System

Abstract

A system is provided.SOLUTION: A system comprising: means for displaying a chat user interface on a home screen; means for receiving an input from a user and converting the AI input into text; means for analyzing the received text and executing various operations; and means for notifying the user of an operation result.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] Describe the "problem that the invention aims to solve" and the "means for solving the problem."

[0005] In recent years, smartphones have become more diverse in functionality, and their settings and operation have become more complex, causing many users to experience difficulties in operating them. There is also a demand for methods to efficiently perform tasks such as setting up various applications, managing schedules, and sending emails. Furthermore, continuous expandability and customizability are also important to enhance user convenience. [Means for solving the problem]

[0006] The present invention provides a terminal equipped with a generative AI model, a system that includes means for displaying a chat user interface on the home screen, means for receiving user input and converting the voice input into text, means for analyzing the received text and performing various operations, and means for notifying the user of the results of the operations. The system also includes means for downloading and installing additional functions and applications from a plug-in market, means for extending existing functions based on user requests, means for implementing calendar reminder functions and email sending functions, means for changing various settings on behalf of the user, means for receiving voice instructions and providing voice feedback, means for analyzing the request content and calling the calendar application API and email sending API, and means for notifying the user of the results of reminder settings and email sending. This system improves user operability and allows for easy expansion and customization of smartphone functions.

[0007] A "generative AI model" is an artificial intelligence algorithm that analyzes user input and generates appropriate responses or actions.

[0008] A "device" is an electronic device such as a smartphone or tablet that is equipped with a generative AI model.

[0009] The "chat user interface" is the screen display portion where the user can enter text and view responses from the generative AI model.

[0010] A "user" is a person who operates a terminal.

[0011] "Means for converting voice input to text" refers to the process of converting a user's voice instructions into text data using a voice recognition function.

[0012] "Means for notifying the user of the operation results" refers to a method of notifying the user of the processing results of the generative AI model using a chat user interface or voice.

[0013] "Plug-in Market" means an online store for downloading and installing additional features and applications.

[0014] The "Calendar reminder function" is a function that reminds users of upcoming events by sending notifications at the date and time specified by the user.

[0015] An "email sending API" is an application program interface for sending emails from a program.

[0016] A "Calendar Application API" is an application program interface for externally controlling the functions of a calendar application. [Brief explanation of the drawings]

[0017] [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

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] 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).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] This invention is a system that uses a terminal equipped with a generative AI model to provide operations and services according to user requests. This system displays a chat user interface on the home screen, receives input from the user, analyzes it, and executes appropriate responses and operations.

[0039] System configuration

[0040] The system includes the following major components:

[0041] 1. Terminal: A device that contains a generative AI model and interacts with the user.

[0042] 2. Generative AI model: Artificial intelligence that analyzes user input and generates appropriate responses or actions.

[0043] 3. Chat user interface: An interface that appears on the home screen and accepts text and voice input.

[0044] 4. Speech recognition function: The function that converts the user's voice input into text.

[0045] 5. Plugin Market: An online store offering additional features and applications.

[0046] 6. Various APIs: Application Program Interfaces for performing specific functions such as sending emails or calendar reminders.

[0047] Program processing

[0048] The program processing of this system is as follows: First, the user inputs text into the chat user interface or issues a voice command. The input is received by the device and converted into text using a speech recognition function as needed. Next, the text is sent to the generative AI model for analysis. Based on the analysis results, the generative AI model determines the appropriate response or operation.

[0049] For example, if a user types "send a new email," the generative AI model next asks the user for the necessary information (recipient, subject, and body) and receives each answer. It then calls the email sending API to send the email. The operation result is generated by the generative AI model and notified to the user via the device.

[0050] Specific examples

[0051] Example 1: Calendar reminder settings

[0052] User: "Set a reminder for a meeting tomorrow at 10 AM."

[0053] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[0054] Generative AI model: Analyzes the received text and asks the user for meeting details (content, location, etc.).

[0055] User: "Project X status review meeting in conference room A."

[0056] Generative AI model: Calls the calendar application API to set a reminder for the specified date and time.

