System

Abstract

An object of the system according to the embodiment is to efficiently acquire necessary information at the time of waking up in the morning and to image daily activities.SOLUTION: A system according to an embodiment includes a news providing unit, a weather information providing unit, a calendar information providing unit, an unread message providing unit, and a radio program generation unit. The news providing unit provides news. The weather information providing unit provides weather information. The calendar information providing unit provides calendar information. The unread message providing unit provides an unread message. The radio program generation unit generates a radio program based on information from the news providing unit, the weather information providing unit, the calendar information providing unit, and the unread message providing unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] With conventional technology, it was difficult to efficiently obtain the necessary information when waking up in the morning and visualize the activities of the day.

[0005] The system according to the embodiment aims to efficiently obtain necessary information when waking up in the morning and to visualize the activities of the day. [Means for solving the problem]

[0006] The system according to the embodiment includes a news providing unit, a weather information providing unit, a calendar information providing unit, an unread message providing unit, and a radio program generating unit. The news providing unit provides news. The weather information providing unit provides weather information. The calendar information providing unit provides calendar information. The unread message providing unit provides unread messages. The radio program generating unit generates a radio program based on information from the news providing unit, the weather information providing unit, the calendar information providing unit, and the unread message providing unit. [Effects of the Invention]

[0007] The system according to the embodiment efficiently acquires necessary information when you wake up in the morning, allowing you to visualize your activities for the day. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

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

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

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

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

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

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

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

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

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

[0028] (Example 1) A system according to an embodiment of the present invention allows users to visualize their day's activities while dozing in bed without opening their eyes. This system delivers information such as news, weather, calendars, and unread important messages in an original radio program format, narrated by AI. This allows users to use the system as content they can listen to in the background. When users wake up in the morning, they can check their schedule for the day and grasp important messages while listening to the latest news and weather information. This allows users to start their day in the best possible way, keeping their brains fully engaged.

[0029] The system according to the embodiment includes a news providing unit, a weather information providing unit, a calendar information providing unit, an unread message providing unit, and a radio program generating unit. The news providing unit provides news. For example, the generation AI collects the latest news and selects information important to the user. The generation AI analyzes news, including major domestic and international news, economic information, sports results, etc., and summarizes it in a form easy to understand for the user. The generation AI receives input from prompts containing instructions for news collection and summarization, and the generation AI generates news based on the prompts. The weather information providing unit provides weather information. For example, the generation AI collects and provides the latest weather information based on the user's location. The generation AI analyzes weather information, including today's weather forecast, temperature, and probability of precipitation, and summarizes it in a form easy to understand for the user. The generation AI receives input from prompts containing instructions for weather information collection and summarization, and the generation AI generates weather information based on the prompts. The calendar information providing unit provides calendar information. For example, the generation AI collects the user's calendar information and provides today's schedule and important events. The generation AI analyzes calendar information, including meeting schedules and birthday reminders, and summarizes it in a form that is easy for the user to understand. The generation AI receives input from prompts containing instructions for collecting and summarizing calendar information, and generates calendar information based on the prompts. The unread message provider provides unread messages. For example, the generation AI collects the user's unread messages and selects and provides important messages. The generation AI analyzes unread messages, including work emails and messages from family, and summarizes them in a form that is easy for the user to understand. The generation AI receives input from prompts containing instructions for collecting and summarizing unread messages, and generates unread messages based on the prompts. The radio program generator generates a radio program based on information from the news provider, weather information provider, calendar information provider, and unread message provider. For example, the generation AI combines the collected news, weather, calendar, and unread important message information to create a narration that is easy for the user to listen to.The input to the generation AI is prompts containing instructions for generating a radio program and narration, and the generation AI generates a radio program based on the prompts. This allows the system according to the embodiment to allow the user to imagine the day's activities while dozing off in bed without opening their eyes. For example, when waking up in the morning, the user can check the day's schedule and grasp important messages while listening to the latest news and weather information. This allows the user to fully utilize their brain and start the day in the best possible way.

[0030] The news providing unit generates personalized comments and questions to attract the user's attention based on the content of the news, thereby stimulating the user's thinking. The news providing unit, for example, analyzes the content of a news article and generates personalized comments based on the user's past browsing history and interests. For example, if the user is interested in economic news, the news providing unit provides detailed comments related to economic news. The news providing unit also analyzes the content of a news article and generates questions to attract the user's attention. For example, if the user is interested in sports news, the news providing unit provides questions related to sports news. This can stimulate the user's thinking and deepen their understanding of the news.

[0031] When providing news, the news providing unit automatically adds related past news and background information, thereby deepening the user's understanding. The news providing unit, for example, analyzes the content of a news article and automatically adds related past news and background information. For example, it provides information on past economic trends and policy changes related to current economic news. The news providing unit also analyzes the content of a news article and provides details and historical background of related events. For example, it provides information on past international relations and historical events related to current international news. This allows the user to deepen their understanding.

