furthermore, the control unit can control the direction of wind by adjusting the angle of the fan in real time. In this way, the control unit can optimize the user's experience by controlling the generated vibrations and wind. Some or all of the above processing in the control unit may be performed using AI, for example, or without AI. For example, the control unit can input the generated vibration and wind data into a generating AI, which can then determine how to control the vibrations and wind.

[0074] The sensory unit can experience controlled vibrations and wind. For example, the sensory unit can experience vibrations using bone conduction earphones. For example, by wearing bone conduction earphones, the sensory unit can transmit vibrations directly to the bones. The sensory unit can also experience wind using a mini fan. For example, the sensory unit can use a mini fan to blow wind onto its face or body. In this way, the sensory unit can enjoy watching movies more realistically by experiencing controlled vibrations and wind. Some or all of the above processing in the sensory unit may be performed using AI, for example, or without AI. For example, the sensory unit can input data on controlled vibrations and wind into a generating AI, which can then determine how to experience them.

[0075] The sensory unit may include bone conduction earphones or a mini fan. The sensory unit can, for example, experience vibrations using bone conduction earphones. For example, the sensory unit can wear bone conduction earphones in its ears and transmit vibrations directly to the bone. The sensory unit can also experience wind using a mini fan. For example, the sensory unit can use a mini fan to blow wind onto its face or body. Thus, the sensory unit can effectively experience vibrations and wind by using bone conduction earphones or a mini fan. Some or all of the above processing in the sensory unit may be performed using AI, for example, or without AI. For example, the sensory unit can input data from bone conduction earphones or a mini fan into a generating AI, which can then determine the method of sensory experience.

[0076] The immersive unit can enjoy movies using AR glasses. The immersive unit can, for example, enjoy movies in its own private space by wearing AR glasses. For example, the immersive unit can display movie footage in front of the user's eyes using AR glasses. This allows the immersive unit to enjoy movies in its own private space by using AR glasses. Some or all of the above processing in the immersive unit may be performed using AI, for example, or without AI. For example, the immersive unit can input data from the AR glasses into a generating AI, which can then determine the method of experience.

[0077] The sensory experience unit can provide people with visual or hearing impairments with the opportunity to enjoy movies. For example, the sensory experience unit can provide visually impaired people with the opportunity to enjoy movies by providing audio guides. For example, the sensory experience unit can generate audio guides in accordance with movie scenes and provide them to visually impaired people. The sensory experience unit can also provide hearing impaired people with the opportunity to enjoy movies by providing subtitles and vibrations. For example, the sensory experience unit can display movie dialogue as subtitles and provide them to hearing impaired people. In this way, the sensory experience unit can provide people with visual or hearing impairments with the opportunity to enjoy movies. Some or all of the above processing in the sensory experience unit may be performed using AI, for example, or without AI. For example, the sensory experience unit can input data of people with visual or hearing impairments into a generating AI, and the generating AI can determine the method of experience.

[0078] The analysis unit can estimate the user's emotions and adjust the video and audio analysis methods based on the estimated user emotions. For example, the analysis unit can estimate the user's emotions using facial recognition technology. For example, the analysis unit can analyze the user's facial expressions captured by a camera and estimate their emotions. The analysis unit can also estimate the user's emotions using voice analysis technology. For example, the analysis unit can analyze the tone and speed of the user's voice recorded by a microphone and estimate their emotions. This allows the analysis unit to adjust the video and audio analysis methods based on the user's emotions, enabling the generation of more appropriate vibrations and wind. Emotion estimation is achieved using an emotion estimation function, for example, with an emotion engine or a generative AI. The generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above-described processing in the analysis unit may be performed using AI, or not using AI. For example, the analysis unit can input user emotion data into the generative AI, which can then adjust the video and audio analysis methods.

[0079] The analysis unit can improve analysis accuracy by referring to past analysis data when analyzing video and audio. For example, the analysis unit can refer to data from the same movie that has been analyzed in the past to optimize the vibration and wind generation patterns for each scene. For example, the analysis unit can adjust the vibration and wind generation method based on past data. The analysis unit can also refer to the user's past viewing history and apply an analysis method tailored to their preferences. For example, the analysis unit can adjust the analysis method based on the genre of movies the user has watched in the past. In this way, the analysis unit improves analysis accuracy by referring to past analysis data. Some or all of the above processing in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input past analysis data into a generation AI, which can then improve the analysis accuracy.

[0080] The analysis unit can adjust the level of detail in its analysis of video and audio based on the importance of each scene. For example, in climactic scenes, the analysis unit can perform a detailed analysis to precisely control the generation of vibrations and wind. For instance, the analysis unit can analyze the video and audio of a climactic scene in detail and adjust the method of generating vibrations and wind. Conversely, in everyday scenes, the analysis unit can perform a simplified analysis to reduce the generation of vibrations and wind. For example, the analysis unit can simplify the analysis of video and audio in everyday scenes and adjust the method of generating vibrations and wind. This allows the analysis unit to generate more appropriate vibrations and wind by adjusting the level of detail in its analysis based on the importance of each scene. Some or all of the above processing in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input scene importance data into a generation AI, which can then adjust the level of detail in its analysis.