[0057] On the device: The user is notified with the message "Reminder set."

[0058] Example 2: Sending email

[0059] User: "Send me a new email."

[0060] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[0061] Generative AI model: Analyzes the received text and asks the user for the email address to send it to.

[0062] User: "example@example.com"

[0063] Generative AI model: Ask for subject and body text.

[0064] User: "Subject: 'Meeting Announcement', Body: 'We have a meeting tomorrow at 10 AM.'"

[0065] Generative AI model: Calls the email sending API to send the email.

[0066] Terminal: Notify the user with the message "Email has been sent."

[0067] Extensions

[0068] This system uses a plugin market to allow users to download and install additional functions and applications. When a user instructs the system to "add a new plugin," the generative AI model accesses the plugin market and downloads and installs the specified plugin. Once the installation is complete, the device notifies the user.

[0069] In this way, the present invention is a system that utilizes generative AI models to respond to various user requests, simplifying smartphone operation and increasing user convenience.

[0070] The processing flow will be explained below.

[0071] Email sending process

[0072] Step 1:

[0073] The user types or speaks "send a new email" in the chat user interface on the home screen.

[0074] Step 2:

[0075] The device receives input from the user, which, if spoken, is converted to text using speech recognition.

[0076] Step 3:

[0077] The device transfers the text data to the generative AI model.

[0078] Step 4:

[0079] The generative AI model analyzes the received text and recognizes that it is a request to "send a new email."

[0080] Step 5:

[0081] The generative AI model generates a message requesting the recipient's email address.

[0082] Step 6:

[0083] The terminal displays this message on the chat user interface or outputs it as a voice message.

[0084] Step 7:

[0085] The user inputs or speaks the email address of the recipient.

[0086] Step 8:

[0087] The device receives the recipient's email address and forwards it to the generative AI model.

[0088] Step 9:

[0089] A generative AI model generates a message with a desired subject and body.

[0090] Step 10:

[0091] The terminal displays this message on the chat user interface or outputs it as a voice message.

[0092] Step 11:

[0093] The user types or speaks the subject and body of the email.

[0094] Step 12:

[0095] The device receives this information and forwards it to the generative AI model.

[0096] Step 13:

[0097] The generative AI model prepares the data to call the email sending API.

[0098] Step 14:

[0099] The generative AI model passes the recipient address, subject, and message body to the email sending API.

[0100] Step 15:

[0101] The device calls the email sending API to send the email.

[0102] Step 16:

[0103] The device receives the transmission results and notifies the generative AI model of the results.

[0104] Step 17:

[0105] If the generative AI model is successful, it generates the message "Email sent" and if it fails, it generates an error message.

[0106] Step 18:

[0107] The terminal displays the generated message on a chat user interface or outputs it as a voice.

[0108] Calendar Reminder Setting Process

[0109] Step 1:

[0110] A user types or speaks into the chat user interface on the home screen, "Set a reminder for a meeting tomorrow at 10 AM."

[0111] Step 2:

[0112] The device receives input from the user, which, if spoken, is converted to text using speech recognition.

[0113] Step 3:

[0114] The device transfers the text data to the generative AI model.

[0115] Step 4:

[0116] The generative AI model analyzes the received text and recognizes it as a request to "set a reminder."

[0117] Step 5:

[0118] The generative AI model generates a message requesting meeting details (content, location, etc.).

[0119] Step 6:

[0120] The terminal displays this message on the chat user interface or outputs it as a voice message.

[0121] Step 7:

[0122] The user types or speaks meeting details.

[0123] Step 8:

[0124] The device receives the meeting details and forwards them to the generative AI model.

[0125] Step 9:

[0126] The generative AI model prepares the data to call the calendar application API.

[0127] Step 10:

[0128] The generative AI model passes the date, time, content, and location to the calendar application API.

[0129] Step 11:

[0130] The device calls the calendar application API to set the reminder.

[0131] Step 12:

[0132] The device receives the reminder setting results and notifies the generative AI model.

[0133] Step 13:

[0134] If the generative AI model is successful, it generates a message saying "Reminder set" and if it fails, it generates an error message.