[0032] The news providing unit can provide a multisensory experience by combining not only sound but also vibration and light patterns when providing news. For example, the news providing unit not only provides the content of a news article by sound but also vibration and light patterns to provide a multisensory experience. For example, when there is important news, the device vibrates to notify the user. Furthermore, the news providing unit can notify the user by combining light patterns when providing the content of a news article by sound. For example, the color or blinking pattern of the light can be changed depending on the importance of the news. This makes it possible to provide a multisensory experience to the user.

[0033] The news providing unit customizes the content of the news based on the user's past behavioral history and interests, and can provide more personalized information. The news providing unit, for example, analyzes the content of a news article and customizes it based on the user's past behavioral history and interests. For example, if the user is interested in economic news, the news providing unit provides economic news preferentially. The news providing unit also analyzes the content of a news article and customizes the news based on the user's interests. For example, if the user is interested in sports news, the news providing unit provides sports news preferentially. This makes it possible to provide personalized information to the user.

[0034] The weather information providing unit can automatically generate suggestions for clothing and belongings that match the user's schedule based on the weather information. The weather information providing unit, for example, analyzes weather information and automatically generates suggestions for clothing and belongings that match the user's schedule. For example, an umbrella or a waterproof jacket is suggested for a rainy day. The weather information providing unit also analyzes weather information and automatically generates suggestions for clothing and belongings that match the user's schedule. For example, a coat or gloves is suggested for a cold day. The weather information providing unit also analyzes weather information and automatically generates suggestions for clothing and belongings that match the user's schedule. For example, a hat or sunglasses is suggested for a hot day. In this way, suggestions for appropriate clothing and belongings can be provided to the user.

[0035] The weather information providing unit can refer to past weather data and weather patterns when providing weather information and predict the impact on the user. For example, when providing weather information, the weather information providing unit can refer to past weather data and weather patterns and predict the impact on the user. For example, based on past data, it predicts the impact of specific weather conditions on the user's health. Furthermore, for example, when providing weather information, the weather information providing unit can refer to past weather data and weather patterns and predict the impact on the user. For example, based on past data, it predicts the impact of specific weather conditions on the user's activity. This makes it possible to predict the impact on the user.

[0036] The weather information providing unit can customize weather information based on the user's health condition and activity level and provide health management advice. The weather information providing unit, for example, analyzes weather information and customizes it based on the user's health condition and activity level. For example, it suggests measures to take on days with a lot of pollen for a user with allergies. The weather information providing unit also analyzes weather information and customizes it based on the user's health condition and activity level. For example, it suggests appropriate exercise times and locations for a user who exercises. This makes it possible to provide health management advice to the user.

[0037] The calendar information providing unit can automatically generate an efficient schedule proposal that matches the user's schedule based on the calendar information. The calendar information providing unit, for example, analyzes the calendar information and automatically generates an efficient schedule proposal that matches the user's schedule. For example, it proposes an optimal schedule taking into consideration the priorities of meetings and tasks. The calendar information providing unit also, for example, analyzes the calendar information and automatically generates an efficient schedule proposal that matches the user's schedule. For example, it proposes an optimal schedule taking into consideration important events and reminders. This makes it possible to provide the user with an efficient schedule proposal.

[0038] The calendar information providing unit can synchronize the calendar information with the schedules of the user's family and friends and suggest joint events and activities. The calendar information providing unit, for example, analyzes the calendar information, synchronizes it with the schedules of the user's family and friends, and suggests joint events and activities. For example, it suggests a schedule of an event that all family members can participate in. The calendar information providing unit can also analyze the calendar information, synchronizes it with the schedules of the user's friends, and suggests joint activities. For example, it suggests a schedule of an event that can be enjoyed together with friends. In this way, joint events and activities can be suggested to the user.

[0039] The calendar information providing unit can customize calendar information based on the user's hobbies and interests and suggest related events and activities. The calendar information providing unit, for example, analyzes calendar information and customizes it based on the user's hobbies and interests. For example, if the user is interested in music, it suggests a schedule of music events. The calendar information providing unit can also analyze calendar information and customize it based on the user's hobbies and interests. For example, if the user is interested in sports, it suggests a schedule of sports events. This makes it possible to suggest events and activities relevant to the user.

[0040] The unread message providing unit can provide messages that are most important to the user on a priority basis based on the contents of the unread messages. The unread message providing unit, for example, analyzes the contents of the unread messages and provides messages that are most important to the user on a priority basis. For example, work emails and messages from family members are displayed on a priority basis. The unread message providing unit can also analyze the contents of the unread messages and provide messages that are most important to the user on a priority basis. For example, emergency messages and important notifications are displayed on a priority basis. This allows messages that are most important to the user to be provided on a priority basis.

[0041] When providing an unread message, the unread message providing unit can refer to related past messages and conversation history to deepen the user's understanding. The unread message providing unit, for example, analyzes the content of the unread message and refers to related past messages and conversation history. For example, based on the past conversation history, provides background information for the current message. Furthermore, the unread message providing unit, for example, analyzes the content of the unread message and refers to related past messages and conversation history. For example, based on past emails and chat history, provides background information for the current message. This can deepen the user's understanding.