[0081] The analysis unit can estimate the user's emotions and determine the priority of the analysis results based on the estimated user emotions. For example, if the user is excited, the analysis unit will prioritize the analysis results of action scenes. For example, the analysis unit can estimate the user's emotions and adjust the vibration and wind generation methods based on the priority of the action scene analysis results. Also, if the user is relaxed, the analysis unit can prioritize the analysis results of quiet scenes. For example, the analysis unit can estimate the user's emotions and adjust the vibration and wind generation methods based on the priority of the quiet scene analysis results. This allows the analysis unit to generate more appropriate vibrations and wind by determining the priority of the analysis results based on the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or a generative AI. The generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input user emotion data into a generative AI, which can then determine the priority of the analysis results.

[0082] The analysis unit can customize its analysis method when analyzing video and audio, taking into account the user's viewing history. For example, the analysis unit can adjust its analysis method based on the genre of movies the user has watched in the past. For example, the analysis unit can refer to the user's viewing history and apply an analysis method tailored to their preferences. The analysis unit can also customize its analysis method based on the type of scenes the user prefers. For example, the analysis unit can analyze the type of scenes the user prefers and adjust the vibration and wind generation method. This allows the analysis unit to generate more appropriate vibrations and wind by customizing its analysis method while considering the user's viewing history. Some or all of the above processing in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input the user's viewing history data into a generation AI, which can then customize the analysis method.

[0083] The analysis unit can select the optimal analysis method when analyzing video and audio, taking into account the user's device information. For example, the analysis unit can adjust the analysis method based on the performance of the device the user is using. For example, the analysis unit can refer to the user's device information and select an analysis method based on the device's performance. The analysis unit can also customize the analysis method based on the screen size of the device the user is using. For example, the analysis unit can adjust the video and audio analysis method based on the device's screen size. This allows the analysis unit to select the optimal analysis method while considering the user's device information, enabling the generation of more appropriate vibrations and wind. Some or all of the above processing in the analysis unit may be performed using AI, for example, or without AI. For example, the analysis unit can input the user's device information into a generation AI, which can then select the optimal analysis method.

[0084] The generation unit can estimate the user's emotions and adjust the method of generating vibrations and wind based on the estimated user emotions. For example, if the user is excited, the generation unit can generate strong vibrations and wind. For example, the generation unit can estimate the user's emotions and generate strong vibrations and wind. The generation unit can also generate gentle vibrations and wind if the user is relaxed. For example, the generation unit can estimate the user's emotions and generate gentle vibrations and wind. This allows the generation unit to provide a more appropriate sensory experience by adjusting the method of generating vibrations and wind based on the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or a generation AI. The generation AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the generation unit may be performed using AI, for example, or without AI. For example, the generation unit can input user emotion data into the generation AI, which can then adjust the method of generating vibrations and wind.

[0085] The generation unit can improve generation accuracy by referring to past generation data when generating vibrations and wind. For example, the generation unit can refer to previously generated vibration and wind data and apply the optimal generation method. For example, the generation unit can adjust the vibration and wind generation method based on past data. The generation unit can also refer to the user's past sensory history and apply a generation method tailored to their preferences. For example, the generation unit can refer to the user's past sensory history and adjust the vibration and wind generation method. As a result, the generation unit improves generation accuracy by referring to past generation data. Some or all of the above processing in the generation unit may be performed using AI, for example, or without AI. For example, the generation unit can input past generation data into a generation AI, which can then improve generation accuracy.

[0086] The generation unit can adjust the level of detail in generating vibrations and wind based on the importance of the scene. For example, in climax scenes, the generation unit performs detailed generation and precisely controls the intensity of vibrations and wind. For example, the generation unit can analyze the video and audio of climax scenes in detail and adjust the method of generating vibrations and wind. Conversely, in everyday scenes, the generation unit can perform simplified generation and reduce the intensity of vibrations and wind. For example, the generation unit can analyze the video and audio of everyday scenes in a simplified manner and adjust the method of generating vibrations and wind. This allows the generation unit to adjust the level of detail in generation based on the importance of the scene, enabling a more appropriate experience. Some or all of the above processing in the generation unit may be performed using AI, for example, or without AI. For example, the generation unit can input scene importance data into a generation AI, which can then adjust the level of detail in generation.

[0087] The generation unit can estimate the user's emotions and determine the priority of vibrations and wind to generate based on the estimated user emotions. For example, if the user is excited, the generation unit will prioritize generating strong vibrations and wind. For example, the generation unit can estimate the user's emotions and prioritize generating strong vibrations and wind. Also, if the user is relaxed, the generation unit can prioritize generating gentle vibrations and wind. For example, the generation unit can estimate the user's emotions and prioritize generating gentle vibrations and wind. In this way, the generation unit can determine the priority of vibrations and wind to generate based on the user's emotions, enabling a more appropriate sensory experience. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or a generation AI. The generation AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the generation unit may be performed using AI, for example, or not using AI. For example, the generation unit can input user emotion data into the generation AI, and the generation AI can determine the priority of vibrations and wind.

