System

Abstract

An object of a system according to an embodiment is to provide a personalized soundscape for healing sadness due to the unhappiness of relatives.SOLUTION: A system according to an embodiment includes a reminiscence information collection unit, a soundscape generation unit, and a soundscape provision unit. The reminiscence information collection unit collects reminiscence information of a user. The soundscape generation unit generates a soundscape based on the reminiscence information collected by the reminiscence information collection unit. The soundscape provider provides the user with the soundscape generated by the soundscape generator.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional techniques have had the problem of not providing sufficient effective relaxation methods to heal grief caused by the misfortune of a family member.

[0005] The system according to the embodiment aims to provide a personalized soundscape to heal the grief caused by a family tragedy. [Means for solving the problem]

[0006] The system according to the embodiment includes a memory information collection unit, a soundscape generation unit, and a soundscape provision unit. The memory information collection unit collects memory information of a user. The soundscape generation unit generates a soundscape based on the memory information collected by the memory information collection unit. The soundscape provision unit provides the soundscape generated by the soundscape generation unit to the user. [Effects of the Invention]

[0007] Embodiments of the system can provide personalized soundscapes to help with grief following a family tragedy. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

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

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

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

[0014] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), and Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

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

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

[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, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

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

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

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

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together 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 the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0027] Note that a device other than the data processing device 12 may 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 a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) A relaxation system according to an embodiment of the present invention allows users to experience personalized soundscapes generated by a generative AI based on their memories of the deceased, thereby providing users with healing and the opportunity to relive their memories.

[0029] A relaxation system according to an embodiment includes a memory information collection unit, a soundscape generation unit, and a soundscape provision unit. The memory information collection unit collects a user's memory information. For example, the user inputs information about memories with the deceased. The user can input information such as places visited with the deceased, activities performed together, and specific sounds (such as the sound of waves or birdsong). The soundscape generation unit generates a soundscape based on the memory information collected by the memory information collection unit. For example, the generation AI generates a personalized soundscape based on the memory information provided by the user. The generation AI uses a text generation AI (e.g., LLM) to generate a soundscape including the sound of waves and the calls of seabirds based on memories of a beach visited with the deceased. The soundscape provision unit provides the user with the soundscape generated by the soundscape generation unit. For example, the user can relive memories with the deceased by listening to the generated soundscape. This allows the relaxation system according to an embodiment to provide the user with healing and the re-experiencing of memories. For example, by listening to a soundscape based on memories of a park where a user spent time with a deceased loved one, the user can recall the emotions and scenery of that time and feel a sense of healing.

[0030] The memory information collection unit can collect related images and videos from the Internet based on the user's memory information, and simultaneously provide visual memories. For example, when a user inputs memories of a deceased person, the memory information collection unit automatically collects related images and videos from the Internet. For example, if a user inputs "memories of the seaside," the generation AI will collect images of seaside scenery and waves and provide visual memories. This can improve the user's relaxation experience by simultaneously providing visual memories.

[0031] The memory information collection unit can analyze the user's voice input and automatically convert the memory information into text using voice recognition technology, which can then be input into the generation AI. For example, when a user inputs a memory of a deceased person by voice, the memory information collection unit automatically converts the voice into text using voice recognition technology and inputs it into the generation AI. For example, if the user says, "We spent time together at the beach," the content is converted into text. This reduces the input burden on the user by converting voice input into text.

[0032] The memory information collection unit allows the generation AI to automatically suggest related literary works and poems based on the user's memory information, deepening emotional empathy. For example, when a user inputs memories of a deceased person, the memory information collection unit allows the generation AI to automatically suggest literary works and poems related to those memories. For example, if a user inputs "memories of the seaside," the generation AI will suggest poems about the sea. This allows the user to deepen emotional empathy by suggesting related literary works and poems.

[0033] The memory information collection unit uses the generation AI to suggest related scents and textures based on the user's memory information, allowing for relaxation using the five senses. For example, when a user inputs a memory of a deceased person, the generation AI automatically suggests scents and textures related to that memory. For example, if a user inputs "memories of the seaside," the generation AI suggests "the scent of the sea" and "the texture of sand." This allows for relaxation using the five senses by suggesting scents and textures.

