System

Abstract

An object of a system according to an embodiment is to generate a AI avatar according to a user's need and to link the virtual avatar with the actual world.SOLUTION: A system includes a generation part, a position information interlocking part, and an action adjustment part. The generation unit generates a AI avatar in accordance with a user's need. The position information linkage unit determines an action of the AI avatar generated by the generation unit on the basis of the position information of the user. The action adjustment unit adjusts the action of the AI avatar determined by the position information linkage unit according to the real-world situation.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technology does not adequately generate AI avatars that meet user needs or link them to the real world, leaving room for improvement.

[0005] The system according to the embodiment aims to generate an AI avatar that meets the needs of the user and link it to the real world. [Means for solving the problem]

[0006] The system according to the embodiment includes a generation unit, a location information linkage unit, and a behavior adjustment unit. The generation unit generates an AI avatar according to the user's needs. The location information linkage unit determines the behavior of the AI ​​avatar generated by the generation unit based on the user's location information. The behavior adjustment unit adjusts the behavior of the AI ​​avatar determined by the location information linkage unit according to the situation in the real world. [Effects of the Invention]

[0007] The system according to the embodiment can generate an AI avatar that meets the user's needs and link it to the real world. [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 pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

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

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

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

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

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

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

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

[0028] (Example 1) The Local Lab system according to the embodiment of the present invention is a system that realizes new connections between people by generating AI avatars that meet the needs of users and linking them with the real world. This allows the Local Lab system to provide users with a new form of human relationships.

[0029] A localab system according to an embodiment includes a generation unit, a location information linkage unit, and a behavior adjustment unit. The generation unit generates an AI avatar according to the user's needs. For example, the generation unit generates an individually customized AI avatar based on prompts containing the user's desired avatar characteristics. The generation AI uses a text generation AI (e.g., LLM) or a multimodal generation AI to set the user's appearance and personality based on the user's preferences and requests. For example, if the user desires a boyfriend who is kind and loves sports, the generation AI generates an avatar that meets those requirements. The location information linkage unit determines how the virtual partner behaves in the real world based on the user's location information. For example, if the user is in a specific location, the AI ​​avatar will engage in conversations and behaviors appropriate to that location. The generation AI determines how the virtual partner behaves in the real world based on the user's location information. The behavior adjustment unit adjusts the AI ​​avatar's behavior according to the situation in the real world. For example, if the user is busy at work, the AI ​​avatar will send a message such as, "Thank you for your hard work. Please take it easy today." Additionally, if the user is traveling, the system provides information about the travel destination and recommended spots. This allows the Localab system to offer users a new form of human relationships. For example, users can communicate with a virtual partner, such as a local boyfriend or girlfriend, as if they were actually there. The system can also be customized to meet the user's needs, providing an individually optimized experience. Furthermore, privacy protection features allow users to use the system with peace of mind.

[0030] The generation unit can analyze the user's past behavioral history or interaction history to generate a more accurate AI avatar. For example, the generation unit collects data on places the user has visited or events they have attended in the past and sets the avatar's hobbies and interests based on that data. For example, the generation unit can make the avatar have detailed knowledge of cafes and restaurants the user frequently visits. The generation unit also analyzes the user's interaction history to learn the user's preferred topics and language. For example, the generation unit can set the avatar to engage in natural conversations based on the user's frequently used phrases and topics. Furthermore, the generation unit learns the user's behavioral patterns and sets the avatar to behave in a way that matches the user's lifestyle. For example, if the user jogs every morning, the avatar can suggest, "How's today's jogging route?" This allows for more accurate avatar generation by analyzing the user's past behavioral history and interaction history.

[0031] The generation unit can acquire the user's biometric information in real time and adjust the AI ​​avatar's responses based on it. For example, the generation unit can monitor the user's heart rate in real time and provide the avatar with advice to help them relax when stress levels rise. For example, it can send a message such as, "Take a deep breath and relax." The generation unit also analyzes the user's facial expressions using a camera, and when the user smiles, the avatar responds with a smile. For example, if the user speaks with a smile, the avatar will also respond with a smile, saying, "You look like you're having fun." The generation unit also collects the user's body temperature and electrodermal activity using sensors to estimate the user's emotional state. For example, if the user is nervous, the avatar will send a message such as, "Relax and speak slowly." This allows the generation unit to acquire the user's biometric information in real time and adjust the avatar's responses based on it.

[0032] The generation unit can provide specific scenarios that reflect the user's hobbies and interests. For example, if the user likes watching sports, the generation unit can provide a scenario in which the avatar watches a game together. For example, the generation unit can start a conversation such as, "Which team are you rooting for today?". If the user's hobby is cooking, the generation unit can provide a scenario in which the avatar cooks together. For example, the generation unit can make a suggestion such as, "Let's try a new recipe together today." If the user likes traveling, the generation unit can provide a scenario in which the avatar provides information about travel destinations. For example, the generation unit can provide information such as, "Here's a recommended destination for your next trip." This makes it possible to provide specific scenarios that reflect the user's hobbies and interests.

[0033] The generation unit generates AI avatars with different cultural backgrounds, allowing users to experience intercultural exchange. For example, the generation unit generates avatars with different cultural backgrounds to provide users with opportunities to learn about those cultures. For example, the avatar may start a conversation by saying, "Today, I'll introduce you to traditional cuisine from my country." The generation unit also provides scenarios for users to participate in intercultural exchange events. For example, the generation unit may suggest, "Let's participate in an intercultural exchange event today." Furthermore, the generation unit provides information for users to learn about different cultures. For example, the generation unit may provide information such as, "Would you like to know more about the culture of this country?" This allows avatars with different cultural backgrounds to be generated, allowing users to experience intercultural exchange.

[0034] The location information interlocking unit can learn the user's past visit history and preferences based on the user's location information and suggest optimal AI avatar behavior. For example, the location information interlocking unit collects data on places the user has visited in the past, and the avatar suggests actions related to those places. For example, it makes a suggestion such as, "There's a cafe you like nearby." The location information interlocking unit also learns the user's preferences, and the avatar suggests actions that match those preferences. For example, it makes a suggestion such as, "Your favorite movie is playing today." Furthermore, the location information interlocking unit provides the avatar with information related to the location based on the user's visit history. For example, it provides information such as, "This place is a place you have visited before." This allows the system to learn the user's past visit history and preferences based on the user's location information and suggest optimal avatar behavior.

[0035] The location information interlocking unit can combine the user's location information and weather information to generate optimal AI avatar behavior and conversation. For example, the location information interlocking unit combines the user's location information with weather information, and the avatar suggests behavior that matches the weather of the day. For example, it makes a suggestion such as, "It's sunny today, so let's go on a picnic outside together." The location information interlocking unit also uses the user's location information and weather information to have the avatar have a conversation about the weather of the day. For example, it makes a conversation such as, "It looks like it's going to rain today, so let's take an umbrella." The location information interlocking unit also uses the user's location information and weather information to have the avatar suggest clothing that matches the weather of the day. For example, it makes a suggestion such as, "It's cold today, so let's wear warm clothes." In this way, the user's location information and weather information can be combined to generate optimal avatar behavior and conversation.

