System

Abstract

A system is provided.SOLUTION: A system comprising: means for converting a user's voice command into text data; means for generating a task by analyzing the user's intention based on the text data; means for optimizing the generated task by referring to the user's past behavior pattern and preference data; means for collecting external information from the Internet; means for integrating and presenting the collected information to the user; and means for executing an action such as an appointment based on the presented information.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] As society ages, the number of senior smartphone users is increasing. However, advances in digital technology are making smartphone operation and usage more complex. Seniors are unable to fully utilize the functions of web services and smartphones, resulting in a decline in convenience and the quality of their daily lives. This invention aims to solve this problem by helping seniors use smartphones and the Internet more effectively. [Means for solving the problem]

[0005] This invention provides a system that includes a means for converting a user's voice commands into text data, a means for analyzing the user's intentions based on the text data and generating a task, a means for referencing the user's past behavioral patterns and preference data and optimizing the generated task, a means for collecting external information from the Internet, a means for integrating the collected information and presenting it to the user, and a means for performing actions such as making a reservation based on the presented information, thereby enabling seniors to receive the optimal service according to their purpose without having to perform complicated operations.

[0006] The term "user" refers to an individual person who uses the system. In particular, the present invention targets senior citizens.

[0007] A "voice command" refers to an instruction or command spoken by a user, which the system recognizes and converts into text to initiate processing.

[0008] "Text data" refers to data that is generated by analyzing a voice command and converting it into a character string format.

[0009] "Analyzing intent" refers to the process of extracting user desires and goals from text data.

[0010] A "task" refers to a specific action or procedure item that is generated based on the user's intention.

[0011] "Behavioral patterns" refer to the history of actions and choices a user has made in the past, and the system uses this information to provide personalized features.

[0012] "Preference Data" refers to a record of a user's past expressed preferences and tastes.

[0013] "Optimizing" refers to adjusting the content and order of tasks to best suit the user based on data about the user's behavioral patterns and preferences.

[0014] "External information" refers to information collected through data sources on the Internet or through APIs.

[0015] "Synthesis" refers to the process of bringing together different pieces of collected information into one coherent form.

[0016] "Presentation" refers to showing the integrated information to the user through a user interface.

[0017] "Reservation" refers to the process of securing a specific service or product.

[0018] "Executing an action" means that the system performs a specific operation or reservation in accordance with the user's instructions. [Brief explanation of the drawings]

[0019] [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. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0020] 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.

[0021] First, the terms used in the following description will be explained.

[0022] 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, a 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), and an APU (Accelerated Processing Unit).

[0023] 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.

[0024] 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.

[0025] 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), Bluetooth (registered trademark), etc.

[0026] 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."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 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.

[0030] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. 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).

[0031] 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.

[0032] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. 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 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The 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.

[0034] 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.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 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.

[0037] 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.

[0038] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0039] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0040] This invention provides an autonomous AI agent called "Concierge" that helps seniors use smartphones and the Internet more effectively, and an embodiment of this invention is described below.

[0041] Receiving User Input

[0042] The user launches a dedicated application on their smartphone and enters a command by voice, such as "I want to go on a trip." The device uses a voice recognition module to convert this voice command into text data and send it to the server.

[0043] User Intention Analysis and Task Generation

[0044] The server analyzes the received text data using a natural language processing (NLP) module to extract the user's purpose (travel planning). Based on the analysis results, it generates the necessary tasks (e.g., booking a hotel, arranging transportation, checking the weather forecast, and listing necessary equipment).

[0045] Personalization and Learning

[0046] The server references the user's past behavioral patterns and preferences to optimize the generated tasks for the user, for example, taking into account the type of accommodation the user prefers based on their past travel history.

[0047] Information gathering and arrangements

[0048] The server uses external APIs to collect necessary information from the Internet. It obtains hotel reservation options through travel site APIs, and suggests optimal travel methods using transportation APIs. It also obtains weather information for the travel period using weather forecast APIs. Similarly, it generates a list of necessary equipment and provides it with online shopping links.

[0049] Displaying results and user confirmation

[0050] The collected information is consolidated on the server and sent as a data package to the device. The device displays this data on a user interface and asks the user for confirmation, such as a message like "Is this plan OK?"

[0051] Booking and confirmation

[0052] The user checks the displayed suggestions and issues a command such as "Book this hotel." The device again converts the speech into text and sends it to the server. The server then reserves the specified hotel and transportation based on the user's instructions. Once the reservation is complete, a notification is sent to the device and displayed to the user.

[0053] Specific examples

[0054] As a specific example, if a user says, "Concierge, I'd like to travel next week," the server performs the following tasks:

[0055] 1. User intent analysis: Extract travel destination, departure date, budget, etc.

[0056] 2. Personalization: Prioritize your preferred accommodation and transportation options based on past data.

[0057] 3. Information gathering: Collecting the best options from multiple travel sites and transportation APIs.

[0058] 4. Displaying results: Travel plans, accommodation, transportation, weather forecast, and a list of necessary equipment are displayed on the user interface.

[0059] 5. Reservation: After user confirmation, the reservation is actually made.

[0060] In this way, the system allows even seniors to easily plan and decide on trips without having to perform complicated operations.

[0061] The processing flow will be explained below.

[0062] Step 1:

[0063] The user launches a dedicated application on their smartphone and issues a voice command such as "I want to go on a trip."

[0064] Step 2:

[0065] The terminal's voice recognition module receives the user's voice commands and converts them into text data.

[0066] Step 3:

[0067] The terminal transmits the converted text data to the server.

[0068] Step 4:

[0069] The server analyzes the received text data using a natural language processing (NLP) module to extract the user's purpose (travel plans).

[0070] Step 5:

[0071] Based on the purpose, the server generates the necessary tasks (reserving a hotel, arranging transportation, checking the weather forecast, listing the necessary equipment).

[0072] Step 6:

[0073] The server references the user's past behavioral patterns and preference data to optimize the generated tasks, for example prioritizing the type of accommodation the user prefers based on their past travel history.

[0074] Step 7:

[0075] The server uses external APIs to collect the necessary information from the Internet. Specifically, it obtains hotel reservation options from travel site APIs, obtains optimal travel methods from transportation APIs, obtains weather information for the travel period from weather forecast APIs, and generates a list of necessary equipment.

[0076] Step 8:

[0077] The server consolidates the collected information and organizes it into a single data package.

[0078] Step 9:

[0079] The server transmits the consolidated data package to the terminal.

[0080] Step 10:

[0081] The device analyzes the transmitted data package and displays it on the user interface, for example displaying a confirmation message saying "Here is the proposed travel plan. What do you want to do?"

[0082] Step 11:

[0083] The user checks the displayed information and then says aloud, "Book this hotel."

[0084] Step 12:

[0085] The device converts the user's voice commands into text and sends it back to the server.

[0086] Step 13:

[0087] The server calls the booking API to reserve the specified hotel and transportation based on the user's instructions.

[0088] Step 14:

[0089] The server notifies the terminal of the reservation result (success / failure).

[0090] Step 15:

[0091] The device will notify the user that the booking is complete and save the trip details.

[0092] Example 1

[0093] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0094] Currently, for seniors to effectively use smartphones and the internet, complex operations and information gathering are required, which presents a major barrier. In particular, tasks related to planning and booking trips are complicated, and the lack of consistent support reduces usability. For this reason, there is a demand for systems that allow seniors to easily use smartphones and the internet.

[0095] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0096] In this invention, the server includes means for converting a user's voice commands into text data, means for analyzing the user's intentions based on the text data and generating a task, means for optimizing the generated task by referring to the user's past behavioral patterns and preference data, means for collecting external information from the Internet, means for integrating the collected information and presenting it to the user, means for performing actions such as making a reservation based on the presented information, means for providing multiple options based on the external data collected via the Internet, and means for obtaining confirmations and instructions from the user using voice recognition. This enables seniors to easily plan and book trips using their smartphones without requiring complex operations.

[0097] "Voice command" refers to an instruction or request input by a user through speech.

[0098] "Text data" refers to data obtained by converting voice commands into text information.

[0099] "User intent" refers to the purpose or request that the user wants to convey through a voice command.

[0100] A "task" refers to a specific process or action that the system should perform based on the user's intentions.

[0101] "Past behavioral patterns" refers to the history of operations and selections that the user has previously made.

[0102] "Preference Data" refers to information about a user's past preferences and selection tendencies.

[0103] "Optimization" refers to adjusting and modifying the generated tasks and suggestions to best suit the user based on the user's requirements, past behavioral patterns, and preferences.

[0104] "External information" refers to data obtained from external sources such as the Internet.

[0105] "Information integration" refers to bringing together collected external information and user data and processing it in a consistent manner.

[0106] An "action" refers to a specific task or operation that is performed through the execution of a task.

[0107] "External data collected via the Internet" refers to data collected from different sources on the Internet.

[0108] "Choices" refers to multiple alternatives or options offered to a user.

[0109] "Speech recognition" refers to the technology and process of converting speech into text data.

[0110] "Confirmation or instruction" refers to voice input made by the user to confirm the system's operation.

[0111] This invention provides an autonomous AI agent called "Concierge" that helps seniors effectively use smartphones and the Internet. Specific embodiments for implementing this invention are described below.

[0112] The user uses a dedicated application on their smartphone. This application uses a voice recognition module (e.g., Google Speech-to-Text API) to convert the user's voice commands into text data. This text data is then sent from the smartphone (device) to the server.

[0113] The server analyzes the received text data using a natural language processing (NLP) module (e.g., OpenAI's GPT-3), extracts the user's intent (e.g., planning a trip), and generates the necessary tasks (e.g., booking a hotel, arranging transportation, checking the weather forecast, and listing the necessary equipment).

[0114] The server then refers to the user's past behavioral patterns and preferences, which are stored in the server's database, and optimizes the generated task by taking into account the user's past travel history. For example, it may prioritize the type of accommodation the user has preferred in the past.

[0115] In addition, the server uses external APIs (e.g., Booking.com API, Google Maps API, Weather.com API) to collect necessary information from the Internet, obtain hotel reservation options based on the travel dates, suggest the best means of transportation, obtain weather forecasts for the travel period, generate a list of necessary equipment, and provide links to online shopping.

[0116] The collected information is consolidated on the server and sent as a data package to the device, which then displays this data on a user interface and asks the user for confirmation, such as "Is this plan OK?"

[0117] The user checks the displayed suggestions and then re-enters a command, such as "Book this hotel." The device converts the speech into text and sends it to the server. The server then reserves the specified hotel and transportation based on the user's instructions. Once the reservation is complete, a notification is sent to the device and displayed to the user.

[0118] Specific examples

[0119] For example, if a user says, "Concierge, I would like to travel next week," the server performs the following tasks:

[0120] 1. Analyzing user intent: Extract travel destination, departure date, budget, etc.

[0121] 2. Personalization: Prioritize your preferred accommodation and transportation options based on past data.

[0122] 3. Information gathering: Collecting the best options from multiple travel sites and transportation APIs.

[0123] 4. Displaying results: The user interface displays the itinerary, accommodation, transportation, weather forecast, and list of necessary equipment.

[0124] 5. Reservation: After user confirmation, the reservation is actually made.

[0125] An example of a prompt sentence is, "A concierge AI that supports travel planning for seniors through voice input would generate a travel plan from the user's voice input and explain the process leading up to the reservation."

[0126] As described above, this invention allows even seniors to easily plan and book trips without having to perform complicated operations.

[0127] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0128] Step 1:

[0129] A user launches a dedicated application on their smartphone and verbally enters a command such as "I want to go on a trip." The device uses a voice recognition module (for example, the Google Speech-to-Text API) to convert this voice command into text data. Specifically, the application receives the voice input and converts it into text. The input is a voice command, and the output is text data.

[0130] Step 2:

[0131] Text data is sent to the server. The server analyzes the received text data using a natural language processing (NLP) module (e.g., OpenAI's GPT-3) to extract the user's intent (e.g., planning a trip). The input is text data, and the output is data indicating the user's intent.

[0132] Step 3:

[0133] Based on the analysis results, the server generates the necessary tasks (e.g., reserving a hotel, arranging transportation, checking the weather forecast, listing necessary equipment). Specifically, the server uses a task generation module to list appropriate tasks based on the user's intent. The input is the user's intent data, and the output is a list of generated tasks.

[0134] Step 4:

[0135] The server optimizes the generated tasks by referencing the user's past behavioral patterns and preference data. For example, it retrieves the user's travel history from a historical database and considers the type of accommodation they preferred in the past. The input is a task list and the user's past data, and the output is an optimized task list.

[0136] Step 5:

[0137] The server uses external APIs (e.g., Booking.com API, Google Maps API, Weather.com API) to collect necessary information from the Internet. This includes obtaining hotel reservation options based on the travel dates, suggesting the best means of transportation, obtaining weather forecasts for the travel period, and generating a list of necessary equipment. The input is the optimized task list, and the output is the collected information data.

[0138] Step 6:

[0139] The collected information is integrated by the server and sent to the terminal as a data package. The terminal displays this data package on a user interface and asks the user for confirmation. Specifically, the terminal receives the data package and visualizes and displays it. The input is the collected information data, and the output is the display data on the user interface.

[0140] Step 7:

[0141] The user checks the displayed suggestions and enters a command by voice, such as "Book this hotel." The device again converts the voice into text and sends it to the server. Specifically, the device receives voice input, converts it into text, and sends it. The input is a voice command, and the output is text data.

[0142] Step 8:

[0143] The server reserves the specified hotel and transportation based on the user's instructions. Once the reservation is complete, a notification is sent to the terminal and displayed to the user. Specifically, the server calls the reservation API, confirms the reservation, and then sends notification data to the terminal. The input is reservation instruction data, and the output is reservation completion notification data.

[0144] (Application example 1)

[0145] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0146] In today's world, seniors face many barriers when using the internet and smartphones. These include complex operations and security risks. Phishing scams and security authentication issues are particularly prevalent when it comes to online transactions, making it difficult for seniors to conduct transactions safely and securely. Therefore, there is a demand for a system that can assist users in conducting transactions online easily and safely.

[0147] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0148] In this invention, the server includes: means for converting a user's voice command into text data; means for analyzing the user's intention based on the text data and generating a task; means for referencing the user's past behavioral patterns and preference data and optimizing the generated task; means for collecting external information from the Internet; means for integrating the collected information and presenting it to the user; means for performing actions such as making a reservation based on the presented information; means for instructing the user to support safe transactions by voice command when conducting a transaction; means for converting the voice command into text data and analyzing the intention; means for collecting security information related to the transaction from an external API and notifying the user of the information; and means for presenting the user with a transaction reliability assessment and security status based on the collected security information. This makes it possible for seniors to conduct transactions over the Internet easily and safely.

[0149] "User voice command" refers to an instruction or request given by a user through a microphone by voice.

[0150] "Text data" refers to data that has been converted from voice commands into text information using voice recognition technology.

[0151] "User intent" refers to the goal or desire the user ultimately aims to achieve based on voice commands or text data.

[0152] A "task" refers to a specific action item that the system automatically generates based on the user's intentions.

[0153] "User's past behavioral patterns" refers to the operation history and behavior history of the user who previously used the system.

[0154] "Preference Data" refers to data regarding a user's tastes and preferences.

[0155] "External information" refers to all information obtained from the Internet or external databases.

[0156] "Presented information" refers to information that integrates collected external information and is displayed in a format that is easy for the user to understand.

[0157] "Actions such as reservations" refers to specific actions such as reservations and procedures that the system automatically performs based on the information confirmed by the user.

[0158] "Security Information" refers to information regarding the reliability rating and security status of a business partner's site or service.

[0159] "External API" refers to a program interface for connecting with other web services or databases.

[0160] "Trustworthiness rating" refers to the criteria and data used to evaluate how trustworthy a service or site is.

[0161] "Security status" refers to whether the site or service is currently safe to use.

[0162] This invention provides an autonomous AI agent system that helps seniors use the Internet safely, particularly by making online transactions easier and more secure.

[0163] The server starts processing when the user inputs a voice command via a smartphone, smart glasses, or head-mounted display. First, it uses a voice recognition module to convert the user's voice command into text data. Next, it uses a natural language processing (NLP) module to analyze the converted text data and extract the user's intent. For example, it recognizes a command such as "Support this transaction" and analyzes that intent.

[0164] Based on the analysis results, the system generates tasks that are in line with the user's intentions. During this task generation stage, the system references the user's past behavioral patterns and preferences to optimize the generated tasks. For example, it adjusts the level of alerts and warnings based on past transaction history and the security notification history the user has received.

[0165] In addition, the server collects external information from the Internet. Specifically, it uses external APIs to obtain security information related to the sites and services of its business partners. This information includes the site's reliability rating and current security status. For example, this includes the expiration date of the SSL certificate and whether the site has been reported as a phishing site.

[0166] The collected information is integrated and presented to the user. The user interface of the terminal displays the reliability rating and security status of the transaction site, including an alert asking, "Is this site safe?" The user can check the displayed information and issue voice commands such as "Make a reservation" or "Continue the transaction" as needed. The server then makes the specific reservation or transaction based on the user's instructions. When the reservation or transaction is completed, a notification is sent to the terminal and displayed to the user.

[0167] For example, if a user says "Support this transaction," the server performs the following steps: First, it checks the transaction partner's site using an external API and collects the SSL certificate expiration date and phishing site report status. It then analyzes this information and notifies the user, "This site is safe. Do you want to continue?", requesting user confirmation.

[0168] An example of a prompt would be:

[0169] "Enter your voice command: Say 'Support this transaction.'"

[0170] In this way, the system of the present invention is a system that provides multifaceted support to seniors so that they can conduct Internet transactions with peace of mind.

[0171] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0172] Step 1:

[0173] The user inputs a voice command. Specifically, the user speaks into a smartphone, smart glasses, or head-mounted display, saying, "Support this transaction." The input is voice data, which is then captured by the terminal.

[0174] Step 2:

[0175] The device converts the voice into text data. Specifically, it uses a speech recognition module on the device (e.g., Google Speech Recognition API) to convert the input voice data into text data in character format. The input in this step is the voice data obtained in step 1, and the output is the converted text data.

[0176] Step 3:

[0177] The server analyzes the user's intent based on the text data. Specifically, it uses a natural language processing (NLP) module to extract the user's intent, "support this transaction," from the text data. The input in this step is the text data obtained in step 2, and the output is the analyzed intent data.

[0178] Step 4:

[0179] The server references the user's past behavioral patterns and preference data to optimize the generated tasks. Specifically, it references the user's past transaction history and alert history from the database and uses this information to prioritize tasks. The inputs in this step are the intent data obtained in step 3 and the user data in the database, and the output is optimized task data.

[0180] Step 5:

[0181] The server collects external information from the Internet. Specifically, it uses an external API (e.g., a security evaluation API) to obtain reliability and security information about partner sites and services. The input to this step is the task data obtained in step 4, and the output is the collected external information.

[0182] Step 6:

[0183] The server consolidates the collected information and presents it to the user. Specifically, it compiles the collected security information (e.g., SSL certificate expiration date, phishing site report status, etc.) and displays it on the device's user interface in a format that is easy for the user to understand. The input in this step is the external information obtained in step 5, and the output is the presented information.

[0184] Step 7:

[0185] The user confirms the presented information and issues a voice command for the next action, such as "continue the transaction" or "make a reservation on this site." The user confirms the presented information in step 6 and then issues a voice command.

[0186] Step 8:

[0187] The device again converts the voice command into text data and sends it to the server. Specifically, it again uses a voice recognition module to convert the voice into text and sends it to the server. The input in this step is the user voice command from step 7, and the output is text data.

[0188] Step 9:

[0189] The server executes the specific reservation or transaction based on the user's instructions. Specifically, it calls the appropriate external API to complete the reservation procedure and notifies the user of the results. The input in this step is the text data from step 8, and the output is the result of the action taken and a notification of it.

[0190] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0191] This invention combines an autonomous AI agent called "Concierge" that helps seniors use smartphones and the Internet more effectively with an emotion engine that recognizes the user's emotions. An embodiment of this invention is described below.