[0034] The soundscape generation unit can generate multiple soundscapes based on the user's memory information and allow the user to select from them. For example, when a user inputs memories of a deceased person, the soundscape generation unit generates multiple soundscapes based on those memories and allows the user to select from them. For example, for "memories of the seaside," different soundscapes such as "the sound of waves" and "seabirds singing" can be generated. By providing multiple soundscapes, this increases the user's options and provides a more personalized experience.

[0035] The soundscape generation unit can include not only natural environmental sounds but also the voice and conversation of the deceased in the soundscape based on the user's memory information. For example, when a user inputs memories of a deceased person, the soundscape generation AI can include not only natural environmental sounds but also the voice and conversation of the deceased in the soundscape based on those memories. For example, for "memories of the seaside," a soundscape including the "sound of waves" and the "voice of the deceased" can be generated. This allows the user to re-experience memories more realistically by including the voice and conversation of the deceased.

[0036] The soundscape generation unit can generate visual images and animations in addition to the soundscape based on the user's memory information, providing a multimedia experience. For example, when a user inputs memories of a deceased person, the soundscape generation unit generates visual images and animations in addition to the soundscape based on those memories, providing a multimedia experience. For example, a multimedia experience including "sounds of waves" and "images of the ocean" can be provided for "memories of the seaside." This can enhance the user's relaxation experience by providing visual images and animations.

[0037] The soundscape generation unit can add a function to read aloud literary works or poetry related to the soundscape based on the user's memory information. For example, when a user inputs memories of a deceased person, the soundscape generation unit adds a function to read aloud literary works or poetry related to the soundscape based on those memories. For example, for "memories of the seaside," a soundscape including "the sound of waves" and "the recitation of poetry about the sea" is provided. This allows the user's relaxation experience to be improved by having literary works or poetry read aloud.

[0038] The soundscape providing unit can add a function to display visual art and photos related to the soundscape based on the user's memory information. For example, when a user inputs memories of a deceased person, the soundscape providing unit adds a function to display visual art and photos related to the soundscape based on those memories. For example, for "memories of the seaside," a soundscape including "the sound of waves" and "photos of the sea" is provided. This can enhance the user's relaxation experience by displaying visual art and photos.

[0039] The soundscape providing unit can add a function to display poetry or literary works related to the soundscape based on the user's memory information. For example, when a user inputs memories of a deceased person, the soundscape providing unit adds a function to display poetry or literary works related to the soundscape based on those memories. For example, for "memories of the seaside," a soundscape including "the sound of waves" and "poetry about the sea" is provided. This can improve the user's relaxation experience by displaying poetry or literary works.

[0040] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0041] The relaxation system may further include a physiological data collection unit that collects physiological data of the user. For example, data such as heart rate, electrodermal activity, and breathing pattern may be collected to monitor the user's relaxation state in real time. This allows the system to provide an optimal relaxation experience based on the user's physiological state. For example, if the heart rate is high, a more soothing soundscape may be provided. Alternatively, if the electrodermal activity is high, a relaxing aroma may be suggested. Furthermore, if the breathing pattern is irregular, a deep breathing guide may be provided.

[0042] The relaxation system can further include a history management unit that records the user's past relaxation experiences. For example, the system can record what soundscapes the user has listened to in the past and what emotional state the user was in, and use this information for the next relaxation experience. This allows for a more personalized relaxation experience based on the user's preferences and tendencies. For example, if a user has previously relaxed by listening to "Seaside Memories," a similar soundscape can be suggested for the next time. Also, if a user has previously relaxed by listening to "Forest Memories," a new forest-related soundscape can be suggested. Furthermore, the system can suggest optimal relaxation methods based on the user's past emotional state.

[0043] The relaxation system may further include a sharing unit for sharing users' relaxation experiences. For example, users can share soundscapes and memory information they have created with other users. This allows users to share their relaxation experiences and deepen empathy. For example, if a user shares "memories of the seaside," other users can also listen to that soundscape. Also, if a user shares "memories of the forest," other users can also listen to that soundscape. Furthermore, new soundscapes can be generated based on the shared memory information.

[0044] The relaxation system may further include a customization unit that customizes the relaxation experience based on the user's emotional state. For example, if the user feels like relaxing, a calming soundscape may be provided. If the user feels like invigorating, a lively soundscape may be provided. Furthermore, if the user feels like concentrating, a soundscape that promotes concentration may be provided. In this way, an optimal relaxation experience can be provided according to the user's emotional state.

[0045] The processing flow of the first embodiment will be briefly explained below.