[0088] The generation unit can customize the generation method for vibrations and wind by taking into account the user's viewing history. For example, the generation unit can adjust the generation method based on the genre of movies the user has watched in the past. For example, the generation unit can refer to the user's viewing history and apply a generation method tailored to their preferences. The generation unit can also customize the generation method based on the type of scenes the user prefers. For example, the generation unit can analyze the type of scenes the user prefers and adjust the vibration and wind generation method. In this way, the generation unit can customize the generation method by taking the user's viewing history into account, enabling a more appropriate experience. Some or all of the above processing in the generation unit may be performed using AI, for example, or without AI. For example, the generation unit can input the user's viewing history data into a generation AI, which can then customize the generation method.

[0089] The generation unit can select the optimal generation method for vibrations and wind by considering the user's device information. For example, the generation unit can adjust the generation method based on the performance of the device the user is using. For example, the generation unit can refer to the user's device information and select a generation method based on the device's performance. The generation unit can also customize the generation method based on the screen size of the device the user is using. For example, the generation unit can adjust the vibration and wind generation method based on the device's screen size. This allows the generation unit to select the optimal generation method by considering the user's device information, resulting in a more appropriate user experience. Some or all of the above-described processes in the generation unit may be performed using AI, for example, or without AI. For example, the generation unit can input the user's device information into a generation AI, which can then select the optimal generation method.

[0090] The control unit can estimate the user's emotions and adjust the vibration and wind control methods based on the estimated emotions. For example, if the user is excited, the control unit may prioritize strong vibrations and wind. For example, the control unit can estimate the user's emotions and prioritize strong vibrations and wind. Also, if the user is relaxed, the control unit may prioritize gentle vibrations and wind. For example, the control unit may estimate the user's emotions and prioritize gentle vibrations and wind. This allows the control unit to provide a more appropriate sensory experience by adjusting the vibration and wind control methods based on the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generative AI. The generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the control unit may be performed using AI, or not using AI. For example, the control unit can input user emotion data into the generative AI, which can then adjust the vibration and wind control methods.

[0091] The control unit can improve control accuracy by referring to past control data when controlling vibration and wind. For example, the control unit can refer to past control data for vibration and wind and apply the optimal control method. For example, the control unit can adjust the vibration and wind control method based on past data. The control unit can also refer to the user's past sensory history and apply a control method tailored to their preferences. For example, the control unit can refer to the user's past sensory history and adjust the vibration and wind control method. As a result, the control unit improves control accuracy by referring to past control data. Some or all of the above processing in the control unit may be performed using AI, for example, or without AI. For example, the control unit can input past control data into a generating AI, which can then improve control accuracy.

[0092] The control unit can adjust the level of detail in vibration and wind control based on the importance of the scene. For example, in climactic scenes, the control unit can perform detailed control, precisely controlling the intensity of vibration and wind. For instance, the control unit can analyze the video and audio of climactic scenes in detail and adjust the vibration and wind control methods. Conversely, in everyday scenes, the control unit can perform simplified control, reducing the intensity of vibration and wind. For example, the control unit can analyze the video and audio of everyday scenes in a simplified manner and adjust the vibration and wind control methods. This allows the control unit to adjust the level of detail in control based on the importance of the scene, enabling a more appropriate sensory experience. Some or all of the above-described processes in the control unit may be performed using AI, for example, or without AI. For example, the control unit can input scene importance data into a generating AI, which can then adjust the level of detail in control.

[0093] The control unit can estimate the user's emotions and determine the priority of vibrations and wind to control based on the estimated emotions. For example, if the user is excited, the control unit may prioritize strong vibrations and wind. For example, the control unit can estimate the user's emotions and prioritize strong vibrations and wind. Also, if the user is relaxed, the control unit may prioritize gentle vibrations and wind. For example, the control unit may estimate the user's emotions and prioritize gentle vibrations and wind. This allows the control unit to provide a more appropriate sensory experience by determining the priority of vibrations and wind to control based on the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generative AI. The generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the control unit may be performed using AI, for example, or without AI. For example, the control unit can input user emotion data into a generative AI, which can then determine the priority of vibrations and wind.

[0094] The control unit can customize the control method for vibration and wind by taking into account the user's viewing history. For example, the control unit can adjust the control method based on the genre of movies the user has watched in the past. For example, the control unit can refer to the user's viewing history and apply a control method tailored to their preferences. The control unit can also customize the control method based on the type of scenes the user prefers. For example, the control unit can analyze the type of scenes the user prefers and adjust the vibration and wind control methods. This allows the control unit to customize the control method by taking into account the user's viewing history, enabling a more appropriate experience. Some or all of the above processing in the control unit may be performed using AI, for example, or without AI. For example, the control unit can input the user's viewing history data into a generating AI, which can then customize the control method.