[0192] Receiving User Input

[0193] The user launches a dedicated application on their smartphone and enters a command by voice, such as "I want to go on a trip." The device uses a voice recognition module to convert this voice command into text data and send it to the server.

[0194] User Intention Analysis and Task Generation

[0195] The server analyzes the received text data using a natural language processing (NLP) module to extract the user's purpose (travel planning). Based on the analysis results, it generates the necessary tasks (e.g., booking a hotel, arranging transportation, checking the weather forecast, and listing necessary equipment).

[0196] User emotion recognition and adjustment

[0197] The server uses an emotion engine to analyze the user's emotional state from their voice commands. Based on this analysis, it can adjust the tasks it generates. For example, if the user is tired, it can suggest a more relaxing plan.

[0198] Personalization and Learning

[0199] The server references the user's past behavioral patterns and preferences to optimize the generated tasks for the user. The emotion engine also records the user's past emotional data and uses it to optimize future tasks. This enables personalization that takes the user's emotional state into account.

[0200] Information gathering and arrangements

[0201] The server uses external APIs to collect necessary information from the Internet. It obtains hotel reservation options through travel site APIs, and suggests optimal travel methods using transportation APIs. It also obtains weather information for the travel period using weather forecast APIs. Similarly, it generates a list of necessary equipment and provides it with online shopping links.

[0202] Displaying results and user confirmation

[0203] The collected information is consolidated on the server and sent as a data package to the device. The device displays this data on a user interface and asks the user for confirmation, such as a message like "Is this plan OK?"

[0204] Booking and confirmation

[0205] The user checks the displayed suggestions and issues a command such as "Book this hotel." The device again converts the speech into text and sends it to the server. Based on the user's instructions, the server calls the reservation API to reserve the specified hotel and transportation. Once the reservation is complete, a notification is sent to the device and displayed to the user.

[0206] Specific examples

[0207] As a specific example, if a user says, "I'd like you to suggest a travel plan that will allow me to relax a little today," the server will perform the following tasks:

[0208] 1. User intent analysis: Extract travel destination, departure date, budget, etc.

[0209] 2. Emotion recognition: Analyze the user's emotional state, such as wanting to relax, from their voice.

[0210] 3. Personalization: Prioritize relaxing accommodation and transportation options based on past data.

[0211] 4. Information gathering: Collecting the best options from multiple travel sites and transportation APIs.

[0212] 5. Displaying results: Travel plans, accommodation, transportation, weather forecast, and a list of necessary equipment are displayed on the user interface.

[0213] 6. Reservation: After user confirmation, the reservation is actually made.

[0214] In this way, by combining the emotion engine, the system allows even seniors to make optimal travel plans and decisions based on their emotional state without having to perform complicated operations.

[0215] The processing flow will be explained below.

[0216] Step 1:

[0217] The user launches a dedicated application on their smartphone and issues a voice command such as, "Please suggest a travel plan that is a little more relaxing today."

[0218] Step 2:

[0219] The terminal's voice recognition module receives the user's voice commands and converts them into text data.

[0220] Step 3:

[0221] The terminal transmits the converted text data to the server.

[0222] Step 4:

[0223] The server analyzes the received text data using a natural language processing (NLP) module to extract the user's intent (suggestions for a relaxing travel plan).

[0224] Step 5:

[0225] The server uses an emotion engine to analyze the user's emotional state (e.g., a desire to relax) from their voice command, and generates tasks (e.g., hotel reservations, transportation arrangements, weather forecasts, and a list of necessary equipment) based on this emotional state.

[0226] Step 6:

[0227] The server optimizes the generated tasks by referring to the user's past behavioral patterns, preference data, and emotion recognition results. Specifically, it prioritizes data on relaxation spots and accommodations visited in the past.

[0228] Step 7:

[0229] The server uses external APIs to collect necessary information from the Internet. It obtains relaxing hotel reservation options through travel site APIs, suggests optimal travel methods using transportation APIs, and uses weather forecast APIs to obtain weather information for the travel period and generate a list of necessary equipment.

[0230] Step 8:

[0231] The server consolidates the collected information and organizes it into a single data package.

[0232] Step 9:

[0233] The server transmits the consolidated data package to the terminal.

[0234] Step 10:

[0235] The device analyzes the transmitted data package and displays it on the user interface, for example displaying a confirmation message saying, "Here are our suggested relaxing travel plans. What do you want to do?"

[0236] Step 11:

[0237] The user checks the displayed information and then says aloud, "Book this hotel."

[0238] Step 12:

[0239] The device converts the user's voice commands into text and sends it back to the server.

[0240] Step 13:

[0241] The server calls the booking API to reserve the specified hotel and transportation based on the user's instructions.

[0242] Step 14:

[0243] The server notifies the terminal of the reservation result (success / failure).

[0244] Step 15:

[0245] The device will notify the user that the booking is complete and save the trip details.

[0246] Example 2

[0247] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0248] It is often difficult for older adults to effectively use smartphones and the internet. Furthermore, tasks such as planning and booking trips are complex, especially when it comes to presenting optimal plans that take into account the user's emotional state. This calls for systems with emotion recognition and personalization capabilities.

[0249] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for converting a user's voice command into text data, means for analyzing the user's intention based on the text data and generating a task, means for optimizing the generated task by referring to the user's past behavioral patterns and preference data, means for analyzing the user's emotional state and adjusting the task, means for collecting external information, means for integrating the collected information and presenting it to the user, and means for performing actions such as making a reservation based on the presented information. This makes it possible to generate and execute an optimal travel plan that takes the user's emotional state into consideration.

[0250] "Voice command" refers to instructions or requests that a user verbally inputs into a smartphone or other device.

[0251] "Text data" refers to text information converted from voice commands using voice recognition technology.

[0252] "Intent analysis" refers to the process of understanding a user's goals and requests from voice commands and generating specific tasks based on that content.

[0253] "Task generation" refers to the process of determining specific tasks and procedures based on the results of intent analysis.

[0254] "Past behavioral patterns" refers to the history of actions and choices made by the user in the past.

[0255] "Preference Data" refers to information relating to a user's personal tastes and preferences.

[0256] "Task optimization" refers to the process of adjusting and improving a task to best suit the user by referring to data on the user's past behavioral patterns and preferences.

[0257] "Emotional state" refers to the emotion or mood of the user when entering a voice command.

[0258] "Means for analyzing emotional state" refers to technology that reads and evaluates emotional nuances from a user's voice or text data.

[0259] "External information" refers to information such as travel information, accommodation information, transportation options, and weather forecasts obtained via the Internet.

[0260] "Means of collecting external information" refers to technology that uses external interfaces and APIs to obtain necessary information from the Internet.

[0261] "Information synthesis" refers to the process of bringing together data collected from multiple sources into a single, unified format.

[0262] "Presentation means" refers to the user interface and display technology used to present the integrated information to the user.

[0263] "Means for executing actions such as reservations" refers to technology that actually carries out reservation procedures or other actions based on the user's confirmation or instructions.

[0264] This invention relates to an autonomous AI agent called "Concierge" that helps seniors use smartphones and the internet more effectively, and is combined with an emotion engine that recognizes the user's emotions. This system implements a series of processes: it receives a user's voice command, analyzes the user's intention, generates a task, optimizes it, and then executes it.

[0265] First, the user launches a dedicated application installed on their smartphone and enters a command by voice, such as "I want to go on a trip." At this time, the device uses the Google Cloud Speech-to-Text API to convert the user's voice command into text data, which is then sent to a server via the Internet.

[0266] The server analyzes the received text data using the Google Cloud Natural Language API and extracts the user's intent. For example, a voice command such as "I want to go on a trip" generates tasks such as selecting a travel destination, booking accommodation, and arranging transportation.

[0267] The server then uses Microsoft Azure Text Analytics for Cognitive Services to analyze the user's emotional state. For example, if the user's intent is "I want to relax," the server can adjust the task to provide a relaxing travel plan based on the emotion recognition results.

[0268] The server then uses Amazon Personalize to optimize the generated tasks based on past behavioral data and user preference patterns. For example, if a user has previously booked a resort hotel, the server will prioritize presenting similar options this time.

[0269] Regarding information gathering, the server uses external interfaces such as Expedia API, Google Maps API, OpenWeatherMap API, etc. to gather the necessary information, such as hotel reservation options, transportation options, weather forecasts, and a list of necessary amenities.

[0270] The collected information is integrated on the server and displayed on a user interface, allowing users to check travel plans, accommodations, transportation options, weather forecasts, lists of necessary supplies, etc. all in one place. For example, if a dedicated application is built with React Native, questions such as "Is this plan okay?" will be displayed on the user interface.

[0271] Finally, the user checks the displayed plan and enters a command such as "Book this hotel" by voice. The device again converts the voice to text data and sends it to the server. The server then calls the Booking.com API, makes the actual reservation, and sends a notification to the device. The user can then complete the entire process by receiving a notification that the reservation has been completed.

[0272] For example, if a user says, "I want some suggestions for relaxing travel destinations today," the system will do the following:

[0273] 1. Convert user voice input into text data

[0274] 2. Analyzing intent from text data and generating travel plans for relaxation

[0275] 3. Emotion recognition to recommend places suitable for relaxation

[0276] 4. Provide optimal plans based on past behavioral data

[0277] 5. Collect the necessary information, consolidate the plan, and display it in the user interface

[0278] 6. After user confirmation, the reservation is actually made

[0279] The system is designed to help seniors navigate complex procedures with ease and can provide a personalized travel experience that takes into account the user's emotions and preferences.

[0280] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0281] Step 1: Receiving User Input

[0282] The user launches the dedicated application and speaks a command such as "I want to go on a trip." The device uses the Google Cloud Speech-to-Text API to convert the voice into text data. This API outputs the voice as text data. The device then sends the converted text data to the server.

[0283] Input: User's voice command

[0284] Data processing: Converting speech to text

[0285] Output: Text data

[0286] Step 2: User intent analysis and task generation

[0287] The server receives the text data sent from the device and analyzes its intent using the Google Cloud Natural Language API. This analysis extracts the user's purpose (e.g., planning a trip). Based on the results, it generates tasks (reserving a hotel, arranging transportation, checking the weather forecast, and listing necessary equipment).

[0288] Input: Text data

[0289] Data processing: Intention analysis and task generation

[0290] Output: Analysis results and task list

[0291] Step 3: Recognizing and adjusting user emotions

[0292] The server uses Microsoft Azure Text Analytics to analyze the user's emotional state from the text data. Based on the obtained emotional state, the content of the generated task is adjusted. For example, if the user feels like "I want to relax," the server generates a plan that allows for more relaxation.

[0293] Input: Text data

[0294] Data processing: Emotional state analysis and task adjustment

[0295] Output: Reconciled task list

[0296] Step 4: Personalize and learn

[0297] The server uses Amazon Personalize to optimize the task by referencing the user's past behavioral patterns and preference data. This optimization suggests a plan based on the user's past tastes and preferences. The emotion engine also records the user's emotional data and uses it for future optimization.

[0298] Input: Adjusted task list and past activity data

[0299] Data Transformation: Personalization and Learning

[0300] Output: Optimized task list

[0301] Step 5: Information gathering and arrangements

[0302] The server uses external APIs (e.g., Expedia API, Google Maps API, OpenWeatherMap API) to collect the necessary information. The collected data includes hotel reservation options, transportation options, weather forecasts, and a list of necessary equipment. Based on this information, a detailed travel plan is created.

[0303] Input: Optimized task list

[0304] Data processing: collecting and integrating external information

[0305] Output: Consolidated information

[0306] Step 6: Displaying the results and user confirmation

[0307] The server sends the collected information to the device, which then displays it in the user interface. For example, if the dedicated application is built with React Native, it will display a message asking, "Is this plan OK?"

[0308] Input: Integrated information

[0309] Data processing: Display of information

[0310] Output: Information displayed in the user interface

[0311] Step 7: Booking and Confirmation

[0312] The user enters a confirmation command by voice, such as "Book this hotel." The device again converts the voice into text data and sends it to the server. The server uses the Booking.com API to reserve the specified hotel and transportation. After the reservation is complete, a notification is sent to the device and displayed to the user.

[0313] Input: Text data of the confirmation command

[0314] Data processing: Reservation procedure execution

[0315] Output: Notification of reservation completion

[0316] This allows the system to automatically handle everything from user voice input to travel planning and arrangements, generating and executing optimal plans that take emotions into consideration.

[0317] (Application example 2)

[0318] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0319] Seniors face challenges in effectively using smartphones and the internet, particularly the complexity and difficulty of voice input and internet searches. Furthermore, existing systems lack the ability to provide personalized services that take into account the user's emotions and current location. In particular, in-store shopping support lacks a means for users to quickly and efficiently find the products they are looking for, and solutions to this issue are needed.

[0320] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0321] In this invention, the server includes: means for converting a user's voice command into text data; means for analyzing the user's intention and generating a task; means for analyzing the user's emotional state; means for optimizing the generated task based on the user's emotional state; means for further optimizing the generated task by referring to the user's past behavioral patterns and preference data; means for collecting external information from the Internet; means for integrating the collected information and presenting it on a user interface; means for performing actions such as making a reservation based on the presented information; means for identifying the location of a product in a store using the user's current location information; and means for presenting the identified product location to the user. This enables seniors to efficiently shop in physical stores via their smartphones and receive personalized support that takes into account their emotions and location information.

[0322] A "user's voice command" is a voice input by a user to give instructions to the system through voice.

[0323] "Text data" is digital data that converts a voice command into a string of characters.

[0324] "Means for analyzing intent" is a function that analyzes the user's purpose and requests from text data.

[0325] A "task" is a series of specific actions or procedures generated based on a user's intentions.

[0326] "Emotional state" refers to the psychological state of the user that is analyzed from their voice and facial expressions.

[0327] "Optimization means" is a function that adjusts the generated tasks and presented information to suit the user's condition and preferences.

[0328] "Past behavioral patterns" are data on actions and choices that a user has previously made.

[0329] "Preference data" is data that indicates the tendency of a user to prefer specific conditions or options.

[0330] "External information" is additional data obtained from the Internet or other external sources.

[0331] "Means of collection" refers to APIs and data access procedures for obtaining external information.

[0332] "Means of integration" refers to the ability to bring together collected data into a single system or display format.

[0333] A "user interface" is a display screen and operating procedures that allow a user to interact with a system.

[0334] "Means for performing actions such as reservations" refers to a function that performs specific operations (e.g., hotel reservations, product purchases) based on user instructions.

[0335] "Current location information" is digital location data that indicates the specific location where a user is currently located.

[0336] A "means for identifying product location" is a technology for determining where a specific product is located within a physical store.

[0337] The "means for presenting the product location" is a function for visually or audibly guiding the user to the location of the identified product.

[0338] This invention is a system that allows users to efficiently shop in physical stores, and uses the following main hardware and software to perform specific data processing and data calculations.

[0339] Hardware and Software Configuration

[0340] Smartphone: A device that acts as an interface between the user and the system.

[0341] Speech Recognition Module: Used to convert user voice input into text data (e.g., speech recognition service).

[0342] Natural Language Processing (NLP) modules: Analyzing user intent from text data (e.g., natural language processing libraries).

[0343] Sentiment analysis engine: Analyzes the emotional state from the user's voice (e.g., emotion analysis service).

[0344] Location services: Obtaining the user's current location (e.g., location services).

[0345] External APIs: Used to collect external information (e.g. online databases, web APIs).

[0346] Database: Stores data about users' past behavior patterns and preferences (e.g., data storage).

[0347] User Interface (UI): The interface that displays collected information and tasks to the user and allows them to perform operations.

[0348] Processing Details

[0349] 1. Receiving user input: The user launches a dedicated application on their smartphone and provides a command by voice, such as "I want to buy toilet paper." The smartphone's voice recognition module converts this voice command into text data.

[0350] 2. User intent analysis and task generation: The server receives the text data, analyzes it with a natural language processing (NLP) module to extract the user's intent (e.g., buying toilet paper), and generates the required task.

[0351] 3. User emotion recognition and task adjustment: The server uses an emotion analysis engine to analyze the user's emotional state (e.g., fatigue) from their voice. Based on the analysis results, the generated task (e.g., suggesting a rest area in a store) is adjusted accordingly.

[0352] 4. Personalization and Learning: The server refers to the user's past behavioral patterns and preferences to optimize the generated tasks for the user. The emotion engine also records past emotion data and uses it to optimize future tasks.

[0353] 5. Information collection and arrangement: The server uses external APIs to collect and integrate necessary information from the Internet (e.g., product locations within the store, information about rest areas).

[0354] 6. Displaying the results and confirming with the user: The collected information is consolidated and sent to a user interface, which displays a message such as "Toilet paper is on the fifth shelf. Also, if you need a break, there is a cafe nearby."

[0355] Specific examples

[0356] As a specific example, consider the process when a user says, "I want to buy toilet paper." First, the voice input is converted into text by the speech recognition module, and the intent is analyzed by the NLP module. Next, the emotion analysis engine determines the user's emotional state, and generates and optimizes corresponding tasks. Information on the location of products in the store and information on rest areas is collected using an external API, and this information is integrated and presented to the user.

[0357] Prompt Sentence Examples

[0358] An example of a prompt to input to a generative AI model is as follows:

[0359] "Design an application that helps users efficiently find the products they need in a physical store. Users input commands via voice, such as "I want milk." An emotion engine is used to recognize the user's state and suggest rest areas if they are tired. The speech is converted into text using a speech recognition module, and a natural language processing module is used to analyze intent, and an emotion analysis engine is used to recognize emotions. Location services are used to identify the location of products, and user preferences are recorded in a database."

[0360] As described above, by providing personalized support that incorporates emotional state and location information, seniors can have an efficient and comfortable shopping experience using their smartphones.

[0361] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0362] Step 1:

[0363] Receiving User Input

[0364] The user launches a dedicated application on their smartphone and speaks, "I want to buy toilet paper." The device's voice recognition module converts this voice command into text data. Specifically, the voice recognition software analyzes the voice waveform and converts it into character string data. At this point, the input is voice data, and the output is text data.

[0365] Step 2:

[0366] User Intention Analysis and Task Generation

[0367] The server receives the text data and analyzes it using a natural language processing (NLP) module. By performing group data and contextual analysis, the system extracts the user's intent (e.g., buying toilet paper). Specifically, it identifies keywords and patterns in the text and generates tasks based on them. The input is text data, and the output is the user's intent and the corresponding task.

[0368] Step 3:

[0369] User Emotion Recognition and Task Adjustment

[0370] The server uses an emotion analysis engine to determine the user's emotion from their voice. It analyzes the tone, speed, and intonation of the voice to evaluate the user's emotional state, such as whether they are tired. Specifically, it extracts voice features and inputs them into an emotion model. This input data is the voice features, and the output is the emotion recognition result. The generated task is then readjusted based on the determination result.

[0371] Step 4:

[0372] Personalization and Learning

[0373] The server further optimizes the task by referencing data on past behavioral patterns and user preferences. It retrieves the user's past choices and purchase history from the database and uses that information to suggest optimal products and services. The input data is past behavioral data, and the output is optimized tasks and recommended products.

[0374] Step 5:

[0375] Information gathering and arrangements

[0376] The server uses external APIs to collect necessary information from the Internet. For example, it obtains information about the location of products in a store or information about nearby rest areas. Specifically, it sends requests to each API and integrates the obtained information. The input data is the response from the external API, and the output is the integrated information.

[0377] Step 6:

[0378] Displaying results and user confirmation

[0379] The server consolidates the collected information and sends it to the user interface. Specifically, it organizes the information using UI components to display the collected data in a visually easy-to-read format. The input data is the consolidated information, and the output is what is displayed on the user interface. The user confirms this information and then voice-inputs, for example, "I want to purchase this product."

[0380] Step 7:

[0381] Booking and confirmation

[0382] Once the server receives confirmation from the user, it executes the reservation. For example, it uses an online shopping API to purchase a product. Specifically, it issues an API call to complete the reservation or purchase. The input data is the user's confirmation instructions, and the output is a confirmation notification of the reservation or purchase. A success notification is displayed on the user interface to inform the user of the result.

