system

Abstract

An object of a system according to an embodiment is to provide optimum BGM in accordance with a use scene or a customer's need.SOLUTION: A system includes a BGM selection part, a prompt generation part, and a BGM provision part. The BGM selection unit selects optimum BGM in accordance with a use scene or a customer's need. The prompt generation unit generates a prompt based on the BGM selected by the BGM selection unit. The BGM providing unit provides BGM based on the prompt generated by the prompt generation unit.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] With conventional technology, it was difficult to provide optimal background music according to the usage situation and customer needs, making it difficult to improve customer satisfaction.

[0005] The system according to the embodiment aims to provide optimal background music according to the usage scene and customer needs. [Means for solving the problem]

[0006] The system according to the embodiment includes a BGM selection unit, a prompt generation unit, and a BGM provision unit. The BGM selection unit selects optimal BGM according to the usage scenario or customer needs. The prompt generation unit generates a prompt based on the BGM selected by the BGM selection unit. The BGM provision unit provides BGM based on the prompt generated by the prompt generation unit. [Effects of the Invention]

[0007] The system according to the embodiment can provide optimal background music according to the usage scene and customer needs. [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 non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[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 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[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) The background music provision system according to an embodiment of the present invention is a system that provides optimal music (BGM) according to the usage scene and customer needs. By providing background music suited to a specific location or scene, this system creates a pleasant experience for customers and aims to improve satisfaction and repeat rates. In this way, the background music provision system can create a pleasant experience for customers and improve satisfaction and repeat rates.

[0029] A BGM provision system according to an embodiment includes a BGM selection unit, a prompt generation unit, and a BGM provision unit. The BGM selection unit selects optimal BGM according to the usage scenario and the customer's needs. For example, the generation AI selects relaxing music for a cafe. The generation AI can also select energetic music for a gym. The generation AI can also select calming music for a restaurant. The prompt generation unit generates a prompt based on the BGM selected by the BGM selection unit. For example, the generation AI can generate a prompt such as "Play music that is best suited to this location" based on the selected BGM. The generation AI can also generate a prompt such as "Play music that suits this scene" based on the selected BGM. The generation AI can also generate a prompt such as "Play music that meets these needs" based on the selected BGM. The BGM provision unit provides BGM based on the prompt generated by the prompt generation unit. For example, the BGM provision unit plays relaxing music based on the prompt generated by the generation AI. The BGM provision unit can also play energetic music based on the prompt generated by the generation AI. The BGM providing unit can also play calming music based on the prompt generated by the generation AI. This allows the BGM providing system according to the embodiment to provide optimal BGM according to the usage scenario and customer needs. For example, providing relaxing music in a cafe can create an environment that encourages customers to stay for a long time. Providing energetic music in a gym can increase motivation for training. Providing calming music in a restaurant can create an atmosphere conducive to enjoying a meal.

[0030] The BGM selection unit can analyze real-time environmental sounds in addition to the usage scene or customer needs and generate background music that harmonizes with them. For example, the BGM selection unit uses a generation AI to collect cafe noises in real time and generate relaxing background music that harmonizes with those sounds. For example, quiet jazz or acoustic music can be provided to match the background sounds of the cafe. The BGM selection unit can also analyze the sounds of gym machinery and people's movements in real time and generate energetic background music that harmonizes with them. For example, fast-paced electronic music can be provided to match the sound of a treadmill. The BGM selection unit can also collect restaurant environmental sounds (e.g., the clatter of dishes and the sounds of conversation) in real time and generate calming background music that harmonizes with them. For example, classical music or a solo piano performance can be provided. This allows for a more natural and comfortable experience by providing background music that harmonizes with real-time environmental sounds.

[0031] The BGM selection unit can learn a customer's past music history or preferences and provide individually customized BGM. For example, the BGM selection unit uses a generative AI to analyze a customer's past music history and provide customized BGM based on those preferences. For example, a customer who previously preferred relaxing music can be offered quiet jazz at a cafe. The BGM selection unit can also learn a customer's music streaming service history and provide individually customized BGM based on that data. For example, a customer who prefers energetic music at the gym can be offered up-tempo rock during workouts. The BGM selection unit can also analyze a customer's music playlist and provide customized BGM based on those preferences. For example, a customer who prefers classical music at a restaurant can be offered baroque music during meals. This allows for improved customer satisfaction by providing customized BGM based on the customer's past music history and preferences.