[0095] The control unit can select the optimal control method when controlling vibration and wind, taking into account the user's device information. For example, the control unit can adjust the control method based on the performance of the device the user is using. For example, the control unit can refer to the user's device information and select a control method based on the device's performance. The control unit can also customize the control method based on the screen size of the device the user is using. For example, the control unit can adjust the vibration and wind control method based on the device's screen size. This allows the control unit to select the optimal control method by taking the user's device information into account, resulting in a more appropriate user experience. Some or all of the above processing in the control unit may be performed using AI, for example, or without AI. For example, the control unit can input the user's device information into a generating AI, which can then select the optimal control method.

[0096] The sensory unit can estimate the user's emotions and adjust the sensory experience based on those emotions. For example, if the user is excited, the sensory unit can make them experience strong vibrations or wind. For example, the sensory unit can estimate the user's emotions and make them experience strong vibrations or wind. Also, if the user is relaxed, the sensory unit can make them experience gentle vibrations or wind. For example, the sensory unit can estimate the user's emotions and make them experience gentle vibrations or wind. In this way, the sensory unit can adjust the sensory experience based on the user's emotions, enabling a more appropriate experience. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or a generative AI. The generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the sensory unit may be performed using AI, for example, or without AI. For example, the sensory unit can input user emotion data into the generative AI, which can then adjust the sensory experience.

[0097] The sensory unit can improve the accuracy of sensory perception by referring to past sensory perception data during sensory perception. For example, the sensory unit can refer to data on vibrations and wind experienced in the past and apply the optimal sensory perception method. For example, the sensory unit can adjust the way vibrations and wind are perceived based on past data. The sensory unit can also refer to the user's past sensory perception history and apply a sensory perception method tailored to their preferences. For example, the sensory unit can refer to the user's past sensory perception history and adjust the way vibrations and wind are perceived. As a result, the sensory unit improves the accuracy of sensory perception by referring to past sensory perception data. Some or all of the above processing in the sensory unit may be performed using AI, for example, or without AI. For example, the sensory unit can input past sensory perception data into a generating AI, which can then improve the accuracy of sensory perception.

[0098] The sensory unit can adjust the level of detail of the sensory experience based on the importance of the scene during the experience. For example, in a climax scene, the sensory unit can provide a detailed sensory experience, precisely controlling the intensity of vibrations and wind. For example, the sensory unit can analyze the video and audio of a climax scene in detail and adjust how vibrations and wind are perceived. Conversely, in everyday scenes, the sensory unit can provide a simplified sensory experience, reducing the intensity of vibrations and wind. For example, the sensory unit can analyze the video and audio of an everyday scene in a simplified manner and adjust how vibrations and wind are perceived. In this way, the sensory unit can provide a more appropriate sensory experience by adjusting the level of detail of the sensory experience based on the importance of the scene. Some or all of the above processing in the sensory unit may be performed using AI, for example, or without AI. For example, the sensory unit can input scene importance data into a generating AI, which can then adjust the level of detail of the sensory experience.

[0099] The sensory unit can estimate the user's emotions and determine the priority of vibrations and winds to be experienced based on the estimated emotions. For example, if the user is excited, the sensory unit will prioritize strong vibrations and winds. For example, the sensory unit can estimate the user's emotions and prioritize strong vibrations and winds to be experienced. Also, if the user is relaxed, the sensory unit can prioritize gentle vibrations and winds to be experienced. For example, the sensory unit can estimate the user's emotions and prioritize gentle vibrations and winds to be experienced. In this way, the sensory unit can determine the priority of vibrations and winds to be experienced based on the user's emotions, enabling a more appropriate sensory experience. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generative AI. The generative AI is a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above processing in the sensory unit may be performed using AI, for example, or without using AI. For example, the sensory unit can input user emotion data into a generating AI, which can then determine the priority of vibrations and wind that the user will experience.

[0100] The sensory unit can customize the sensory experience by considering the user's viewing history during the experience. For example, the sensory unit can adjust the sensory experience based on the genre of movies the user has watched in the past. For example, the sensory unit can refer to the user's viewing history and apply a sensory experience tailored to their preferences. The sensory unit can also customize the sensory experience based on the type of scenes the user prefers. For example, the sensory unit can analyze the type of scenes the user prefers and adjust the vibration and wind sensations. In this way, the sensory unit can customize the sensory experience by considering the user's viewing history, enabling a more appropriate experience. Some or all of the above processing in the sensory unit may be performed using AI, for example, or without AI. For example, the sensory unit can input the user's viewing history data into a generating AI, which can then customize the sensory experience.

[0101] The sensory unit can select the optimal sensory experience method while considering the user's device information. For example, the sensory unit can adjust the sensory experience method based on the performance of the device the user is using. For example, the sensory unit can refer to the user's device information and select a sensory experience method based on the device's performance. The sensory unit can also customize the sensory experience method based on the screen size of the device the user is using. For example, the sensory unit can adjust the vibration and wind sensations based on the device's screen size. This allows the sensory unit to select the optimal sensory experience method while considering the user's device information, enabling a more appropriate experience. Some or all of the above processing in the sensory unit may be performed using AI, for example, or without AI. For example, the sensory unit can input the user's device information into a generating AI, which can then select the optimal sensory experience method.