[0036] The behavior adjustment unit allows the AI ​​avatar to introduce the history and culture of a place depending on the place the user visits. For example, the behavior adjustment unit allows the avatar to introduce the history of a place the user visits. For example, it provides information such as, "This place was an important battlefield in the past." The behavior adjustment unit also allows the avatar to introduce the culture of a place the user visits. For example, it provides information such as, "A festival is held in this area every year." The behavior adjustment unit also allows the avatar to introduce historical events and people of a place the user visits. For example, it provides information such as, "This place is where a famous historical figure was born." This allows the avatar to introduce the history and culture of a place depending on the place the user visits.

[0037] The behavior adjustment unit allows the AI ​​avatar to suggest local events and activities based on the user's location information. For example, the behavior adjustment unit allows the avatar to suggest local events based on the user's location information. For example, the behavior adjustment unit makes a suggestion such as, "There's a music festival being held nearby, let's go together." The behavior adjustment unit also allows the avatar to suggest local activities based on the user's location information. For example, the behavior adjustment unit makes a suggestion such as, "There's a hiking spot nearby, let's go together." The behavior adjustment unit also allows the avatar to suggest local tourist spots based on the user's location information. For example, the behavior adjustment unit makes a suggestion such as, "There's a famous tourist spot nearby, let's go together." This allows the avatar to suggest local events and activities based on the user's location information.

[0038] The behavior adjustment unit can combine the user's location information and time period to generate optimal behavior for the AI ​​avatar. For example, the behavior adjustment unit combines the user's location information and time period and suggests behavior for the avatar that is appropriate for that time period. For example, it may suggest, "It's late at night, so it's time to get some rest." The behavior adjustment unit also has the avatar engage in conversation appropriate for that time period based on the user's location information and time period. For example, it may say, "It's early in the morning, so let's start the day energetically." The behavior adjustment unit also has the avatar engage in conversation appropriate for that time period based on the user's location information and time period. For example, it may say, "It's daytime, so let's go for a walk outside." In this way, the optimal behavior for the avatar can be generated by combining the user's location information and time period.

[0039] The behavior adjustment unit can analyze the user's location information and the behavior of people around them and adjust the behavior of the AI ​​avatar based on that information. The behavior adjustment unit, for example, analyzes the user's location information and the behavior of people around them, and the avatar takes actions that suit the situation. For example, if the user is in a crowded place, the avatar may suggest, "Walk carefully." Also, if the user is in a quiet place, the behavior adjustment unit may suggest actions for the avatar to take to relax. For example, the behavior adjustment unit may suggest, "Let's take a short break here." Furthermore, when the user interacts with people around them in a specific place, the behavior adjustment unit may have the avatar engage in conversation that is tailored to the situation. For example, the behavior adjustment unit may suggest, "This is how you greet people in this place." This allows the avatar to analyze the user's location information and the behavior of people around them and adjust its behavior based on that information.

[0040] The behavior adjustment unit allows the AI ​​avatar to introduce local specialties and famous foods of a location based on the user's location information. For example, the behavior adjustment unit allows the avatar to introduce local specialties of a location based on the user's location information. For example, it provides information such as, "This area is famous for its delicious apples." The behavior adjustment unit also allows the avatar to introduce local specialties of a location based on the user's location information. For example, it provides information such as, "This is the local specialty of this area." The behavior adjustment unit also allows the avatar to introduce tourist attractions of a location based on the user's location information. For example, it provides information such as, "There are tourist attractions like this in this area." This allows the avatar to introduce local specialties and famous foods of a location based on the user's location information.

[0041] The behavior adjustment unit allows the AI ​​avatar to converse in the local language or dialect based on the user's location information. For example, the behavior adjustment unit allows the avatar to converse in the local dialect based on the user's location information. For example, the behavior adjustment unit may start a conversation such as, "This is how you greet people here." The behavior adjustment unit also allows the avatar to converse in the local language based on the user's location information. For example, the behavior adjustment unit may start a conversation such as, "This is the kind of language we use in this area." Furthermore, the behavior adjustment unit allows the avatar to converse about the local culture based on the user's location information. For example, the behavior adjustment unit may start a conversation such as, "This is the kind of culture we have in this area." This allows the avatar to converse in the local language or dialect based on the user's location information.

[0042] The generation unit can analyze the user's tone of voice and speaking style and customize the voice and speaking style of the AI ​​avatar based on that. For example, the generation unit analyzes the user's tone of voice and customizes the avatar so that it speaks in the same tone. For example, if the user speaks in a soft tone, the avatar also responds in a soft tone. The generation unit also analyzes the user's speaking style and customizes the avatar so that it speaks in the same way. For example, if the user speaks slowly, the avatar is set to speak slowly as well. Furthermore, the generation unit analyzes the characteristics of the user's voice and customizes the avatar so that it speaks in a voice that reflects those characteristics. For example, if the user speaks in a high-pitched voice, the avatar also responds in a high-pitched voice. In this way, the user's tone of voice and speaking style can be analyzed and the avatar's voice and speaking style can be customized based on that.

[0043] The generation unit can learn the user's lifestyle and daily routine and set the AI ​​avatar's behavior pattern that is optimal for that lifestyle. For example, the generation unit learns the user's lifestyle and sets the avatar to behave in a way that suits that lifestyle. For example, if the user jogs every morning, the avatar might suggest, "How's your jogging route today?" The generation unit also learns the user's daily routine and sets the avatar to behave in a way that suits that routine. For example, if the user reads every night, the avatar might suggest, "Which book should you read today?" Furthermore, the generation unit allows the avatar to provide advice that is tailored to the user's lifestyle and routine, such as advice like, "Take a short break today." In this way, the generation unit can learn the user's lifestyle and daily routine and set the avatar's behavior pattern that is optimal for that lifestyle.

[0044] The generation unit can incorporate information about the user's pets and family, and generate behavior and conversation for the AI ​​avatar accordingly. For example, the generation unit incorporates information about the user's pet, and the avatar talks about the pet. For example, it might start a conversation like, "Did you take your dog for a walk today?" The generation unit also incorporates information about the user's family, and the avatar talks about the family. For example, it might start a conversation like, "Are you spending time with your family today?" Furthermore, the generation unit uses information about the user's pets and family to cause the avatar to act based on that information. For example, if the user is with their pet, the avatar might suggest, "Let's play together." This makes it possible to incorporate information about the user's pets and family, and generate behavior and conversation for the avatar accordingly.

[0045] The generation unit enables the AI ​​avatar to provide health advice based on the user's health condition and fitness goals. The generation unit, for example, monitors the user's health condition, and the avatar provides appropriate health advice. For example, it sends a message such as, "Drink plenty of water today." The generation unit also enables the avatar to provide advice tailored to the user's fitness goals based on those goals. For example, it sends a message such as, "Work hard on your strength training today." Furthermore, the generation unit enables the avatar to support the user toward those goals based on the user's health condition and fitness goals. For example, it gives advice such as, "Take a short break today." This allows the avatar to provide health advice based on the user's health condition and fitness goals.

[0046] The location information linking unit allows the AI ​​avatar to introduce local specialties and famous foods of a location based on the user's location information. For example, the location information linking unit allows the avatar to introduce local specialties of a location based on the user's location information. For example, it provides information such as, "This area is famous for its delicious apples." The location information linking unit also allows the avatar to introduce local specialties of a location based on the user's location information. For example, it provides information such as, "This is the local specialty of this area." The location information linking unit also allows the avatar to introduce tourist attractions of a location based on the user's location information. For example, it provides information such as, "There are tourist attractions like this in this area." This allows the avatar to introduce local specialties and famous foods of a location based on the user's location information.