[0135] Step 14:

[0136] The terminal displays the generated message on a chat user interface or outputs it as a voice.

[0137] Example 1

[0138] 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."

[0139] In conventional smart devices and virtual assistants, systems for quickly and accurately responding to user operation requests have not been fully established. Furthermore, it has been difficult to provide various functions in an integrated manner, resulting in reduced user convenience. The objective of this invention is to provide a system that utilizes generative AI models to quickly and accurately respond to various user requests and execute operations.

[0140] 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.

[0141] In this invention, the server uses a terminal equipped with a generative AI model and includes: means for displaying a chat user interface on a home screen; means for receiving input from a user and converting the voice input into text; means for sending the received text to the generative AI model and analyzing it; means for generating appropriate responses and operations and displaying them to the user; means for obtaining necessary additional information from the user; means for calling various APIs to execute operations; and means for notifying the user of the results of the operations. This enables prompt and accurate responses and operations to be executed in response to various user requests. A "generative AI model" is an artificial intelligence model that analyzes user input and generates appropriate responses and operations.

[0142] A "terminal" is a device that is equipped with a generative AI model and interacts with the user.

[0143] A "chat user interface" is an interface that is displayed on the home screen and accepts text and voice input from the user.

[0144] The "voice recognition function" is a function that converts a user's voice input into text.

[0145] An "API" is an application program interface for performing a specific function.

[0146] "Online Store" means a digital platform for providing additional features and applications.

[0147] The "calendar function" is a function for managing schedules and setting reminders.

[0148] The "email sending function" is a function for sending e-mail to a destination specified by the user.

[0149] The "means for changing various settings on behalf of the user" refers to a means for adjusting the system settings based on the user's instructions.

[0150] This invention is a system that uses a terminal equipped with a generative AI model to provide operations and services according to user requests. This system displays a chat user interface on the home screen, receives input from the user, analyzes it, and executes appropriate responses and operations.

[0151] System configuration

[0152] The system includes the following major components:

[0153] 1. Terminal: A device that contains a generative AI model and interacts with the user.

[0154] 2. Generative AI model: Artificial intelligence that analyzes user input and generates appropriate responses or actions.

[0155] 3. Chat user interface: An interface that appears on the home screen and accepts text and voice input.

[0156] 4. Speech recognition: A function that converts user voice input into text. For example, we use the Google Speech-to-Text API.

[0157] 5. Online Store: A platform that offers additional features and applications.

[0158] 6. Various APIs: Application Program Interfaces for performing specific functions, such as sending emails or calendar reminders.

[0159] Program processing

[0160] The program in this system operates in the following steps: First, the user inputs text into the chat user interface or issues a voice command. The input is received by the device and converted into text using a speech recognition function as needed. The text is then sent to the generative AI model for analysis. Based on the analysis results, the generative AI model determines and executes an appropriate response or operation.

[0161] For example, if a user instructs the model to "send a new email," the generative AI model will then ask the user for the necessary information (recipient, subject, and body) and receive each response. It will then call the email sending API and send the email. The operation result is generated by the generative AI model and notified to the user via the device.

[0162] Specific examples

[0163] Example 1: Calendar reminder settings

[0164] 1. User: "Set a reminder for a meeting tomorrow at 10 AM."

[0165] 2. Terminal: Receives user input and converts it to text using speech recognition if necessary.

[0166] 3. Generative AI model: Analyzes the received text and asks the user for meeting details (content, location, etc.).

[0167] 4. User: "Project X status review meeting. Location: Conference Room A."

[0168] 5. Generative AI model: Calls the calendar application API to set a reminder for the specified date and time.

[0169] 6. Device: Notify the user with the message "Reminder has been set."

[0170] Example 2: Sending email

[0171] 1. User: "Send me a new email."

[0172] 2. Terminal: Receives user input and converts it to text using speech recognition if necessary.

[0173] 3. Generative AI model: Analyzes the received text and asks the user for the email address to send it to.

[0174] 4. User: "example@example.com"

[0175] 5. Generative AI model: Ask for subject and body text.

[0176] 6. User: "Subject: 'Meeting Announcement', Body: 'We'll be meeting tomorrow at 10 AM.'"