[0032] The BGM providing unit can comprehensively control not only background music but also environmental elements such as lighting and fragrance. For example, the BGM providing unit uses a generation AI to provide relaxing background music along with warm lighting and the aroma of coffee depending on the usage scenario of a cafe. This creates an environment where customers can relax. Similarly, the BGM providing unit provides energetic background music along with bright lighting and a fresh fragrance depending on the usage scenario of a gym. This creates an environment where customers can concentrate on their training. Similarly, the BGM providing unit provides calming background music along with soft lighting and an appetizing fragrance depending on the usage scenario of a restaurant. This creates an environment where customers can enjoy their meal. This comprehensive control of not only background music but also environmental elements such as lighting and fragrance further improves the customer experience.

[0033] The BGM selection unit can provide BGM appropriate for different cultural spheres or countries. For example, the BGM selection unit uses a generation AI to provide relaxing BGM appropriate for cafes in different cultural spheres. For example, a Japanese cafe might provide music using traditional Japanese instruments, while a French cafe might provide chanson. The BGM selection unit also provides energetic BGM appropriate for gyms in different countries. For example, an American gym might provide hip hop, while a Brazilian gym might provide samba. The BGM selection unit also provides calming BGM appropriate for restaurants in different cultural spheres. For example, an Italian restaurant might provide opera, and an Indian restaurant might provide Bollywood music. This allows the system to accommodate international customers by providing BGM appropriate for different cultural spheres or countries.

[0034] The BGM selection unit can select BGM in accordance with the time of day or seasonal changes, taking into account changes in the time of day or the season. For example, the generation AI selects BGM in accordance with the usage scenario of a cafe, taking into account changes in the time of day or the season. For example, refreshing music is provided in the morning, and relaxing music in the evening. The BGM selection unit also selects BGM in accordance with the usage scenario of a gym, taking into account changes in the time of day or the season. For example, energetic music is provided in the summer, and warm music in the winter. The BGM selection unit also selects BGM in accordance with the usage scenario of a restaurant, taking into account changes in the time of day or the season. For example, light music is provided in the daytime, and calm music in the evening. This allows for the provision of BGM that takes into account changes in the time of day or the season, thereby providing more appropriate BGM.

[0035] The BGM selection unit can monitor the customer's biometric information in real time and select BGM based on that information. For example, the BGM selection unit uses a generation AI to monitor the customer's heart rate in real time and select optimal BGM based on that data. For example, if the heart rate is high, relaxing music is provided. The BGM selection unit can also monitor the customer's stress level in real time and select optimal BGM based on that data. For example, if the stress level is high, relaxing music is provided. The BGM selection unit can also monitor the customer's biometric information in real time and select optimal BGM based on that data. For example, if the heart rate or stress level is low, energetic music is provided. This makes it possible to improve the customer's experience by providing optimal BGM based on the customer's biometric information.

[0036] The BGM providing unit can provide not only background music but also audio guides or narration. For example, the BGM providing unit uses a generation AI to provide an audio guide introducing the cafe's menu and recommended products along with relaxing background music depending on the scene of the cafe. The BGM providing unit also provides an audio guide providing training instructions and advice along with energetic background music depending on the scene of the gym. The BGM providing unit also provides a narration explaining the dishes and introducing recommended wines along with calming background music depending on the scene of the restaurant. This allows for an improved customer experience by providing not only background music but also audio guides and narration.

[0037] The BGM providing unit can work with different devices to provide background music seamlessly. For example, the BGM providing unit's generation AI works with a smartphone to provide relaxing background music at a cafe. For example, it seamlessly switches the music a customer is playing on their smartphone to the cafe's speakers. The BGM providing unit also works with a smart speaker to provide energetic background music depending on the gym usage scenario. For example, it seamlessly switches the music a customer is playing on their smart speaker to the gym's speakers. The BGM providing unit also works with a smartphone or smart speaker to provide calming background music depending on the restaurant usage scenario. For example, it seamlessly switches the music a customer is playing on their smartphone to the restaurant's speakers. This allows for seamless BGM provision through collaboration with different devices, improving the customer experience.

[0038] The BGM selection unit can provide background music that takes into account the event theme or the participant profiles. For example, the BGM selection unit uses a generation AI to provide background music that is appropriate for a specific location or scene based on the event theme. For example, romantic music is provided to match a wedding theme. The BGM selection unit also considers the participant profiles and provides background music that takes into account the participant profiles. For example, calm music is provided that matches the participants' industries and positions in a business meeting. The BGM selection unit also combines the event theme and the participant profiles to provide optimal background music. For example, pop music that children can enjoy is provided for a children's event. This allows the atmosphere of the event to be optimized by providing background music that matches the event theme and the participant profiles.