[0042] The unread message providing unit can customize unread messages based on the user's current situation and schedule, and provide them at the optimal timing. The unread message providing unit, for example, analyzes the content of the unread message and customizes it based on the user's current situation and schedule. For example, if the user is in a meeting, an important message is notified later. The unread message providing unit also analyzes the content of the unread message and customizes it based on the user's current situation and schedule. For example, if the user is driving, a message is notified later. This makes it possible to provide messages to the user at the optimal timing.

[0043] The unread message providing unit can filter unread messages based on the user's interests and priorities, and provide only important information. The unread message providing unit, for example, analyzes the contents of unread messages and filters them based on the user's interests and priorities. For example, work emails and messages from family members are displayed with priority. The unread message providing unit can also analyze the contents of unread messages and filter them based on the user's interests and priorities. For example, important notifications and emergency contacts are displayed with priority. This makes it possible to provide only important information to the user.

[0044] The radio program generation unit generates personalized comments and questions to attract the user's attention based on the content of the radio program, thereby facilitating the user's thinking. The radio program generation unit, for example, analyzes the content of the radio program and generates personalized comments based on the user's past behavioral history and interests. For example, if the user is interested in economic news, the radio program generation unit provides detailed comments related to economic news. The radio program generation unit also analyzes the content of the radio program and generates questions to attract the user's attention. For example, if the user is interested in sports news, the radio program generation unit provides questions related to sports news. This can stimulate the user's thinking and deepen their understanding of the radio program.

[0045] The radio program generation unit customizes the content of the radio program based on the user's past behavioral history and interests, thereby providing more personalized information. The radio program generation unit, for example, analyzes the content of the radio program and customizes it based on the user's past behavioral history and interests. For example, if the user is interested in economic news, economic news is provided preferentially. The radio program generation unit also analyzes the content of the radio program and customizes the program based on the user's interests. For example, if the user is interested in sports news, sports news is provided preferentially. This makes it possible to provide personalized information to the user.

[0046] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0047] When providing news, the news provider automatically adds related past news and background information, deepening the user's understanding. For example, it analyzes the content of a news article and automatically adds related past news and background information. It provides information on past economic trends and policy changes related to current economic news. The news provider also analyzes the content of a news article and provides details and historical background of related events. It provides information on past international relations and historical events related to current international news. This allows the user to deepen their understanding.

[0048] The news presentation unit can provide a multisensory experience by combining not only sound but also vibration and light patterns when providing news. For example, a multisensory experience can be provided by not only providing the content of a news article by sound but also by combining vibration and light patterns. When there is important news, the device vibrates to notify the user. Furthermore, when providing the content of a news article by sound, the news presentation unit can also notify the user by combining light patterns. The color and blinking pattern of the light can be changed depending on the importance of the news. This can provide a multisensory experience for the user.

[0049] The news providing unit customizes the content of the news based on the user's past behavior history and interests, and can provide more personalized information. For example, the content of a news article is analyzed and customized based on the user's past behavior history and interests. If the user is interested in economic news, economic news is provided preferentially. The news providing unit also analyzes the content of a news article and customizes the news based on the user's interests. If the user is interested in sports news, sports news is provided preferentially. This makes it possible to provide personalized information to the user.

[0050] The weather information providing unit can automatically generate suggestions for clothing and belongings that match the user's schedule based on the weather information. For example, it analyzes weather information and automatically generates suggestions for clothing and belongings that match the user's schedule. For example, it suggests an umbrella or a waterproof jacket on a rainy day. The weather information providing unit also analyzes weather information and automatically generates suggestions for clothing and belongings that match the user's schedule. For example, it suggests a coat or gloves on a cold day. The weather information providing unit also analyzes weather information and automatically generates suggestions for clothing and belongings that match the user's schedule. For example, it suggests a hat or sunglasses on a hot day. In this way, it is possible to provide the user with suggestions for appropriate clothing and belongings.

[0051] When providing weather information, the weather information providing unit can refer to past weather data and weather patterns to predict the impact on the user. For example, when providing weather information, past weather data and weather patterns are referenced to predict the impact on the user. Based on the past data, the impact of specific weather conditions on the user's health is predicted. Furthermore, when providing weather information, the weather information providing unit refers to past weather data and weather patterns to predict the impact on the user. Based on the past data, the impact of specific weather conditions on the user's activity is predicted. This makes it possible to predict the impact on the user.

[0052] The weather information providing unit can customize weather information based on the user's health condition and activity level and provide health management advice. For example, the weather information providing unit analyzes the weather information and customizes it based on the user's health condition and activity level. For a user with allergies, the weather information providing unit suggests measures to take on days with high pollen counts. The weather information providing unit also analyzes the weather information and customizes it based on the user's health condition and activity level. For a user who exercises, the weather information providing unit suggests appropriate exercise times and locations. This makes it possible to provide health management advice to the user.

[0053] The processing flow of the first embodiment will be briefly explained below.