[0177] 7. Generative AI model: Calls the email sending API and sends the email.

[0178] 8. Terminal: Notify the user with the message "Email has been sent."

[0179] Extensions

[0180] This system allows users to download and install additional features and applications using an online store. When a user requests "add a new plugin," the generative AI model accesses the online store, downloads, and installs the specified plugin. Once the installation is complete, the device notifies the user.

[0181] In this way, the present invention is a system that utilizes a generative AI model to respond to a variety of user requests, simplify terminal operation, and increase user convenience.

[0182] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0183] Step 1:

[0184] A user enters text into the chat user interface or issues a voice command, which generates input data. Text is received as input data, and voice is received as voice data.

[0185] Step 2:

[0186] The device receives user input. If it is voice input, it converts the voice data into text data using the speech recognition function. The input is voice data, and the output is text data. Specifically, it converts the voice into text using the Google Speech-to-Text API.

[0187] Step 3:

[0188] The text data received by the device is sent to the generative AI model. Here, the input data (text) is passed to the generative AI model, which then performs an analysis process. The generative AI model receives the input text and performs data calculations for analysis. This analysis clarifies the requested content.

[0189] Step 4:

[0190] The generative AI model analyzes the text data and determines the appropriate response or operation. Based on the analysis results, it generates a prompt to ask the user for the next required information (for example, recipient, subject, and body of an email when sending one). The input is the analyzed data, and the output is the prompt. The specific operation uses a natural language processing algorithm within the model.

[0191] Step 5:

[0192] The terminal will then generate a prompt and notify the user. If the user enters additional information or a response, that data will be sent back to the terminal. The input is the user's response data, and the output is the updated user data.

[0193] Step 6:

[0194] The generative AI model receives additional information from the user and executes operations by calling various APIs as necessary. For example, it calls an email sending API to send an email. In this procedure, the input is the updated user data, and the output is the result of executing the API call. As a specific operation, the actual operation is performed using the defined API interface.

[0195] Step 7:

[0196] The device notifies the user of the operation result. For example, a message such as "Email sent" or "Reminder set" is generated and provided to the user. The input is the result of the API call, and the output is the notification message. The device displays the message on the user's screen.

[0197] Through the above steps, a terminal system utilizing a generative AI model can respond quickly and accurately to user input and provide a variety of operations and services.

[0198] (Application example 1)

[0199] 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."

[0200] Autonomous vehicles require passengers to easily set their destinations and respond quickly in emergencies. However, current systems lack the high level of interactivity required for this, making it difficult for them to understand user instructions in real time and respond appropriately. Furthermore, complex systems with multiple functions can be difficult for users to use. Furthermore, there is a growing need for systems that can provide specific functions within autonomous vehicles and respond flexibly to situations.

[0201] 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.

[0202] In this invention, the server is a terminal equipped with a generative AI model and includes: means for displaying a chat user interface on a home screen; means for receiving input from a user and converting the voice input into text; means for analyzing the received text and performing various operations; means for notifying the user of the operation results; means for setting a destination in an autonomous vehicle; and means for sending notifications to contacts in the event of an emergency. This allows the user to easily set a destination and respond quickly to emergencies. Furthermore, by utilizing the generative AI model, the system becomes highly interactive and can respond appropriately to user instructions in real time.

[0203] A "generative AI model" is a type of artificial intelligence that analyzes user input and generates appropriate responses and operations.

[0204] "Terminal" refers to a device that is equipped with a generative AI model and interacts with the user.

[0205] A "chat user interface" is an interface that is displayed on the home screen and accepts text and voice input from the user.

[0206] The "means for converting speech input to text" is a processing function that recognizes the user's speech and converts it into text form.

[0207] "Means for analyzing received text and performing various operations" refers to a function that analyzes text received from a user using a generative AI model and performs specific operations based on the results.

[0208] "Means for notifying the user of the operation results" is a function for informing the user of the results of the operation performed by the generative AI model.

[0209] The "means for setting a destination in an autonomous vehicle" is a function that sets a destination based on user instructions within the autonomous vehicle system.