[0039] The BGM selection unit can analyze the acoustic characteristics of a location or scene and provide the optimal BGM for that location. For example, the BGM selection unit uses a generation AI to analyze the acoustic characteristics of a hotel lobby and provide luxurious BGM according to the reverberation and noise level. For example, classical music is provided when there is little reverberation. The BGM selection unit also analyzes the acoustic characteristics of a spa and provides relaxation music. For example, music incorporating natural sounds is provided when the noise level is high. The BGM selection unit also analyzes the acoustic characteristics of an event venue and provides BGM that matches the theme. For example, music with a simple melody is provided when there is a lot of reverberation. This allows for a more appropriate musical experience by providing the optimal BGM based on the acoustic characteristics of the location or scene.

[0040] The BGM providing unit can provide not only BGM but also video or visual effects in an integrated manner. For example, the BGM providing unit uses a generation AI to provide video and visual effects along with luxurious BGM according to the hotel lobby. For example, luxurious video is displayed on a screen in the lobby. The BGM providing unit also provides natural video and visual effects along with relaxation music according to the spa usage scenario. For example, natural scenery is projected onto the walls of the spa. The BGM providing unit also provides video and visual effects along with BGM according to the theme of the event venue. For example, video that matches the theme of the event is displayed on a screen. This allows for the integrated provision of not only BGM but also video and visual effects, further improving the customer experience.

[0041] The BGM selection unit can dynamically change the BGM in response to changes in location or scene. For example, the generation AI dynamically changes the BGM in response to the usage status of a hotel lobby. For example, relaxing music is provided when the lobby is crowded, and luxurious music is provided when the lobby is empty. The BGM selection unit also dynamically changes the BGM in response to the usage status of a spa. For example, relaxing music is provided when there are many users, and quiet music is provided when there are few users. The BGM selection unit also dynamically changes the BGM in response to the situation at an event venue. For example, music that matches the theme of the event is provided in accordance with the progress of the event. This allows the BGM to be dynamically changed in response to changes in location or scene, providing a more appropriate musical experience.

[0042] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0043] The BGM providing system can also analyze a user's activity history and provide the optimal BGM for a specific activity. For example, it can analyze the music a user has listened to while running in the past and provide the optimal BGM for similar activities. It can also analyze the music a user has listened to while reading and provide the optimal BGM for reading. It can also analyze the music a user has listened to while cooking and provide the optimal BGM for cooking. This can improve the user's experience by providing the optimal BGM based on the user's activity history.

[0044] The BGM providing system can also monitor the user's health condition and provide optimal BGM based on that data. For example, it can monitor the user's blood pressure and heart rate and provide relaxing BGM when relaxation is needed. It can also analyze the user's sleep patterns and provide BGM to improve sleep quality. It can also monitor the user's exercise volume and provide BGM to promote post-exercise recovery. This allows the system to support the user's health by providing optimal BGM based on the user's health condition.

[0045] The BGM providing system can also take the user's schedule into account and provide the optimal BGM for a specific time period. For example, it can analyze the user's work schedule and provide BGM to improve concentration. It can also take the user's relaxation time into account and provide relaxing BGM. It can also take the user's sleep time into account and provide BGM to promote sleep. In this way, the quality of life of the user can be improved by providing the optimal BGM based on the user's schedule.

[0046] The BGM providing system can also learn the user's favorite genres and artists and provide optimal BGM based on that. For example, it can analyze the user's favorite music genre and provide BGM based on that genre. It can also analyze the music of the user's favorite artists and provide BGM based on that artist. It can also analyze the user's favorite instruments and tones and provide BGM based on that. This can improve user satisfaction by providing optimal BGM based on the user's musical preferences.

[0047] The processing flow of the first embodiment will be briefly explained below.

[0048] Step 1: The BGM selection unit selects the optimal BGM based on the usage situation and customer needs. For example, the AI ​​generator might select relaxing music for a cafe, energetic music for a gym, and calming music for a restaurant. Step 2: The prompt generator generates a prompt based on the background music selected by the background music selector. For example, the AI ​​generates prompts such as "Play music that best suits this location" or "Play music that suits this scene" based on the selected background music. Step 3: The background music providing unit provides background music based on the prompt generated by the prompt generating unit. For example, the background music providing unit plays relaxing music, energetic music, or calming music based on the prompt generated by the generation AI.