[0054] Step 1: The news provider provides news. For example, the generation AI collects the latest news and selects information that is important to the user. The generation AI analyzes news, including major domestic and international news, economic information, and sports results, and summarizes it in a way that is easy for the user to understand. The input to the generation AI is a prompt containing instructions for collecting and summarizing news, and the generation AI generates news based on the prompt. Step 2: The weather information provider provides weather information. For example, the generation AI collects and provides the latest weather information based on the user's location. The generation AI analyzes weather information, including today's weather forecast, temperature, and probability of precipitation, and summarizes it in a form that is easy for the user to understand. The input to the generation AI is a prompt containing instructions for collecting and summarizing weather information, and the generation AI generates weather information based on the prompt. Step 3: The calendar information provider provides calendar information. For example, the generation AI collects the user's calendar information and provides today's schedule and important events. The generation AI analyzes calendar information, including meeting schedules and birthday reminders, and summarizes it in a way that is easy for the user to understand. The input to the generation AI is a prompt containing instructions for collecting and summarizing calendar information, and the generation AI generates calendar information based on the prompt. Step 4: The unread message provider provides unread messages. For example, the generation AI collects the user's unread messages and selects and provides important messages. The generation AI analyzes unread messages, including work emails and messages from family, and summarizes them in a way that is easy for the user to understand. The input to the generation AI is a prompt containing instructions for collecting and summarizing unread messages, and the generation AI generates unread messages based on the prompt. Step 5: The radio program generation unit generates a radio program based on information from the news provider, weather information provider, calendar information provider, and unread message provider. For example, the generation AI combines the collected news, weather, calendar, and unread important message information to create a narration that is easy for users to listen to. The input to the generation AI is a prompt containing instructions for generating the radio program and the narration, and the generation AI generates the radio program based on the prompt.

[0055] (Example 2) A system according to an embodiment of the present invention allows users to visualize their day's activities while dozing in bed without opening their eyes. This system delivers information such as news, weather, calendars, and unread important messages in an original radio program format, narrated by AI. This allows users to use the system as content they can listen to in the background. When users wake up in the morning, they can check their schedule for the day and grasp important messages while listening to the latest news and weather information. This allows users to start their day in the best possible way, keeping their brains fully engaged.

[0056] The system according to the embodiment includes a news providing unit, a weather information providing unit, a calendar information providing unit, an unread message providing unit, and a radio program generating unit. The news providing unit provides news. For example, the generation AI collects the latest news and selects information important to the user. The generation AI analyzes news, including major domestic and international news, economic information, sports results, etc., and summarizes it in a form easy to understand for the user. The generation AI receives input from prompts containing instructions for news collection and summarization, and the generation AI generates news based on the prompts. The weather information providing unit provides weather information. For example, the generation AI collects and provides the latest weather information based on the user's location. The generation AI analyzes weather information, including today's weather forecast, temperature, and probability of precipitation, and summarizes it in a form easy to understand for the user. The generation AI receives input from prompts containing instructions for weather information collection and summarization, and the generation AI generates weather information based on the prompts. The calendar information providing unit provides calendar information. For example, the generation AI collects the user's calendar information and provides today's schedule and important events. The generation AI analyzes calendar information, including meeting schedules and birthday reminders, and summarizes it in a form that is easy for the user to understand. The generation AI receives input from prompts containing instructions for collecting and summarizing calendar information, and generates calendar information based on the prompts. The unread message provider provides unread messages. For example, the generation AI collects the user's unread messages and selects and provides important messages. The generation AI analyzes unread messages, including work emails and messages from family, and summarizes them in a form that is easy for the user to understand. The generation AI receives input from prompts containing instructions for collecting and summarizing unread messages, and generates unread messages based on the prompts. The radio program generator generates a radio program based on information from the news provider, weather information provider, calendar information provider, and unread message provider. For example, the generation AI combines the collected news, weather, calendar, and unread important message information to create a narration that is easy for the user to listen to.The input to the generation AI is prompts containing instructions for generating a radio program and narration, and the generation AI generates a radio program based on the prompts. This allows the system according to the embodiment to allow the user to imagine the day's activities while dozing off in bed without opening their eyes. For example, when waking up in the morning, the user can check the day's schedule and grasp important messages while listening to the latest news and weather information. This allows the user to fully utilize their brain and start the day in the best possible way.

[0057] The news providing unit generates personalized comments and questions to attract the user's attention based on the content of the news, thereby stimulating the user's thinking. The news providing unit, for example, analyzes the content of a news article and generates personalized comments based on the user's past browsing history and interests. For example, if the user is interested in economic news, the news providing unit provides detailed comments related to economic news. The news providing unit also analyzes the content of a news article and generates questions to attract the user's attention. For example, if the user is interested in sports news, the news providing unit provides questions related to sports news. This can stimulate the user's thinking and deepen their understanding of the news.

[0058] When providing news, the news providing unit automatically adds related past news and background information, thereby deepening the user's understanding. The news providing unit, for example, analyzes the content of a news article and automatically adds related past news and background information. For example, it provides information on past economic trends and policy changes related to current economic news. The news providing unit also analyzes the content of a news article and provides details and historical background of related events. For example, it provides information on past international relations and historical events related to current international news. This allows the user to deepen their understanding.

[0059] The news providing unit can use the emotion estimation function to analyze the emotional impact of news content on the user and reconstruct the news to elicit positive emotions. The news providing unit, for example, analyzes the content of a news article and uses the emotion estimation function to analyze the emotional impact on the user. For example, it reconstructs a negative news article from a positive perspective and provides it to the user. The news providing unit can also analyze the content of a news article and use the emotion estimation function to reconstruct the news to elicit positive emotions in the user. For example, it can reconstruct disaster news and provide information on the progress of reconstruction and relief activities. This can elicit positive emotions in the user.