[0383] As described above, by designing detailed processing content and specific operations at each step, seniors can shop comfortably and efficiently.

[0384] 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.

[0385] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. 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 voice, text data indicating text, and image data indicating an image is also input. 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.

[0386] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0387] [Second embodiment]

[0388] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0389] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0390] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. 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).

[0391] 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.

[0392] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0393] 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 surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0394] 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.

[0395] 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.

[0396] 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 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.

[0397] 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.

[0398] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0399] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0400] This invention provides an autonomous AI agent called "Concierge" that helps seniors use smartphones and the Internet more effectively, and an embodiment of this invention is described below.

[0401] Receiving User Input

[0402] The user launches a dedicated application on their smartphone and enters a command by voice, such as "I want to go on a trip." The device uses a voice recognition module to convert this voice command into text data and send it to the server.

[0403] User Intention Analysis and Task Generation

[0404] The server analyzes the received text data using a natural language processing (NLP) module to extract the user's purpose (travel planning). Based on the analysis results, it generates the necessary tasks (e.g., booking a hotel, arranging transportation, checking the weather forecast, and listing necessary equipment).

[0405] Personalization and Learning

[0406] The server references the user's past behavioral patterns and preferences to optimize the generated tasks for the user, for example, taking into account the type of accommodation the user prefers based on their past travel history.

[0407] Information gathering and arrangements

[0408] The server uses external APIs to collect necessary information from the Internet. It obtains hotel reservation options through travel site APIs, and suggests optimal travel methods using transportation APIs. It also obtains weather information for the travel period using weather forecast APIs. Similarly, it generates a list of necessary equipment and provides it with online shopping links.

[0409] Displaying results and user confirmation

[0410] The collected information is consolidated on the server and sent as a data package to the device. The device displays this data on a user interface and asks the user for confirmation, such as a message like "Is this plan OK?"

[0411] Booking and confirmation

[0412] The user checks the displayed suggestions and issues a command such as "Book this hotel." The device again converts the speech into text and sends it to the server. The server then reserves the specified hotel and transportation based on the user's instructions. Once the reservation is complete, a notification is sent to the device and displayed to the user.

[0413] Specific examples

[0414] As a specific example, if a user says, "Concierge, I'd like to travel next week," the server performs the following tasks:

[0415] 1. User intent analysis: Extract travel destination, departure date, budget, etc.

[0416] 2. Personalization: Prioritize your preferred accommodation and transportation options based on past data.

[0417] 3. Information gathering: Collecting the best options from multiple travel sites and transportation APIs.

[0418] 4. Displaying results: Travel plans, accommodation, transportation, weather forecast, and a list of necessary equipment are displayed on the user interface.

[0419] 5. Reservation: After user confirmation, the reservation is actually made.

[0420] In this way, the system allows even seniors to easily plan and decide on trips without having to perform complicated operations.

[0421] The processing flow will be explained below.

[0422] Step 1:

[0423] The user launches a dedicated application on their smartphone and issues a voice command such as "I want to go on a trip."

[0424] Step 2:

[0425] The terminal's voice recognition module receives the user's voice commands and converts them into text data.

[0426] Step 3:

[0427] The terminal transmits the converted text data to the server.

[0428] Step 4:

[0429] The server analyzes the received text data using a natural language processing (NLP) module to extract the user's purpose (travel plans).

[0430] Step 5:

[0431] Based on the purpose, the server generates the necessary tasks (reserving a hotel, arranging transportation, checking the weather forecast, listing the necessary equipment).

[0432] Step 6:

[0433] The server references the user's past behavioral patterns and preference data to optimize the generated tasks, for example prioritizing the type of accommodation the user prefers based on their past travel history.

[0434] Step 7:

[0435] The server uses external APIs to collect the necessary information from the Internet. Specifically, it obtains hotel reservation options from travel site APIs, obtains optimal travel methods from transportation APIs, obtains weather information for the travel period from weather forecast APIs, and generates a list of necessary equipment.

[0436] Step 8:

[0437] The server consolidates the collected information and organizes it into a single data package.

[0438] Step 9:

[0439] The server transmits the consolidated data package to the terminal.

[0440] Step 10:

[0441] The device analyzes the transmitted data package and displays it on the user interface, for example displaying a confirmation message saying "Here is the proposed travel plan. What do you want to do?"

[0442] Step 11:

[0443] The user checks the displayed information and then says aloud, "Book this hotel."

[0444] Step 12:

[0445] The device converts the user's voice commands into text and sends it back to the server.

[0446] Step 13:

[0447] The server calls the booking API to reserve the specified hotel and transportation based on the user's instructions.

[0448] Step 14:

[0449] The server notifies the terminal of the reservation result (success / failure).

[0450] Step 15:

[0451] The device will notify the user that the booking is complete and save the trip details.

[0452] Example 1

[0453] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0454] Currently, for seniors to effectively use smartphones and the internet, complex operations and information gathering are required, which presents a major barrier. In particular, tasks related to planning and booking trips are complicated, and the lack of consistent support reduces usability. For this reason, there is a demand for systems that allow seniors to easily use smartphones and the internet.

[0455] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0456] In this invention, the server includes means for converting a user's voice commands into text data, means for analyzing the user's intentions based on the text data and generating a task, means for optimizing the generated task by referring to the user's past behavioral patterns and preference data, means for collecting external information from the Internet, means for integrating the collected information and presenting it to the user, means for performing actions such as making a reservation based on the presented information, means for providing multiple options based on the external data collected via the Internet, and means for obtaining confirmations and instructions from the user using voice recognition. This enables seniors to easily plan and book trips using their smartphones without requiring complex operations.

[0457] "Voice command" refers to an instruction or request input by a user through speech.

[0458] "Text data" refers to data obtained by converting voice commands into text information.

[0459] "User intent" refers to the purpose or request that the user wants to convey through a voice command.

[0460] A "task" refers to a specific process or action that the system should perform based on the user's intentions.

[0461] "Past behavioral patterns" refers to the history of operations and selections that the user has previously made.

[0462] "Preference Data" refers to information about a user's past preferences and selection tendencies.

[0463] "Optimization" refers to adjusting and modifying the generated tasks and suggestions to best suit the user based on the user's requirements, past behavioral patterns, and preferences.

[0464] "External information" refers to data obtained from external sources such as the Internet.

[0465] "Information integration" refers to bringing together collected external information and user data and processing it in a consistent manner.

[0466] An "action" refers to a specific task or operation that is performed through the execution of a task.

[0467] "External data collected via the Internet" refers to data collected from different sources on the Internet.

[0468] "Choices" refers to multiple alternatives or options offered to a user.

[0469] "Speech recognition" refers to the technology and process of converting speech into text data.

[0470] "Confirmation or instruction" refers to voice input made by the user to confirm the system's operation.

[0471] This invention provides an autonomous AI agent called "Concierge" that helps seniors effectively use smartphones and the Internet. Specific embodiments for implementing this invention are described below.

[0472] The user uses a dedicated application on their smartphone. This application uses a voice recognition module (e.g., Google Speech-to-Text API) to convert the user's voice commands into text data. This text data is then sent from the smartphone (device) to the server.

[0473] The server analyzes the received text data using a natural language processing (NLP) module (e.g., OpenAI's GPT-3), extracts the user's intent (e.g., planning a trip), and generates the necessary tasks (e.g., booking a hotel, arranging transportation, checking the weather forecast, and listing the necessary equipment).

[0474] The server then refers to the user's past behavioral patterns and preferences, which are stored in the server's database, and optimizes the generated task by taking into account the user's past travel history. For example, it may prioritize the type of accommodation the user has preferred in the past.

[0475] In addition, the server uses external APIs (e.g., Booking.com API, Google Maps API, Weather.com API) to collect necessary information from the Internet, obtain hotel reservation options based on the travel dates, suggest the best means of transportation, obtain weather forecasts for the travel period, generate a list of necessary equipment, and provide links to online shopping.

[0476] The collected information is consolidated on the server and sent as a data package to the device, which then displays this data on a user interface and asks the user for confirmation, such as "Is this plan OK?"

[0477] The user checks the displayed suggestions and then re-enters a command, such as "Book this hotel." The device converts the speech into text and sends it to the server. The server then reserves the specified hotel and transportation based on the user's instructions. Once the reservation is complete, a notification is sent to the device and displayed to the user.

[0478] Specific examples

[0479] For example, if a user says, "Concierge, I would like to travel next week," the server performs the following tasks:

[0480] 1. Analyzing user intent: Extract travel destination, departure date, budget, etc.

[0481] 2. Personalization: Prioritize your preferred accommodation and transportation options based on past data.

[0482] 3. Information gathering: Collecting the best options from multiple travel sites and transportation APIs.

[0483] 4. Displaying results: The user interface displays the itinerary, accommodation, transportation, weather forecast, and list of necessary equipment.

[0484] 5. Reservation: After user confirmation, the reservation is actually made.

[0485] An example of a prompt sentence is, "A concierge AI that supports travel planning for seniors through voice input would generate a travel plan from the user's voice input and explain the process leading up to the reservation."

[0486] As described above, this invention allows even seniors to easily plan and book trips without having to perform complicated operations.

[0487] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0488] Step 1:

[0489] A user launches a dedicated application on their smartphone and verbally enters a command such as "I want to go on a trip." The device uses a voice recognition module (for example, the Google Speech-to-Text API) to convert this voice command into text data. Specifically, the application receives the voice input and converts it into text. The input is a voice command, and the output is text data.

[0490] Step 2:

[0491] Text data is sent to the server. The server analyzes the received text data using a natural language processing (NLP) module (e.g., OpenAI's GPT-3) to extract the user's intent (e.g., planning a trip). The input is text data, and the output is data indicating the user's intent.

[0492] Step 3:

[0493] Based on the analysis results, the server generates the necessary tasks (e.g., reserving a hotel, arranging transportation, checking the weather forecast, listing necessary equipment). Specifically, the server uses a task generation module to list appropriate tasks based on the user's intent. The input is the user's intent data, and the output is a list of generated tasks.

[0494] Step 4:

[0495] The server optimizes the generated tasks by referencing the user's past behavioral patterns and preference data. For example, it retrieves the user's travel history from a historical database and considers the type of accommodation they preferred in the past. The input is a task list and the user's past data, and the output is an optimized task list.

[0496] Step 5:

[0497] The server uses external APIs (e.g., Booking.com API, Google Maps API, Weather.com API) to collect necessary information from the Internet. This includes obtaining hotel reservation options based on the travel dates, suggesting the best means of transportation, obtaining weather forecasts for the travel period, and generating a list of necessary equipment. The input is the optimized task list, and the output is the collected information data.

[0498] Step 6:

[0499] The collected information is integrated by the server and sent to the terminal as a data package. The terminal displays this data package on a user interface and asks the user for confirmation. Specifically, the terminal receives the data package and visualizes and displays it. The input is the collected information data, and the output is the display data on the user interface.

[0500] Step 7:

[0501] The user checks the displayed suggestions and enters a command by voice, such as "Book this hotel." The device again converts the voice into text and sends it to the server. Specifically, the device receives voice input, converts it into text, and sends it. The input is a voice command, and the output is text data.

[0502] Step 8:

[0503] The server reserves the specified hotel and transportation based on the user's instructions. Once the reservation is complete, a notification is sent to the terminal and displayed to the user. Specifically, the server calls the reservation API, confirms the reservation, and then sends notification data to the terminal. The input is reservation instruction data, and the output is reservation completion notification data.

[0504] (Application example 1)

[0505] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0506] In today's world, seniors face many barriers when using the internet and smartphones. These include complex operations and security risks. Phishing scams and security authentication issues are particularly prevalent when it comes to online transactions, making it difficult for seniors to conduct transactions safely and securely. Therefore, there is a demand for a system that can assist users in conducting transactions online easily and safely.

[0507] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0508] In this invention, the server includes: means for converting a user's voice command into text data; means for analyzing the user's intention based on the text data and generating a task; means for referencing the user's past behavioral patterns and preference data and optimizing the generated task; means for collecting external information from the Internet; means for integrating the collected information and presenting it to the user; means for performing actions such as making a reservation based on the presented information; means for instructing the user to support safe transactions by voice command when conducting a transaction; means for converting the voice command into text data and analyzing the intention; means for collecting security information related to the transaction from an external API and notifying the user of the information; and means for presenting the user with a transaction reliability assessment and security status based on the collected security information. This makes it possible for seniors to conduct transactions over the Internet easily and safely.

[0509] "User voice command" refers to an instruction or request given by a user through a microphone by voice.

[0510] "Text data" refers to data that has been converted from voice commands into text information using voice recognition technology.

[0511] "User intent" refers to the goal or desire the user ultimately aims to achieve based on voice commands or text data.

[0512] A "task" refers to a specific action item that the system automatically generates based on the user's intentions.

[0513] "User's past behavioral patterns" refers to the operation history and behavior history of the user who previously used the system.

[0514] "Preference Data" refers to data regarding a user's tastes and preferences.

[0515] "External information" refers to all information obtained from the Internet or external databases.

[0516] "Presented information" refers to information that integrates collected external information and is displayed in a format that is easy for the user to understand.

[0517] "Actions such as reservations" refers to specific actions such as reservations and procedures that the system automatically performs based on the information confirmed by the user.

[0518] "Security Information" refers to information regarding the reliability rating and security status of a business partner's site or service.

[0519] "External API" refers to a program interface for connecting with other web services or databases.

[0520] "Trustworthiness rating" refers to the criteria and data used to evaluate how trustworthy a service or site is.

[0521] "Security status" refers to whether the site or service is currently safe to use.

[0522] This invention provides an autonomous AI agent system that helps seniors use the Internet safely, particularly by making online transactions easier and more secure.

[0523] The server starts processing when the user inputs a voice command via a smartphone, smart glasses, or head-mounted display. First, it uses a voice recognition module to convert the user's voice command into text data. Next, it uses a natural language processing (NLP) module to analyze the converted text data and extract the user's intent. For example, it recognizes a command such as "Support this transaction" and analyzes that intent.

[0524] Based on the analysis results, the system generates tasks that are in line with the user's intentions. During this task generation stage, the system references the user's past behavioral patterns and preferences to optimize the generated tasks. For example, it adjusts the level of alerts and warnings based on past transaction history and the security notification history the user has received.

[0525] In addition, the server collects external information from the Internet. Specifically, it uses external APIs to obtain security information related to the sites and services of its business partners. This information includes the site's reliability rating and current security status. For example, this includes the expiration date of the SSL certificate and whether the site has been reported as a phishing site.

[0526] The collected information is integrated and presented to the user. The user interface of the terminal displays the reliability rating and security status of the transaction site, including an alert asking, "Is this site safe?" The user can check the displayed information and issue voice commands such as "Make a reservation" or "Continue the transaction" as needed. The server then makes the specific reservation or transaction based on the user's instructions. When the reservation or transaction is completed, a notification is sent to the terminal and displayed to the user.

[0527] For example, if a user says "Support this transaction," the server performs the following steps: First, it checks the transaction partner's site using an external API and collects the SSL certificate expiration date and phishing site report status. It then analyzes this information and notifies the user, "This site is safe. Do you want to continue?", requesting user confirmation.

[0528] An example of a prompt would be:

[0529] "Enter your voice command: Say 'Support this transaction.'"

[0530] In this way, the system of the present invention is a system that provides multifaceted support to seniors so that they can conduct Internet transactions with peace of mind.

[0531] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0532] Step 1:

[0533] The user inputs a voice command. Specifically, the user speaks into a smartphone, smart glasses, or head-mounted display, saying, "Support this transaction." The input is voice data, which is then captured by the terminal.

[0534] Step 2:

[0535] The device converts the voice into text data. Specifically, it uses a speech recognition module on the device (e.g., Google Speech Recognition API) to convert the input voice data into text data in character format. The input in this step is the voice data obtained in step 1, and the output is the converted text data.

[0536] Step 3:

[0537] The server analyzes the user's intent based on the text data. Specifically, it uses a natural language processing (NLP) module to extract the user's intent, "support this transaction," from the text data. The input in this step is the text data obtained in step 2, and the output is the analyzed intent data.

[0538] Step 4:

[0539] The server references the user's past behavioral patterns and preference data to optimize the generated tasks. Specifically, it references the user's past transaction history and alert history from the database and uses this information to prioritize tasks. The inputs in this step are the intent data obtained in step 3 and the user data in the database, and the output is optimized task data.

[0540] Step 5:

[0541] The server collects external information from the Internet. Specifically, it uses an external API (e.g., a security evaluation API) to obtain reliability and security information about partner sites and services. The input to this step is the task data obtained in step 4, and the output is the collected external information.

[0542] Step 6:

[0543] The server consolidates the collected information and presents it to the user. Specifically, it compiles the collected security information (e.g., SSL certificate expiration date, phishing site report status, etc.) and displays it on the device's user interface in a format that is easy for the user to understand. The input in this step is the external information obtained in step 5, and the output is the presented information.

[0544] Step 7:

[0545] The user confirms the presented information and issues a voice command for the next action, such as "continue the transaction" or "make a reservation on this site." The user confirms the presented information in step 6 and then issues a voice command.

[0546] Step 8:

[0547] The device again converts the voice command into text data and sends it to the server. Specifically, it again uses a voice recognition module to convert the voice into text and sends it to the server. The input in this step is the user voice command from step 7, and the output is text data.

[0548] Step 9:

[0549] The server executes the specific reservation or transaction based on the user's instructions. Specifically, it calls the appropriate external API to complete the reservation procedure and notifies the user of the results. The input in this step is the text data from step 8, and the output is the result of the action taken and a notification of it.

[0550] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0551] This invention combines an autonomous AI agent called "Concierge" that helps seniors use smartphones and the Internet more effectively with an emotion engine that recognizes the user's emotions. An embodiment of this invention is described below.

[0552] Receiving User Input

[0553] The user launches a dedicated application on their smartphone and enters a command by voice, such as "I want to go on a trip." The device uses a voice recognition module to convert this voice command into text data and send it to the server.

[0554] User Intention Analysis and Task Generation

[0555] The server analyzes the received text data using a natural language processing (NLP) module to extract the user's purpose (travel planning). Based on the analysis results, it generates the necessary tasks (e.g., booking a hotel, arranging transportation, checking the weather forecast, and listing necessary equipment).

[0556] User emotion recognition and adjustment

[0557] The server uses an emotion engine to analyze the user's emotional state from their voice commands. Based on this analysis, it can adjust the tasks it generates. For example, if the user is tired, it can suggest a more relaxing plan.

[0558] Personalization and Learning

[0559] The server references the user's past behavioral patterns and preferences to optimize the generated tasks for the user. The emotion engine also records the user's past emotional data and uses it to optimize future tasks. This enables personalization that takes the user's emotional state into account.

[0560] Information gathering and arrangements

[0561] The server uses external APIs to collect necessary information from the Internet. It obtains hotel reservation options through travel site APIs, and suggests optimal travel methods using transportation APIs. It also obtains weather information for the travel period using weather forecast APIs. Similarly, it generates a list of necessary equipment and provides it with online shopping links.

[0562] Displaying results and user confirmation

[0563] The collected information is consolidated on the server and sent as a data package to the device. The device displays this data on a user interface and asks the user for confirmation, such as a message like "Is this plan OK?"

[0564] Booking and confirmation

[0565] The user checks the displayed suggestions and issues a command such as "Book this hotel." The device again converts the speech into text and sends it to the server. Based on the user's instructions, the server calls the reservation API to reserve the specified hotel and transportation. Once the reservation is complete, a notification is sent to the device and displayed to the user.

[0566] Specific examples

[0567] As a specific example, if a user says, "I'd like you to suggest a travel plan that will allow me to relax a little today," the server will perform the following tasks:

[0568] 1. User intent analysis: Extract travel destination, departure date, budget, etc.

[0569] 2. Emotion recognition: Analyze the user's emotional state, such as wanting to relax, from their voice.