[0049] (Example 2) The background music provision system according to an embodiment of the present invention is a system that provides optimal music (BGM) according to the usage scene and customer needs. By providing background music suited to a specific location or scene, this system creates a pleasant experience for customers and aims to improve satisfaction and repeat rates. In this way, the background music provision system can create a pleasant experience for customers and improve satisfaction and repeat rates.

[0050] A BGM provision system according to an embodiment includes a BGM selection unit, a prompt generation unit, and a BGM provision unit. The BGM selection unit selects optimal BGM according to the usage scenario and the customer's needs. For example, the generation AI selects relaxing music for a cafe. The generation AI can also select energetic music for a gym. The generation AI can also select calming music for a restaurant. The prompt generation unit generates a prompt based on the BGM selected by the BGM selection unit. For example, the generation AI can generate a prompt such as "Play music that is best suited to this location" based on the selected BGM. The generation AI can also generate a prompt such as "Play music that suits this scene" based on the selected BGM. The generation AI can also generate a prompt such as "Play music that meets these needs" based on the selected BGM. The BGM provision unit provides BGM based on the prompt generated by the prompt generation unit. For example, the BGM provision unit plays relaxing music based on the prompt generated by the generation AI. The BGM provision unit can also play energetic music based on the prompt generated by the generation AI. The BGM providing unit can also play calming music based on the prompt generated by the generation AI. This allows the BGM providing system according to the embodiment to provide optimal BGM according to the usage scenario and customer needs. For example, providing relaxing music in a cafe can create an environment that encourages customers to stay for a long time. Providing energetic music in a gym can increase motivation for training. Providing calming music in a restaurant can create an atmosphere conducive to enjoying a meal.

[0051] The BGM selection unit can analyze real-time environmental sounds in addition to the usage scene or customer needs and generate background music that harmonizes with them. For example, the BGM selection unit uses a generation AI to collect cafe noises in real time and generate relaxing background music that harmonizes with those sounds. For example, quiet jazz or acoustic music can be provided to match the background sounds of the cafe. The BGM selection unit can also analyze the sounds of gym machinery and people's movements in real time and generate energetic background music that harmonizes with them. For example, fast-paced electronic music can be provided to match the sound of a treadmill. The BGM selection unit can also collect restaurant environmental sounds (e.g., the clatter of dishes and the sounds of conversation) in real time and generate calming background music that harmonizes with them. For example, classical music or a solo piano performance can be provided. This allows for a more natural and comfortable experience by providing background music that harmonizes with real-time environmental sounds.

[0052] The BGM selection unit can learn a customer's past music history or preferences and provide individually customized BGM. For example, the BGM selection unit uses a generative AI to analyze a customer's past music history and provide customized BGM based on those preferences. For example, a customer who previously preferred relaxing music can be offered quiet jazz at a cafe. The BGM selection unit can also learn a customer's music streaming service history and provide individually customized BGM based on that data. For example, a customer who prefers energetic music at the gym can be offered up-tempo rock during workouts. The BGM selection unit can also analyze a customer's music playlist and provide customized BGM based on those preferences. For example, a customer who prefers classical music at a restaurant can be offered baroque music during meals. This allows for improved customer satisfaction by providing customized BGM based on the customer's past music history and preferences.

[0053] The BGM selection unit can estimate a customer's current emotional state and provide background music that best suits that emotion. For example, the BGM selection unit uses a generation AI to analyze a customer's facial expressions and voice to estimate their current emotional state. For example, if a customer is relaxed, the BGM selection unit provides relaxing background music in a cafe. The BGM selection unit also monitors a customer's heart rate and stress level in real time and estimates their emotional state based on that data. For example, if a customer is feeling high stress at the gym, the BGM selection unit provides relaxing background music. The BGM selection unit also analyzes a customer's social media posts and messages to estimate their current emotional state. For example, if a customer is feeling positive, the BGM selection unit provides enjoyable background music in a restaurant. This improves the customer experience by providing optimal background music based on the customer's current emotional state.