[0060] The news providing unit can provide a multisensory experience by combining not only sound but also vibration and light patterns when providing news. For example, the news providing unit not only provides the content of a news article by sound but also vibration and light patterns to provide a multisensory experience. For example, when there is important news, the device vibrates to notify the user. Furthermore, the news providing unit can notify the user by combining light patterns when providing the content of a news article by sound. For example, the color or blinking pattern of the light can be changed depending on the importance of the news. This makes it possible to provide a multisensory experience to the user.

[0061] The news providing unit customizes the content of the news based on the user's past behavioral history and interests, and can provide more personalized information. The news providing unit, for example, analyzes the content of a news article and customizes it based on the user's past behavioral history and interests. For example, if the user is interested in economic news, the news providing unit provides economic news preferentially. The news providing unit also analyzes the content of a news article and customizes the news based on the user's interests. For example, if the user is interested in sports news, the news providing unit provides sports news preferentially. This makes it possible to provide personalized information to the user.

[0062] The weather information providing unit can automatically generate suggestions for clothing and belongings that match the user's schedule based on the weather information. The weather information providing unit, for example, analyzes weather information and automatically generates suggestions for clothing and belongings that match the user's schedule. For example, an umbrella or a waterproof jacket is suggested for a rainy day. The weather information providing unit also analyzes weather information and automatically generates suggestions for clothing and belongings that match the user's schedule. For example, a coat or gloves is suggested for a cold day. The weather information providing unit also analyzes weather information and automatically generates suggestions for clothing and belongings that match the user's schedule. For example, a hat or sunglasses is suggested for a hot day. In this way, suggestions for appropriate clothing and belongings can be provided to the user.

[0063] The weather information providing unit can refer to past weather data and weather patterns when providing weather information and predict the impact on the user. For example, when providing weather information, the weather information providing unit can refer to past weather data and weather patterns and predict the impact on the user. For example, based on past data, it predicts the impact of specific weather conditions on the user's health. Furthermore, for example, when providing weather information, the weather information providing unit can refer to past weather data and weather patterns and predict the impact on the user. For example, based on past data, it predicts the impact of specific weather conditions on the user's activity. This makes it possible to predict the impact on the user.

[0064] The weather information providing unit can use the emotion estimation function to analyze the emotional impact of weather information on the user and reconstruct the information to elicit positive emotions. The weather information providing unit, for example, analyzes weather information and uses the emotion estimation function to analyze the emotional impact on the user. For example, weather information for a rainy day is reconstructed from a positive perspective and provided to the user. The weather information providing unit also analyzes weather information and uses the emotion estimation function to reconstruct the information to elicit positive emotions in the user. For example, weather information for a cloudy day is reconstructed and indoor activities that can be enjoyed are suggested. This makes it possible to elicit positive emotions in the user.

[0065] The weather information providing unit can customize weather information based on the user's health condition and activity level and provide health management advice. The weather information providing unit, for example, analyzes weather information and customizes it based on the user's health condition and activity level. For example, it suggests measures to take on days with a lot of pollen for a user with allergies. The weather information providing unit also analyzes weather information and customizes it based on the user's health condition and activity level. For example, it suggests appropriate exercise times and locations for a user who exercises. This makes it possible to provide health management advice to the user.

[0066] The weather information providing unit can use the emotion estimation function to monitor the user's emotional reaction to weather information in real time, and if a negative reaction occurs, provide additional positive information. The weather information providing unit, for example, monitors the user's emotional reaction to weather information in real time, and if a negative reaction occurs, provide additional positive information. For example, after providing weather information for a rainy day, it suggests indoor activities that can be enjoyed. The weather information providing unit can also monitor the user's emotional reaction to weather information in real time, and if a negative reaction occurs, provide additional positive information. For example, after providing weather information for a cloudy day, it suggests relaxing activities. In this way, it is possible to provide positive information to the user.

[0067] The calendar information providing unit can automatically generate an efficient schedule proposal that matches the user's schedule based on the calendar information. The calendar information providing unit, for example, analyzes the calendar information and automatically generates an efficient schedule proposal that matches the user's schedule. For example, it proposes an optimal schedule taking into consideration the priorities of meetings and tasks. The calendar information providing unit also, for example, analyzes the calendar information and automatically generates an efficient schedule proposal that matches the user's schedule. For example, it proposes an optimal schedule taking into consideration important events and reminders. This makes it possible to provide the user with an efficient schedule proposal.

[0068] The calendar information providing unit can use the emotion estimation function to analyze the emotional impact that calendar information has on the user and reconstruct the information to elicit positive emotions. The calendar information providing unit, for example, analyzes calendar information and uses the emotion estimation function to analyze the emotional impact that calendar information has on the user. For example, it reconstructs a schedule of important meetings from a positive perspective and provides it to the user. The calendar information providing unit also analyzes calendar information and uses the emotion estimation function to reconstruct information to elicit positive emotions in the user. For example, it reconstructs a schedule for a busy day and suggests times for relaxation. This makes it possible to elicit positive emotions in the user.