[0570] 3. Personalization: Prioritize relaxing accommodation and transportation options based on past data.

[0571] 4. Information gathering: Collecting the best options from multiple travel sites and transportation APIs.

[0572] 5. Displaying results: Travel plans, accommodation, transportation, weather forecast, and a list of necessary equipment are displayed on the user interface.

[0573] 6. Reservation: After user confirmation, the reservation is actually made.

[0574] In this way, by combining the emotion engine, the system allows even seniors to make optimal travel plans and decisions based on their emotional state without having to perform complicated operations.

[0575] The processing flow will be explained below.

[0576] Step 1:

[0577] The user launches a dedicated application on their smartphone and issues a voice command such as, "Please suggest a travel plan that is a little more relaxing today."

[0578] Step 2:

[0579] The terminal's voice recognition module receives the user's voice commands and converts them into text data.

[0580] Step 3:

[0581] The terminal transmits the converted text data to the server.

[0582] Step 4:

[0583] The server analyzes the received text data using a natural language processing (NLP) module to extract the user's intent (suggestions for a relaxing travel plan).

[0584] Step 5:

[0585] The server uses an emotion engine to analyze the user's emotional state (e.g., a desire to relax) from their voice command, and generates tasks (e.g., hotel reservations, transportation arrangements, weather forecasts, and a list of necessary equipment) based on this emotional state.

[0586] Step 6:

[0587] The server optimizes the generated tasks by referring to the user's past behavioral patterns, preference data, and emotion recognition results. Specifically, it prioritizes data on relaxation spots and accommodations visited in the past.

[0588] Step 7:

[0589] The server uses external APIs to collect necessary information from the Internet. It obtains relaxing hotel reservation options through travel site APIs, suggests optimal travel methods using transportation APIs, and uses weather forecast APIs to obtain weather information for the travel period and generate a list of necessary equipment.

[0590] Step 8:

[0591] The server consolidates the collected information and organizes it into a single data package.

[0592] Step 9:

[0593] The server transmits the consolidated data package to the terminal.

[0594] Step 10:

[0595] The device analyzes the transmitted data package and displays it on the user interface, for example displaying a confirmation message saying, "Here are our suggested relaxing travel plans. What do you want to do?"

[0596] Step 11:

[0597] The user checks the displayed information and then says aloud, "Book this hotel."

[0598] Step 12:

[0599] The device converts the user's voice commands into text and sends it back to the server.

[0600] Step 13:

[0601] The server calls the booking API to reserve the specified hotel and transportation based on the user's instructions.

[0602] Step 14:

[0603] The server notifies the terminal of the reservation result (success / failure).

[0604] Step 15:

[0605] The device will notify the user that the booking is complete and save the trip details.

[0606] Example 2

[0607] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0608] It is often difficult for older adults to effectively use smartphones and the internet. Furthermore, tasks such as planning and booking trips are complex, especially when it comes to presenting optimal plans that take into account the user's emotional state. This calls for systems with emotion recognition and personalization capabilities.

[0609] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for converting a user's voice command into text data, means for analyzing the user's intention based on the text data and generating a task, means for optimizing the generated task by referring to the user's past behavioral patterns and preference data, means for analyzing the user's emotional state and adjusting the task, means for collecting external information, means for integrating the collected information and presenting it to the user, and means for performing actions such as making a reservation based on the presented information. This makes it possible to generate and execute an optimal travel plan that takes the user's emotional state into consideration.

[0610] "Voice command" refers to instructions or requests that a user verbally inputs into a smartphone or other device.

[0611] "Text data" refers to text information converted from voice commands using voice recognition technology.

[0612] "Intent analysis" refers to the process of understanding a user's goals and requests from voice commands and generating specific tasks based on that content.

[0613] "Task generation" refers to the process of determining specific tasks and procedures based on the results of intent analysis.

[0614] "Past behavioral patterns" refers to the history of actions and choices made by the user in the past.

[0615] "Preference Data" refers to information relating to a user's personal tastes and preferences.

[0616] "Task optimization" refers to the process of adjusting and improving a task to best suit the user by referring to data on the user's past behavioral patterns and preferences.

[0617] "Emotional state" refers to the emotion or mood of the user when entering a voice command.

[0618] "Means for analyzing emotional state" refers to technology that reads and evaluates emotional nuances from a user's voice or text data.

[0619] "External information" refers to information such as travel information, accommodation information, transportation options, and weather forecasts obtained via the Internet.

[0620] "Means of collecting external information" refers to technology that uses external interfaces and APIs to obtain necessary information from the Internet.

[0621] "Information synthesis" refers to the process of bringing together data collected from multiple sources into a single, unified format.

[0622] "Presentation means" refers to the user interface and display technology used to present the integrated information to the user.

[0623] "Means for executing actions such as reservations" refers to technology that actually carries out reservation procedures or other actions based on the user's confirmation or instructions.

[0624] This invention relates to an autonomous AI agent called "Concierge" that helps seniors use smartphones and the internet more effectively, and is combined with an emotion engine that recognizes the user's emotions. This system implements a series of processes: it receives a user's voice command, analyzes the user's intention, generates a task, optimizes it, and then executes it.

[0625] First, the user launches a dedicated application installed on their smartphone and enters a command by voice, such as "I want to go on a trip." At this time, the device uses the Google Cloud Speech-to-Text API to convert the user's voice command into text data, which is then sent to a server via the Internet.

[0626] The server analyzes the received text data using the Google Cloud Natural Language API and extracts the user's intent. For example, a voice command such as "I want to go on a trip" generates tasks such as selecting a travel destination, booking accommodation, and arranging transportation.

[0627] The server then uses Microsoft Azure Text Analytics for Cognitive Services to analyze the user's emotional state. For example, if the user's intent is "I want to relax," the server can adjust the task to provide a relaxing travel plan based on the emotion recognition results.

[0628] The server then uses Amazon Personalize to optimize the generated tasks based on past behavioral data and user preference patterns. For example, if a user has previously booked a resort hotel, the server will prioritize presenting similar options this time.

[0629] Regarding information gathering, the server uses external interfaces such as Expedia API, Google Maps API, OpenWeatherMap API, etc. to gather the necessary information, such as hotel reservation options, transportation options, weather forecasts, and a list of necessary amenities.

[0630] The collected information is integrated on the server and displayed on a user interface, allowing users to check travel plans, accommodations, transportation options, weather forecasts, lists of necessary supplies, etc. all in one place. For example, if a dedicated application is built with React Native, questions such as "Is this plan okay?" will be displayed on the user interface.

[0631] Finally, the user checks the displayed plan and enters a command such as "Book this hotel" by voice. The device again converts the voice to text data and sends it to the server. The server then calls the Booking.com API, makes the actual reservation, and sends a notification to the device. The user can then complete the entire process by receiving a notification that the reservation has been completed.

[0632] For example, if a user says, "I want some suggestions for relaxing travel destinations today," the system will do the following:

[0633] 1. Convert user voice input into text data

[0634] 2. Analyzing intent from text data and generating travel plans for relaxation

[0635] 3. Emotion recognition to recommend places suitable for relaxation

[0636] 4. Provide optimal plans based on past behavioral data

[0637] 5. Collect the necessary information, consolidate the plan, and display it in the user interface

[0638] 6. After user confirmation, the reservation is actually made

[0639] The system is designed to help seniors navigate complex procedures with ease and can provide a personalized travel experience that takes into account the user's emotions and preferences.

[0640] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0641] Step 1: Receiving User Input

[0642] The user launches the dedicated application and speaks a command such as "I want to go on a trip." The device uses the Google Cloud Speech-to-Text API to convert the voice into text data. This API outputs the voice as text data. The device then sends the converted text data to the server.

[0643] Input: User's voice command

[0644] Data processing: Converting speech to text

[0645] Output: Text data

[0646] Step 2: User intent analysis and task generation

[0647] The server receives the text data sent from the device and analyzes its intent using the Google Cloud Natural Language API. This analysis extracts the user's purpose (e.g., planning a trip). Based on the results, it generates tasks (reserving a hotel, arranging transportation, checking the weather forecast, and listing necessary equipment).

[0648] Input: Text data

[0649] Data processing: Intention analysis and task generation

[0650] Output: Analysis results and task list

[0651] Step 3: Recognizing and adjusting user emotions

[0652] The server uses Microsoft Azure Text Analytics to analyze the user's emotional state from the text data. Based on the obtained emotional state, the content of the generated task is adjusted. For example, if the user feels like "I want to relax," the server generates a plan that allows for more relaxation.

[0653] Input: Text data

[0654] Data processing: Emotional state analysis and task adjustment

[0655] Output: Reconciled task list

[0656] Step 4: Personalize and learn

[0657] The server uses Amazon Personalize to optimize the task by referencing the user's past behavioral patterns and preference data. This optimization suggests a plan based on the user's past tastes and preferences. The emotion engine also records the user's emotional data and uses it for future optimization.

[0658] Input: Adjusted task list and past activity data

[0659] Data Transformation: Personalization and Learning

[0660] Output: Optimized task list

[0661] Step 5: Information gathering and arrangements

[0662] The server uses external APIs (e.g., Expedia API, Google Maps API, OpenWeatherMap API) to collect the necessary information. The collected data includes hotel reservation options, transportation options, weather forecasts, and a list of necessary equipment. Based on this information, a detailed travel plan is created.

[0663] Input: Optimized task list

[0664] Data processing: collecting and integrating external information

[0665] Output: Consolidated information

[0666] Step 6: Displaying the results and user confirmation

[0667] The server sends the collected information to the device, which then displays it in the user interface. For example, if the dedicated application is built with React Native, it will display a message asking, "Is this plan OK?"

[0668] Input: Integrated information

[0669] Data processing: Display of information

[0670] Output: Information displayed in the user interface

[0671] Step 7: Booking and Confirmation

[0672] The user enters a confirmation command by voice, such as "Book this hotel." The device again converts the voice into text data and sends it to the server. The server uses the Booking.com API to reserve the specified hotel and transportation. After the reservation is complete, a notification is sent to the device and displayed to the user.

[0673] Input: Text data of the confirmation command

[0674] Data processing: Reservation procedure execution

[0675] Output: Notification of reservation completion

[0676] This allows the system to automatically handle everything from user voice input to travel planning and arrangements, generating and executing optimal plans that take emotions into consideration.

[0677] (Application example 2)

[0678] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0679] Seniors face challenges in effectively using smartphones and the internet, particularly the complexity and difficulty of voice input and internet searches. Furthermore, existing systems lack the ability to provide personalized services that take into account the user's emotions and current location. In particular, in-store shopping support lacks a means for users to quickly and efficiently find the products they are looking for, and solutions to this issue are needed.

[0680] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0681] In this invention, the server includes: means for converting a user's voice command into text data; means for analyzing the user's intention and generating a task; means for analyzing the user's emotional state; means for optimizing the generated task based on the user's emotional state; means for further optimizing the generated task by referring to the user's past behavioral patterns and preference data; means for collecting external information from the Internet; means for integrating the collected information and presenting it on a user interface; means for performing actions such as making a reservation based on the presented information; means for identifying the location of a product in a store using the user's current location information; and means for presenting the identified product location to the user. This enables seniors to efficiently shop in physical stores via their smartphones and receive personalized support that takes into account their emotions and location information.

[0682] A "user's voice command" is a voice input by a user to give instructions to the system through voice.

[0683] "Text data" is digital data that converts a voice command into a string of characters.

[0684] "Means for analyzing intent" is a function that analyzes the user's purpose and requests from text data.

[0685] A "task" is a series of specific actions or procedures generated based on a user's intentions.

[0686] "Emotional state" refers to the psychological state of the user that is analyzed from their voice and facial expressions.

[0687] "Optimization means" is a function that adjusts the generated tasks and presented information to suit the user's condition and preferences.

[0688] "Past behavioral patterns" are data on actions and choices that a user has previously made.

[0689] "Preference data" is data that indicates the tendency of a user to prefer specific conditions or options.

[0690] "External information" is additional data obtained from the Internet or other external sources.

[0691] "Means of collection" refers to APIs and data access procedures for obtaining external information.

[0692] "Means of integration" refers to the ability to bring together collected data into a single system or display format.

[0693] A "user interface" is a display screen and operating procedures that allow a user to interact with a system.

[0694] "Means for performing actions such as reservations" refers to a function that performs specific operations (e.g., hotel reservations, product purchases) based on user instructions.

[0695] "Current location information" is digital location data that indicates the specific location where a user is currently located.

[0696] A "means for identifying product location" is a technology for determining where a specific product is located within a physical store.

[0697] The "means for presenting the product location" is a function for visually or audibly guiding the user to the location of the identified product.

[0698] This invention is a system that allows users to efficiently shop in physical stores, and uses the following main hardware and software to perform specific data processing and data calculations.

[0699] Hardware and Software Configuration

[0700] Smartphone: A device that acts as an interface between the user and the system.

[0701] Speech Recognition Module: Used to convert user voice input into text data (e.g., speech recognition service).

[0702] Natural Language Processing (NLP) modules: Analyzing user intent from text data (e.g., natural language processing libraries).

[0703] Sentiment analysis engine: Analyzes the emotional state from the user's voice (e.g., emotion analysis service).

[0704] Location services: Obtaining the user's current location (e.g., location services).

[0705] External APIs: Used to collect external information (e.g. online databases, web APIs).

[0706] Database: Stores data about users' past behavior patterns and preferences (e.g., data storage).

[0707] User Interface (UI): The interface that displays collected information and tasks to the user and allows them to perform operations.

[0708] Processing Details

[0709] 1. Receiving user input: The user launches a dedicated application on their smartphone and provides a command by voice, such as "I want to buy toilet paper." The smartphone's voice recognition module converts this voice command into text data.

[0710] 2. User intent analysis and task generation: The server receives the text data, analyzes it with a natural language processing (NLP) module to extract the user's intent (e.g., buying toilet paper), and generates the required task.

[0711] 3. User emotion recognition and task adjustment: The server uses an emotion analysis engine to analyze the user's emotional state (e.g., fatigue) from their voice. Based on the analysis results, the generated task (e.g., suggesting a rest area in a store) is adjusted accordingly.

[0712] 4. Personalization and Learning: The server refers to the user's past behavioral patterns and preferences to optimize the generated tasks for the user. The emotion engine also records past emotion data and uses it to optimize future tasks.

[0713] 5. Information collection and arrangement: The server uses external APIs to collect and integrate necessary information from the Internet (e.g., product locations within the store, information about rest areas).

[0714] 6. Displaying the results and confirming with the user: The collected information is consolidated and sent to a user interface, which displays a message such as "Toilet paper is on the fifth shelf. Also, if you need a break, there is a cafe nearby."

[0715] Specific examples

[0716] As a specific example, consider the process when a user says, "I want to buy toilet paper." First, the voice input is converted into text by the speech recognition module, and the intent is analyzed by the NLP module. Next, the emotion analysis engine determines the user's emotional state, and generates and optimizes corresponding tasks. Information on the location of products in the store and information on rest areas is collected using an external API, and this information is integrated and presented to the user.

[0717] Prompt Sentence Examples

[0718] An example of a prompt to input to a generative AI model is as follows:

[0719] "Design an application that helps users efficiently find the products they need in a physical store. Users input commands via voice, such as "I want milk." An emotion engine is used to recognize the user's state and suggest rest areas if they are tired. The speech is converted into text using a speech recognition module, and a natural language processing module is used to analyze intent, and an emotion analysis engine is used to recognize emotions. Location services are used to identify the location of products, and user preferences are recorded in a database."

[0720] As described above, by providing personalized support that incorporates emotional state and location information, seniors can have an efficient and comfortable shopping experience using their smartphones.

[0721] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0722] Step 1:

[0723] Receiving User Input

[0724] The user launches a dedicated application on their smartphone and speaks, "I want to buy toilet paper." The device's voice recognition module converts this voice command into text data. Specifically, the voice recognition software analyzes the voice waveform and converts it into character string data. At this point, the input is voice data, and the output is text data.

[0725] Step 2:

[0726] User Intention Analysis and Task Generation

[0727] The server receives the text data and analyzes it using a natural language processing (NLP) module. By performing group data and contextual analysis, the system extracts the user's intent (e.g., buying toilet paper). Specifically, it identifies keywords and patterns in the text and generates tasks based on them. The input is text data, and the output is the user's intent and the corresponding task.

[0728] Step 3:

[0729] User Emotion Recognition and Task Adjustment

[0730] The server uses an emotion analysis engine to determine the user's emotion from their voice. It analyzes the tone, speed, and intonation of the voice to evaluate the user's emotional state, such as whether they are tired. Specifically, it extracts voice features and inputs them into an emotion model. This input data is the voice features, and the output is the emotion recognition result. The generated task is then readjusted based on the determination result.

[0731] Step 4:

[0732] Personalization and Learning

[0733] The server further optimizes the task by referencing data on past behavioral patterns and user preferences. It retrieves the user's past choices and purchase history from the database and uses that information to suggest optimal products and services. The input data is past behavioral data, and the output is optimized tasks and recommended products.

[0734] Step 5:

[0735] Information gathering and arrangements

[0736] The server uses external APIs to collect necessary information from the Internet. For example, it obtains information about the location of products in a store or information about nearby rest areas. Specifically, it sends requests to each API and integrates the obtained information. The input data is the response from the external API, and the output is the integrated information.

[0737] Step 6:

[0738] Displaying results and user confirmation

[0739] The server consolidates the collected information and sends it to the user interface. Specifically, it organizes the information using UI components to display the collected data in a visually easy-to-read format. The input data is the consolidated information, and the output is what is displayed on the user interface. The user confirms this information and then voice-inputs, for example, "I want to purchase this product."

[0740] Step 7:

[0741] Booking and confirmation

[0742] Once the server receives confirmation from the user, it executes the reservation. For example, it uses an online shopping API to purchase a product. Specifically, it issues an API call to complete the reservation or purchase. The input data is the user's confirmation instructions, and the output is a confirmation notification of the reservation or purchase. A success notification is displayed on the user interface to inform the user of the result.

[0743] As described above, by designing detailed processing content and specific operations at each step, seniors can shop comfortably and efficiently.

[0744] 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.

[0745] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. 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 voice, text data indicating text, and image data indicating an image is also input. 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.

[0746] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0747] [Third embodiment]

[0748] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0749] 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.

[0750] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. 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).

[0751] 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.

[0752] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0753] 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 surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0754] 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.

[0755] 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.

[0756] 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 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.

[0757] 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.

[0758] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0759] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0760] This invention provides an autonomous AI agent called "Concierge" that helps seniors use smartphones and the Internet more effectively, and an embodiment of this invention is described below.

[0761] Receiving User Input

[0762] The user launches a dedicated application on their smartphone and enters a command by voice, such as "I want to go on a trip." The device uses a voice recognition module to convert this voice command into text data and send it to the server.

[0763] User Intention Analysis and Task Generation

[0764] The server analyzes the received text data using a natural language processing (NLP) module to extract the user's purpose (travel planning). Based on the analysis results, it generates the necessary tasks (e.g., booking a hotel, arranging transportation, checking the weather forecast, and listing necessary equipment).

[0765] Personalization and Learning

[0766] The server references the user's past behavioral patterns and preferences to optimize the generated tasks for the user, for example, taking into account the type of accommodation the user prefers based on their past travel history.

[0767] Information gathering and arrangements

[0768] The server uses external APIs to collect necessary information from the Internet. It obtains hotel reservation options through travel site APIs, and suggests optimal travel methods using transportation APIs. It also obtains weather information for the travel period using weather forecast APIs. Similarly, it generates a list of necessary equipment and provides it with online shopping links.

[0769] Displaying results and user confirmation

[0770] The collected information is consolidated on the server and sent as a data package to the device. The device displays this data on a user interface and asks the user for confirmation, such as a message like "Is this plan OK?"

[0771] Booking and confirmation

[0772] The user checks the displayed suggestions and issues a command such as "Book this hotel." The device again converts the speech into text and sends it to the server. The server then reserves the specified hotel and transportation based on the user's instructions. Once the reservation is complete, a notification is sent to the device and displayed to the user.