[0047] The location information interlocking unit enables the AI ​​avatar to converse in the local language or dialect based on the user's location information. For example, the location information interlocking unit causes the avatar to converse in the local dialect based on the user's location information. For example, the location information interlocking unit may start a conversation such as, "This is how you greet people here." The location information interlocking unit also causes the avatar to converse in the local language based on the user's location information. For example, the conversation may start with, "These are the words we use in this area." Furthermore, the location information interlocking unit causes the avatar to converse about the local culture based on the user's location information. For example, the conversation may start with, "This is the culture we have in this area." This allows the avatar to converse in the local language or dialect based on the user's location information.

[0048] The location information linking unit allows the AI ​​avatar to introduce local specialties and famous foods of a location based on the user's location information. For example, the location information linking unit allows the avatar to introduce local specialties of a location based on the user's location information. For example, it provides information such as, "This area is famous for its delicious apples." The location information linking unit also allows the avatar to introduce local specialties of a location based on the user's location information. For example, it provides information such as, "This is the local specialty of this area." The location information linking unit also allows the avatar to introduce tourist attractions of a location based on the user's location information. For example, it provides information such as, "There are tourist attractions like this in this area." This allows the avatar to introduce local specialties and famous foods of a location based on the user's location information.

[0049] The location information interlocking unit enables the AI ​​avatar to converse in the local language or dialect based on the user's location information. For example, the location information interlocking unit causes the avatar to converse in the local dialect based on the user's location information. For example, the location information interlocking unit may start a conversation such as, "This is how you greet people here." The location information interlocking unit also causes the avatar to converse in the local language based on the user's location information. For example, the conversation may start with, "These are the words we use in this area." Furthermore, the location information interlocking unit causes the avatar to converse about the local culture based on the user's location information. For example, the conversation may start with, "This is the culture we have in this area." This allows the avatar to converse in the local language or dialect based on the user's location information.

[0050] The location information linking unit allows the AI ​​avatar to introduce local specialties and famous foods of a location based on the user's location information. For example, the location information linking unit allows the avatar to introduce local specialties of a location based on the user's location information. For example, it provides information such as, "This area is famous for its delicious apples." The location information linking unit also allows the avatar to introduce local specialties of a location based on the user's location information. For example, it provides information such as, "This is the local specialty of this area." The location information linking unit also allows the avatar to introduce tourist attractions of a location based on the user's location information. For example, it provides information such as, "There are tourist attractions like this in this area." This allows the avatar to introduce local specialties and famous foods of a location based on the user's location information.

[0051] The location information interlocking unit enables the AI ​​avatar to converse in the local language or dialect based on the user's location information. For example, the location information interlocking unit causes the avatar to converse in the local dialect based on the user's location information. For example, the location information interlocking unit may start a conversation such as, "This is how you greet people here." The location information interlocking unit also causes the avatar to converse in the local language based on the user's location information. For example, the conversation may start with, "These are the words we use in this area." Furthermore, the location information interlocking unit causes the avatar to converse about the local culture based on the user's location information. For example, the conversation may start with, "This is the culture we have in this area." This allows the avatar to converse in the local language or dialect based on the user's location information.

[0052] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0053] The generation unit can analyze the user's tone of voice and speaking style, and customize the voice and speaking style of the AI ​​avatar based on that. For example, the user's tone of voice can be analyzed and the avatar can be customized to speak in the same tone. If the user speaks in a gentle tone, the avatar will respond in a gentle tone. The generation unit can also analyze the user's speaking style and customize the avatar to speak in the same way. If the user speaks slowly, the avatar can also be set to speak slowly. Furthermore, the generation unit can analyze the user's voice characteristics and customize the avatar to speak in a voice that reflects those characteristics. If the user speaks in a high-pitched voice, the avatar will respond in a high-pitched voice. This allows the user's tone of voice and speaking style to be analyzed and the avatar's voice and speaking style to be customized based on that.

[0054] The generation unit can learn the user's lifestyle and daily routine and set the AI ​​avatar's behavioral patterns that are optimal for that lifestyle. For example, it can learn the user's lifestyle and set the avatar to behave in a way that suits that lifestyle. If the user jogs every morning, the avatar can suggest, "How's your jogging route today?" It can also learn the user's daily routine and set the avatar to behave in a way that suits that routine. If the user reads every night, the avatar can suggest, "Which book should we read today?" Furthermore, based on the user's lifestyle and routine, the avatar can provide advice that is tailored to that lifestyle. For example, it can advise, "Take a short break today." In this way, it can learn the user's lifestyle and daily routine and set the avatar's behavioral patterns that are optimal for that lifestyle.

[0055] The generation unit can incorporate information about the user's pets and family, and generate the AI ​​avatar's behavior and conversation accordingly. For example, information about the user's pets can be incorporated, and the avatar can talk about the pet. If the user has a dog, the avatar can start a conversation such as, "Did you take your dog for a walk today?". Information about the user's family can also be incorporated, and the avatar can talk about the family. If the user often spends time with their family, the avatar can start a conversation such as, "Are you spending time with your family today?". Furthermore, based on the information about the user's pets and family, the avatar can act accordingly. If the user is with their pet, the avatar can make suggestions such as, "Let's play together." This allows the system to incorporate information about the user's pets and family, and generate the avatar's behavior and conversation accordingly.

[0056] The generation unit enables the AI ​​avatar to provide health advice based on the user's health condition and fitness goals. For example, the avatar monitors the user's health condition and provides appropriate health advice. If the user tends to neglect hydration, the avatar will send a message such as "Make sure to drink plenty of water today." The avatar will also provide advice tailored to the user's fitness goals. If the user's goal is muscle training, the avatar will send a message such as "Let's work hard on muscle training today." Furthermore, the avatar will support the user toward their goals based on their health condition and fitness goals. If the user is tired, the avatar will give advice such as "Take a short break today." This allows the avatar to provide health advice based on the user's health condition and fitness goals.

[0057] The behavior adjustment unit allows the AI ​​avatar to introduce the history and culture of a place depending on the place the user visits. For example, the avatar introduces the history of the place the user visits. If the user visits a historical place, the avatar provides information such as, "This place was once an important battlefield." The avatar also introduces the culture of the place the user visits. If the user participates in a cultural event, the avatar provides information such as, "A festival is held in this area every year." The avatar also introduces historical events and people in the place the user visits. If the user visits the birthplace of a famous historical figure, the avatar provides information such as, "This place is where a famous historical figure was born." This allows the avatar to introduce the history and culture of a place depending on the place the user visits.

[0058] The behavior adjustment unit allows the AI ​​avatar to suggest local events and activities based on the user's location information. For example, the avatar suggests local events based on the user's location information. If the user is in a tourist spot, the avatar may make a suggestion such as, "There's a music festival being held nearby, let's go together." The avatar may also suggest local activities based on the user's location information. If the user is in a place rich in nature, the avatar may make a suggestion such as, "There's a hiking spot nearby, let's go together." The avatar may also suggest local tourist spots based on the user's location information. If the user is in a tourist spot, the avatar may make a suggestion such as, "There's a famous tourist spot nearby, let's go together." This allows the avatar to suggest local events and activities based on the user's location information.