[0069] The calendar information providing unit can synchronize the calendar information with the schedules of the user's family and friends and suggest joint events and activities. The calendar information providing unit, for example, analyzes the calendar information, synchronizes it with the schedules of the user's family and friends, and suggests joint events and activities. For example, it suggests a schedule of an event that all family members can participate in. The calendar information providing unit can also analyze the calendar information, synchronizes it with the schedules of the user's friends, and suggests joint activities. For example, it suggests a schedule of an event that can be enjoyed together with friends. In this way, joint events and activities can be suggested to the user.

[0070] The calendar information providing unit can customize calendar information based on the user's hobbies and interests and suggest related events and activities. The calendar information providing unit, for example, analyzes calendar information and customizes it based on the user's hobbies and interests. For example, if the user is interested in music, it suggests a schedule of music events. The calendar information providing unit can also analyze calendar information and customize it based on the user's hobbies and interests. For example, if the user is interested in sports, it suggests a schedule of sports events. This makes it possible to suggest events and activities relevant to the user.

[0071] The calendar information providing unit uses the emotion estimation function to monitor the user's emotional response to the calendar information in real time, and if a negative response is detected, additional positive information can be provided. The calendar information providing unit, for example, monitors the user's emotional response to the calendar information in real time, and if a negative response is detected, additional positive information can be provided. For example, after providing a schedule for an important meeting, it can suggest a relaxing activity. The calendar information providing unit also monitors the user's emotional response to the calendar information in real time, and if a negative response is detected, it can suggest a relaxing time. In this way, it is possible to provide positive information to the user.

[0072] The unread message providing unit can provide messages that are most important to the user on a priority basis based on the contents of the unread messages. The unread message providing unit, for example, analyzes the contents of the unread messages and provides messages that are most important to the user on a priority basis. For example, work emails and messages from family members are displayed on a priority basis. The unread message providing unit can also analyze the contents of the unread messages and provide messages that are most important to the user on a priority basis. For example, emergency messages and important notifications are displayed on a priority basis. This allows messages that are most important to the user to be provided on a priority basis.

[0073] When providing an unread message, the unread message providing unit can refer to related past messages and conversation history to deepen the user's understanding. The unread message providing unit, for example, analyzes the content of the unread message and refers to related past messages and conversation history. For example, based on the past conversation history, provides background information for the current message. Furthermore, the unread message providing unit, for example, analyzes the content of the unread message and refers to related past messages and conversation history. For example, based on past emails and chat history, provides background information for the current message. This can deepen the user's understanding.

[0074] The unread message providing unit can customize unread messages based on the user's current situation and schedule, and provide them at the optimal timing. The unread message providing unit, for example, analyzes the content of the unread message and customizes it based on the user's current situation and schedule. For example, if the user is in a meeting, an important message is notified later. The unread message providing unit also analyzes the content of the unread message and customizes it based on the user's current situation and schedule. For example, if the user is driving, a message is notified later. This makes it possible to provide messages to the user at the optimal timing.

[0075] The unread message providing unit can filter unread messages based on the user's interests and priorities, and provide only important information. The unread message providing unit, for example, analyzes the contents of unread messages and filters them based on the user's interests and priorities. For example, work emails and messages from family members are displayed with priority. The unread message providing unit can also analyze the contents of unread messages and filter them based on the user's interests and priorities. For example, important notifications and emergency contacts are displayed with priority. This makes it possible to provide only important information to the user.

[0076] The unread message providing unit can use the emotion estimation function to monitor the user's emotional reaction to unread messages in real time, and provide additional positive information if a negative reaction occurs. The unread message providing unit, for example, monitors the user's emotional reaction to unread messages in real time, and provides additional positive information if a negative reaction occurs. For example, after receiving an emergency call, it provides an encouraging message. The unread message providing unit can also monitor the user's emotional reaction to unread messages in real time, and provide additional positive information if a negative reaction occurs. For example, after receiving an important notification, it can suggest a relaxing activity. This makes it possible to provide positive information to the user.

[0077] The radio program generation unit generates personalized comments and questions to attract the user's attention based on the content of the radio program, thereby facilitating the user's thinking. The radio program generation unit, for example, analyzes the content of the radio program and generates personalized comments based on the user's past behavioral history and interests. For example, if the user is interested in economic news, the radio program generation unit provides detailed comments related to economic news. The radio program generation unit also analyzes the content of the radio program and generates questions to attract the user's attention. For example, if the user is interested in sports news, the radio program generation unit provides questions related to sports news. This can stimulate the user's thinking and deepen their understanding of the radio program.

[0078] The radio program generation unit can use the emotion estimation function to analyze the emotional impact of the content of a radio program on a user and reconstruct the program to elicit positive emotions. The radio program generation unit, for example, analyzes the content of a radio program and uses the emotion estimation function to analyze the emotional impact on a user. For example, it reconstructs negative news from a positive perspective and provides it to the user. The radio program generation unit also analyzes the content of a radio program and uses the emotion estimation function to reconstruct the program to elicit positive emotions in the user. For example, it reconstructs disaster news and provides information on the progress of reconstruction and relief activities. This makes it possible to elicit positive emotions in the user.