[0210] The "means for sending a notification to a contact in an emergency" is a function for quickly sending a notification to a designated contact in an emergency.

[0211] "Means to download and install from the Plug-in Market" refers to the ability to download and install additional features and applications from an online store.

[0212] "Means for providing plug-ins that optimize operation in an autonomous vehicle" refers to a function that provides additional plug-ins to optimize operation and functionality in an autonomous vehicle.

[0213] The "means for providing navigation information in real time" is a function for providing navigation information related to a destination or current location designated by the user in real time.

[0214] This invention relates to a system that automatically sets destinations and responds to emergencies based on user instructions in a device equipped with a generative AI model and in an autonomous vehicle. This system is highly interactive and provides operations and services that respond to user requests in real time.

[0215] Main components of the system

[0216] 1. Terminal: A device that is equipped with a generative AI model and interacts with the user. This terminal can be realized, for example, as a display installed in an autonomous vehicle or a smartphone held by the user.

[0217] 2. Generative AI models: These are artificial intelligence models that analyze user input and generate appropriate responses or actions. Examples include OpenAI's GPT-3.

[0218] 3. Chat user interface: This is the interface that appears on the home screen and accepts text and voice input from the user.

[0219] 4. Speech recognition function: This is a function that converts user voice input into text. For example, the speech_recognition module is used.

[0220] 5. Navigation module: This module allows users to set up navigation to a destination specified by the user. It uses map services such as Google Maps API.

[0221] 6. Emergency contact function: This function is used to send notifications to contacts in the event of an emergency. Email is typically sent using the SMTP protocol.

[0222] 7. Plug-in Market: An online store offering additional features and applications.

[0223] Program processing

[0224] The system works as follows: First, the device receives voice input from the user. The voice input is converted to text using the speech_recognition module. Next, the text is sent to a generative AI model (e.g., GPT-3) for analysis. Based on the results of this analysis, appropriate navigation settings and emergency contact operations are determined. For navigation, a route to the specified destination is set using the Google Maps API, and the results are notified to the user via the device. In the event of an emergency, a notification is sent to the specified contacts using SMTP.

[0225] Usage example

[0226] Example prompt 1:

[0227] User: "Please set your next destination to Tokyo Station."

[0228] The device converts the speech into text, and the generative AI model analyzes it to set navigation with "Tokyo Station" as the destination. It then calls the Google Maps API to start route guidance and notifies the user of the results.

[0229] Example prompt 2:

[0230] User: "Please contact your emergency contact."

[0231] The device converts the speech into text, which the generative AI model analyzes and sends a notification to the designated emergency contacts. An email is sent to the emergency contacts using the SMTP protocol.

[0232] In this way, the present invention provides a system that significantly improves passenger convenience in autonomous vehicles and also enables rapid response in emergencies.

[0233] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0234] Step 1:

[0235] The user inputs a command by voice, for example, "Please set the next destination to Tokyo Station."

[0236] Step 2:

[0237] The terminal receives the user's voice. The received voice data is converted into text data using a speech recognition module (speech_recognition). The input is voice data, and the output is text data. The specific operation of this conversion is to process the voice signal as digital data and analyze it using a language model.

[0238] Step 3:

[0239] The device sends the generated text to a generative AI model (e.g., GPT-3) for analysis. The input is the text data generated in step 2, and the output is the analysis results (including commands and specific operation instructions). Specifically, the process involves inputting text data into a generative AI model, analyzing the output, and determining the appropriate operation.

[0240] Step 4:

[0241] Based on the analysis results of the generative AI model, the navigation module (Google Maps API) is called. In this step, destination information is extracted from the analysis results and navigation settings are made. The input is the analysis results, and the output is the set route information. Specifically, the destination information is sent to the Google Maps API endpoint and route information is received.

[0242] Step 5:

[0243] The device notifies the user of navigation information obtained from the Google Maps API. The input is route information obtained from the Google Maps API, and the output is navigation instructions on the device's screen or via voice. Specifically, the device displays route information on the user interface and provides voice guidance if voice output is available.