[0054] The BGM providing unit can comprehensively control not only background music but also environmental elements such as lighting and fragrance. For example, the BGM providing unit uses a generation AI to provide relaxing background music along with warm lighting and the aroma of coffee depending on the usage scenario of a cafe. This creates an environment where customers can relax. Similarly, the BGM providing unit provides energetic background music along with bright lighting and a fresh fragrance depending on the usage scenario of a gym. This creates an environment where customers can concentrate on their training. Similarly, the BGM providing unit provides calming background music along with soft lighting and an appetizing fragrance depending on the usage scenario of a restaurant. This creates an environment where customers can enjoy their meal. This comprehensive control of not only background music but also environmental elements such as lighting and fragrance further improves the customer experience.

[0055] The BGM selection unit can provide BGM appropriate for different cultural spheres or countries. For example, the BGM selection unit uses a generation AI to provide relaxing BGM appropriate for cafes in different cultural spheres. For example, a Japanese cafe might provide music using traditional Japanese instruments, while a French cafe might provide chanson. The BGM selection unit also provides energetic BGM appropriate for gyms in different countries. For example, an American gym might provide hip hop, while a Brazilian gym might provide samba. The BGM selection unit also provides calming BGM appropriate for restaurants in different cultural spheres. For example, an Italian restaurant might provide opera, and an Indian restaurant might provide Bollywood music. This allows the system to accommodate international customers by providing BGM appropriate for different cultural spheres or countries.

[0056] The BGM selection unit monitors changes in a customer's emotions in real time while they are listening to the BGM and can dynamically change the BGM as needed. For example, the BGM selection unit uses a generation AI to analyze the customer's facial expressions and voice in real time and monitor changes in emotions. For example, if a customer relaxing in a cafe begins to feel stressed, the BGM selection unit changes the BGM to something more relaxing. The BGM selection unit also monitors the customer's heart rate and stress level in real time and dynamically changes the BGM according to changes in emotions. For example, if a customer listening to energetic music at the gym begins to feel tired, the BGM selection unit changes to something more refreshing. The BGM selection unit also analyzes the customer's social media posts and messages in real time and dynamically changes the BGM according to changes in emotions. For example, if a customer listening to cheerful music in a restaurant begins to feel negative, the BGM selection unit changes to something more cheerful. This allows the BGM to be dynamically changed according to changes in the customer's emotions, providing more appropriate BGM.

[0057] The BGM selection unit can select BGM in accordance with the time of day or seasonal changes, taking into account changes in the time of day or the season. For example, the generation AI selects BGM in accordance with the usage scenario of a cafe, taking into account changes in the time of day or the season. For example, refreshing music is provided in the morning, and relaxing music in the evening. The BGM selection unit also selects BGM in accordance with the usage scenario of a gym, taking into account changes in the time of day or the season. For example, energetic music is provided in the summer, and warm music in the winter. The BGM selection unit also selects BGM in accordance with the usage scenario of a restaurant, taking into account changes in the time of day or the season. For example, light music is provided in the daytime, and calm music in the evening. This allows for the provision of BGM that takes into account changes in the time of day or the season, thereby providing more appropriate BGM.

[0058] The BGM selection unit can monitor the customer's biometric information in real time and select BGM based on that information. For example, the BGM selection unit uses a generation AI to monitor the customer's heart rate in real time and select optimal BGM based on that data. For example, if the heart rate is high, relaxing music is provided. The BGM selection unit can also monitor the customer's stress level in real time and select optimal BGM based on that data. For example, if the stress level is high, relaxing music is provided. The BGM selection unit can also monitor the customer's biometric information in real time and select optimal BGM based on that data. For example, if the heart rate or stress level is low, energetic music is provided. This makes it possible to improve the customer's experience by providing optimal BGM based on the customer's biometric information.

[0059] The BGM selection unit can analyze a customer's emotional history and select optimal BGM based on their past emotional patterns. For example, the BGM selection unit uses a generation AI to analyze a customer's past emotional history and select optimal BGM based on that data. For example, if a customer has previously preferred relaxing music, quiet jazz music can be served at a cafe. The BGM selection unit also selects BGM according to the customer's past emotional patterns based on their emotional history. For example, if a customer prefers energetic music at the gym, up-tempo rock music can be served during workouts. The BGM selection unit also analyzes a customer's emotional history and selects optimal BGM based on that data. For example, if a customer prefers classical music at a restaurant, baroque music can be served during meals. This allows the customer's experience to be improved by providing optimal BGM based on the customer's emotional history.