[0059] The behavior adjustment unit can combine the user's location information and time of day to generate optimal behavior for the AI ​​avatar. For example, by combining the user's location information and time of day, the avatar suggests behavior appropriate for that time of day. If the user is out late at night, the avatar may suggest, "It's late, so it's time to get some rest." In addition, based on the user's location information and time of day, the avatar may engage in conversation appropriate for that time of day. If the user starts their activities early in the morning, the avatar may engage in conversation such as, "It's early in the morning, so let's start the day energetically." In addition, based on the user's location information and time of day, the avatar may suggest activities appropriate for that time of day. If the user is out during the day, the avatar may suggest, "It's daytime, so let's go for a walk outside." In this way, the optimal avatar behavior can be generated by combining the user's location information and time of day.

[0060] The processing flow of the first embodiment will be briefly explained below.

[0061] Step 1: The generator generates an AI avatar based on the user's needs. For example, the generator generates an individually customized AI avatar based on prompts containing the user's desired avatar characteristics. The generator uses text generation AI (e.g., LLM) or multimodal generation AI to set the appearance and personality based on the user's preferences and requests. For example, if the user desires a boyfriend who is kind and likes sports, the generator AI generates an avatar that meets those requirements. Step 2: The location information linkage unit determines how the virtual partner will behave in the real world based on the user's location information. For example, if the user is in a specific location, the AI ​​avatar will have conversations and behave in a way that is appropriate for that location. Step 3: The behavior adjustment unit adjusts the AI ​​avatar's behavior according to the situation in the real world. For example, if the user is busy at work, the AI ​​avatar will send a message such as "Thank you for your hard work, please take a good rest today." If the user is traveling, the AI ​​avatar will provide information about the travel destination and recommended spots.

[0062] (Example 2) The Local Lab system according to the embodiment of the present invention is a system that realizes new connections between people by generating AI avatars that meet the needs of users and linking them with the real world. This allows the Local Lab system to provide users with a new form of human relationships.

[0063] A localab system according to an embodiment includes a generation unit, a location information linkage unit, and a behavior adjustment unit. The generation unit generates an AI avatar according to the user's needs. For example, the generation unit generates an individually customized AI avatar based on prompts containing the user's desired avatar characteristics. The generation AI uses a text generation AI (e.g., LLM) or a multimodal generation AI to set the user's appearance and personality based on the user's preferences and requests. For example, if the user desires a boyfriend who is kind and loves sports, the generation AI generates an avatar that meets those requirements. The location information linkage unit determines how the virtual partner behaves in the real world based on the user's location information. For example, if the user is in a specific location, the AI ​​avatar will engage in conversations and behaviors appropriate to that location. The generation AI determines how the virtual partner behaves in the real world based on the user's location information. The behavior adjustment unit adjusts the AI ​​avatar's behavior according to the situation in the real world. For example, if the user is busy at work, the AI ​​avatar will send a message such as, "Thank you for your hard work. Please take it easy today." Additionally, if the user is traveling, the system provides information about the destination and recommended spots. This allows the Localab system to offer users a new form of human relationships. For example, users can communicate with a virtual partner, such as a local boyfriend or girlfriend, as if they were in real life. The system can also be customized to meet the user's needs, providing an individually optimized experience. Furthermore, privacy protection features allow users to use the system with peace of mind.

[0064] The generation unit can analyze the user's past behavioral history or interaction history to generate a more accurate AI avatar. For example, the generation unit collects data on places the user has visited or events they have attended in the past and sets the avatar's hobbies and interests based on that data. For example, the generation unit can make the avatar have detailed knowledge of cafes and restaurants the user frequently visits. The generation unit also analyzes the user's interaction history to learn the user's preferred topics and language. For example, the generation unit can set the avatar to engage in natural conversations based on the user's frequently used phrases and topics. Furthermore, the generation unit learns the user's behavioral patterns and sets the avatar to behave in a way that matches the user's lifestyle. For example, if the user jogs every morning, the avatar can suggest, "How's today's jogging route?" This allows for more accurate avatar generation by analyzing the user's past behavioral history and interaction history.

[0065] The generation unit can acquire the user's biometric information in real time and adjust the AI ​​avatar's responses based on it. For example, the generation unit can monitor the user's heart rate in real time and provide the avatar with advice to help them relax when stress levels rise. For example, it can send a message such as, "Take a deep breath and relax." The generation unit also analyzes the user's facial expressions using a camera, and when the user smiles, the avatar responds with a smile. For example, if the user speaks with a smile, the avatar will also respond with a smile, saying, "You look like you're having fun." The generation unit also collects the user's body temperature and electrodermal activity using sensors to estimate the user's emotional state. For example, if the user is nervous, the avatar will send a message such as, "Relax and speak slowly." This allows the generation unit to acquire the user's biometric information in real time and adjust the avatar's responses based on it.

[0066] The generation unit uses the emotion estimation function to generate an AI avatar according to the user's emotional state, and can provide an AI avatar that helps the user relax. For example, the generation unit analyzes the user's emotional state in real time, and if the user is under high stress, it generates an avatar that has a relaxing effect. For example, it provides an avatar that speaks in a calming voice. Furthermore, if the user is happy, the generation unit behaves as if the avatar is sharing the joy with the user. For example, it sends a message such as "Let's celebrate together." Furthermore, if the user is sad, the generation unit behaves as if the avatar is comforting the user. For example, it sends a message such as "It's okay, I'm always here for you." In this way, the emotion estimation function can be used to provide an avatar that helps the user relax.

[0067] The generation unit can provide specific scenarios that reflect the user's hobbies and interests. For example, if the user likes watching sports, the generation unit can provide a scenario in which the avatar watches a game together. For example, the generation unit can start a conversation such as, "Which team are you rooting for today?". If the user's hobby is cooking, the generation unit can provide a scenario in which the avatar cooks together. For example, the generation unit can make a suggestion such as, "Let's try a new recipe together today." If the user likes traveling, the generation unit can provide a scenario in which the avatar provides information about travel destinations. For example, the generation unit can provide information such as, "Here's a recommended destination for your next trip." This makes it possible to provide specific scenarios that reflect the user's hobbies and interests.

[0068] The generation unit generates AI avatars with different cultural backgrounds, allowing users to experience intercultural exchange. For example, the generation unit generates avatars with different cultural backgrounds to provide users with opportunities to learn about those cultures. For example, the avatar may start a conversation by saying, "Today, I'll introduce you to traditional cuisine from my country." The generation unit also provides scenarios for users to participate in intercultural exchange events. For example, the generation unit may suggest, "Let's participate in an intercultural exchange event today." Furthermore, the generation unit provides information for users to learn about different cultures. For example, the generation unit may provide information such as, "Would you like to know more about the culture of this country?" This allows avatars with different cultural backgrounds to be generated, allowing users to experience intercultural exchange.

[0069] The generation unit can use the emotion estimation function to automatically generate an AI avatar that suits a specific emotion when the user feels that emotion. For example, when the user feels sad, the generation unit automatically generates an avatar that comforts the user. For example, it provides an avatar that sends a message such as "Don't worry, I'm always here for you." The generation unit also automatically generates an avatar that shares the user's joy when the user is happy. For example, it provides an avatar that sends a message such as "Let's celebrate together." Furthermore, when the user feels like relaxing, the generation unit automatically generates an avatar that has a relaxing effect. For example, it provides an avatar that speaks in a calming voice. In this way, when the user feels a specific emotion, an avatar that suits that emotion can be automatically generated.