[0046] Step 1: The memory information collection unit collects the user's memory information. For example, the user inputs information about memories with the deceased. The user can input information such as places visited with the deceased, activities they did together, and specific sounds (such as the sound of waves or birds singing). Step 2: The soundscape generation unit generates a soundscape based on the memory information collected by the memory information collection unit. For example, the generation AI generates a personalized soundscape based on the memory information provided by the user. The generation AI uses a text generation AI (e.g., LLM) to generate a soundscape including the sounds of waves and seabirds based on memories of a seaside visit with the deceased. Step 3: The soundscape providing unit provides the user with the soundscape generated by the soundscape generating unit. For example, the user can relive memories of the deceased by listening to the generated soundscape. In this way, the relaxation system according to the embodiment can provide the user with healing and the ability to relive memories.

[0047] (Example 2) A relaxation system according to an embodiment of the present invention allows users to experience personalized soundscapes generated by a generative AI based on their memories of the deceased, thereby providing users with healing and the opportunity to relive their memories.

[0048] A relaxation system according to an embodiment includes a memory information collection unit, a soundscape generation unit, and a soundscape provision unit. The memory information collection unit collects a user's memory information. For example, the user inputs information about memories with the deceased. The user can input information such as places visited with the deceased, activities performed together, and specific sounds (such as the sound of waves or birdsong). The soundscape generation unit generates a soundscape based on the memory information collected by the memory information collection unit. For example, the generation AI generates a personalized soundscape based on the memory information provided by the user. The generation AI uses a text generation AI (e.g., LLM) to generate a soundscape including the sound of waves and the calls of seabirds based on memories of a beach visited with the deceased. The soundscape provision unit provides the user with the soundscape generated by the soundscape generation unit. For example, the user can relive memories with the deceased by listening to the generated soundscape. This allows the relaxation system according to an embodiment to provide the user with healing and the re-experiencing of memories. For example, by listening to a soundscape based on memories of a park where a user spent time with a deceased loved one, the user can recall the emotions and scenery of that time and feel a sense of healing.

[0049] The memory information collection unit can collect related images and videos from the Internet based on the user's memory information, and simultaneously provide visual memories. For example, when a user inputs memories of a deceased person, the memory information collection unit automatically collects related images and videos from the Internet. For example, if a user inputs "memories of the seaside," the generation AI will collect images of seaside scenery and waves and provide visual memories. This can improve the user's relaxation experience by simultaneously providing visual memories.

[0050] The memory information collection unit can analyze the user's voice input and automatically convert the memory information into text using voice recognition technology, which can then be input into the generation AI. For example, when a user inputs a memory of a deceased person by voice, the memory information collection unit automatically converts the voice into text using voice recognition technology and inputs it into the generation AI. For example, if the user says, "We spent time together at the beach," the content is converted into text. This reduces the input burden on the user by converting voice input into text.

[0051] The memory information collection unit can use the emotion estimation function to analyze the emotional nuances of the memory information entered by the user and suggest additional information to elicit positive emotions. For example, when a user enters a memory of a deceased person, the memory information collection unit can use the emotion estimation function to analyze the emotional nuances of the memory and suggest additional information to elicit positive emotions. For example, if a user enters "I had fun," the generation AI would suggest "a photo of me smiling at that time." This can improve the user's relaxation experience by suggesting additional information to elicit positive emotions.

[0052] The memory information collection unit allows the generation AI to automatically suggest related literary works and poems based on the user's memory information, deepening emotional empathy. For example, when a user inputs memories of a deceased person, the memory information collection unit allows the generation AI to automatically suggest literary works and poems related to those memories. For example, if a user inputs "memories of the seaside," the generation AI will suggest poems about the sea. This allows the user to deepen emotional empathy by suggesting related literary works and poems.

[0053] The memory information collection unit uses the generation AI to suggest related scents and textures based on the user's memory information, allowing for relaxation using the five senses. For example, when a user inputs a memory of a deceased person, the generation AI automatically suggests scents and textures related to that memory. For example, if a user inputs "memories of the seaside," the generation AI suggests "the scent of the sea" and "the texture of sand." This allows for relaxation using the five senses by suggesting scents and textures.