[0244] Step 6:

[0245] In an emergency, the user may give instructions for emergency contact. For example, the user may give instructions by voice such as "Please contact the emergency contact." The input is voice data from the user.

[0246] Step 7:

[0247] As in step 2, the device receives the user's voice and converts it into text using speech recognition. The input is voice data and the output is text data.

[0248] Step 8:

[0249] The generative AI model analyzes the text data and identifies emergency contact instructions. The input is the text data, and the output is the emergency contact instructions.

[0250] Step 9:

[0251] The terminal uses the emergency contact function to send a notification to the specified contact. In this step, the input is the emergency contact instructions, and the output is the result of sending the notification using SMTP. The specific operation is to send an email containing the specified message to the emergency contact address.

[0252] In this way, a system is realized that performs navigation settings and emergency contact according to user instructions.

[0253] 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.

[0254] This invention is a system that uses a terminal equipped with a generative AI model to provide operations and services according to user requests. This system displays a chat user interface on the home screen, receives user input, analyzes it, and executes appropriate responses and operations. In addition, by incorporating an emotion engine, it recognizes the user's emotions and provides responses and operations according to the emotions.

[0255] System configuration

[0256] The system includes the following major components:

[0257] 1. Terminal: A device that contains a generative AI model and interacts with the user.

[0258] 2. Generative AI model: Artificial intelligence that analyzes user input and generates appropriate responses or actions.

[0259] 3. Chat user interface: An interface that appears on the home screen and accepts text and voice input.

[0260] 4. Speech recognition function: The function that converts the user's voice input into text.

[0261] 5. Plugin Market: An online store offering additional features and applications.

[0262] 6. APIs: Application Program Interfaces for performing specific functions such as sending emails or calendar reminders.

[0263] 7. Emotion Engine: Recognizes emotions from user voice and text inputs and generates corresponding responses.

[0264] Program processing

[0265] The program processing of this system is as follows: First, the user inputs text into the chat user interface or issues a voice command. The input is received by the device and converted into text using a speech recognition function as needed. Next, the text is sent to the generative AI model for analysis. Based on the analysis results, the generative AI model determines the appropriate response or operation.

[0266] The emotion engine analyzes emotions from the user's voice or text input and passes the results to the generative AI model, which then generates responses and actions taking the emotional data into account. For example, if the user is feeling stressed, the generative AI model will generate a more polite response. It can also suggest appropriate plugins based on the user's emotions.

[0267] Specific examples

[0268] Example 1: Emotion-recognition-based calendar reminder setting

[0269] User: "Set a reminder for a meeting tomorrow at 10 AM."

[0270] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[0271] Generative AI model: Analyzes the received text and asks the user for meeting details (content, location, etc.).

[0272] Emotion engine: Detects stress levels from the user's voice.

[0273] Generative AI models generate polite responses (e.g., "Good work. Can you tell me what the meeting was about?").

[0274] User: "Project X status review meeting in conference room A."

[0275] Generative AI model: Calls the calendar application API to set a reminder for the specified date and time.

[0276] On your device: Notify the user with the message "Your reminder has been set. Is there anything else we can help you with?"

[0277] Example 2: Emotion recognition in email sending

[0278] User: "Send me a new email."

[0279] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[0280] Generative AI model: Analyzes the received text and asks the user for the email address to send it to.

[0281] Emotion Engine: Detects gratitude from the user's voice.

[0282] Generative AI models generate responses tailored to the sentiment of gratitude (e.g., "Thank you. Can you give me your email address?").

[0283] User: "example@example.com"

[0284] Generative AI model: Ask for subject and body text.

[0285] User: "Subject: 'Meeting Announcement', Body: 'We have a meeting tomorrow at 10 AM.'"

[0286] Generative AI model: Calls the email sending API to send the email.

[0287] Terminal: Notify the user with the message "Your email has been sent. Is there anything else we can help you with?"

[0288] Extensions

[0289] This system can download and install additional functions and applications using the plugin market. When the user instructs the system to "add a new plugin," the generative AI model accesses the plugin market and downloads and installs the specified plugin. It can also suggest appropriate plugins based on the analysis results of the emotion engine. For example, if the user is feeling stressed, it will suggest relaxation-related plugins.