[0070] The location information interlocking unit can learn the user's past visit history and preferences based on the user's location information and suggest optimal AI avatar behavior. For example, the location information interlocking unit collects data on places the user has visited in the past, and the avatar suggests actions related to those places. For example, it makes a suggestion such as, "There's a cafe you like nearby." The location information interlocking unit also learns the user's preferences, and the avatar suggests actions that match those preferences. For example, it makes a suggestion such as, "Your favorite movie is playing today." Furthermore, the location information interlocking unit provides the avatar with information related to the location based on the user's visit history. For example, it provides information such as, "This place is a place you have visited before." This allows the system to learn the user's past visit history and preferences based on the user's location information and suggest optimal avatar behavior.

[0071] The location information interlocking unit can combine the user's location information and weather information to generate optimal AI avatar behavior and conversation. For example, the location information interlocking unit combines the user's location information with weather information, and the avatar suggests behavior that matches the weather of the day. For example, it makes a suggestion such as, "It's sunny today, so let's go on a picnic outside together." The location information interlocking unit also uses the user's location information and weather information to have the avatar have a conversation about the weather of the day. For example, it makes a conversation such as, "It looks like it's going to rain today, so let's take an umbrella." The location information interlocking unit also uses the user's location information and weather information to have the avatar suggest clothing that matches the weather of the day. For example, it makes a suggestion such as, "It's cold today, so let's wear warm clothes." In this way, the user's location information and weather information can be combined to generate optimal avatar behavior and conversation.

[0072] The location information interlocking unit can use the emotion estimation function to estimate the user's emotional state based on the user's location information and adjust the behavior of the AI ​​avatar based on that. The location information interlocking unit can, for example, estimate the user's emotional state based on the user's location information, and the avatar can behave in accordance with that emotion. For example, if the user is in a crowded place, the avatar can send a message such as "It's okay, calm down." Furthermore, if the user is in a quiet place, the location information interlocking unit can suggest actions for the avatar to take to relax. For example, it can suggest "Let's take a short break here." Furthermore, if the user shows an emotional reaction in a specific place, the location information interlocking unit can cause the avatar to behave in accordance with that emotion. For example, if the user is in a sad place, the avatar can send a message such as "It's okay, I'm always here for you." This allows the emotion estimation function to estimate the user's emotional state based on the user's location information and adjust the avatar's behavior based on that emotion.

[0073] The behavior adjustment unit allows the AI ​​avatar to introduce the history and culture of a place depending on the place the user visits. For example, the behavior adjustment unit allows the avatar to introduce the history of a place the user visits. For example, it provides information such as, "This place was an important battlefield in the past." The behavior adjustment unit also allows the avatar to introduce the culture of a place the user visits. For example, it provides information such as, "A festival is held in this area every year." The behavior adjustment unit also allows the avatar to introduce historical events and people of a place the user visits. For example, it provides information such as, "This place is where a famous historical figure was born." This allows the avatar to introduce the history and culture of a place depending on the place the user visits.

[0074] The behavior adjustment unit allows the AI ​​avatar to suggest local events and activities based on the user's location information. For example, the behavior adjustment unit allows the avatar to suggest local events based on the user's location information. For example, the behavior adjustment unit makes a suggestion such as, "There's a music festival being held nearby, let's go together." The behavior adjustment unit also allows the avatar to suggest local activities based on the user's location information. For example, the behavior adjustment unit makes a suggestion such as, "There's a hiking spot nearby, let's go together." The behavior adjustment unit also allows the avatar to suggest local tourist spots based on the user's location information. For example, the behavior adjustment unit makes a suggestion such as, "There's a famous tourist spot nearby, let's go together." This allows the avatar to suggest local events and activities based on the user's location information.

[0075] The behavior adjustment unit can use the emotion estimation function to automatically generate behavior for the AI ​​avatar according to the emotions the user feels at a specific location. For example, if the user is relaxing at a specific location, the behavior adjustment unit automatically generates behavior for the avatar that matches that emotion. For example, it makes a suggestion such as, "Let's take a short break here." Furthermore, if the user is feeling stressed at a specific location, the behavior adjustment unit automatically generates behavior for the avatar to relax. For example, it makes a suggestion such as, "Take a deep breath and relax." Furthermore, if the user is happy at a specific location, the behavior adjustment unit automatically generates behavior for the avatar to share the joy with the user. For example, it makes a suggestion such as, "Let's celebrate together." In this way, the emotion estimation function can automatically generate behavior for the avatar according to the emotions the user feels at a specific location.

[0076] The behavior adjustment unit can combine the user's location information and time period to generate optimal behavior for the AI ​​avatar. For example, the behavior adjustment unit combines the user's location information and time period and suggests behavior for the avatar that is appropriate for that time period. For example, it may suggest, "It's late at night, so it's time to get some rest." The behavior adjustment unit also has the avatar engage in conversation appropriate for that time period based on the user's location information and time period. For example, it may say, "It's early in the morning, so let's start the day energetically." The behavior adjustment unit also has the avatar engage in conversation appropriate for that time period based on the user's location information and time period. For example, it may say, "It's daytime, so let's go for a walk outside." In this way, the optimal behavior for the avatar can be generated by combining the user's location information and time period.

[0077] The behavior adjustment unit can analyze the user's location information and the behavior of people around them and adjust the behavior of the AI ​​avatar based on that information. The behavior adjustment unit, for example, analyzes the user's location information and the behavior of people around them, and the avatar takes actions that suit the situation. For example, if the user is in a crowded place, the avatar may suggest, "Walk carefully." Also, if the user is in a quiet place, the behavior adjustment unit may suggest actions for the avatar to take to relax. For example, the behavior adjustment unit may suggest, "Let's take a short break here." Furthermore, when the user interacts with people around them in a specific place, the behavior adjustment unit may have the avatar engage in conversation that is tailored to the situation. For example, the behavior adjustment unit may suggest, "This is how you greet people in this place." This allows the avatar to analyze the user's location information and the behavior of people around them and adjust its behavior based on that information.

[0078] The behavior adjustment unit can use the emotion estimation function to estimate the user's emotional state based on the user's location information and adjust the behavior of the AI ​​avatar based on that. The behavior adjustment unit can estimate the user's emotional state based on the user's location information, and the avatar can behave in accordance with that emotion. For example, if the user is in a crowded place, the avatar can send a message such as "It's okay, calm down." If the user is in a quiet place, the behavior adjustment unit can suggest actions for the avatar to relax. For example, the behavior adjustment unit can suggest "Let's take a short break here." Furthermore, if the user shows an emotional reaction in a specific place, the avatar can behave in accordance with that emotion. For example, if the user is in a sad place, the avatar can send a message such as "It's okay, I'm always here for you." This allows the emotion estimation function to estimate the user's emotional state based on the user's location information and adjust the avatar's behavior based on that emotion.