[0079] The radio program generation unit customizes the content of the radio program based on the user's past behavioral history and interests, thereby providing more personalized information. The radio program generation unit, for example, analyzes the content of the radio program and customizes it based on the user's past behavioral history and interests. For example, if the user is interested in economic news, economic news is provided preferentially. The radio program generation unit also analyzes the content of the radio program and customizes the program based on the user's interests. For example, if the user is interested in sports news, sports news is provided preferentially. This makes it possible to provide personalized information to the user.

[0080] The radio program generation unit uses the emotion estimation function to monitor the user's emotional response to the content of the radio program in real time, and if a negative response occurs, it can provide additional positive information. The radio program generation unit, for example, monitors the user's emotional response to the content of the radio program in real time, and if a negative response occurs, it can provide additional positive information. For example, after listening to disaster news, it can provide information on the progress of reconstruction and relief activities. The radio program generation unit also monitors the user's emotional response to the content of the radio program in real time, and if a negative response occurs, it can provide additional positive information. For example, after listening to economic news, it can provide information on economic recovery and success stories. This makes it possible to provide positive information to the user.

[0081] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0082] The news providing unit can generate personalized comments and questions to attract the user's attention based on the content of the news, thereby stimulating the user's thinking. For example, the content of a news article can be analyzed to generate personalized comments based on the user's past browsing history and interests. If the user is interested in economic news, detailed comments related to economic news can be provided. The news providing unit can also analyze the content of a news article to generate questions to attract the user's attention. If the user is interested in sports news, questions related to sports news can be provided. This can stimulate the user's thinking and deepen their understanding of the news.

[0083] When providing news, the news provider automatically adds related past news and background information, deepening the user's understanding. For example, it analyzes the content of a news article and automatically adds related past news and background information. It provides information on past economic trends and policy changes related to current economic news. The news provider also analyzes the content of a news article and provides details and historical background of related events. It provides information on past international relations and historical events related to current international news. This allows the user to deepen their understanding.

[0084] The news providing unit can use the emotion estimation function to analyze the emotional impact of news content on the user and reconstruct the news to elicit positive emotions. For example, the content of a news article is analyzed and the emotion estimation function is used to analyze the emotional impact on the user. A negative news article is reconstructed from a positive perspective and provided to the user. The news providing unit also analyzes the content of a news article and uses the emotion estimation function to reconstruct the news to elicit positive emotions in the user. Disaster news is reconstructed to provide information on the progress of reconstruction and relief activities. This makes it possible to elicit positive emotions in the user.

[0085] The news presentation unit can provide a multisensory experience by combining not only sound but also vibration and light patterns when providing news. For example, a multisensory experience can be provided by not only providing the content of a news article by sound but also by combining vibration and light patterns. When there is important news, the device vibrates to notify the user. Furthermore, when providing the content of a news article by sound, the news presentation unit can also notify the user by combining light patterns. The color and blinking pattern of the light can be changed depending on the importance of the news. This can provide a multisensory experience for the user.

[0086] The news providing unit customizes the content of the news based on the user's past behavior history and interests, and can provide more personalized information. For example, the content of a news article is analyzed and customized based on the user's past behavior history and interests. If the user is interested in economic news, economic news is provided preferentially. The news providing unit also analyzes the content of a news article and customizes the news based on the user's interests. If the user is interested in sports news, sports news is provided preferentially. This makes it possible to provide personalized information to the user.

[0087] The weather information providing unit can automatically generate suggestions for clothing and belongings that match the user's schedule based on the weather information. For example, it analyzes weather information and automatically generates suggestions for clothing and belongings that match the user's schedule. For example, it suggests an umbrella or a waterproof jacket on a rainy day. The weather information providing unit also analyzes weather information and automatically generates suggestions for clothing and belongings that match the user's schedule. For example, it suggests a coat or gloves on a cold day. The weather information providing unit also analyzes weather information and automatically generates suggestions for clothing and belongings that match the user's schedule. For example, it suggests a hat or sunglasses on a hot day. In this way, it is possible to provide the user with suggestions for appropriate clothing and belongings.

[0088] When providing weather information, the weather information providing unit can refer to past weather data and weather patterns to predict the impact on the user. For example, when providing weather information, past weather data and weather patterns are referenced to predict the impact on the user. Based on the past data, the impact of specific weather conditions on the user's health is predicted. Furthermore, when providing weather information, the weather information providing unit refers to past weather data and weather patterns to predict the impact on the user. Based on the past data, the impact of specific weather conditions on the user's activity is predicted. This makes it possible to predict the impact on the user.

[0089] The weather information providing unit can use the emotion estimation function to analyze the emotional impact of weather information on the user and reconstruct the information to elicit positive emotions. For example, the weather information providing unit analyzes weather information and uses the emotion estimation function to analyze the emotional impact on the user. Weather information for rainy days is reconstructed from a positive perspective and provided to the user. The weather information providing unit also analyzes weather information and uses the emotion estimation function to reconstruct the information to elicit positive emotions in the user. Weather information for cloudy days is reconstructed and indoor activities that can be enjoyed are suggested. This makes it possible to elicit positive emotions in the user.