[0773] Specific examples

[0774] As a specific example, if a user says, "Concierge, I'd like to travel next week," the server performs the following tasks:

[0775] 1. User intent analysis: Extract travel destination, departure date, budget, etc.

[0776] 2. Personalization: Prioritize your preferred accommodation and transportation options based on past data.

[0777] 3. Information gathering: Collecting the best options from multiple travel sites and transportation APIs.

[0778] 4. Displaying results: Travel plans, accommodation, transportation, weather forecast, and a list of necessary equipment are displayed on the user interface.

[0779] 5. Reservation: After user confirmation, the reservation is actually made.

[0780] In this way, the system allows even seniors to easily plan and decide on trips without having to perform complicated operations.

[0781] The processing flow will be explained below.

[0782] Step 1:

[0783] The user launches a dedicated application on their smartphone and issues a voice command such as "I want to go on a trip."

[0784] Step 2:

[0785] The terminal's voice recognition module receives the user's voice commands and converts them into text data.

[0786] Step 3:

[0787] The terminal transmits the converted text data to the server.

[0788] Step 4:

[0789] The server analyzes the received text data using a natural language processing (NLP) module to extract the user's purpose (travel plans).

[0790] Step 5:

[0791] Based on the purpose, the server generates the necessary tasks (reserving a hotel, arranging transportation, checking the weather forecast, listing the necessary equipment).

[0792] Step 6:

[0793] The server references the user's past behavioral patterns and preference data to optimize the generated tasks, for example prioritizing the type of accommodation the user prefers based on their past travel history.

[0794] Step 7:

[0795] The server uses external APIs to collect the necessary information from the Internet. Specifically, it obtains hotel reservation options from travel site APIs, obtains optimal travel methods from transportation APIs, obtains weather information for the travel period from weather forecast APIs, and generates a list of necessary equipment.

[0796] Step 8:

[0797] The server consolidates the collected information and organizes it into a single data package.

[0798] Step 9:

[0799] The server transmits the consolidated data package to the terminal.

[0800] Step 10:

[0801] The device analyzes the transmitted data package and displays it on the user interface, for example displaying a confirmation message saying "Here is the proposed travel plan. What do you want to do?"

[0802] Step 11:

[0803] The user checks the displayed information and then says aloud, "Book this hotel."

[0804] Step 12:

[0805] The device converts the user's voice commands into text and sends it back to the server.

[0806] Step 13:

[0807] The server calls the booking API to reserve the specified hotel and transportation based on the user's instructions.

[0808] Step 14:

[0809] The server notifies the terminal of the reservation result (success / failure).

[0810] Step 15:

[0811] The device will notify the user that the booking is complete and save the trip details.

[0812] Example 1

[0813] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0814] Currently, for seniors to effectively use smartphones and the internet, complex operations and information gathering are required, which presents a major barrier. In particular, tasks related to planning and booking trips are complicated, and the lack of consistent support reduces usability. For this reason, there is a demand for systems that allow seniors to easily use smartphones and the internet.

[0815] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0816] In this invention, the server includes means for converting a user's voice commands into text data, means for analyzing the user's intentions based on the text data and generating a task, means for optimizing the generated task by referring to the user's past behavioral patterns and preference data, means for collecting external information from the Internet, means for integrating the collected information and presenting it to the user, means for performing actions such as making a reservation based on the presented information, means for providing multiple options based on the external data collected via the Internet, and means for obtaining confirmations and instructions from the user using voice recognition. This enables seniors to easily plan and book trips using their smartphones without requiring complex operations.

[0817] "Voice command" refers to an instruction or request input by a user through speech.

[0818] "Text data" refers to data obtained by converting voice commands into text information.

[0819] "User intent" refers to the purpose or request that the user wants to convey through a voice command.

[0820] A "task" refers to a specific process or action that the system should perform based on the user's intentions.

[0821] "Past behavioral patterns" refers to the history of operations and selections that the user has previously made.

[0822] "Preference Data" refers to information about a user's past preferences and selection tendencies.

[0823] "Optimization" refers to adjusting and modifying the generated tasks and suggestions to best suit the user based on the user's requirements, past behavioral patterns, and preferences.

[0824] "External information" refers to data obtained from external sources such as the Internet.

[0825] "Information integration" refers to bringing together collected external information and user data and processing it in a consistent manner.

[0826] An "action" refers to a specific task or operation that is performed through the execution of a task.

[0827] "External data collected via the Internet" refers to data collected from different sources on the Internet.

[0828] "Choices" refers to multiple alternatives or options offered to a user.

[0829] "Speech recognition" refers to the technology and process of converting speech into text data.

[0830] "Confirmation or instruction" refers to voice input made by the user to confirm the system's operation.

[0831] This invention provides an autonomous AI agent called "Concierge" that helps seniors effectively use smartphones and the Internet. Specific embodiments for implementing this invention are described below.

[0832] The user uses a dedicated application on their smartphone. This application uses a voice recognition module (e.g., Google Speech-to-Text API) to convert the user's voice commands into text data. This text data is then sent from the smartphone (device) to the server.

[0833] The server analyzes the received text data using a natural language processing (NLP) module (e.g., OpenAI's GPT-3), extracts the user's intent (e.g., planning a trip), and generates the necessary tasks (e.g., booking a hotel, arranging transportation, checking the weather forecast, and listing the necessary equipment).

[0834] The server then refers to the user's past behavioral patterns and preferences, which are stored in the server's database, and optimizes the generated task by taking into account the user's past travel history. For example, it may prioritize the type of accommodation the user has preferred in the past.

[0835] In addition, the server uses external APIs (e.g., Booking.com API, Google Maps API, Weather.com API) to collect necessary information from the Internet, obtain hotel reservation options based on the travel dates, suggest the best means of transportation, obtain weather forecasts for the travel period, generate a list of necessary equipment, and provide links to online shopping.

[0836] The collected information is consolidated on the server and sent as a data package to the device, which then displays this data on a user interface and asks the user for confirmation, such as "Is this plan OK?"

[0837] The user checks the displayed suggestions and then re-enters a command, such as "Book this hotel." The device converts the speech into text and sends it to the server. The server then reserves the specified hotel and transportation based on the user's instructions. Once the reservation is complete, a notification is sent to the device and displayed to the user.

[0838] Specific examples

[0839] For example, if a user says, "Concierge, I would like to travel next week," the server performs the following tasks:

[0840] 1. Analyzing user intent: Extract travel destination, departure date, budget, etc.

[0841] 2. Personalization: Prioritize your preferred accommodation and transportation options based on past data.

[0842] 3. Information gathering: Collecting the best options from multiple travel sites and transportation APIs.

[0843] 4. Displaying results: The user interface displays the itinerary, accommodation, transportation, weather forecast, and list of necessary equipment.

[0844] 5. Reservation: After user confirmation, the reservation is actually made.

[0845] An example of a prompt sentence is, "A concierge AI that supports travel planning for seniors through voice input would generate a travel plan from the user's voice input and explain the process leading up to the reservation."

[0846] As described above, this invention allows even seniors to easily plan and book trips without having to perform complicated operations.

[0847] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0848] Step 1:

[0849] A user launches a dedicated application on their smartphone and verbally enters a command such as "I want to go on a trip." The device uses a voice recognition module (for example, the Google Speech-to-Text API) to convert this voice command into text data. Specifically, the application receives the voice input and converts it into text. The input is a voice command, and the output is text data.

[0850] Step 2:

[0851] Text data is sent to the server. The server analyzes the received text data using a natural language processing (NLP) module (e.g., OpenAI's GPT-3) to extract the user's intent (e.g., planning a trip). The input is text data, and the output is data indicating the user's intent.

[0852] Step 3:

[0853] Based on the analysis results, the server generates the necessary tasks (e.g., reserving a hotel, arranging transportation, checking the weather forecast, listing necessary equipment). Specifically, the server uses a task generation module to list appropriate tasks based on the user's intent. The input is the user's intent data, and the output is a list of generated tasks.

[0854] Step 4:

[0855] The server optimizes the generated tasks by referencing the user's past behavioral patterns and preference data. For example, it retrieves the user's travel history from a historical database and considers the type of accommodation they preferred in the past. The input is a task list and the user's past data, and the output is an optimized task list.

[0856] Step 5:

[0857] The server uses external APIs (e.g., Booking.com API, Google Maps API, Weather.com API) to collect necessary information from the Internet. This includes obtaining hotel reservation options based on the travel dates, suggesting the best means of transportation, obtaining weather forecasts for the travel period, and generating a list of necessary equipment. The input is the optimized task list, and the output is the collected information data.

[0858] Step 6:

[0859] The collected information is integrated by the server and sent to the terminal as a data package. The terminal displays this data package on a user interface and asks the user for confirmation. Specifically, the terminal receives the data package and visualizes and displays it. The input is the collected information data, and the output is the display data on the user interface.

[0860] Step 7:

[0861] The user checks the displayed suggestions and enters a command by voice, such as "Book this hotel." The device again converts the voice into text and sends it to the server. Specifically, the device receives voice input, converts it into text, and sends it. The input is a voice command, and the output is text data.

[0862] Step 8:

[0863] The server reserves the specified hotel and transportation based on the user's instructions. Once the reservation is complete, a notification is sent to the terminal and displayed to the user. Specifically, the server calls the reservation API, confirms the reservation, and then sends notification data to the terminal. The input is reservation instruction data, and the output is reservation completion notification data.

[0864] (Application example 1)

[0865] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0866] In today's world, seniors face many barriers when using the internet and smartphones. These include complex operations and security risks. Phishing scams and security authentication issues are particularly prevalent when it comes to online transactions, making it difficult for seniors to conduct transactions safely and securely. Therefore, there is a demand for a system that can assist users in conducting transactions online easily and safely.

[0867] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0868] In this invention, the server includes: means for converting a user's voice command into text data; means for analyzing the user's intention based on the text data and generating a task; means for referencing the user's past behavioral patterns and preference data and optimizing the generated task; means for collecting external information from the Internet; means for integrating the collected information and presenting it to the user; means for performing actions such as making a reservation based on the presented information; means for instructing the user to support safe transactions by voice command when conducting a transaction; means for converting the voice command into text data and analyzing the intention; means for collecting security information related to the transaction from an external API and notifying the user of the information; and means for presenting the user with a transaction reliability assessment and security status based on the collected security information. This makes it possible for seniors to conduct transactions over the Internet easily and safely.

[0869] "User voice command" refers to an instruction or request given by a user through a microphone by voice.

[0870] "Text data" refers to data that has been converted from voice commands into text information using voice recognition technology.

[0871] "User intent" refers to the goal or desire the user ultimately aims to achieve based on voice commands or text data.

[0872] A "task" refers to a specific action item that the system automatically generates based on the user's intentions.

[0873] "User's past behavioral patterns" refers to the operation history and behavior history of the user who previously used the system.

[0874] "Preference Data" refers to data regarding a user's tastes and preferences.

[0875] "External information" refers to all information obtained from the Internet or external databases.

[0876] "Presented information" refers to information that integrates collected external information and is displayed in a format that is easy for the user to understand.

[0877] "Actions such as reservations" refers to specific actions such as reservations and procedures that the system automatically performs based on the information confirmed by the user.

[0878] "Security Information" refers to information regarding the reliability rating and security status of a business partner's site or service.

[0879] "External API" refers to a program interface for connecting with other web services or databases.

[0880] "Trustworthiness rating" refers to the criteria and data used to evaluate how trustworthy a service or site is.

[0881] "Security status" refers to whether the site or service is currently safe to use.

[0882] This invention provides an autonomous AI agent system that helps seniors use the Internet safely, particularly by making online transactions easier and more secure.

[0883] The server starts processing when the user inputs a voice command via a smartphone, smart glasses, or head-mounted display. First, it uses a voice recognition module to convert the user's voice command into text data. Next, it uses a natural language processing (NLP) module to analyze the converted text data and extract the user's intent. For example, it recognizes a command such as "Support this transaction" and analyzes that intent.

[0884] Based on the analysis results, the system generates tasks that are in line with the user's intentions. During this task generation stage, the system references the user's past behavioral patterns and preferences to optimize the generated tasks. For example, it adjusts the level of alerts and warnings based on past transaction history and the security notification history the user has received.

[0885] In addition, the server collects external information from the Internet. Specifically, it uses external APIs to obtain security information related to the sites and services of its business partners. This information includes the site's reliability rating and current security status. For example, this includes the expiration date of the SSL certificate and whether the site has been reported as a phishing site.

[0886] The collected information is integrated and presented to the user. The user interface of the terminal displays the reliability rating and security status of the transaction site, including an alert asking, "Is this site safe?" The user can check the displayed information and issue voice commands such as "Make a reservation" or "Continue the transaction" as needed. The server then makes the specific reservation or transaction based on the user's instructions. When the reservation or transaction is completed, a notification is sent to the terminal and displayed to the user.

[0887] For example, if a user says "Support this transaction," the server performs the following steps: First, it checks the transaction partner's site using an external API and collects the SSL certificate expiration date and phishing site report status. It then analyzes this information and notifies the user, "This site is safe. Do you want to continue?", requesting user confirmation.

[0888] An example of a prompt would be:

[0889] "Enter your voice command: Say 'Support this transaction.'"

[0890] In this way, the system of the present invention is a system that provides multifaceted support to seniors so that they can conduct Internet transactions with peace of mind.

[0891] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0892] Step 1:

[0893] The user inputs a voice command. Specifically, the user speaks into a smartphone, smart glasses, or head-mounted display, saying, "Support this transaction." The input is voice data, which is then captured by the terminal.

[0894] Step 2:

[0895] The device converts the voice into text data. Specifically, it uses a speech recognition module on the device (e.g., Google Speech Recognition API) to convert the input voice data into text data in character format. The input in this step is the voice data obtained in step 1, and the output is the converted text data.

[0896] Step 3:

[0897] The server analyzes the user's intent based on the text data. Specifically, it uses a natural language processing (NLP) module to extract the user's intent, "support this transaction," from the text data. The input in this step is the text data obtained in step 2, and the output is the analyzed intent data.

[0898] Step 4:

[0899] The server references the user's past behavioral patterns and preference data to optimize the generated tasks. Specifically, it references the user's past transaction history and alert history from the database and uses this information to prioritize tasks. The inputs in this step are the intent data obtained in step 3 and the user data in the database, and the output is optimized task data.

[0900] Step 5:

[0901] The server collects external information from the Internet. Specifically, it uses an external API (e.g., a security evaluation API) to obtain reliability and security information about partner sites and services. The input to this step is the task data obtained in step 4, and the output is the collected external information.

[0902] Step 6:

[0903] The server consolidates the collected information and presents it to the user. Specifically, it compiles the collected security information (e.g., SSL certificate expiration date, phishing site report status, etc.) and displays it on the device's user interface in a format that is easy for the user to understand. The input in this step is the external information obtained in step 5, and the output is the presented information.

[0904] Step 7:

[0905] The user confirms the presented information and issues a voice command for the next action, such as "continue the transaction" or "make a reservation on this site." The user confirms the presented information in step 6 and then issues a voice command.

[0906] Step 8:

[0907] The device again converts the voice command into text data and sends it to the server. Specifically, it again uses a voice recognition module to convert the voice into text and sends it to the server. The input in this step is the user voice command from step 7, and the output is text data.

[0908] Step 9:

[0909] The server executes the specific reservation or transaction based on the user's instructions. Specifically, it calls the appropriate external API to complete the reservation procedure and notifies the user of the results. The input in this step is the text data from step 8, and the output is the result of the action taken and a notification of it.

[0910] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0911] This invention combines an autonomous AI agent called "Concierge" that helps seniors use smartphones and the Internet more effectively with an emotion engine that recognizes the user's emotions. An embodiment of this invention is described below.

[0912] Receiving User Input

[0913] The user launches a dedicated application on their smartphone and enters a command by voice, such as "I want to go on a trip." The device uses a voice recognition module to convert this voice command into text data and send it to the server.

[0914] User Intention Analysis and Task Generation

[0915] The server analyzes the received text data using a natural language processing (NLP) module to extract the user's purpose (travel planning). Based on the analysis results, it generates the necessary tasks (e.g., booking a hotel, arranging transportation, checking the weather forecast, and listing necessary equipment).

[0916] User emotion recognition and adjustment

[0917] The server uses an emotion engine to analyze the user's emotional state from their voice commands. Based on this analysis, it can adjust the tasks it generates. For example, if the user is tired, it can suggest a more relaxing plan.

[0918] Personalization and Learning

[0919] The server references the user's past behavioral patterns and preferences to optimize the generated tasks for the user. The emotion engine also records the user's past emotional data and uses it to optimize future tasks. This enables personalization that takes the user's emotional state into account.

[0920] Information gathering and arrangements

[0921] The server uses external APIs to collect necessary information from the Internet. It obtains hotel reservation options through travel site APIs, and suggests optimal travel methods using transportation APIs. It also obtains weather information for the travel period using weather forecast APIs. Similarly, it generates a list of necessary equipment and provides it with online shopping links.

[0922] Displaying results and user confirmation

[0923] The collected information is consolidated on the server and sent as a data package to the device. The device displays this data on a user interface and asks the user for confirmation, such as a message like "Is this plan OK?"

[0924] Booking and confirmation

[0925] The user checks the displayed suggestions and issues a command such as "Book this hotel." The device again converts the speech into text and sends it to the server. Based on the user's instructions, the server calls the reservation API to reserve the specified hotel and transportation. Once the reservation is complete, a notification is sent to the device and displayed to the user.

[0926] Specific examples

[0927] As a specific example, if a user says, "I'd like you to suggest a travel plan that will allow me to relax a little today," the server will perform the following tasks:

[0928] 1. User intent analysis: Extract travel destination, departure date, budget, etc.

[0929] 2. Emotion recognition: Analyze the user's emotional state, such as wanting to relax, from their voice.

[0930] 3. Personalization: Prioritize relaxing accommodation and transportation options based on past data.

[0931] 4. Information gathering: Collecting the best options from multiple travel sites and transportation APIs.

[0932] 5. Displaying results: Travel plans, accommodation, transportation, weather forecast, and a list of necessary equipment are displayed on the user interface.

[0933] 6. Reservation: After user confirmation, the reservation is actually made.

[0934] In this way, by combining the emotion engine, the system allows even seniors to make optimal travel plans and decisions based on their emotional state without having to perform complicated operations.

[0935] The processing flow will be explained below.

[0936] Step 1:

[0937] The user launches a dedicated application on their smartphone and issues a voice command such as, "Please suggest a travel plan that is a little more relaxing today."

[0938] Step 2:

[0939] The terminal's voice recognition module receives the user's voice commands and converts them into text data.

[0940] Step 3:

[0941] The terminal transmits the converted text data to the server.

[0942] Step 4:

[0943] The server analyzes the received text data using a natural language processing (NLP) module to extract the user's intent (suggestions for a relaxing travel plan).

[0944] Step 5:

[0945] The server uses an emotion engine to analyze the user's emotional state (e.g., a desire to relax) from their voice command, and generates tasks (e.g., hotel reservations, transportation arrangements, weather forecasts, and a list of necessary equipment) based on this emotional state.

[0946] Step 6:

[0947] The server optimizes the generated tasks by referring to the user's past behavioral patterns, preference data, and emotion recognition results. Specifically, it prioritizes data on relaxation spots and accommodations visited in the past.

[0948] Step 7:

[0949] The server uses external APIs to collect necessary information from the Internet. It obtains relaxing hotel reservation options through travel site APIs, suggests optimal travel methods using transportation APIs, and uses weather forecast APIs to obtain weather information for the travel period and generate a list of necessary equipment.

[0950] Step 8:

[0951] The server consolidates the collected information and organizes it into a single data package.

[0952] Step 9:

[0953] The server transmits the consolidated data package to the terminal.

[0954] Step 10:

[0955] The device analyzes the transmitted data package and displays it on the user interface, for example displaying a confirmation message saying, "Here are our suggested relaxing travel plans. What do you want to do?"