[0079] The behavior adjustment unit allows the AI ​​avatar to introduce local specialties and famous foods of a location based on the user's location information. For example, the behavior adjustment unit allows the avatar to introduce local specialties of a location based on the user's location information. For example, it provides information such as, "This area is famous for its delicious apples." The behavior adjustment unit also allows the avatar to introduce local specialties of a location based on the user's location information. For example, it provides information such as, "This is the local specialty of this area." The behavior adjustment unit also allows the avatar to introduce tourist attractions of a location based on the user's location information. For example, it provides information such as, "There are tourist attractions like this in this area." This allows the avatar to introduce local specialties and famous foods of a location based on the user's location information.

[0080] The behavior adjustment unit allows the AI ​​avatar to converse in the local language or dialect based on the user's location information. For example, the behavior adjustment unit allows the avatar to converse in the local dialect based on the user's location information. For example, the behavior adjustment unit may start a conversation such as, "This is how you greet people here." The behavior adjustment unit also allows the avatar to converse in the local language based on the user's location information. For example, the behavior adjustment unit may start a conversation such as, "This is the kind of language we use in this area." Furthermore, the behavior adjustment unit allows the avatar to converse about the local culture based on the user's location information. For example, the behavior adjustment unit may start a conversation such as, "This is the kind of culture we have in this area." This allows the avatar to converse in the local language or dialect based on the user's location information.

[0081] The behavior adjustment unit can use the emotion estimation function to automatically generate behavior for the AI ​​avatar according to the emotions the user feels at a specific location. For example, if the user is relaxing at a specific location, the behavior adjustment unit automatically generates behavior for the avatar that matches that emotion. For example, it makes a suggestion such as, "Let's take a short break here." Furthermore, if the user is feeling stressed at a specific location, the behavior adjustment unit automatically generates behavior for the avatar to relax. For example, it makes a suggestion such as, "Take a deep breath and relax." Furthermore, if the user is happy at a specific location, the behavior adjustment unit automatically generates behavior for the avatar to share the joy with the user. For example, it makes a suggestion such as, "Let's celebrate together." In this way, the emotion estimation function can automatically generate behavior for the avatar according to the emotions the user feels at a specific location.

[0082] The generation unit can analyze the user's tone of voice and speaking style and customize the voice and speaking style of the AI ​​avatar based on that. For example, the generation unit analyzes the user's tone of voice and customizes the avatar so that it speaks in the same tone. For example, if the user speaks in a soft tone, the avatar also responds in a soft tone. The generation unit also analyzes the user's speaking style and customizes the avatar so that it speaks in the same way. For example, if the user speaks slowly, the avatar is set to speak slowly as well. Furthermore, the generation unit analyzes the characteristics of the user's voice and customizes the avatar so that it speaks in a voice that reflects those characteristics. For example, if the user speaks in a high-pitched voice, the avatar also responds in a high-pitched voice. In this way, the user's tone of voice and speaking style can be analyzed and the avatar's voice and speaking style can be customized based on that.

[0083] The generation unit can learn the user's lifestyle and daily routine and set the AI ​​avatar's behavior pattern that is optimal for that lifestyle. For example, the generation unit learns the user's lifestyle and sets the avatar to behave in a way that suits that lifestyle. For example, if the user jogs every morning, the avatar might suggest, "How's your jogging route today?" The generation unit also learns the user's daily routine and sets the avatar to behave in a way that suits that routine. For example, if the user reads every night, the avatar might suggest, "Which book should you read today?" Furthermore, the generation unit allows the avatar to provide advice that is tailored to the user's lifestyle and routine, such as advice like, "Take a short break today." In this way, the generation unit can learn the user's lifestyle and daily routine and set the avatar's behavior pattern that is optimal for that lifestyle.

[0084] The generation unit can use the emotion estimation function to automatically change the appearance and clothing of the AI ​​avatar according to the user's emotions. For example, when the user feels like relaxing, the generation unit automatically changes the avatar's appearance and clothing to something that has a relaxing effect. For example, the avatar changes to casual clothing. Furthermore, when the user is happy, the generation unit changes the avatar's appearance and clothing to bright colors. For example, the avatar is set to wear bright-colored clothing. Furthermore, when the user is sad, the generation unit changes the avatar's appearance and clothing to something that has a comforting effect. For example, the avatar is set to have a calm expression. In this way, the emotion estimation function can be used to automatically change the avatar's appearance and clothing according to the user's emotions.

[0085] The generation unit can incorporate information about the user's pets and family, and generate behavior and conversation for the AI ​​avatar accordingly. For example, the generation unit incorporates information about the user's pet, and the avatar talks about the pet. For example, it might start a conversation like, "Did you take your dog for a walk today?" The generation unit also incorporates information about the user's family, and the avatar talks about the family. For example, it might start a conversation like, "Are you spending time with your family today?" Furthermore, the generation unit uses information about the user's pets and family to cause the avatar to act based on that information. For example, if the user is with their pet, the avatar might suggest, "Let's play together." This makes it possible to incorporate information about the user's pets and family, and generate behavior and conversation for the avatar accordingly.

[0086] The generation unit enables the AI ​​avatar to provide health advice based on the user's health condition and fitness goals. The generation unit, for example, monitors the user's health condition, and the avatar provides appropriate health advice. For example, it sends a message such as, "Drink plenty of water today." The generation unit also enables the avatar to provide advice tailored to the user's fitness goals based on those goals. For example, it sends a message such as, "Work hard on your strength training today." Furthermore, the generation unit enables the avatar to support the user toward those goals based on the user's health condition and fitness goals. For example, it gives advice such as, "Take a short break today." This allows the avatar to provide health advice based on the user's health condition and fitness goals.

[0087] The generation unit can use the emotion estimation function to automatically generate an AI avatar behavior that is optimal for a particular emotion when the user feels that emotion. For example, when the user feels stressed, the generation unit automatically generates an avatar behavior that has a relaxing effect. For example, it makes a suggestion such as, "Let's take a deep breath together." Furthermore, when the user is happy, the generation unit automatically generates an avatar behavior that shares the joy with the user. For example, it makes a suggestion such as, "Let's celebrate together." Furthermore, when the user is sad, the generation unit automatically generates an avatar behavior that comforts the user. For example, it makes a suggestion such as, "It's okay, I'm always here for you." In this way, when the user feels a particular emotion, the emotion estimation function can automatically generate an avatar behavior that is optimal for that emotion.

[0088] The location information linking unit allows the AI ​​avatar to introduce local specialties and famous foods of a location based on the user's location information. For example, the location information linking unit allows the avatar to introduce local specialties of a location based on the user's location information. For example, it provides information such as, "This area is famous for its delicious apples." The location information linking unit also allows the avatar to introduce local specialties of a location based on the user's location information. For example, it provides information such as, "This is the local specialty of this area." The location information linking unit also allows the avatar to introduce tourist attractions of a location based on the user's location information. For example, it provides information such as, "There are tourist attractions like this in this area." This allows the avatar to introduce local specialties and famous foods of a location based on the user's location information.

[0089] The location information interlocking unit enables the AI ​​avatar to converse in the local language or dialect based on the user's location information. For example, the location information interlocking unit causes the avatar to converse in the local dialect based on the user's location information. For example, the location information interlocking unit may start a conversation such as, "This is how you greet people here." The location information interlocking unit also causes the avatar to converse in the local language based on the user's location information. For example, the conversation may start with, "These are the words we use in this area." Furthermore, the location information interlocking unit causes the avatar to converse about the local culture based on the user's location information. For example, the conversation may start with, "This is the culture we have in this area." This allows the avatar to converse in the local language or dialect based on the user's location information.