[0054] The memory information collection unit uses the emotion estimation function to analyze the emotions in the memory information entered by the user in real time and can suggest music or art that will elicit positive emotions. For example, when a user enters memories of a deceased person, the memory information collection unit uses the emotion estimation function to analyze the emotions in the memory in real time and suggests music that will elicit positive emotions. For example, if a user enters "It was fun," the generation AI will suggest "fun music." This can improve the user's relaxation experience by suggesting music or art that will elicit positive emotions.

[0055] The soundscape generation unit can generate multiple soundscapes based on the user's memory information and allow the user to select from them. For example, when a user inputs memories of a deceased person, the soundscape generation unit generates multiple soundscapes based on those memories and allows the user to select from them. For example, for "memories of the seaside," different soundscapes such as "the sound of waves" and "seabirds singing" can be generated. By providing multiple soundscapes, this increases the user's options and provides a more personalized experience.

[0056] The soundscape generation unit can include not only natural environmental sounds but also the voice and conversation of the deceased in the soundscape based on the user's memory information. For example, when a user inputs memories of a deceased person, the soundscape generation AI can include not only natural environmental sounds but also the voice and conversation of the deceased in the soundscape based on those memories. For example, for "memories of the seaside," a soundscape including the "sound of waves" and the "voice of the deceased" can be generated. This allows the user to re-experience memories more realistically by including the voice and conversation of the deceased.

[0057] The soundscape generation unit can use the emotion estimation function to dynamically adjust the tone and tempo of the soundscape according to the user's emotional state. For example, when a user inputs a memory of a deceased loved one, the soundscape generation unit uses the emotion estimation function to analyze the emotional state of the memory and dynamically adjust the tone and tempo of the soundscape. For example, if a user inputs "sad," the generation AI generates a soundscape with a "calm tone." This allows the soundscape to be dynamically adjusted according to the user's emotional state, providing a more effective relaxation experience.

[0058] The soundscape generation unit can generate visual images and animations in addition to the soundscape based on the user's memory information, providing a multimedia experience. For example, when a user inputs memories of a deceased person, the soundscape generation unit generates visual images and animations in addition to the soundscape based on those memories, providing a multimedia experience. For example, a multimedia experience including "sounds of waves" and "images of the ocean" can be provided for "memories of the seaside." This can enhance the user's relaxation experience by providing visual images and animations.

[0059] The soundscape generation unit can add a function to read aloud literary works or poetry related to the soundscape based on the user's memory information. For example, when a user inputs memories of a deceased person, the soundscape generation unit adds a function to read aloud literary works or poetry related to the soundscape based on those memories. For example, for "memories of the seaside," a soundscape including "the sound of waves" and "the recitation of poetry about the sea" is provided. This allows the user's relaxation experience to be improved by having literary works or poetry read aloud.

[0060] The soundscape generation unit can use the emotion estimation function to suggest aromas and scents suitable for the soundscape according to the user's emotional state. For example, when a user inputs memories of a deceased loved one, the soundscape generation unit uses the emotion estimation function to analyze the emotional state of the memory and suggests aromas and scents suitable for the soundscape. For example, if a user inputs "sad," the generation AI would suggest "aromas with a relaxing effect." This allows the user's relaxation experience to be improved by suggesting aromas and scents.

[0061] The soundscape providing unit can monitor the user's emotional state and change the content of the soundscape as needed. For example, while the user is listening to a soundscape, the generation AI monitors the user's emotional state and changes the content of the soundscape as needed. For example, if the user feels "sad," the generation AI changes the soundscape to one with a "calm tone." This makes it possible to provide a more effective relaxation experience by monitoring the user's emotional state and changing the soundscape as needed.

[0062] The soundscape providing unit can use the emotion estimation function to analyze changes in a user's emotions while they are listening to the soundscape and add sounds that elicit those emotions at optimal timing. For example, while a user is listening to a soundscape, the soundscape providing unit can use the emotion estimation function to analyze changes in the user's emotions and add sounds that elicit those emotions at optimal timing. For example, if the user feels "sad," the generation AI can add "calming sounds." This can improve the user's relaxation experience by adding sounds that elicit those emotions.

[0063] The soundscape providing unit can add a function to display visual art and photos related to the soundscape based on the user's memory information. For example, when a user inputs memories of a deceased person, the soundscape providing unit adds a function to display visual art and photos related to the soundscape based on those memories. For example, for "memories of the seaside," a soundscape including "the sound of waves" and "photos of the sea" is provided. This can enhance the user's relaxation experience by displaying visual art and photos.