[0060] The BGM providing unit can provide not only background music but also audio guides or narration. For example, the BGM providing unit uses a generation AI to provide an audio guide introducing the cafe's menu and recommended products along with relaxing background music depending on the scene of the cafe. The BGM providing unit also provides an audio guide providing training instructions and advice along with energetic background music depending on the scene of the gym. The BGM providing unit also provides a narration explaining the dishes and introducing recommended wines along with calming background music depending on the scene of the restaurant. This allows for an improved customer experience by providing not only background music but also audio guides and narration.

[0061] The BGM providing unit can work with different devices to provide background music seamlessly. For example, the BGM providing unit's generation AI works with a smartphone to provide relaxing background music at a cafe. For example, it seamlessly switches the music a customer is playing on their smartphone to the cafe's speakers. The BGM providing unit also works with a smart speaker to provide energetic background music depending on the gym usage scenario. For example, it seamlessly switches the music a customer is playing on their smart speaker to the gym's speakers. The BGM providing unit also works with a smartphone or smart speaker to provide calming background music depending on the restaurant usage scenario. For example, it seamlessly switches the music a customer is playing on their smartphone to the restaurant's speakers. This allows for seamless BGM provision through collaboration with different devices, improving the customer experience.

[0062] The BGM selection unit monitors changes in a customer's emotions in real time while they are listening to background music and can continuously provide optimal background music. For example, the BGM selection unit uses a generation AI to analyze a customer's facial expressions and voice in real time to analyze emotional changes. For example, if a customer relaxing in a cafe begins to feel stressed, the BGM selection unit changes to something more relaxing. The BGM selection unit also monitors a customer's heart rate and stress level in real time and continuously provides background music in response to emotional changes. For example, if a customer listening to energetic music at the gym begins to feel tired, the BGM selection unit changes to something more refreshing. The BGM selection unit also analyzes a customer's social media posts and messages in real time and continuously provides background music in response to emotional changes. For example, if a customer listening to cheerful music in a restaurant begins to feel negative, the BGM selection unit changes to something more cheerful. This improves the customer experience by continuously providing optimal background music in response to changes in the customer's emotions.

[0063] The BGM selection unit can provide background music that takes into account the event theme or the participant profiles. For example, the BGM selection unit uses a generation AI to provide background music that is appropriate for a specific location or scene based on the event theme. For example, romantic music is provided to match a wedding theme. The BGM selection unit also considers the participant profiles and provides background music that takes into account the participant profiles. For example, calm music is provided that matches the participants' industries and positions in a business meeting. The BGM selection unit also combines the event theme and the participant profiles to provide optimal background music. For example, pop music that children can enjoy is provided for a children's event. This allows the atmosphere of the event to be optimized by providing background music that matches the event theme and the participant profiles.

[0064] The BGM selection unit can analyze the acoustic characteristics of a location or scene and provide the optimal BGM for that location. For example, the BGM selection unit uses a generation AI to analyze the acoustic characteristics of a hotel lobby and provide luxurious BGM according to the reverberation and noise level. For example, classical music is provided when there is little reverberation. The BGM selection unit also analyzes the acoustic characteristics of a spa and provides relaxation music. For example, music incorporating natural sounds is provided when the noise level is high. The BGM selection unit also analyzes the acoustic characteristics of an event venue and provides BGM that matches the theme. For example, music with a simple melody is provided when there is a lot of reverberation. This allows for a more appropriate musical experience by providing the optimal BGM based on the acoustic characteristics of the location or scene.

[0065] The BGM selection unit can estimate the emotions of people in a location or scene in real time and provide the BGM that best suits those emotions. For example, the BGM selection unit uses a generation AI to analyze the facial expressions and voices of people in a hotel lobby in real time to estimate their emotions. For example, it can provide luxurious BGM to people who are relaxing. The BGM selection unit can also monitor the heart rates and stress levels of people in a spa in real time to estimate their emotions. For example, it can provide relaxation music to people with high stress levels. The BGM selection unit can also analyze the social media posts and messages of people at an event venue in real time to estimate their emotions. For example, it can provide fun BGM that matches the theme to people with positive emotions. This allows for a more appropriate music experience by providing the optimal BGM based on the emotions of people in a location or scene.

[0066] The BGM providing unit can provide not only BGM but also video or visual effects in an integrated manner. For example, the BGM providing unit uses a generation AI to provide video and visual effects along with luxurious BGM according to the hotel lobby. For example, luxurious video is displayed on a screen in the lobby. The BGM providing unit also provides natural video and visual effects along with relaxation music according to the spa usage scenario. For example, natural scenery is projected onto the walls of the spa. The BGM providing unit also provides video and visual effects along with BGM according to the theme of the event venue. For example, video that matches the theme of the event is displayed on a screen. This allows for the integrated provision of not only BGM but also video and visual effects, further improving the customer experience.