[0102] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0103] Immersive home theater systems can monitor the user's heart rate and adjust the generation of vibrations and wind based on changes in heart rate. For example, if the user's heart rate increases, the system can generate stronger vibrations and wind, and if the heart rate decreases, it can generate gentler vibrations and wind. This allows for a more realistic experience based on the user's physiological responses. Furthermore, heart rate data can be compared with past data to improve analysis accuracy. For example, by referring to past heart rate data and learning the user's response patterns, it becomes possible to generate more appropriate vibrations and wind. In addition, heart rate data can be analyzed in combination with other physiological data (e.g., skin electrical activity and respiratory rate). This allows for a more accurate estimation of the user's emotions and state, and optimizes the experience.

[0104] Immersive home theater systems can track the user's gaze and adjust the generation of vibrations and wind based on their eye movements. For example, if the user is focusing on a particular scene, the system can generate vibrations and wind that match that scene. This allows for a more immersive experience based on the user's visual interests. Furthermore, gaze data can be compared with past gaze data to improve analysis accuracy. For instance, by referencing past gaze data and learning the user's gaze patterns, more appropriate vibrations and wind can be generated. In addition, gaze data can be analyzed in combination with other data (such as heart rate and facial expression data). This allows for a more accurate estimation of the user's emotions and state, and optimizes the immersive experience.

[0105] An immersive home theater system can monitor the user's body temperature and adjust the generation of vibrations and airflow based on changes in body temperature. For example, if the user's body temperature rises, the system can generate cooling airflow, and if it falls, it can generate warm airflow. This allows for a more comfortable experience based on the user's physiological state. Furthermore, body temperature data can be compared with past data to improve analysis accuracy. For example, by referring to past body temperature data and learning the user's body temperature change patterns, more appropriate vibrations and airflow can be generated. In addition, body temperature data can be analyzed in combination with other physiological data (e.g., heart rate and skin electrical activity). This allows for a more accurate estimation of the user's emotions and state, and optimizes the immersive experience.

[0106] An immersive home theater system can monitor the user's breathing rate and adjust the generation of vibrations and wind based on changes in breathing. For example, if the user's breathing rate increases, the system can generate stronger vibrations and wind, and if it decreases, it can generate gentler vibrations and wind. This allows for a more realistic experience based on the user's physiological responses. Furthermore, the breathing rate data can be compared with past data to improve analysis accuracy. For example, by referring to past breathing rate data and learning the user's breathing pattern, it becomes possible to generate more appropriate vibrations and wind. In addition, breathing rate data can be analyzed in combination with other physiological data (e.g., heart rate and body temperature). This allows for a more accurate estimation of the user's emotions and state, and optimizes the immersive experience.

[0107] An immersive home theater system can monitor the user's skin electrical activity and adjust the generation of vibrations and wind based on changes in this activity. For example, if the user's skin electrical activity increases, the system can generate stronger vibrations and wind, and if it decreases, it can generate gentler vibrations and wind. This allows for a more realistic experience based on the user's physiological responses. Furthermore, the skin electrical activity data can be compared with past data to improve analysis accuracy. For example, by referring to past skin electrical activity data and learning the user's response patterns, it becomes possible to generate more appropriate vibrations and wind. In addition, skin electrical activity data can be analyzed in combination with other physiological data (e.g., heart rate and respiratory rate). This allows for a more accurate estimation of the user's emotions and state, and optimizes the immersive experience.

[0108] An immersive home theater system can generate scents tailored to movie scenes based on the user's preferences and viewing history. For example, it can generate a spicy scent during action scenes and a lavender scent during relaxing scenes. This allows users to enjoy scents that match the movie scenes, providing a more immersive experience. Furthermore, scent generation can be optimized by referencing past viewing history and preference data. For instance, it can learn scents a user has liked in the past and generate the same scent in similar scenes. In addition, scent generation can be combined with other sensory elements (such as vibration or wind). This allows users to enjoy multiple senses simultaneously, providing a more realistic experience.

[0109] Immersive home theater systems can detect the user's seat position and posture, and adjust the generation of vibrations and wind based on seat movements. For example, if the user is leaning forward, the system can generate strong vibrations and wind, while if the user is sitting relaxed, it can generate gentler vibrations and wind. This allows for a more appropriate experience based on the user's posture. Furthermore, seat movement data can be compared with past data to improve analysis accuracy. For example, by referring to past seat movement data and learning the user's posture patterns, it becomes possible to generate more appropriate vibrations and wind. In addition, seat movement data can be analyzed in combination with other data (e.g., heart rate and gaze data). This allows for a more accurate estimation of the user's emotions and state, and optimizes the experience.