[0064] The soundscape providing unit can add a function to display poetry or literary works related to the soundscape based on the user's memory information. For example, when a user inputs memories of a deceased person, the soundscape providing unit adds a function to display poetry or literary works related to the soundscape based on those memories. For example, for "memories of the seaside," a soundscape including "the sound of waves" and "poetry about the sea" is provided. This can improve the user's relaxation experience by displaying poetry or literary works.

[0065] The soundscape providing unit can use the emotion estimation function to analyze emotional changes while the user is listening to the soundscape and provide a meditation guide to deepen relaxation at the optimal timing. For example, while the user is listening to the soundscape, the soundscape providing unit can use the emotion estimation function to analyze the emotional changes and provide a meditation guide to deepen relaxation at the optimal timing. For example, if the user feels like "I want to relax," the generation AI can provide a "deep breathing guide." This can improve the user's relaxation experience by providing a meditation guide.

[0066] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0067] The relaxation system may further include a physiological data collection unit that collects physiological data of the user. For example, data such as heart rate, electrodermal activity, and breathing pattern may be collected to monitor the user's relaxation state in real time. This allows the system to provide an optimal relaxation experience based on the user's physiological state. For example, if the heart rate is high, a more soothing soundscape may be provided. Alternatively, if the electrodermal activity is high, a relaxing aroma may be suggested. Furthermore, if the breathing pattern is irregular, a deep breathing guide may be provided.

[0068] The relaxation system can further include a history management unit that records the user's past relaxation experiences. For example, the system can record what soundscapes the user has listened to in the past and what emotional state the user was in, and use this information for the next relaxation experience. This allows for a more personalized relaxation experience based on the user's preferences and tendencies. For example, if a user has previously relaxed by listening to "Seaside Memories," a similar soundscape can be suggested for the next time. Also, if a user has previously relaxed by listening to "Forest Memories," a new forest-related soundscape can be suggested. Furthermore, the system can suggest optimal relaxation methods based on the user's past emotional state.

[0069] The relaxation system may further include a sharing unit for sharing users' relaxation experiences. For example, users can share soundscapes and memory information they have created with other users. This allows users to share their relaxation experiences and deepen empathy. For example, if a user shares "memories of the seaside," other users can also listen to that soundscape. Also, if a user shares "memories of the forest," other users can also listen to that soundscape. Furthermore, new soundscapes can be generated based on the shared memory information.

[0070] The relaxation system may further include a customization unit that customizes the relaxation experience based on the user's emotional state. For example, if the user feels like relaxing, a calming soundscape may be provided. If the user feels like invigorating, a lively soundscape may be provided. Furthermore, if the user feels like concentrating, a soundscape that promotes concentration may be provided. In this way, an optimal relaxation experience can be provided according to the user's emotional state.

[0071] The relaxation system may further include a guide unit that guides the user through a relaxation experience based on the user's emotional state. For example, if the user feels like relaxing, a guide to deep breathing may be provided. If the user feels like invigorating, a guide to exercise may be provided. If the user feels like concentrating, a guide to meditation may be provided. In this way, the optimal relaxation experience can be provided according to the user's emotional state.

[0072] The relaxation system may further include an evaluation unit that evaluates the relaxation experience based on the user's emotional state. For example, if the user feels relaxed, the experience may be rated highly. If the user feels energized, the experience may be rated highly. If the user feels focused, the experience may be rated highly. In this way, the relaxation experience may be evaluated according to the user's emotional state and utilized for the next experience.

[0073] The relaxation system may further include an adjuster that adjusts the relaxation experience based on the user's emotional state. For example, if the user feels like relaxing, a calming soundscape may be provided. If the user feels like invigorating, a lively soundscape may be provided. If the user feels like concentrating, a soundscape that promotes concentration may be provided. In this way, an optimal relaxation experience can be provided according to the user's emotional state.

[0074] The relaxation system may further include an optimization unit that optimizes the relaxation experience based on the user's emotional state. For example, if the user feels like relaxing, a calming soundscape may be provided. If the user feels like invigorating, a lively soundscape may be provided. If the user feels like concentrating, a soundscape that promotes concentration may be provided. In this way, the optimal relaxation experience can be provided according to the user's emotional state.