[0090] The location information interlocking unit can use the emotion estimation function to automatically generate behavior for the AI ​​avatar according to the emotions the user feels at a specific location. For example, if the user is relaxing at a specific location, the location information interlocking unit automatically generates behavior for the avatar that matches that emotion. For example, it makes a suggestion such as, "Let's take a short break here." Furthermore, if the user is feeling stressed at a specific location, the location information interlocking unit automatically generates behavior for the avatar to relax. For example, it makes a suggestion such as, "Take a deep breath and relax." Furthermore, if the user is happy at a specific location, the location information interlocking unit automatically generates behavior for the avatar to share the joy with the user. For example, it makes a suggestion such as, "Let's celebrate together." In this way, the emotion estimation function can automatically generate behavior for the avatar according to the emotions the user feels at a specific location.

[0091] The location information linking unit allows the AI ​​avatar to introduce local specialties and famous foods of a location based on the user's location information. For example, the location information linking unit allows the avatar to introduce local specialties of a location based on the user's location information. For example, it provides information such as, "This area is famous for its delicious apples." The location information linking unit also allows the avatar to introduce local specialties of a location based on the user's location information. For example, it provides information such as, "This is the local specialty of this area." The location information linking unit also allows the avatar to introduce tourist attractions of a location based on the user's location information. For example, it provides information such as, "There are tourist attractions like this in this area." This allows the avatar to introduce local specialties and famous foods of a location based on the user's location information.

[0092] The location information interlocking unit enables the AI ​​avatar to converse in the local language or dialect based on the user's location information. For example, the location information interlocking unit causes the avatar to converse in the local dialect based on the user's location information. For example, the location information interlocking unit may start a conversation such as, "This is how you greet people here." The location information interlocking unit also causes the avatar to converse in the local language based on the user's location information. For example, the conversation may start with, "These are the words we use in this area." Furthermore, the location information interlocking unit causes the avatar to converse about the local culture based on the user's location information. For example, the conversation may start with, "This is the culture we have in this area." This allows the avatar to converse in the local language or dialect based on the user's location information.

[0093] The location information interlocking unit can use the emotion estimation function to automatically generate behavior for the AI ​​avatar according to the emotions the user feels at a specific location. For example, if the user is relaxing at a specific location, the location information interlocking unit automatically generates behavior for the avatar that matches that emotion. For example, it makes a suggestion such as, "Let's take a short break here." Furthermore, if the user is feeling stressed at a specific location, the location information interlocking unit automatically generates behavior for the avatar to relax. For example, it makes a suggestion such as, "Take a deep breath and relax." Furthermore, if the user is happy at a specific location, the location information interlocking unit automatically generates behavior for the avatar to share the joy with the user. For example, it makes a suggestion such as, "Let's celebrate together." In this way, the emotion estimation function can automatically generate behavior for the avatar according to the emotions the user feels at a specific location.

[0094] The location information linking unit allows the AI ​​avatar to introduce local specialties and famous foods of a location based on the user's location information. For example, the location information linking unit allows the avatar to introduce local specialties of a location based on the user's location information. For example, it provides information such as, "This area is famous for its delicious apples." The location information linking unit also allows the avatar to introduce local specialties of a location based on the user's location information. For example, it provides information such as, "This is the local specialty of this area." The location information linking unit also allows the avatar to introduce tourist attractions of a location based on the user's location information. For example, it provides information such as, "There are tourist attractions like this in this area." This allows the avatar to introduce local specialties and famous foods of a location based on the user's location information.

[0095] The location information interlocking unit enables the AI ​​avatar to converse in the local language or dialect based on the user's location information. For example, the location information interlocking unit causes the avatar to converse in the local dialect based on the user's location information. For example, the location information interlocking unit may start a conversation such as, "This is how you greet people here." The location information interlocking unit also causes the avatar to converse in the local language based on the user's location information. For example, the conversation may start with, "These are the words we use in this area." Furthermore, the location information interlocking unit causes the avatar to converse about the local culture based on the user's location information. For example, the conversation may start with, "This is the culture we have in this area." This allows the avatar to converse in the local language or dialect based on the user's location information.

[0096] The location information interlocking unit can use the emotion estimation function to automatically generate behavior for the AI ​​avatar according to the emotions the user feels at a specific location. For example, if the user is relaxing at a specific location, the location information interlocking unit automatically generates behavior for the avatar that matches that emotion. For example, it makes a suggestion such as, "Let's take a short break here." Furthermore, if the user is feeling stressed at a specific location, the location information interlocking unit automatically generates behavior for the avatar to relax. For example, it makes a suggestion such as, "Take a deep breath and relax." Furthermore, if the user is happy at a specific location, the location information interlocking unit automatically generates behavior for the avatar to share the joy with the user. For example, it makes a suggestion such as, "Let's celebrate together." In this way, the emotion estimation function can automatically generate behavior for the avatar according to the emotions the user feels at a specific location.

[0097] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0098] The generation unit can analyze the user's tone of voice and speaking style, and customize the voice and speaking style of the AI ​​avatar based on that. For example, the user's tone of voice can be analyzed and the avatar can be customized to speak in the same tone. If the user speaks in a gentle tone, the avatar will respond in a gentle tone. The generation unit can also analyze the user's speaking style and customize the avatar to speak in the same way. If the user speaks slowly, the avatar can also be set to speak slowly. Furthermore, the generation unit can analyze the user's voice characteristics and customize the avatar to speak in a voice that reflects those characteristics. If the user speaks in a high-pitched voice, the avatar will respond in a high-pitched voice. This allows the user's tone of voice and speaking style to be analyzed and the avatar's voice and speaking style to be customized based on that.

[0099] The generation unit can learn the user's lifestyle and daily routine and set the AI ​​avatar's behavioral patterns that are optimal for that lifestyle. For example, it can learn the user's lifestyle and set the avatar to behave in a way that suits that lifestyle. If the user jogs every morning, the avatar can suggest, "How's your jogging route today?" It can also learn the user's daily routine and set the avatar to behave in a way that suits that routine. If the user reads every night, the avatar can suggest, "Which book should we read today?" Furthermore, based on the user's lifestyle and routine, the avatar can provide advice that is tailored to that lifestyle. For example, it can advise, "Take a short break today." In this way, it can learn the user's lifestyle and daily routine and set the avatar's behavioral patterns that are optimal for that lifestyle.

[0100] The generation unit can incorporate information about the user's pets and family, and generate the AI ​​avatar's behavior and conversation accordingly. For example, information about the user's pets can be incorporated, and the avatar can talk about the pet. If the user has a dog, the avatar can start a conversation such as, "Did you take your dog for a walk today?". Information about the user's family can also be incorporated, and the avatar can talk about the family. If the user often spends time with their family, the avatar can start a conversation such as, "Are you spending time with your family today?". Furthermore, based on the information about the user's pets and family, the avatar can act accordingly. If the user is with their pet, the avatar can make suggestions such as, "Let's play together." This allows the system to incorporate information about the user's pets and family, and generate the avatar's behavior and conversation accordingly.