[0110] Immersive home theater systems can analyze the tone and volume of the user's voice and adjust the generation of vibrations and wind based on changes in the voice. For example, if the user is excited and speaking loudly, the system can generate strong vibrations and wind, while if the user is speaking quietly, it can generate gentler vibrations and wind. This allows for a more realistic experience based on changes in the user's voice. Furthermore, voice data can be compared with past data to improve analysis accuracy. For example, by referring to past voice data and learning the user's voice patterns, it becomes possible to generate more appropriate vibrations and wind. In addition, voice data can be analyzed in combination with other data (e.g., heart rate and eye gaze data). This allows for a more accurate estimation of the user's emotions and state, and optimizes the immersive experience.

[0111] An immersive home theater system can monitor changes in the user's weight and adjust the generation of vibrations and wind based on those changes. For example, if the user is sitting with weight on the device, the system can generate strong vibrations and wind, while if the user is sitting without weight on the device, it can generate gentler vibrations and wind. This allows for a more appropriate experience based on the user's weight changes. Furthermore, weight data can be compared with past data to improve analysis accuracy. For example, by referring to past weight data and learning the user's weight change patterns, it becomes possible to generate more appropriate vibrations and wind. In addition, weight data can be analyzed in combination with other data (e.g., heart rate and gaze data). This allows for a more accurate estimation of the user's emotions and state, and optimizes the experience.

[0112] An immersive home theater system can analyze ambient sounds around the user and adjust the generation of vibrations and wind based on changes in those sounds. For example, in a quiet environment, the system can generate gentle vibrations and wind, while in a noisy environment, it can generate stronger vibrations and wind. This allows for a more appropriate sensory experience based on the user's surroundings. Furthermore, the accuracy of the analysis can be improved by comparing the ambient sound data with past data. For instance, by referencing past ambient sound data and learning the user's ambient sound patterns, more appropriate vibrations and wind can be generated. In addition, ambient sound data can be analyzed in combination with other data (such as heart rate and gaze data). This allows for a more accurate estimation of the user's emotions and state, and optimizes the sensory experience.

[0113] The following briefly describes the processing flow for example form 2.

[0114] Step 1: The analysis unit analyzes the video and audio. For example, the analysis unit recognizes and analyzes the video and audio of a movie. The analysis unit can use AI to analyze the content of the video and audio. For example, the analysis unit can use a speech recognition algorithm to analyze the audio of a movie. The analysis unit can also use an image recognition algorithm to analyze the video of a movie. Step 2: The generation unit generates vibrations and wind based on the information analyzed by the analysis unit. The generation unit generates vibrations and wind using, for example, a vibration motor or a blower. The generation unit can adjust the method of generating vibrations and wind using AI. For example, the generation unit adjusts the method of generating vibration patterns based on the information analyzed by the AI. The generation unit can also set the wind intensity and direction based on the information analyzed by the AI. Step 3: The control unit controls the vibrations and wind generated by the generation unit. The control unit controls the vibrations and wind using, for example, feedback control or PID control. The control unit can use AI to adjust the control method for vibrations and wind. For example, the control unit performs real-time control based on information analyzed by the AI. The control unit can also adjust the intensity and duration of vibrations and wind based on information analyzed by the AI. Step 4: The sensory unit experiences vibrations and wind controlled by the control unit. The sensory unit experiences vibrations and wind using, for example, bone conduction earphones or a mini fan. The sensory unit can adjust the way it experiences vibrations using AI. For example, the sensory unit adjusts the intensity and duration of vibrations and wind based on information analyzed by the AI. The sensory unit can also enjoy movies using AR glasses. The sensory unit provides people with visual or hearing impairments with the opportunity to enjoy movies.

[0115] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0116] Data generation model 58 is a form of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0117] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0118] Each of the multiple elements described above, including the analysis unit, generation unit, control unit, and sensory experience unit, is implemented in at least one of the smart device 14 and the data processing unit 12. For example, the analysis unit is implemented by the processor 46 of the smart device 14 and the specific processing unit 290 of the data processing unit 12, and recognizes and analyzes the video and audio of the movie. The generation unit is implemented by the control unit 46A of the smart device 14 and the specific processing unit 290 of the data processing unit 12, and generates vibrations and wind. The control unit is implemented by the control unit 46A of the smart device 14 and the specific processing unit 290 of the data processing unit 12, and controls the generated vibrations and wind. The sensory experience unit is implemented by the control unit 46A of the smart device 14 and the specific processing unit 290 of the data processing unit 12, and allows the user to experience the vibrations and wind. The correspondence between each unit and the device or control unit is not limited to the example described above, and various modifications are possible.

[0119] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0120] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0121] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0122] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0123] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0124] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0125] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0126] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing by the processor 28. The storage 32 stores the specific processing program 56.