[0075] The relaxation system may further include a personalization unit that personalizes the relaxation experience based on the user's emotional state. For example, if the user feels like relaxing, a calming soundscape may be provided. If the user feels like invigorating, a lively soundscape may be provided. If the user feels like concentrating, a soundscape that promotes concentration may be provided. In this way, an optimal relaxation experience can be provided according to the user's emotional state.

[0076] The relaxation system may further include a customization unit that customizes the relaxation experience based on the user's emotional state. For example, if the user feels like relaxing, a calming soundscape may be provided. If the user feels like invigorating, a lively soundscape may be provided. Furthermore, if the user feels like concentrating, a soundscape that promotes concentration may be provided. In this way, an optimal relaxation experience can be provided according to the user's emotional state.

[0077] The processing flow of the second embodiment will be briefly explained below.

[0078] Step 1: The memory information collection unit collects the user's memory information. For example, the user inputs information about memories with the deceased. The user can input information such as places visited with the deceased, activities they did together, and specific sounds (such as the sound of waves or birds singing). Step 2: The soundscape generation unit generates a soundscape based on the memory information collected by the memory information collection unit. For example, the generation AI generates a personalized soundscape based on the memory information provided by the user. The generation AI uses a text generation AI (e.g., LLM) to generate a soundscape including the sounds of waves and seabirds based on memories of a seaside visit with the deceased. Step 3: The soundscape providing unit provides the user with the soundscape generated by the soundscape generating unit. For example, the user can relive memories of the deceased by listening to the generated soundscape. In this way, the relaxation system according to the embodiment can provide the user with healing and the ability to relive memories.

[0079] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0080] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0081] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, 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.

[0082] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0083] 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.

[0084] 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, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0085] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0086] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0087] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0088] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0089] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0090] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0091] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0092] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. 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 the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0093] Note that a device other than the data processing device 12 may 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 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0094] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0095] The data generation model 58 is a so-called generative AI. An example of the 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 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0096] 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 executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0097] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0098] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0099] 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, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0100] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0101] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0102] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0103] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0104] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0105] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0106] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0107] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0108] Note that a device other than the data processing device 12 may 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 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0109] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0110] The data generation model 58 is a so-called generative AI. An example of the 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 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0111] 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 executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0112] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0113] 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.

[0114] 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, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0115] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0116] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0117] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0118] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0119] The control 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0120] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0121] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0122] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0123] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0124] Note that a device other than the data processing device 12 may 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 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0125] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0126] The data generation model 58 is a so-called generative AI. An example of the 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 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0127] 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 executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0128] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0129] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0130] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0131] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0132] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0133] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0134] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0135] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0136] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0137] 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.

[0138] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0139] The hardware resource for executing a specific process can be any of the following processors: A CPU is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A dedicated electrical circuit, such as a field-programmable gate array (FPGA), a programmable logic device (PLD), or an application-specific integrated circuit (ASIC), is a processor with a circuit configuration specifically designed to execute a specific process. Each processor has built-in or connected memory, and uses the memory to execute the specific process.

[0140] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0141] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0142] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0143] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0144] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0145] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0146] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. a memory information collection unit that collects memory information of a user; a soundscape generation unit that generates a soundscape based on the memory information collected by the memory information collection unit; a soundscape providing unit that provides the soundscape generated by the soundscape generating unit to a user. A system characterized by:

2. The memory information collection unit Using an emotion estimation function, the emotional nuances of the memory information entered by the user are analyzed, and additional information is suggested to elicit positive emotions.

2. The system of claim 1.

3. The memory information collection unit Based on the user's memories, the AI ​​automatically suggests related literary works and poems, deepening emotional empathy.

2. The system of claim 1.

4. The soundscape generation unit Based on the user's memory information, multiple soundscapes are generated and the user can select one.

2. The system of claim 1.

5. The soundscape generation unit Using emotion estimation capabilities to dynamically adjust the tone and tempo of the soundscape depending on the emotional state of the user.

2. The system of claim 1.

6. The soundscape providing unit Based on the user's feedback, the content of the soundscape is adjusted in real time to provide an optimal relaxation experience.

2. The system of claim 1.

7. The soundscape providing unit Monitoring the user's emotional state and modifying the content of the soundscape as needed 2. The system of claim 1.

8. The soundscape providing unit Using an emotion estimation function, the emotional changes of the user while listening to the soundscape are analyzed, and a meditation guide is provided to deepen relaxation at the optimal timing.

2. The system of claim 1.

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