[0956] Step 11:

[0957] The user checks the displayed information and then says aloud, "Book this hotel."

[0958] Step 12:

[0959] The device converts the user's voice commands into text and sends it back to the server.

[0960] Step 13:

[0961] The server calls the booking API to reserve the specified hotel and transportation based on the user's instructions.

[0962] Step 14:

[0963] The server notifies the terminal of the reservation result (success / failure).

[0964] Step 15:

[0965] The device will notify the user that the booking is complete and save the trip details.

[0966] Example 2

[0967] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0968] It is often difficult for older adults to effectively use smartphones and the internet. Furthermore, tasks such as planning and booking trips are complex, especially when it comes to presenting optimal plans that take into account the user's emotional state. This calls for systems with emotion recognition and personalization capabilities.

[0969] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for converting a user's voice command into text data, means for analyzing the user's intention based on the text data and generating a task, means for optimizing the generated task by referring to the user's past behavioral patterns and preference data, means for analyzing the user's emotional state and adjusting the task, means for collecting external information, means for integrating the collected information and presenting it to the user, and means for performing actions such as making a reservation based on the presented information. This makes it possible to generate and execute an optimal travel plan that takes the user's emotional state into consideration.

[0970] "Voice command" refers to instructions or requests that a user verbally inputs into a smartphone or other device.

[0971] "Text data" refers to text information converted from voice commands using voice recognition technology.

[0972] "Intent analysis" refers to the process of understanding a user's goals and requests from voice commands and generating specific tasks based on that content.

[0973] "Task generation" refers to the process of determining specific tasks and procedures based on the results of intent analysis.

[0974] "Past behavioral patterns" refers to the history of actions and choices made by the user in the past.

[0975] "Preference Data" refers to information relating to a user's personal tastes and preferences.

[0976] "Task optimization" refers to the process of adjusting and improving a task to best suit the user by referring to data on the user's past behavioral patterns and preferences.

[0977] "Emotional state" refers to the emotion or mood of the user when entering a voice command.

[0978] "Means for analyzing emotional state" refers to technology that reads and evaluates emotional nuances from a user's voice or text data.

[0979] "External information" refers to information such as travel information, accommodation information, transportation options, and weather forecasts obtained via the Internet.

[0980] "Means of collecting external information" refers to technology that uses external interfaces and APIs to obtain necessary information from the Internet.

[0981] "Information synthesis" refers to the process of bringing together data collected from multiple sources into a single, unified format.

[0982] "Presentation means" refers to the user interface and display technology used to present the integrated information to the user.

[0983] "Means for executing actions such as reservations" refers to technology that actually carries out reservation procedures or other actions based on the user's confirmation or instructions.

[0984] This invention relates to an autonomous AI agent called "Concierge" that helps seniors use smartphones and the internet more effectively, and is combined with an emotion engine that recognizes the user's emotions. This system implements a series of processes: it receives a user's voice command, analyzes the user's intention, generates a task, optimizes it, and then executes it.

[0985] First, the user launches a dedicated application installed on their smartphone and enters a command by voice, such as "I want to go on a trip." At this time, the device uses the Google Cloud Speech-to-Text API to convert the user's voice command into text data, which is then sent to a server via the Internet.

[0986] The server analyzes the received text data using the Google Cloud Natural Language API and extracts the user's intent. For example, a voice command such as "I want to go on a trip" generates tasks such as selecting a travel destination, booking accommodation, and arranging transportation.

[0987] The server then uses Microsoft Azure Text Analytics for Cognitive Services to analyze the user's emotional state. For example, if the user's intent is "I want to relax," the server can adjust the task to provide a relaxing travel plan based on the emotion recognition results.

[0988] The server then uses Amazon Personalize to optimize the generated tasks based on past behavioral data and user preference patterns. For example, if a user has previously booked a resort hotel, the server will prioritize presenting similar options this time.

[0989] Regarding information gathering, the server uses external interfaces such as Expedia API, Google Maps API, OpenWeatherMap API, etc. to gather the necessary information, such as hotel reservation options, transportation options, weather forecasts, and a list of necessary amenities.

[0990] The collected information is integrated on the server and displayed on a user interface, allowing users to check travel plans, accommodations, transportation options, weather forecasts, lists of necessary supplies, etc. all in one place. For example, if a dedicated application is built with React Native, questions such as "Is this plan okay?" will be displayed on the user interface.

[0991] Finally, the user checks the displayed plan and enters a command such as "Book this hotel" by voice. The device again converts the voice to text data and sends it to the server. The server then calls the Booking.com API, makes the actual reservation, and sends a notification to the device. The user can then complete the entire process by receiving a notification that the reservation has been completed.

[0992] For example, if a user says, "I want some suggestions for relaxing travel destinations today," the system will do the following:

[0993] 1. Convert user voice input into text data

[0994] 2. Analyzing intent from text data and generating travel plans for relaxation

[0995] 3. Emotion recognition to recommend places suitable for relaxation

[0996] 4. Provide optimal plans based on past behavioral data

[0997] 5. Collect the necessary information, consolidate the plan, and display it in the user interface

[0998] 6. After user confirmation, the reservation is actually made

[0999] The system is designed to help seniors navigate complex procedures with ease and can provide a personalized travel experience that takes into account the user's emotions and preferences.

[1000] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1001] Step 1: Receiving User Input

[1002] The user launches the dedicated application and speaks a command such as "I want to go on a trip." The device uses the Google Cloud Speech-to-Text API to convert the voice into text data. This API outputs the voice as text data. The device then sends the converted text data to the server.

[1003] Input: User's voice command

[1004] Data processing: Converting speech to text

[1005] Output: Text data

[1006] Step 2: User intent analysis and task generation

[1007] The server receives the text data sent from the device and analyzes its intent using the Google Cloud Natural Language API. This analysis extracts the user's purpose (e.g., planning a trip). Based on the results, it generates tasks (reserving a hotel, arranging transportation, checking the weather forecast, and listing necessary equipment).

[1008] Input: Text data

[1009] Data processing: Intention analysis and task generation

[1010] Output: Analysis results and task list

[1011] Step 3: Recognizing and adjusting user emotions

[1012] The server uses Microsoft Azure Text Analytics to analyze the user's emotional state from the text data. Based on the obtained emotional state, the content of the generated task is adjusted. For example, if the user feels like "I want to relax," the server generates a plan that allows for more relaxation.

[1013] Input: Text data

[1014] Data processing: Emotional state analysis and task adjustment

[1015] Output: Reconciled task list

[1016] Step 4: Personalize and learn

[1017] The server uses Amazon Personalize to optimize the task by referencing the user's past behavioral patterns and preference data. This optimization suggests a plan based on the user's past tastes and preferences. The emotion engine also records the user's emotional data and uses it for future optimization.

[1018] Input: Adjusted task list and past activity data

[1019] Data Transformation: Personalization and Learning

[1020] Output: Optimized task list

[1021] Step 5: Information gathering and arrangements

[1022] The server uses external APIs (e.g., Expedia API, Google Maps API, OpenWeatherMap API) to collect the necessary information. The collected data includes hotel reservation options, transportation options, weather forecasts, and a list of necessary equipment. Based on this information, a detailed travel plan is created.

[1023] Input: Optimized task list

[1024] Data processing: collecting and integrating external information

[1025] Output: Consolidated information

[1026] Step 6: Displaying the results and user confirmation

[1027] The server sends the collected information to the device, which then displays it in the user interface. For example, if the dedicated application is built with React Native, it will display a message asking, "Is this plan OK?"

[1028] Input: Integrated information

[1029] Data processing: Display of information

[1030] Output: Information displayed in the user interface

[1031] Step 7: Booking and Confirmation

[1032] The user enters a confirmation command by voice, such as "Book this hotel." The device again converts the voice into text data and sends it to the server. The server uses the Booking.com API to reserve the specified hotel and transportation. After the reservation is complete, a notification is sent to the device and displayed to the user.

[1033] Input: Text data of the confirmation command

[1034] Data processing: Reservation procedure execution

[1035] Output: Notification of reservation completion

[1036] This allows the system to automatically handle everything from user voice input to travel planning and arrangements, generating and executing optimal plans that take emotions into consideration.

[1037] (Application example 2)

[1038] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1039] Seniors face challenges in effectively using smartphones and the internet, particularly the complexity and difficulty of voice input and internet searches. Furthermore, existing systems lack the ability to provide personalized services that take into account the user's emotions and current location. In particular, in-store shopping support lacks a means for users to quickly and efficiently find the products they are looking for, and solutions to this issue are needed.

[1040] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1041] In this invention, the server includes: means for converting a user's voice command into text data; means for analyzing the user's intention and generating a task; means for analyzing the user's emotional state; means for optimizing the generated task based on the user's emotional state; means for further optimizing the generated task by referring to the user's past behavioral patterns and preference data; means for collecting external information from the Internet; means for integrating the collected information and presenting it on a user interface; means for performing actions such as making a reservation based on the presented information; means for identifying the location of a product in a store using the user's current location information; and means for presenting the identified product location to the user. This enables seniors to efficiently shop in physical stores via their smartphones and receive personalized support that takes into account their emotions and location information.

[1042] A "user's voice command" is a voice input by a user to give instructions to the system through voice.

[1043] "Text data" is digital data that converts a voice command into a string of characters.

[1044] "Means for analyzing intent" is a function that analyzes the user's purpose and requests from text data.

[1045] A "task" is a series of specific actions or procedures generated based on a user's intentions.

[1046] "Emotional state" refers to the psychological state of the user that is analyzed from their voice and facial expressions.

[1047] "Optimization means" is a function that adjusts the generated tasks and presented information to suit the user's condition and preferences.

[1048] "Past behavioral patterns" are data on actions and choices that a user has previously made.

[1049] "Preference data" is data that indicates the tendency of a user to prefer specific conditions or options.

[1050] "External information" is additional data obtained from the Internet or other external sources.

[1051] "Means of collection" refers to APIs and data access procedures for obtaining external information.

[1052] "Means of integration" refers to the ability to bring together collected data into a single system or display format.

[1053] A "user interface" is a display screen and operating procedures that allow a user to interact with a system.

[1054] "Means for performing actions such as reservations" refers to a function that performs specific operations (e.g., hotel reservations, product purchases) based on user instructions.

[1055] "Current location information" is digital location data that indicates the specific location where a user is currently located.

[1056] A "means for identifying product location" is a technology for determining where a specific product is located within a physical store.

[1057] The "means for presenting the product location" is a function for visually or audibly guiding the user to the location of the identified product.

[1058] This invention is a system that allows users to efficiently shop in physical stores, and uses the following main hardware and software to perform specific data processing and data calculations.

[1059] Hardware and Software Configuration

[1060] Smartphone: A device that acts as an interface between the user and the system.

[1061] Speech Recognition Module: Used to convert user voice input into text data (e.g., speech recognition service).

[1062] Natural Language Processing (NLP) modules: Analyzing user intent from text data (e.g., natural language processing libraries).

[1063] Sentiment analysis engine: Analyzes the emotional state from the user's voice (e.g., emotion analysis service).

[1064] Location services: Obtaining the user's current location (e.g., location services).

[1065] External APIs: Used to collect external information (e.g. online databases, web APIs).

[1066] Database: Stores data about users' past behavior patterns and preferences (e.g., data storage).

[1067] User Interface (UI): The interface that displays collected information and tasks to the user and allows them to perform operations.

[1068] Processing Details

[1069] 1. Receiving user input: The user launches a dedicated application on their smartphone and provides a command by voice, such as "I want to buy toilet paper." The smartphone's voice recognition module converts this voice command into text data.

[1070] 2. User intent analysis and task generation: The server receives the text data, analyzes it with a natural language processing (NLP) module to extract the user's intent (e.g., buying toilet paper), and generates the required task.

[1071] 3. User emotion recognition and task adjustment: The server uses an emotion analysis engine to analyze the user's emotional state (e.g., fatigue) from their voice. Based on the analysis results, the generated task (e.g., suggesting a rest area in a store) is adjusted accordingly.

[1072] 4. Personalization and Learning: The server refers to the user's past behavioral patterns and preferences to optimize the generated tasks for the user. The emotion engine also records past emotion data and uses it to optimize future tasks.

[1073] 5. Information collection and arrangement: The server uses external APIs to collect and integrate necessary information from the Internet (e.g., product locations within the store, information about rest areas).

[1074] 6. Displaying the results and confirming with the user: The collected information is consolidated and sent to a user interface, which displays a message such as "Toilet paper is on the fifth shelf. Also, if you need a break, there is a cafe nearby."

[1075] Specific examples

[1076] As a specific example, consider the process when a user says, "I want to buy toilet paper." First, the voice input is converted into text by the speech recognition module, and the intent is analyzed by the NLP module. Next, the emotion analysis engine determines the user's emotional state, and generates and optimizes corresponding tasks. Information on the location of products in the store and information on rest areas is collected using an external API, and this information is integrated and presented to the user.

[1077] Prompt Sentence Examples

[1078] An example of a prompt to input to a generative AI model is as follows:

[1079] "Design an application that helps users efficiently find the products they need in a physical store. Users input commands via voice, such as "I want milk." An emotion engine is used to recognize the user's state and suggest rest areas if they are tired. The speech is converted into text using a speech recognition module, and a natural language processing module is used to analyze intent, and an emotion analysis engine is used to recognize emotions. Location services are used to identify the location of products, and user preferences are recorded in a database."

[1080] As described above, by providing personalized support that incorporates emotional state and location information, seniors can have an efficient and comfortable shopping experience using their smartphones.

[1081] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1082] Step 1:

[1083] Receiving User Input

[1084] The user launches a dedicated application on their smartphone and speaks, "I want to buy toilet paper." The device's voice recognition module converts this voice command into text data. Specifically, the voice recognition software analyzes the voice waveform and converts it into character string data. At this point, the input is voice data, and the output is text data.

[1085] Step 2:

[1086] User Intention Analysis and Task Generation

[1087] The server receives the text data and analyzes it using a natural language processing (NLP) module. By performing group data and contextual analysis, the system extracts the user's intent (e.g., buying toilet paper). Specifically, it identifies keywords and patterns in the text and generates tasks based on them. The input is text data, and the output is the user's intent and the corresponding task.

[1088] Step 3:

[1089] User Emotion Recognition and Task Adjustment

[1090] The server uses an emotion analysis engine to determine the user's emotion from their voice. It analyzes the tone, speed, and intonation of the voice to evaluate the user's emotional state, such as whether they are tired. Specifically, it extracts voice features and inputs them into an emotion model. This input data is the voice features, and the output is the emotion recognition result. The generated task is then readjusted based on the determination result.

[1091] Step 4:

[1092] Personalization and Learning

[1093] The server further optimizes the task by referencing data on past behavioral patterns and user preferences. It retrieves the user's past choices and purchase history from the database and uses that information to suggest optimal products and services. The input data is past behavioral data, and the output is optimized tasks and recommended products.

[1094] Step 5:

[1095] Information gathering and arrangements

[1096] The server uses external APIs to collect necessary information from the Internet. For example, it obtains information about the location of products in a store or information about nearby rest areas. Specifically, it sends requests to each API and integrates the obtained information. The input data is the response from the external API, and the output is the integrated information.

[1097] Step 6:

[1098] Displaying results and user confirmation

[1099] The server consolidates the collected information and sends it to the user interface. Specifically, it organizes the information using UI components to display the collected data in a visually easy-to-read format. The input data is the consolidated information, and the output is what is displayed on the user interface. The user confirms this information and then voice-inputs, for example, "I want to purchase this product."

[1100] Step 7:

[1101] Booking and confirmation

[1102] Once the server receives confirmation from the user, it executes the reservation. For example, it uses an online shopping API to purchase a product. Specifically, it issues an API call to complete the reservation or purchase. The input data is the user's confirmation instructions, and the output is a confirmation notification of the reservation or purchase. A success notification is displayed on the user interface to inform the user of the result.

[1103] As described above, by designing detailed processing content and specific operations at each step, seniors can shop comfortably and efficiently.

[1104] 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.

[1105] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. 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 voice, text data indicating text, and image data indicating an image is also input. 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.

[1106] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1107] [Fourth embodiment]

[1108] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1109] 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.

[1110] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. 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).

[1111] 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.

[1112] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1113] 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 surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1114] 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.

[1115] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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.

[1116] 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.

[1117] 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 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.

[1118] 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.

[1119] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1120] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1121] This invention provides an autonomous AI agent called "Concierge" that helps seniors use smartphones and the Internet more effectively, and an embodiment of this invention is described below.

[1122] Receiving User Input

[1123] The user launches a dedicated application on their smartphone and enters a command by voice, such as "I want to go on a trip." The device uses a voice recognition module to convert this voice command into text data and send it to the server.

[1124] User Intention Analysis and Task Generation

[1125] The server analyzes the received text data using a natural language processing (NLP) module to extract the user's purpose (travel planning). Based on the analysis results, it generates the necessary tasks (e.g., booking a hotel, arranging transportation, checking the weather forecast, and listing necessary equipment).

[1126] Personalization and Learning

[1127] The server references the user's past behavioral patterns and preferences to optimize the generated tasks for the user, for example, taking into account the type of accommodation the user prefers based on their past travel history.

[1128] Information gathering and arrangements

[1129] The server uses external APIs to collect necessary information from the Internet. It obtains hotel reservation options through travel site APIs, and suggests optimal travel methods using transportation APIs. It also obtains weather information for the travel period using weather forecast APIs. Similarly, it generates a list of necessary equipment and provides it with online shopping links.

[1130] Displaying results and user confirmation

[1131] The collected information is consolidated on the server and sent as a data package to the device. The device displays this data on a user interface and asks the user for confirmation, such as a message like "Is this plan OK?"

[1132] Booking and confirmation

[1133] The user checks the displayed suggestions and issues a command such as "Book this hotel." The device again converts the speech into text and sends it to the server. The server then reserves the specified hotel and transportation based on the user's instructions. Once the reservation is complete, a notification is sent to the device and displayed to the user.

[1134] Specific examples

[1135] As a specific example, if a user says, "Concierge, I'd like to travel next week," the server performs the following tasks:

[1136] 1. User intent analysis: Extract travel destination, departure date, budget, etc.

[1137] 2. Personalization: Prioritize your preferred accommodation and transportation options based on past data.

[1138] 3. Information gathering: Collecting the best options from multiple travel sites and transportation APIs.

[1139] 4. Displaying results: Travel plans, accommodation, transportation, weather forecast, and a list of necessary equipment are displayed on the user interface.

[1140] 5. Reservation: After user confirmation, the reservation is actually made.

[1141] In this way, the system allows even seniors to easily plan and decide on trips without having to perform complicated operations.

[1142] The processing flow will be explained below.

[1143] Step 1:

[1144] The user launches a dedicated application on their smartphone and issues a voice command such as "I want to go on a trip."

[1145] Step 2:

[1146] The terminal's voice recognition module receives the user's voice commands and converts them into text data.

[1147] Step 3:

[1148] The terminal transmits the converted text data to the server.

[1149] Step 4:

[1150] The server analyzes the received text data using a natural language processing (NLP) module to extract the user's purpose (travel plans).

[1151] Step 5:

[1152] Based on the purpose, the server generates the necessary tasks (reserving a hotel, arranging transportation, checking the weather forecast, listing the necessary equipment).

[1153] Step 6:

[1154] The server references the user's past behavioral patterns and preference data to optimize the generated tasks, for example prioritizing the type of accommodation the user prefers based on their past travel history.

[1155] Step 7:

[1156] The server uses external APIs to collect the necessary information from the Internet. Specifically, it obtains hotel reservation options from travel site APIs, obtains optimal travel methods from transportation APIs, obtains weather information for the travel period from weather forecast APIs, and generates a list of necessary equipment.

[1157] Step 8:

[1158] The server consolidates the collected information and organizes it into a single data package.

[1159] Step 9:

[1160] The server transmits the consolidated data package to the terminal.