[0127] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0128] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0129] In the smart glasses 214, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0130] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0131] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0132] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0133] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0134] Each of the multiple elements described above, including the analysis unit, generation unit, control unit, and sensory experience unit, is implemented in at least one of the smart glasses 214 and the data processing unit 12. For example, the analysis unit is implemented by the processor 46 of the smart glasses 214 and the specific processing unit 290 of the data processing unit 12, and recognizes and analyzes the images and sounds of a movie. The generation unit is implemented by the control unit 46A of the smart glasses 214 and the specific processing unit 290 of the data processing unit 12, and generates vibrations and wind. The control unit is implemented by the control unit 46A of the smart glasses 214 and the specific processing unit 290 of the data processing unit 12, and controls the generated vibrations and wind. The sensory experience unit is implemented by the control unit 46A of the smart glasses 214 and the specific processing unit 290 of the data processing unit 12, and allows the user to experience the vibrations and wind. The correspondence between each unit and the device or control unit is not limited to the example described above, and various modifications are possible.

[0135] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0136] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0137] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0138] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0139] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0140] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0141] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0142] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0143] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0144] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0145] In the headset terminal 314, specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50 and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific program 60 executed on the RAM 48. The headset terminal 314 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0146] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0147] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0148] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0149] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0150] Each of the multiple elements described above, including the analysis unit, generation unit, control unit, and sensory experience unit, is implemented in at least one of the headset terminal 314 and the data processing unit 12. For example, the analysis unit is implemented by the processor 46 of the headset terminal 314 and the specific processing unit 290 of the data processing unit 12, and recognizes and analyzes the video and audio of the movie. The generation unit is implemented by the control unit 46A of the headset terminal 314 and the specific processing unit 290 of the data processing unit 12, and generates vibrations and wind. The control unit is implemented by the control unit 46A of the headset terminal 314 and the specific processing unit 290 of the data processing unit 12, and controls the generated vibrations and wind. The sensory experience unit is implemented by the control unit 46A of the headset terminal 314 and the specific processing unit 290 of the data processing unit 12, and allows the user to experience the vibrations and wind. The correspondence between each unit and the device or control unit is not limited to the example described above, and various modifications are possible.

[0151] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0152] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0153] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0154] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0155] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0156] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS image sensor or CCD image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0157] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0158] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. The robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0159] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0160] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0161] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0162] In robot 414, specific processing is performed by processor 46. A specific program 60 is stored in storage 50. Processor 46 reads the specific program 60 from storage 50 and executes it on RAM 48. The specific processing is achieved by processor 46 acting as a control unit 46A according to the specific program 60 executed on RAM 48. Robot 414 also has data generation model 58 and emotion identification model 59, similar to those of the robot, and can perform processing similar to that of the specific processing unit 290 using these models.

[0163] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0164] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0165] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0166] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or an external device, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0167] Each of the multiple elements described above, including the analysis unit, generation unit, control unit, and sensory experience unit, is implemented in at least one of the robot 414 and the data processing unit 12. For example, the analysis unit is implemented by the processor 46 of the robot 414 and the specific processing unit 290 of the data processing unit 12, and recognizes and analyzes the images and sounds of a movie. The generation unit is implemented by the control unit 46A of the robot 414 and the specific processing unit 290 of the data processing unit 12, and generates vibrations and wind. The control unit is implemented by the control unit 46A of the robot 414 and the specific processing unit 290 of the data processing unit 12, and controls the generated vibrations and wind. The sensory experience unit is implemented by the control unit 46A of the robot 414 and the specific processing unit 290 of the data processing unit 12, and allows the user to experience the vibrations and wind. The correspondence between each unit and the device or control unit is not limited to the example described above, and various modifications are possible.

[0168] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0169] Figure 9 shows the emotion map 400, in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0170] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0171] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0172] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, and motorcycles, emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated based, for example, on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0173] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0174] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0175] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing method for the specific process may be used, which includes computer 22 and multiple other computers.

[0176] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0177] 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.

[0178] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0179] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0180] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0181] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0182] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0183] Furthermore, although the above-described examples were divided into four embodiments, some or all of these embodiments may be combined. Also, the smart device 14, smart glasses 214, headset terminal 314, and robot 414 are just examples, and they may be combined, or other devices may be used. Also, although the above-described examples were divided into two embodiments, Embodiment 1 and Embodiment 2, these may be combined.