[0067] The BGM selection unit can dynamically change the BGM in response to changes in location or scene. For example, the generation AI dynamically changes the BGM in response to the usage status of a hotel lobby. For example, relaxing music is provided when the lobby is crowded, and luxurious music is provided when the lobby is empty. The BGM selection unit also dynamically changes the BGM in response to the usage status of a spa. For example, relaxing music is provided when there are many users, and quiet music is provided when there are few users. The BGM selection unit also dynamically changes the BGM in response to the situation at an event venue. For example, music that matches the theme of the event is provided in accordance with the progress of the event. This allows the BGM to be dynamically changed in response to changes in location or scene, providing a more appropriate musical experience.

[0068] The BGM selection unit can monitor emotional changes of people in a location or scene in real time and continuously provide optimal BGM. For example, the BGM selection unit uses a generation AI to analyze the facial expressions and voices of people in a hotel lobby in real time and monitor emotional changes. For example, if people who are relaxing begin to feel stressed, the BGM selection unit changes to something more relaxing. The BGM selection unit also monitors the heart rates and stress levels of people in a spa in real time and continuously provides BGM according to emotional changes. For example, if people with high stress levels begin to relax, the BGM selection unit changes to something more relaxing. The BGM selection unit also analyzes social media posts and messages of people at an event venue in real time and continuously provides BGM according to emotional changes. For example, if people with positive emotions begin to feel negative, the BGM selection unit changes to something more enjoyable. This allows for a more appropriate music experience by continuously providing optimal BGM based on the emotional changes of people in a location or scene.

[0069] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0070] The BGM providing system can also analyze a user's activity history and provide the optimal BGM for a specific activity. For example, it can analyze the music a user has listened to while running in the past and provide the optimal BGM for similar activities. It can also analyze the music a user has listened to while reading and provide the optimal BGM for reading. It can also analyze the music a user has listened to while cooking and provide the optimal BGM for cooking. This can improve the user's experience by providing the optimal BGM based on the user's activity history.

[0071] The BGM providing system can also monitor the user's health condition and provide optimal BGM based on that data. For example, it can monitor the user's blood pressure and heart rate and provide relaxing BGM when relaxation is needed. It can also analyze the user's sleep patterns and provide BGM to improve sleep quality. It can also monitor the user's exercise volume and provide BGM to promote post-exercise recovery. This allows the system to support the user's health by providing optimal BGM based on the user's health condition.

[0072] The BGM providing system can also take the user's schedule into account and provide the optimal BGM for a specific time period. For example, it can analyze the user's work schedule and provide BGM to improve concentration. It can also take the user's relaxation time into account and provide relaxing BGM. It can also take the user's sleep time into account and provide BGM to promote sleep. In this way, the quality of life of the user can be improved by providing the optimal BGM based on the user's schedule.

[0073] The BGM providing system can also learn the user's favorite genres and artists and provide optimal BGM based on that. For example, it can analyze the user's favorite music genre and provide BGM based on that genre. It can also analyze the music of the user's favorite artists and provide BGM based on that artist. It can also analyze the user's favorite instruments and tones and provide BGM based on that. This can improve user satisfaction by providing optimal BGM based on the user's musical preferences.

[0074] The BGM providing system can also estimate the user's emotions and provide optimal BGM based on those emotions. For example, if the user is feeling stressed, relaxing BGM can be provided. If the user is excited, calming BGM can be provided. Furthermore, if the user is sad, mood-boosting BGM can be provided. In this way, the user's mood can be improved by providing optimal BGM based on the user's emotions.

[0075] The BGM providing system can also analyze the user's emotional history and provide optimal BGM based on past emotional patterns. For example, if the user has previously preferred listening to relaxing music, the system can provide relaxing BGM in a similar situation. If the user has previously preferred listening to energetic music, the system can provide energetic BGM in a similar situation. If the user has previously preferred listening to calming music, the system can provide calming BGM in a similar situation. This improves the user's experience by providing optimal BGM based on the user's emotional history.