[0101] The generation unit enables the AI ​​avatar to provide health advice based on the user's health condition and fitness goals. For example, the avatar monitors the user's health condition and provides appropriate health advice. If the user tends to neglect hydration, the avatar will send a message such as "Make sure to drink plenty of water today." The avatar will also provide advice tailored to the user's fitness goals. If the user's goal is muscle training, the avatar will send a message such as "Let's work hard on muscle training today." Furthermore, the avatar will support the user toward their goals based on their health condition and fitness goals. If the user is tired, the avatar will give advice such as "Take a short break today." This allows the avatar to provide health advice based on the user's health condition and fitness goals.

[0102] The generation unit can automatically change the appearance and clothing of the AI ​​avatar according to the user's emotions. For example, when the user feels like relaxing, the avatar's appearance and clothing can be automatically changed to have a relaxing effect. The avatar can change to casual clothing. Also, when the user is happy, the avatar's appearance and clothing can be changed to bright colors. The avatar can be set to wear bright-colored clothing. Furthermore, when the user is sad, the avatar's appearance and clothing can be changed to have a comforting effect. The avatar can be set to have a calm expression. In this way, the emotion estimation function can be used to automatically change the avatar's appearance and clothing according to the user's emotions.

[0103] The generation unit can use the emotion estimation function to automatically generate an AI avatar behavior that is optimal for a particular emotion when the user feels that emotion. For example, when the user feels stressed, the avatar will automatically generate an action that has a relaxing effect. The avatar will make a suggestion such as, "Let's take a deep breath together." Similarly, when the user is happy, the avatar will automatically generate an action to share the joy. The avatar will make a suggestion such as, "Let's celebrate together." Furthermore, when the user is sad, the avatar will automatically generate an action to comfort the user. The avatar will make a suggestion such as, "It's okay, I'm always here for you." In this way, when the user feels a particular emotion, the emotion estimation function can automatically generate an avatar behavior that is optimal for that emotion.

[0104] The behavior adjustment unit allows the AI ​​avatar to introduce the history and culture of a place depending on the place the user visits. For example, the avatar introduces the history of the place the user visits. If the user visits a historical place, the avatar provides information such as, "This place was once an important battlefield." The avatar also introduces the culture of the place the user visits. If the user participates in a cultural event, the avatar provides information such as, "A festival is held in this area every year." The avatar also introduces historical events and people in the place the user visits. If the user visits the birthplace of a famous historical figure, the avatar provides information such as, "This place is where a famous historical figure was born." This allows the avatar to introduce the history and culture of a place depending on the place the user visits.

[0105] The behavior adjustment unit allows the AI ​​avatar to suggest local events and activities based on the user's location information. For example, the avatar suggests local events based on the user's location information. If the user is in a tourist spot, the avatar may make a suggestion such as, "There's a music festival being held nearby, let's go together." The avatar may also suggest local activities based on the user's location information. If the user is in a place rich in nature, the avatar may make a suggestion such as, "There's a hiking spot nearby, let's go together." The avatar may also suggest local tourist spots based on the user's location information. If the user is in a tourist spot, the avatar may make a suggestion such as, "There's a famous tourist spot nearby, let's go together." This allows the avatar to suggest local events and activities based on the user's location information.

[0106] The behavior adjustment unit can use the emotion estimation function to automatically generate behavior for the AI ​​avatar according to the emotions the user feels at a specific location. For example, if the user is relaxing at a specific location, the avatar will automatically generate behavior that matches that emotion. The avatar will make a suggestion such as, "Let's take a short break here." Also, if the user is feeling stressed at a specific location, the avatar will automatically generate behavior to help the user relax. The avatar will make a suggestion such as, "Take a deep breath and relax." Furthermore, if the user is happy at a specific location, the avatar will automatically generate behavior to share the joy with the user. The avatar will make a suggestion such as, "Let's celebrate together." In this way, the emotion estimation function can automatically generate behavior for the avatar according to the emotions the user feels at a specific location.

[0107] The behavior adjustment unit can combine the user's location information and time of day to generate optimal behavior for the AI ​​avatar. For example, by combining the user's location information and time of day, the avatar suggests behavior appropriate for that time of day. If the user is out late at night, the avatar may suggest, "It's late, so it's time to get some rest." In addition, based on the user's location information and time of day, the avatar may engage in conversation appropriate for that time of day. If the user starts their activities early in the morning, the avatar may engage in conversation such as, "It's early in the morning, so let's start the day energetically." In addition, based on the user's location information and time of day, the avatar may suggest activities appropriate for that time of day. If the user is out during the day, the avatar may suggest, "It's daytime, so let's go for a walk outside." In this way, the optimal avatar behavior can be generated by combining the user's location information and time of day.

[0108] The processing flow of the second embodiment will be briefly explained below.

[0109] Step 1: The generator generates an AI avatar based on the user's needs. For example, the generator generates an individually customized AI avatar based on prompts containing the user's desired avatar characteristics. The generator uses text generation AI (e.g., LLM) or multimodal generation AI to set the appearance and personality based on the user's preferences and requests. For example, if the user desires a boyfriend who is kind and likes sports, the generator AI generates an avatar that meets those requirements. Step 2: The location information linkage unit determines how the virtual partner will behave in the real world based on the user's location information. For example, if the user is in a specific location, the AI ​​avatar will have conversations and behave in a way that is appropriate for that location. Step 3: The behavior adjustment unit adjusts the AI ​​avatar's behavior according to the situation in the real world. For example, if the user is busy at work, the AI ​​avatar will send a message such as "Thank you for your hard work, please take a good rest today." If the user is traveling, the AI ​​avatar will provide information about the travel destination and recommended spots.

[0110] 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.

[0111] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0112] 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.

[0113] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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.

[0118] 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).

[0119] 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.

[0120] 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.

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

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

[0123] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

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

[0125] The specific processing unit 290 transmits the result of the specific processing to the 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.

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

[0127] The data processing system 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.

[0128] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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).

[0134] 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.

[0135] 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.

[0136] 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.

[0137] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0138] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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.

[0143] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0144] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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).

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0154] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0155] 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.

[0156] 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.

[0157] 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.

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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.

[0162] 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).

[0163] 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 "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[0164] 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."

[0165] 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.

[0166] 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.

[0167] 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.

[0168] 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.

[0169] 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.

[0170] 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.

[0171] 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.

[0172] 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.

[0173] 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.

[0174] 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.

[0175] 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.

[0176] 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]

[0177] 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 generation unit that generates an AI avatar according to the user's needs; a location information linkage unit that determines the behavior of the AI ​​avatar generated by the generation unit based on user location information; and a behavior adjustment unit that adjusts the behavior of the AI ​​avatar determined by the location information linkage unit in accordance with the situation in the real world. A system characterized by:

2. The generation unit Using an emotion estimation function, the AI ​​avatar is generated according to the emotional state of the user, and the AI ​​avatar is provided so that the user can relax. The system of claim 1 .

3. The generation unit The AI ​​avatars are generated with different cultural backgrounds, allowing the users to experience intercultural exchange. The system of claim 1 .

4. The location information linking unit Based on the user's location information, the system learns past visit history and preferences and suggests optimal actions for the AI ​​avatar. The system of claim 1 .

5. The behavior adjustment unit Depending on the location the user visits, the AI ​​avatar introduces the history and culture of that location. The system of claim 1 .

Images