[0184] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and other things that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0185] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0186] (Note 1) An analysis unit that analyzes video and audio, A generation unit that generates vibrations and wind based on the information analyzed by the aforementioned analysis unit, A control unit that controls the vibrations and wind generated by the generation unit, The system includes a sensory unit that allows users to experience vibrations and wind controlled by the control unit. A system characterized by the following features. (Note 2) The aforementioned analysis unit, Recognizes and analyzes video and audio. The system described in Appendix 1, characterized by the features described herein. (Note 3) The generating unit is Based on the analyzed information, vibrations and wind are generated. The system described in Appendix 1, characterized by the features described herein. (Note 4) The control unit, Controlling the generated vibrations and wind The system described in Appendix 1, characterized by the features described herein. (Note 5) The aforementioned sensory unit is Experience controlled vibrations and wind. The system described in Appendix 1, characterized by the features described herein. (Note 6) The aforementioned sensory unit is Includes bone conduction earphones and mini fans. The system described in Appendix 1, characterized by the features described herein. (Note 7) The aforementioned sensory unit is Enjoy movies using AR glasses The system described in Appendix 1, characterized by the features described herein. (Note 8) The aforementioned sensory unit is Providing people with visual or hearing impairments with the opportunity to enjoy movies. The system described in Appendix 1, characterized by the features described herein. (Note 9) The aforementioned analysis unit, The system estimates the user's emotions and adjusts the video and audio analysis methods based on the estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 10) The aforementioned analysis unit, When analyzing video and audio, past analysis data is referenced to improve analysis accuracy. The system described in Appendix 1, characterized by the features described herein. (Note 11) The aforementioned analysis unit, When analyzing video and audio, the level of detail of the analysis is adjusted based on the importance of each scene. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned analysis unit, It estimates the user's emotions and prioritizes the analysis results based on the estimated user emotions. The system described in Appendix 1, characterized by the features described herein. (Note 13) The aforementioned analysis unit, When analyzing video and audio, the analysis method is customized by taking into account the user's viewing history. The system described in Appendix 1, characterized by the features described herein. (Note 14) The aforementioned analysis unit, When analyzing video and audio, the optimal analysis method is selected by considering the user's device information. The system described in Appendix 1, characterized by the features described herein. (Note 15) The generating unit is The system estimates the user's emotions and adjusts the vibration and wind generation methods based on the estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 16) The generating unit is When generating vibrations or wind, past generation data is referenced to improve generation accuracy. The system described in Appendix 1, characterized by the features described herein. (Note 17) The generating unit is When generating vibrations or wind, adjust the level of detail based on the importance of the scene. The system described in Appendix 1, characterized by the features described herein. (Note 18) The generating unit is It estimates the user's emotions and determines the priority of vibrations and wind effects to generate based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 19) The generating unit is When generating vibrations or wind, the generation method is customized based on the user's viewing history. The system described in Appendix 1, characterized by the features described herein. (Note 20) The generating unit is When generating vibrations or wind, the system selects the optimal generation method by considering the user's device information. The system described in Appendix 1, characterized by the features described herein. (Note 21) The control unit, It estimates the user's emotions and adjusts the vibration and wind control methods based on the estimated user emotions. The system described in Appendix 1, characterized by the features described herein. (Note 22) The control unit, When controlling vibrations or wind, past control data is referenced to improve control accuracy. The system described in Appendix 1, characterized by the features described herein. (Note 23) The control unit, When controlling vibrations and wind, adjust the level of detail of the control based on the importance of the scene. The system described in Appendix 1, characterized by the features described herein. (Note 24) The control unit, It estimates the user's emotions and determines the priority of vibrations and wind to control based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 25) The control unit, When controlling vibrations and wind, the control method is customized based on the user's viewing history. The system described in Appendix 1, characterized by the features described herein. (Note 26) The control unit, When controlling vibrations or wind, the optimal control method is selected by considering the user's device information. The system described in Appendix 1, characterized by the features described herein. (Note 27) The aforementioned sensory unit is It estimates the user's emotions and adjusts the user experience based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 28) The aforementioned sensory unit is When experiencing something, past experience data is referenced to improve the accuracy of the experience. The system described in Appendix 1, characterized by the features described herein. (Note 29) The aforementioned sensory unit is When experiencing a scene, the level of detail is adjusted based on the importance of that scene. The system described in Appendix 1, characterized by the features described herein. (Note 30) The aforementioned sensory unit is It estimates the user's emotions and determines the priority of vibrations and wind sensations based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 31) The aforementioned sensory unit is During the user experience, the experience method is customized by taking into account the user's viewing history. The system described in Appendix 1, characterized by the features described herein. (Note 32) The aforementioned sensory unit is During the user experience, the system selects the optimal experience method by considering the user's device information. The system described in Appendix 1, characterized by the features described herein. [Explanation of symbols]

[0187] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. An analysis unit that analyzes video and audio, A generation unit that generates vibrations and wind based on the information analyzed by the aforementioned analysis unit, A control unit that controls the vibrations and wind generated by the generation unit, The system includes a sensory unit that allows users to experience vibrations and wind controlled by the control unit. A system characterized by the following features.

2. The aforementioned analysis unit, Recognizes and analyzes video and audio. The system according to feature 1.

3. The generating unit is Based on the analyzed information, vibrations and wind are generated. The system according to feature 1.

4. The control unit, Controlling the generated vibrations and wind The system according to feature 1.

5. The aforementioned sensory unit is Experience controlled vibrations and wind. The system according to feature 1.

6. The aforementioned sensory unit is Includes bone conduction earphones and mini fans. The system according to feature 1.

7. The aforementioned sensory unit is Enjoy movies using AR glasses The system according to feature 1.

8. The aforementioned sensory unit is Providing people with visual or hearing impairments with the opportunity to enjoy movies. The system according to feature 1.

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