[0076] The BGM providing system can also monitor changes in the user's emotions in real time and dynamically change the BGM as needed. For example, if the user is relaxed, relaxing BGM can be provided, and if the user begins to feel stressed, the BGM can be changed to more relaxing BGM. Also, if the user is listening to energetic music, energetic BGM can be provided, and if the user begins to feel tired, the BGM can be changed to refreshing BGM. Furthermore, if the user is listening to happy music, happy BGM can be provided, and if the user begins to feel negative emotions, the BGM can be changed to even more happy BGM. In this way, by dynamically changing the BGM according to changes in the user's emotions, more appropriate BGM can be provided.

[0077] The BGM providing system can also estimate the user's emotions and provide optimal BGM based on those emotions. For example, if the user is feeling stressed, relaxing BGM can be provided. If the user is excited, calming BGM can be provided. Furthermore, if the user is sad, mood-boosting BGM can be provided. In this way, the user's mood can be improved by providing optimal BGM based on the user's emotions.

[0078] The BGM providing system can also analyze the user's emotional history and provide optimal BGM based on past emotional patterns. For example, if the user has previously preferred listening to relaxing music, the system can provide relaxing BGM in a similar situation. If the user has previously preferred listening to energetic music, the system can provide energetic BGM in a similar situation. If the user has previously preferred listening to calming music, the system can provide calming BGM in a similar situation. This improves the user's experience by providing optimal BGM based on the user's emotional history.

[0079] The BGM providing system can also monitor changes in the user's emotions in real time and dynamically change the BGM as needed. For example, if the user is relaxed, relaxing BGM can be provided, and if the user begins to feel stressed, the BGM can be changed to more relaxing BGM. Also, if the user is listening to energetic music, energetic BGM can be provided, and if the user begins to feel tired, the BGM can be changed to refreshing BGM. Furthermore, if the user is listening to happy music, happy BGM can be provided, and if the user begins to feel negative emotions, the BGM can be changed to even more happy BGM. In this way, by dynamically changing the BGM according to changes in the user's emotions, more appropriate BGM can be provided.

[0080] The processing flow of the second embodiment will be briefly explained below.

[0081] Step 1: The BGM selection unit selects the optimal BGM based on the usage situation and customer needs. For example, the AI ​​generator might select relaxing music for a cafe, energetic music for a gym, and calming music for a restaurant. Step 2: The prompt generator generates a prompt based on the background music selected by the background music selector. For example, the AI ​​generates prompts such as "Play music that best suits this location" or "Play music that suits this scene" based on the selected background music. Step 3: The background music providing unit provides background music based on the prompt generated by the prompt generating unit. For example, the background music providing unit plays relaxing music, energetic music, or calming music based on the prompt generated by the generation AI.

[0082] 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.

[0083] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> 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.

[0084] 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.

[0085] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0086] 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.

[0087] 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.

[0088] 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.

[0089] 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.

[0090] 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).

[0091] 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.

[0092] 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.

[0093] 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.

[0094] 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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0095] 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. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0096] 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.

[0097] 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.

[0098] 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.

[0099] 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.

[0100] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0101] 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.

[0102] 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.

[0103] 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.

[0104] 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.

[0105] 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).

[0106] 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.

[0107] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0108] 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.

[0109] 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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0110] In the headset type terminal 314, 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 headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0111] 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.

[0112] 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.

[0113] 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.

[0114] 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.

[0115] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0116] 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.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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).

[0121] 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.

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0126] In the robot 414, 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. The robot 414 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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).

[0135] 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.

[0136] 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."

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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]

[0149] 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 BGM selection unit that selects the most suitable BGM according to the usage scene or customer needs; a prompt generation unit that generates a prompt based on the background music selected by the background music selection unit; a background music providing unit that provides background music based on the prompt generated by the prompt generating unit. A system characterized by:

2. The BGM selection unit Analyzing real-time environmental sounds in addition to the usage scene or the customer needs, and generating background music that harmonizes with them The system of claim 1 .

3. The BGM selection unit Learn the customer's past music history or preferences and provide individually customized background music The system of claim 1 .

4. The BGM selection unit Estimate the customer's current emotional state and provide the background music that best suits that emotion. The system of claim 1 .

5. The background music providing unit In addition to the background music, environmental elements such as lighting and fragrance are also controlled in an integrated manner. The system of claim 1 .

6. The BGM selection unit Providing background music according to the usage scene in different cultural areas or countries The system of claim 1 .

7. The BGM selection unit The emotional changes of the customer while listening to the background music are monitored in real time, and the background music is dynamically changed as necessary. The system of claim 1 .

8. The BGM selection unit Consider the time of day or seasonal changes and select the appropriate background music accordingly. The system of claim 1 .

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