[0090] The weather information providing unit can customize weather information based on the user's health condition and activity level and provide health management advice. For example, the weather information providing unit analyzes the weather information and customizes it based on the user's health condition and activity level. For a user with allergies, the weather information providing unit suggests measures to take on days with high pollen counts. The weather information providing unit also analyzes the weather information and customizes it based on the user's health condition and activity level. For a user who exercises, the weather information providing unit suggests appropriate exercise times and locations. This makes it possible to provide health management advice to the user.

[0091] The weather information providing unit can use the emotion estimation function to monitor the user's emotional reaction to weather information in real time, and if a negative reaction occurs, provide additional positive information. For example, the user's emotional reaction to weather information can be monitored in real time, and if a negative reaction occurs, provide additional positive information. After providing weather information for a rainy day, indoor activities that can be enjoyed are suggested. Furthermore, the weather information providing unit can monitor the user's emotional reaction to weather information in real time, and if a negative reaction occurs, provide additional positive information. After providing weather information for a cloudy day, relaxing activities are suggested. In this way, positive information can be provided to the user.

[0092] The processing flow of the second embodiment will be briefly explained below.

[0093] Step 1: The news provider provides news. For example, the generation AI collects the latest news and selects information that is important to the user. The generation AI analyzes news, including major domestic and international news, economic information, and sports results, and summarizes it in a way that is easy for the user to understand. The input to the generation AI is a prompt containing instructions for collecting and summarizing news, and the generation AI generates news based on the prompt. Step 2: The weather information provider provides weather information. For example, the generation AI collects and provides the latest weather information based on the user's location. The generation AI analyzes weather information, including today's weather forecast, temperature, and probability of precipitation, and summarizes it in a form that is easy for the user to understand. The input to the generation AI is a prompt containing instructions for collecting and summarizing weather information, and the generation AI generates weather information based on the prompt. Step 3: The calendar information provider provides calendar information. For example, the generation AI collects the user's calendar information and provides today's schedule and important events. The generation AI analyzes calendar information, including meeting schedules and birthday reminders, and summarizes it in a way that is easy for the user to understand. The input to the generation AI is a prompt containing instructions for collecting and summarizing calendar information, and the generation AI generates calendar information based on the prompt. Step 4: The unread message provider provides unread messages. For example, the generation AI collects the user's unread messages and selects and provides important messages. The generation AI analyzes unread messages, including work emails and messages from family, and summarizes them in a way that is easy for the user to understand. The input to the generation AI is a prompt containing instructions for collecting and summarizing unread messages, and the generation AI generates unread messages based on the prompt. Step 5: The radio program generation unit generates a radio program based on information from the news provider, weather information provider, calendar information provider, and unread message provider. For example, the generation AI combines the collected news, weather, calendar, and unread important message information to create a narration that is easy for users to listen to. The input to the generation AI is a prompt containing instructions for generating the radio program and the narration, and the generation AI generates the radio program based on the prompt.

[0094] 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.

[0095] 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.

[0096] 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.

[0097] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0098] 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.

[0099] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0100] The 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.

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

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

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

[0104] Fig. 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.

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

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

[0107] In the 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.

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

[0109] The specific processing unit 290 transmits the result of the specific processing to the 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.

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

[0111] The data processing system 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.

[0112] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0113] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0114] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0115] The 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.

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

[0117] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (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).

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

[0119] 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.

[0120] 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.

[0121] 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.

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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.

[0127] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0128] 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.

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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).

[0133] 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.

[0134] 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.

[0135] 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.

[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 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.

[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 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.

[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 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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).

[0147] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0148] 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."

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] 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.

[0154] 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.

[0155] 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.

[0156] 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.

[0157] 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.

[0158] 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.

[0159] 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.

[0160] 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]

[0161] 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 news department that provides news; a weather information providing unit that provides weather information; a calendar information providing unit that provides calendar information; an unread message providing unit that provides unread messages; a radio program generation unit that generates a radio program based on information from the news providing unit, the weather information providing unit, the calendar information providing unit, and the unread message providing unit. A system characterized by:

2. The news providing unit The news is delivered in a multi-sensory way, combining not only sound but also vibration and light patterns.

2. The system of claim 1.

3. The weather information providing unit Analyzing the emotional impact of the weather information on the user and reconstructing the weather information to elicit positive emotions.

2. The system of claim 1.

4. The calendar information providing unit Based on the calendar information, an efficient schedule proposal tailored to the user's schedule is automatically generated.

2. The system of claim 1.

5. The unread message providing unit Based on the contents of the unread messages, messages that are most important to the user are provided with priority.

2. The system of claim 1.

6. The radio program generation unit Analyzing the emotional impact of the content of the radio program on the user and reconstructing the radio program to elicit positive emotions.

2. The system of claim 1.

7. The news providing unit Analyzing the emotional impact of the news content on the user and reconstructing the news to elicit positive emotions.

2. The system of claim 1.

8. The weather information providing unit The system monitors users' emotional reactions to the weather information in real time, and if a negative reaction occurs, provides additional positive information.

2. The system of claim 1.

Images