[1161] Step 10:

[1162] The device analyzes the transmitted data package and displays it on the user interface, for example displaying a confirmation message saying "Here is the proposed travel plan. What do you want to do?"

[1163] Step 11:

[1164] The user checks the displayed information and then says aloud, "Book this hotel."

[1165] Step 12:

[1166] The device converts the user's voice commands into text and sends it back to the server.

[1167] Step 13:

[1168] The server calls the booking API to reserve the specified hotel and transportation based on the user's instructions.

[1169] Step 14:

[1170] The server notifies the terminal of the reservation result (success / failure).

[1171] Step 15:

[1172] The device will notify the user that the booking is complete and save the trip details.

[1173] Example 1

[1174] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1175] Currently, for seniors to effectively use smartphones and the internet, complex operations and information gathering are required, which presents a major barrier. In particular, tasks related to planning and booking trips are complicated, and the lack of consistent support reduces usability. For this reason, there is a demand for systems that allow seniors to easily use smartphones and the internet.

[1176] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1177] In this invention, the server includes means for converting a user's voice commands into text data, means for analyzing the user's intentions based on the text data and generating a task, means for optimizing the generated task by referring to the user's past behavioral patterns and preference data, means for collecting external information from the Internet, means for integrating the collected information and presenting it to the user, means for performing actions such as making a reservation based on the presented information, means for providing multiple options based on the external data collected via the Internet, and means for obtaining confirmations and instructions from the user using voice recognition. This enables seniors to easily plan and book trips using their smartphones without requiring complex operations.

[1178] "Voice command" refers to an instruction or request input by a user through speech.

[1179] "Text data" refers to data obtained by converting voice commands into text information.

[1180] "User intent" refers to the purpose or request that the user wants to convey through a voice command.

[1181] A "task" refers to a specific process or action that the system should perform based on the user's intentions.

[1182] "Past behavioral patterns" refers to the history of operations and selections that the user has previously made.

[1183] "Preference Data" refers to information about a user's past preferences and selection tendencies.

[1184] "Optimization" refers to adjusting and modifying the generated tasks and suggestions to best suit the user based on the user's requirements, past behavioral patterns, and preferences.

[1185] "External information" refers to data obtained from external sources such as the Internet.

[1186] "Information integration" refers to bringing together collected external information and user data and processing it in a consistent manner.

[1187] An "action" refers to a specific task or operation that is performed through the execution of a task.

[1188] "External data collected via the Internet" refers to data collected from different sources on the Internet.

[1189] "Choices" refers to multiple alternatives or options offered to a user.

[1190] "Speech recognition" refers to the technology and process of converting speech into text data.

[1191] "Confirmation or instruction" refers to voice input made by the user to confirm the system's operation.

[1192] This invention provides an autonomous AI agent called "Concierge" that helps seniors effectively use smartphones and the Internet. Specific embodiments for implementing this invention are described below.

[1193] The user uses a dedicated application on their smartphone. This application uses a voice recognition module (e.g., Google Speech-to-Text API) to convert the user's voice commands into text data. This text data is then sent from the smartphone (device) to the server.

[1194] The server analyzes the received text data using a natural language processing (NLP) module (e.g., OpenAI's GPT-3), extracts the user's intent (e.g., planning a trip), and generates the necessary tasks (e.g., booking a hotel, arranging transportation, checking the weather forecast, and listing the necessary equipment).

[1195] The server then refers to the user's past behavioral patterns and preferences, which are stored in the server's database, and optimizes the generated task by taking into account the user's past travel history. For example, it may prioritize the type of accommodation the user has preferred in the past.

[1196] In addition, the server uses external APIs (e.g., Booking.com API, Google Maps API, Weather.com API) to collect necessary information from the Internet, obtain hotel reservation options based on the travel dates, suggest the best means of transportation, obtain weather forecasts for the travel period, generate a list of necessary equipment, and provide links to online shopping.

[1197] The collected information is consolidated on the server and sent as a data package to the device, which then displays this data on a user interface and asks the user for confirmation, such as "Is this plan OK?"

[1198] The user checks the displayed suggestions and then re-enters a command, such as "Book this hotel." The device converts the speech into text and sends it to the server. The server then reserves the specified hotel and transportation based on the user's instructions. Once the reservation is complete, a notification is sent to the device and displayed to the user.

[1199] Specific examples

[1200] For example, if a user says, "Concierge, I would like to travel next week," the server performs the following tasks:

[1201] 1. Analyzing user intent: Extract travel destination, departure date, budget, etc.

[1202] 2. Personalization: Prioritize your preferred accommodation and transportation options based on past data.

[1203] 3. Information gathering: Collecting the best options from multiple travel sites and transportation APIs.

[1204] 4. Displaying results: The user interface displays the itinerary, accommodation, transportation, weather forecast, and list of necessary equipment.

[1205] 5. Reservation: After user confirmation, the reservation is actually made.

[1206] An example of a prompt sentence is, "A concierge AI that supports travel planning for seniors through voice input would generate a travel plan from the user's voice input and explain the process leading up to the reservation."

[1207] As described above, this invention allows even seniors to easily plan and book trips without having to perform complicated operations.

[1208] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1209] Step 1:

[1210] A user launches a dedicated application on their smartphone and verbally enters a command such as "I want to go on a trip." The device uses a voice recognition module (for example, the Google Speech-to-Text API) to convert this voice command into text data. Specifically, the application receives the voice input and converts it into text. The input is a voice command, and the output is text data.

[1211] Step 2:

[1212] Text data is sent to the server. The server analyzes the received text data using a natural language processing (NLP) module (e.g., OpenAI's GPT-3) to extract the user's intent (e.g., planning a trip). The input is text data, and the output is data indicating the user's intent.

[1213] Step 3:

[1214] Based on the analysis results, the server generates the necessary tasks (e.g., reserving a hotel, arranging transportation, checking the weather forecast, listing necessary equipment). Specifically, the server uses a task generation module to list appropriate tasks based on the user's intent. The input is the user's intent data, and the output is a list of generated tasks.

[1215] Step 4:

[1216] The server optimizes the generated tasks by referencing the user's past behavioral patterns and preference data. For example, it retrieves the user's travel history from a historical database and considers the type of accommodation they preferred in the past. The input is a task list and the user's past data, and the output is an optimized task list.

[1217] Step 5:

[1218] The server uses external APIs (e.g., Booking.com API, Google Maps API, Weather.com API) to collect necessary information from the Internet. This includes obtaining hotel reservation options based on the travel dates, suggesting the best means of transportation, obtaining weather forecasts for the travel period, and generating a list of necessary equipment. The input is the optimized task list, and the output is the collected information data.

[1219] Step 6:

[1220] The collected information is integrated by the server and sent to the terminal as a data package. The terminal displays this data package on a user interface and asks the user for confirmation. Specifically, the terminal receives the data package and visualizes and displays it. The input is the collected information data, and the output is the display data on the user interface.

[1221] Step 7:

[1222] The user checks the displayed suggestions and enters a command by voice, such as "Book this hotel." The device again converts the voice into text and sends it to the server. Specifically, the device receives voice input, converts it into text, and sends it. The input is a voice command, and the output is text data.

[1223] Step 8:

[1224] The server reserves the specified hotel and transportation based on the user's instructions. Once the reservation is complete, a notification is sent to the terminal and displayed to the user. Specifically, the server calls the reservation API, confirms the reservation, and then sends notification data to the terminal. The input is reservation instruction data, and the output is reservation completion notification data.

[1225] (Application example 1)

[1226] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1227] In today's world, seniors face many barriers when using the internet and smartphones. These include complex operations and security risks. Phishing scams and security authentication issues are particularly prevalent when it comes to online transactions, making it difficult for seniors to conduct transactions safely and securely. Therefore, there is a demand for a system that can assist users in conducting transactions online easily and safely.

[1228] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1229] In this invention, the server includes: means for converting a user's voice command into text data; means for analyzing the user's intention based on the text data and generating a task; means for referencing the user's past behavioral patterns and preference data and optimizing the generated task; means for collecting external information from the Internet; means for integrating the collected information and presenting it to the user; means for performing actions such as making a reservation based on the presented information; means for instructing the user to support safe transactions by voice command when conducting a transaction; means for converting the voice command into text data and analyzing the intention; means for collecting security information related to the transaction from an external API and notifying the user of the information; and means for presenting the user with a transaction reliability assessment and security status based on the collected security information. This makes it possible for seniors to conduct transactions over the Internet easily and safely.

[1230] "User voice command" refers to an instruction or request given by a user through a microphone by voice.

[1231] "Text data" refers to data that has been converted from voice commands into text information using voice recognition technology.

[1232] "User intent" refers to the goal or desire the user ultimately aims to achieve based on voice commands or text data.

[1233] A "task" refers to a specific action item that the system automatically generates based on the user's intentions.

[1234] "User's past behavioral patterns" refers to the operation history and behavior history of the user who previously used the system.

[1235] "Preference Data" refers to data regarding a user's tastes and preferences.

[1236] "External information" refers to all information obtained from the Internet or external databases.

[1237] "Presented information" refers to information that integrates collected external information and is displayed in a format that is easy for the user to understand.

[1238] "Actions such as reservations" refers to specific actions such as reservations and procedures that the system automatically performs based on the information confirmed by the user.

[1239] "Security Information" refers to information regarding the reliability rating and security status of a business partner's site or service.

[1240] "External API" refers to a program interface for connecting with other web services or databases.

[1241] "Trustworthiness rating" refers to the criteria and data used to evaluate how trustworthy a service or site is.

[1242] "Security status" refers to whether the site or service is currently safe to use.

[1243] This invention provides an autonomous AI agent system that helps seniors use the Internet safely, particularly by making online transactions easier and more secure.

[1244] The server starts processing when the user inputs a voice command via a smartphone, smart glasses, or head-mounted display. First, it uses a voice recognition module to convert the user's voice command into text data. Next, it uses a natural language processing (NLP) module to analyze the converted text data and extract the user's intent. For example, it recognizes a command such as "Support this transaction" and analyzes that intent.

[1245] Based on the analysis results, the system generates tasks that are in line with the user's intentions. During this task generation stage, the system references the user's past behavioral patterns and preferences to optimize the generated tasks. For example, it adjusts the level of alerts and warnings based on past transaction history and the security notification history the user has received.

[1246] In addition, the server collects external information from the Internet. Specifically, it uses external APIs to obtain security information related to the sites and services of its business partners. This information includes the site's reliability rating and current security status. For example, this includes the expiration date of the SSL certificate and whether the site has been reported as a phishing site.

[1247] The collected information is integrated and presented to the user. The user interface of the terminal displays the reliability rating and security status of the transaction site, including an alert asking, "Is this site safe?" The user can check the displayed information and issue voice commands such as "Make a reservation" or "Continue the transaction" as needed. The server then makes the specific reservation or transaction based on the user's instructions. When the reservation or transaction is completed, a notification is sent to the terminal and displayed to the user.

[1248] For example, if a user says "Support this transaction," the server performs the following steps: First, it checks the transaction partner's site using an external API and collects the SSL certificate expiration date and phishing site report status. It then analyzes this information and notifies the user, "This site is safe. Do you want to continue?", requesting user confirmation.

[1249] An example of a prompt would be:

[1250] "Enter your voice command: Say 'Support this transaction.'"

[1251] In this way, the system of the present invention is a system that provides multifaceted support to seniors so that they can conduct Internet transactions with peace of mind.

[1252] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1253] Step 1:

[1254] The user inputs a voice command. Specifically, the user speaks into a smartphone, smart glasses, or head-mounted display, saying, "Support this transaction." The input is voice data, which is then captured by the terminal.

[1255] Step 2:

[1256] The device converts the voice into text data. Specifically, it uses a speech recognition module on the device (e.g., Google Speech Recognition API) to convert the input voice data into text data in character format. The input in this step is the voice data obtained in step 1, and the output is the converted text data.

[1257] Step 3:

[1258] The server analyzes the user's intent based on the text data. Specifically, it uses a natural language processing (NLP) module to extract the user's intent, "support this transaction," from the text data. The input in this step is the text data obtained in step 2, and the output is the analyzed intent data.

[1259] Step 4:

[1260] The server references the user's past behavioral patterns and preference data to optimize the generated tasks. Specifically, it references the user's past transaction history and alert history from the database and uses this information to prioritize tasks. The inputs in this step are the intent data obtained in step 3 and the user data in the database, and the output is optimized task data.

[1261] Step 5:

[1262] The server collects external information from the Internet. Specifically, it uses an external API (e.g., a security evaluation API) to obtain reliability and security information about partner sites and services. The input to this step is the task data obtained in step 4, and the output is the collected external information.

[1263] Step 6:

[1264] The server consolidates the collected information and presents it to the user. Specifically, it compiles the collected security information (e.g., SSL certificate expiration date, phishing site report status, etc.) and displays it on the device's user interface in a format that is easy for the user to understand. The input in this step is the external information obtained in step 5, and the output is the presented information.

[1265] Step 7:

[1266] The user confirms the presented information and issues a voice command for the next action, such as "continue the transaction" or "make a reservation on this site." The user confirms the presented information in step 6 and then issues a voice command.

[1267] Step 8:

[1268] The device again converts the voice command into text data and sends it to the server. Specifically, it again uses a voice recognition module to convert the voice into text and sends it to the server. The input in this step is the user voice command from step 7, and the output is text data.

[1269] Step 9:

[1270] The server executes the specific reservation or transaction based on the user's instructions. Specifically, it calls the appropriate external API to complete the reservation procedure and notifies the user of the results. The input in this step is the text data from step 8, and the output is the result of the action taken and a notification of it.

[1271] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1272] This invention combines an autonomous AI agent called "Concierge" that helps seniors use smartphones and the Internet more effectively with an emotion engine that recognizes the user's emotions. An embodiment of this invention is described below.

[1273] Receiving User Input

[1274] The user launches a dedicated application on their smartphone and enters a command by voice, such as "I want to go on a trip." The device uses a voice recognition module to convert this voice command into text data and send it to the server.

[1275] User Intention Analysis and Task Generation

[1276] The server analyzes the received text data using a natural language processing (NLP) module to extract the user's purpose (travel planning). Based on the analysis results, it generates the necessary tasks (e.g., booking a hotel, arranging transportation, checking the weather forecast, and listing necessary equipment).

[1277] User emotion recognition and adjustment

[1278] The server uses an emotion engine to analyze the user's emotional state from their voice commands. Based on this analysis, it can adjust the tasks it generates. For example, if the user is tired, it can suggest a more relaxing plan.

[1279] Personalization and Learning

[1280] The server references the user's past behavioral patterns and preferences to optimize the generated tasks for the user. The emotion engine also records the user's past emotional data and uses it to optimize future tasks. This enables personalization that takes the user's emotional state into account.

[1281] Information gathering and arrangements

[1282] The server uses external APIs to collect necessary information from the Internet. It obtains hotel reservation options through travel site APIs, and suggests optimal travel methods using transportation APIs. It also obtains weather information for the travel period using weather forecast APIs. Similarly, it generates a list of necessary equipment and provides it with online shopping links.

[1283] Displaying results and user confirmation

[1284] The collected information is consolidated on the server and sent as a data package to the device. The device displays this data on a user interface and asks the user for confirmation, such as a message like "Is this plan OK?"

[1285] Booking and confirmation

[1286] The user checks the displayed suggestions and issues a command such as "Book this hotel." The device again converts the speech into text and sends it to the server. Based on the user's instructions, the server calls the reservation API to reserve the specified hotel and transportation. Once the reservation is complete, a notification is sent to the device and displayed to the user.

[1287] Specific examples

[1288] As a specific example, if a user says, "I'd like you to suggest a travel plan that will allow me to relax a little today," the server will perform the following tasks:

[1289] 1. User intent analysis: Extract travel destination, departure date, budget, etc.

[1290] 2. Emotion recognition: Analyze the user's emotional state, such as wanting to relax, from their voice.

[1291] 3. Personalization: Prioritize relaxing accommodation and transportation options based on past data.

[1292] 4. Information gathering: Collecting the best options from multiple travel sites and transportation APIs.

[1293] 5. Displaying results: Travel plans, accommodation, transportation, weather forecast, and a list of necessary equipment are displayed on the user interface.

[1294] 6. Reservation: After user confirmation, the reservation is actually made.

[1295] In this way, by combining the emotion engine, the system allows even seniors to make optimal travel plans and decisions based on their emotional state without having to perform complicated operations.

[1296] The processing flow will be explained below.

[1297] Step 1:

[1298] The user launches a dedicated application on their smartphone and issues a voice command such as, "Please suggest a travel plan that is a little more relaxing today."

[1299] Step 2:

[1300] The terminal's voice recognition module receives the user's voice commands and converts them into text data.

[1301] Step 3:

[1302] The terminal transmits the converted text data to the server.

[1303] Step 4:

[1304] The server analyzes the received text data using a natural language processing (NLP) module to extract the user's intent (suggestions for a relaxing travel plan).

[1305] Step 5:

[1306] The server uses an emotion engine to analyze the user's emotional state (e.g., a desire to relax) from their voice command, and generates tasks (e.g., hotel reservations, transportation arrangements, weather forecasts, and a list of necessary equipment) based on this emotional state.

[1307] Step 6:

[1308] The server optimizes the generated tasks by referring to the user's past behavioral patterns, preference data, and emotion recognition results. Specifically, it prioritizes data on relaxation spots and accommodations visited in the past.

[1309] Step 7:

[1310] The server uses external APIs to collect necessary information from the Internet. It obtains relaxing hotel reservation options through travel site APIs, suggests optimal travel methods using transportation APIs, and uses weather forecast APIs to obtain weather information for the travel period and generate a list of necessary equipment.

[1311] Step 8:

[1312] The server consolidates the collected information and organizes it into a single data package.

[1313] Step 9:

[1314] The server transmits the consolidated data package to the terminal.

[1315] Step 10:

[1316] The device analyzes the transmitted data package and displays it on the user interface, for example displaying a confirmation message saying, "Here are our suggested relaxing travel plans. What do you want to do?"

[1317] Step 11:

[1318] The user checks the displayed information and then says aloud, "Book this hotel."

[1319] Step 12:

[1320] The device converts the user's voice commands into text and sends it back to the server.

[1321] Step 13:

[1322] The server calls the booking API to reserve the specified hotel and transportation based on the user's instructions.

[1323] Step 14:

[1324] The server notifies the terminal of the reservation result (success / failure).

[1325] Step 15:

[1326] The device will notify the user that the booking is complete and save the trip details.

[1327] Example 2

[1328] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1329] It is often difficult for older adults to effectively use smartphones and the internet. Furthermore, tasks such as planning and booking trips are complex, especially when it comes to presenting optimal plans that take into account the user's emotional state. This calls for systems with emotion recognition and personalization capabilities.

[1330] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for converting a user's voice command into text data, means for analyzing the user's intention based on the text data and generating a task, means for optimizing the generated task by referring to the user's past behavioral patterns and preference data, means for analyzing the user's emotional state and adjusting the task, means for collecting external information, means for integrating the collected information and presenting it to the user, and means for performing actions such as making a reservation based on the presented information. This makes it possible to generate and execute an optimal travel plan that takes the user's emotional state into consideration.

[1331] "Voice command" refers to instructions or requests that a user verbally inputs into a smartphone or other device.

[1332] "Text data" refers to text information converted from voice commands using voice recognition technology.

[1333] "Intent analysis" refers to the process of understanding a user's goals and requests from voice commands and generating specific tasks based on that content.

[1334] "Task generation" refers to the process of determining specific tasks and procedures based on the results of intent analysis.

[1335] "Past behavioral patterns" refers to the history of actions and choices made by the user in the past.

[1336] "Preference Data" refers to information relating to a user's personal tastes and preferences.

[1337] "Task optimization" refers to the process of adjusting and improving a task to best suit the user by referring to data on the user's past behavioral patterns and preferences.

[1338] "Emotional state" refers to the emotion or mood of the user when entering a voice command.

[1339] "Means for analyzing emotional state" refers to technology that reads and evaluates emotional nuances from a user's voice or text data.

[1340] "External information" refers to information such as travel information, accommodation information, transportation options, and weather forecasts obtained via the Internet.

[1341] "Means of collecting external information" refers to technology that uses external interfaces and APIs to obtain necessary information from the Internet.

[1342] "Information synthesis" refers to the process of bringing together data collected from multiple sources into a single, unified format.

[1343] "Presentation means" refers to the user interface and display technology used to present the integrated information to the user.

[1344] "Means for executing actions such as reservations" refers to technology that actually carries out reservation procedures or other actions based on the user's confirmation or instructions.

[1345] This invention relates to an autonomous AI agent called "Concierge" that helps seniors use smartphones and the internet more effectively, and is combined with an emotion engine that recognizes the user's emotions. This system implements a series of processes: it receives a user's voice command, analyzes the user's intention, generates a task, optimizes it, and then executes it.

[1346] First, the user launches a dedicated application installed on their smartphone and enters a command by voice, such as "I want to go on a trip." At this time, the device uses the Google Cloud Speech-to-Text API to convert the user's voice command into text data, which is then sent to a server via the Internet.

[1347] The server analyzes the received text data using the Google Cloud Natural Language API and extracts the user's intent. For example, a voice command such as "I want to go on a trip" generates tasks such as selecting a travel destination, booking accommodation, and arranging transportation.

[1348] The server then uses Microsoft Azure Text Analytics for Cognitive Services to analyze the user's emotional state. For example, if the user's intent is "I want to relax," the server can adjust the task to provide a relaxing travel plan based on the emotion recognition results.

[1349] The server then uses Amazon Personalize to optimize the generated tasks based on past behavioral data and user preference patterns. For example, if a user has previously booked a resort hotel, the server will prioritize presenting similar options this time.

[1350] Regarding information gathering, the server uses external interfaces such as Expedia API, Google Maps API, OpenWeatherMap API, etc. to gather the necessary information, such as hotel reservation options, transportation options, weather forecasts, and a list of necessary amenities.

[1351] The collected information is integrated on the server and displayed on a user interface, allowing users to check travel plans, accommodations, transportation options, weather forecasts, lists of necessary supplies, etc. all in one place. For example, if a dedicated application is built with React Native, questions such as "Is this plan okay?" will be displayed on the user interface.

[1352] Finally, the user checks the displayed plan and enters a command such as "Book this hotel" by voice. The device again converts the voice to text data and sends it to the server. The server then calls the Booking.com API, makes the actual reservation, and sends a notification to the device. The user can then complete the entire process by receiving a notification that the reservation has been completed.

[1353] For example, if a user says, "I want some suggestions for relaxing travel destinations today," the system will do the following:

[1354] 1. Convert user voice input into text data

[1355] 2. Analyzing intent from text data and generating travel plans for relaxation

[1356] 3. Emotion recognition to recommend places suitable for relaxation

[1357] 4. Provide optimal plans based on past behavioral data

[1358] 5. Collect the necessary information, consolidate the plan, and display it in the user interface

[1359] 6. After user confirmation, the reservation is actually made

[1360] The system is designed to help seniors navigate complex procedures with ease and can provide a personalized travel experience that takes into account the user's emotions and preferences.

[1361] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1362] Step 1: Receiving User Input

[1363] The user launches the dedicated application and speaks a command such as "I want to go on a trip." The device uses the Google Cloud Speech-to-Text API to convert the voice into text data. This API outputs the voice as text data. The device then sends the converted text data to the server.

[1364] Input: User's voice command

[1365] Data processing: Converting speech to text

[1366] Output: Text data

[1367] Step 2: User intent analysis and task generation

[1368] The server receives the text data sent from the device and analyzes its intent using the Google Cloud Natural Language API. This analysis extracts the user's purpose (e.g., planning a trip). Based on the results, it generates tasks (reserving a hotel, arranging transportation, checking the weather forecast, and listing necessary equipment).

[1369] Input: Text data

[1370] Data processing: Intention analysis and task generation

[1371] Output: Analysis results and task list

[1372] Step 3: Recognizing and adjusting user emotions

[1373] The server uses Microsoft Azure Text Analytics to analyze the user's emotional state from the text data. Based on the obtained emotional state, the content of the generated task is adjusted. For example, if the user feels like "I want to relax," the server generates a plan that allows for more relaxation.

[1374] Input: Text data

[1375] Data processing: Emotional state analysis and task adjustment

[1376] Output: Reconciled task list

[1377] Step 4: Personalize and learn

[1378] The server uses Amazon Personalize to optimize the task by referencing the user's past behavioral patterns and preference data. This optimization suggests a plan based on the user's past tastes and preferences. The emotion engine also records the user's emotional data and uses it for future optimization.

[1379] Input: Adjusted task list and past activity data

[1380] Data Transformation: Personalization and Learning

[1381] Output: Optimized task list

[1382] Step 5: Information gathering and arrangements

[1383] The server uses external APIs (e.g., Expedia API, Google Maps API, OpenWeatherMap API) to collect the necessary information. The collected data includes hotel reservation options, transportation options, weather forecasts, and a list of necessary equipment. Based on this information, a detailed travel plan is created.

[1384] Input: Optimized task list

[1385] Data processing: collecting and integrating external information

[1386] Output: Consolidated information

[1387] Step 6: Displaying the results and user confirmation

[1388] The server sends the collected information to the device, which then displays it in the user interface. For example, if the dedicated application is built with React Native, it will display a message asking, "Is this plan OK?"

[1389] Input: Integrated information

[1390] Data processing: Display of information

[1391] Output: Information displayed in the user interface

[1392] Step 7: Booking and Confirmation

[1393] The user enters a confirmation command by voice, such as "Book this hotel." The device again converts the voice into text data and sends it to the server. The server uses the Booking.com API to reserve the specified hotel and transportation. After the reservation is complete, a notification is sent to the device and displayed to the user.

[1394] Input: Text data of the confirmation command

[1395] Data processing: Reservation procedure execution

[1396] Output: Notification of reservation completion

[1397] This allows the system to automatically handle everything from user voice input to travel planning and arrangements, generating and executing optimal plans that take emotions into consideration.

[1398] (Application example 2)

[1399] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1400] Seniors face challenges in effectively using smartphones and the internet, particularly the complexity and difficulty of voice input and internet searches. Furthermore, existing systems lack the ability to provide personalized services that take into account the user's emotions and current location. In particular, in-store shopping support lacks a means for users to quickly and efficiently find the products they are looking for, and solutions to this issue are needed.

[1401] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1402] In this invention, the server includes: means for converting a user's voice command into text data; means for analyzing the user's intention and generating a task; means for analyzing the user's emotional state; means for optimizing the generated task based on the user's emotional state; means for further optimizing the generated task by referring to the user's past behavioral patterns and preference data; means for collecting external information from the Internet; means for integrating the collected information and presenting it on a user interface; means for performing actions such as making a reservation based on the presented information; means for identifying the location of a product in a store using the user's current location information; and means for presenting the identified product location to the user. This enables seniors to efficiently shop in physical stores via their smartphones and receive personalized support that takes into account their emotions and location information.

[1403] A "user's voice command" is a voice input by a user to give instructions to the system through voice.

[1404] "Text data" is digital data that converts a voice command into a string of characters.

[1405] "Means for analyzing intent" is a function that analyzes the user's purpose and requests from text data.

[1406] A "task" is a series of specific actions or procedures generated based on a user's intentions.

[1407] "Emotional state" refers to the psychological state of the user that is analyzed from their voice and facial expressions.

[1408] "Optimization means" is a function that adjusts the generated tasks and presented information to suit the user's condition and preferences.

[1409] "Past behavioral patterns" are data on actions and choices that a user has previously made.

[1410] "Preference data" is data that indicates the tendency of a user to prefer specific conditions or options.

[1411] "External information" is additional data obtained from the Internet or other external sources.

[1412] "Means of collection" refers to APIs and data access procedures for obtaining external information.

[1413] "Means of integration" refers to the ability to bring together collected data into a single system or display format.

[1414] A "user interface" is a display screen and operating procedures that allow a user to interact with a system.

[1415] "Means for performing actions such as reservations" refers to a function that performs specific operations (e.g., hotel reservations, product purchases) based on user instructions.

[1416] "Current location information" is digital location data that indicates the specific location where a user is currently located.

[1417] A "means for identifying product location" is a technology for determining where a specific product is located within a physical store.

[1418] The "means for presenting the product location" is a function for visually or audibly guiding the user to the location of the identified product.

[1419] This invention is a system that allows users to efficiently shop in physical stores, and uses the following main hardware and software to perform specific data processing and data calculations.

[1420] Hardware and Software Configuration

[1421] Smartphone: A device that acts as an interface between the user and the system.

[1422] Speech Recognition Module: Used to convert user voice input into text data (e.g., speech recognition service).

[1423] Natural Language Processing (NLP) modules: Analyzing user intent from text data (e.g., natural language processing libraries).

[1424] Sentiment analysis engine: Analyzes the emotional state from the user's voice (e.g., emotion analysis service).

[1425] Location services: Obtaining the user's current location (e.g., location services).

[1426] External APIs: Used to collect external information (e.g. online databases, web APIs).

[1427] Database: Stores data about users' past behavior patterns and preferences (e.g., data storage).

[1428] User Interface (UI): The interface that displays collected information and tasks to the user and allows them to perform operations.

[1429] Processing Details

[1430] 1. Receiving user input: The user launches a dedicated application on their smartphone and provides a command by voice, such as "I want to buy toilet paper." The smartphone's voice recognition module converts this voice command into text data.

[1431] 2. User intent analysis and task generation: The server receives the text data, analyzes it with a natural language processing (NLP) module to extract the user's intent (e.g., buying toilet paper), and generates the required task.

[1432] 3. User emotion recognition and task adjustment: The server uses an emotion analysis engine to analyze the user's emotional state (e.g., fatigue) from their voice. Based on the analysis results, the generated task (e.g., suggesting a rest area in a store) is adjusted accordingly.

[1433] 4. Personalization and Learning: The server refers to the user's past behavioral patterns and preferences to optimize the generated tasks for the user. The emotion engine also records past emotion data and uses it to optimize future tasks.

[1434] 5. Information collection and arrangement: The server uses external APIs to collect and integrate necessary information from the Internet (e.g., product locations within the store, information about rest areas).

[1435] 6. Displaying the results and confirming with the user: The collected information is consolidated and sent to a user interface, which displays a message such as "Toilet paper is on the fifth shelf. Also, if you need a break, there is a cafe nearby."

[1436] Specific examples

[1437] As a specific example, consider the process when a user says, "I want to buy toilet paper." First, the voice input is converted into text by the speech recognition module, and the intent is analyzed by the NLP module. Next, the emotion analysis engine determines the user's emotional state, and generates and optimizes corresponding tasks. Information on the location of products in the store and information on rest areas is collected using an external API, and this information is integrated and presented to the user.

[1438] Prompt Sentence Examples

[1439] An example of a prompt to input to a generative AI model is as follows:

[1440] "Design an application that helps users efficiently find the products they need in a physical store. Users input commands via voice, such as "I want milk." An emotion engine is used to recognize the user's state and suggest rest areas if they are tired. The speech is converted into text using a speech recognition module, and a natural language processing module is used to analyze intent, and an emotion analysis engine is used to recognize emotions. Location services are used to identify the location of products, and user preferences are recorded in a database."

[1441] As described above, by providing personalized support that incorporates emotional state and location information, seniors can have an efficient and comfortable shopping experience using their smartphones.

[1442] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1443] Step 1:

[1444] Receiving User Input

[1445] The user launches a dedicated application on their smartphone and speaks, "I want to buy toilet paper." The device's voice recognition module converts this voice command into text data. Specifically, the voice recognition software analyzes the voice waveform and converts it into character string data. At this point, the input is voice data, and the output is text data.

[1446] Step 2:

[1447] User Intention Analysis and Task Generation

[1448] The server receives the text data and analyzes it using a natural language processing (NLP) module. By performing group data and contextual analysis, the system extracts the user's intent (e.g., buying toilet paper). Specifically, it identifies keywords and patterns in the text and generates tasks based on them. The input is text data, and the output is the user's intent and the corresponding task.

[1449] Step 3:

[1450] User Emotion Recognition and Task Adjustment

[1451] The server uses an emotion analysis engine to determine the user's emotion from their voice. It analyzes the tone, speed, and intonation of the voice to evaluate the user's emotional state, such as whether they are tired. Specifically, it extracts voice features and inputs them into an emotion model. This input data is the voice features, and the output is the emotion recognition result. The generated task is then readjusted based on the determination result.

[1452] Step 4:

[1453] Personalization and Learning

[1454] The server further optimizes the task by referencing data on past behavioral patterns and user preferences. It retrieves the user's past choices and purchase history from the database and uses that information to suggest optimal products and services. The input data is past behavioral data, and the output is optimized tasks and recommended products.

[1455] Step 5:

[1456] Information gathering and arrangements

[1457] The server uses external APIs to collect necessary information from the Internet. For example, it obtains information about the location of products in a store or information about nearby rest areas. Specifically, it sends requests to each API and integrates the obtained information. The input data is the response from the external API, and the output is the integrated information.

[1458] Step 6:

[1459] Displaying results and user confirmation

[1460] The server consolidates the collected information and sends it to the user interface. Specifically, it organizes the information using UI components to display the collected data in a visually easy-to-read format. The input data is the consolidated information, and the output is what is displayed on the user interface. The user confirms this information and then voice-inputs, for example, "I want to purchase this product."

[1461] Step 7:

[1462] Booking and confirmation

[1463] Once the server receives confirmation from the user, it executes the reservation. For example, it uses an online shopping API to purchase a product. Specifically, it issues an API call to complete the reservation or purchase. The input data is the user's confirmation instructions, and the output is a confirmation notification of the reservation or purchase. A success notification is displayed on the user interface to inform the user of the result.

[1464] As described above, by designing detailed processing content and specific operations at each step, seniors can shop comfortably and efficiently.

[1465] 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.

[1466] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. 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 voice, text data indicating text, and image data indicating an image is also input. 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.

[1467] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1468] 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.

[1469] FIG. 9 is a diagram illustrating 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 actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect 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.

[1470] 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.

[1471] 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).

[1472] 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 indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, 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 indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1473] 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."

[1474] 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.

[1475] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1476] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1477] 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.

[1478] 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.

[1479] 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.

[1480] The hardware resource for executing a specific process can be any of the following processors: An example of a processor 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. Another example of a processor is 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.

[1481] The hardware resource that executes the specific processing 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 processing may be a single processor.

[1482] 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.

[1483] 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.

[1484] 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.

[1485] 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.

[1486] The following is further disclosed regarding the above embodiment.

[1487] (Claim 1)

[1488] means for converting a user's voice commands into text data;

[1489] means for analyzing a user's intention based on the text data and generating a task;

[1490] A means for optimizing the generated task by referring to data on the user's past behavioral patterns and preferences;

[1491] a means of collecting external information from the Internet;

[1492] a means for aggregating and presenting the collected information to the user;

[1493] means for taking an action, such as making a reservation, based on the presented information;

[1494] A system including:

[1495] (Claim 2)

[1496] 10. The system of claim 1, wherein the tasks include planning a trip, booking accommodations, arranging transportation, getting a weather forecast, and generating a list of necessary supplies.

[1497] (Claim 3)

[1498] 2. The system according to claim 1, further comprising means for collecting information using an external API and presenting optimal options to the user.

[1499] "Example 1"

[1500] (Claim 1)

[1501] means for converting a user's voice commands into text data;

[1502] means for analyzing a user's intention based on the text data and generating a task;

[1503] A means for optimizing the generated task by referring to data on the user's past behavioral patterns and preferences;

[1504] a means of collecting external information from the Internet;

[1505] a means for aggregating and presenting the collected information to the user;

[1506] means for taking an action, such as making a reservation, based on the presented information;

[1507] A means of providing multiple options based on external data collected via the Internet;

[1508] a means for obtaining confirmation or instructions from a user using voice recognition;

[1509] A system including:

[1510] (Claim 2)

[1511] 10. The system of claim 1, wherein the tasks include planning a trip, booking accommodations, arranging transportation, getting a weather forecast, and generating a list of necessary supplies.

[1512] (Claim 3)

[1513] 2. The system according to claim 1, further comprising means for collecting information using an external API and presenting optimal options to the user.

[1514] "Application Example 1"

[1515] (Claim 1)

[1516] means for converting a user's voice commands into text data;

[1517] means for analyzing a user's intention based on the text data and generating a task;

[1518] A means for optimizing the generated task by referring to data on the user's past behavioral patterns and preferences;

[1519] a means of collecting external information from the Internet;

[1520] a means for aggregating and presenting the collected information to the user;

[1521] means for taking an action, such as making a reservation, based on the presented information;

[1522] means for prompting a user to support a secure transaction by voice command when making a transaction;

[1523] means for converting the voice command into text data and analyzing its intent;

[1524] A means for collecting security information related to the transaction from an external API and notifying the user of the information;

[1525] a means for presenting a reliability evaluation and security status of a transaction to a user based on the collected security information;

[1526] A system including:

[1527] (Claim 2)

[1528] 10. The system of claim 1, wherein the tasks include planning a trip, booking accommodations, arranging transportation, obtaining weather forecasts, generating a list of necessary supplies, and supporting security for a transaction.

[1529] (Claim 3)

[1530] 10. The system of claim 1, further comprising means for utilizing an external API to collect information, present the user with optimal options, and also collect transaction security information.

[1531] "Example 2: Combining Emotion Engines"

[1532] (Claim 1)

[1533] means for converting a user's voice commands into text data;

[1534] means for analyzing a user's intention based on the text data and generating a task;

[1535] A means for optimizing the generated task by referring to data on the user's past behavioral patterns and preferences;

[1536] means for analyzing the user's emotional state and adjusting the task;

[1537] a means of collecting external information from the Internet;

[1538] a means for aggregating and presenting the collected information to the user;

[1539] means for taking an action, such as making a reservation, based on the presented information;

[1540] A system including:

[1541] (Claim 2)

[1542] 10. The system of claim 1, wherein the tasks include planning a trip, booking accommodations, arranging transportation, getting a weather forecast, and generating a list of necessary supplies.

[1543] (Claim 3)

[1544] 10. The system according to claim 1, further comprising means for collecting information using an external interface and presenting the user with the most suitable options.

[1545] "Application example 2 when combining emotion engines"

[1546] (Claim 1)

[1547] means for converting a user's voice commands into text data;

[1548] means for analyzing a user's intention based on the text data and generating a task;

[1549] means for analyzing the emotional state of a user;

[1550] means for optimizing the generated task based on the emotional state;

[1551] A means for further optimizing the generated task by referring to data on the user's past behavioral patterns and preferences;

[1552] a means of collecting external information from the Internet;

[1553] means for aggregating the collected information and presenting it in a user interface;

[1554] means for taking an action, such as making a reservation, based on the presented information;

[1555] A means for identifying the location of a product in a store using current location information of a user;

[1556] means for presenting the identified product location to a user;

[1557] A system including:

[1558] (Claim 2)

[1559] 2. The system of claim 1, wherein the tasks include planning a trip, booking accommodations, arranging transportation, getting a weather forecast, generating a list of supplies needed, or navigating products in a store.

[1560] (Claim 3)

[1561] 2. The system according to claim 1, further comprising means for collecting information using an external API and presenting optimal options to the user. [Explanation of symbols]

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Claims

1. means for converting a user's voice commands into text data; means for analyzing a user's intention based on the text data and generating a task; A means for optimizing the generated task by referring to data on the user's past behavioral patterns and preferences; a means of collecting external information from the Internet; a means for aggregating and presenting the collected information to the user; means for taking an action, such as making a reservation, based on the presented information; A system including:

2. The system of claim 1 , wherein the tasks include planning a trip, booking accommodations, arranging transportation, obtaining weather forecasts, and generating a list of necessary equipment.

3. The system according to claim 1, further comprising means for collecting information using an external API and presenting optimal options to the user.

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