[0290] In this way, by utilizing a generative AI model and an emotion engine, the present invention provides a system that responds to various user requests, simplifies smartphone operation, and improves user convenience. Furthermore, by executing appropriate responses and operations based on the user's emotional state, more human-like interactions can be achieved.

[0291] The processing flow will be explained below.

[0292] Email sending process including emotion recognition

[0293] Step 1:

[0294] The user types or speaks "send a new email" in the chat user interface on the home screen.

[0295] Step 2:

[0296] The device receives input from the user, which, if spoken, is converted to text using speech recognition.

[0297] Step 3:

[0298] The device transfers the text data to the generative AI model.

[0299] Step 4:

[0300] The generative AI model analyzes the received text and recognizes that it is a request to "send a new email."

[0301] Step 5:

[0302] The generative AI model generates a message requesting the recipient's email address.

[0303] Step 6:

[0304] The terminal displays this message on the chat user interface or outputs it as a voice message.

[0305] Step 7:

[0306] The user inputs or speaks the email address of the recipient.

[0307] Step 8:

[0308] The device receives the recipient's email address and forwards it to the generative AI model.

[0309] Step 9:

[0310] The emotion engine analyzes the user input (voice or text) up to this point and identifies the user's emotion.

[0311] Step 10:

[0312] The generative AI model takes into account the output of the emotion engine to determine the appropriate tone of the response. For example, if the user is nervous, the generative AI model will generate a message that responds in a calm tone.

[0313] Step 11:

[0314] A generative AI model generates a message with a desired subject and body.

[0315] Step 12:

[0316] The terminal displays this message on the chat user interface or outputs it as a voice message.

[0317] Step 13:

[0318] The user types or speaks the subject and body of the email.

[0319] Step 14:

[0320] The device receives this information and forwards it to the generative AI model.

[0321] Step 15:

[0322] The generative AI model prepares the data to call the email sending API.

[0323] Step 16:

[0324] The generative AI model passes the recipient address, subject, and message body to the email sending API.

[0325] Step 17:

[0326] The device calls the email sending API to send the email.

[0327] Step 18:

[0328] The device receives the transmission results and notifies the generative AI model of the results.

[0329] Step 19:

[0330] If the generative AI model is successful, it generates the message "Email sent" and if it fails, it generates an error message.

[0331] Step 20:

[0332] The terminal displays the generated message on a chat user interface or outputs it as a voice.

[0333] Calendar reminder setting process using emotion recognition

[0334] Step 1:

[0335] A user types or speaks into the chat user interface on the home screen, "Set a reminder for a meeting tomorrow at 10 AM."

[0336] Step 2:

[0337] The device receives input from the user, which, if spoken, is converted to text using speech recognition.

[0338] Step 3:

[0339] The device transfers the text data to the generative AI model.

[0340] Step 4:

[0341] The generative AI model analyzes the received text and recognizes it as a request to "set a reminder."

[0342] Step 5:

[0343] The emotion engine analyzes the user input (voice or text) up to this point and identifies the user's emotion.

[0344] Step 6:

[0345] The generative AI model takes into account the output of the emotion engine and asks the user for meeting details (content, location, etc.) in an appropriate tone.

[0346] Step 7:

[0347] The terminal displays the message generated by the generation AI model on the chat user interface or outputs it as audio.

[0348] Step 8:

[0349] The user types or speaks meeting details.

[0350] Step 9:

[0351] The device receives the meeting details and forwards them to the generative AI model.

[0352] Step 10:

[0353] The generative AI model prepares the data to call the calendar application API.

[0354] Step 11:

[0355] The generative AI model passes the date, time, content, and location to the calendar application API.

[0356] Step 12:

[0357] The device calls the calendar application API to set the reminder.

[0358] Step 13:

[0359] The device receives the reminder setting results and notifies the generative AI model.

[0360] Step 14:

[0361] If the generative AI model is successful, it generates a message saying "Reminder set" and if it fails, it generates an error message.

[0362] Step 15:

[0363] The terminal displays the generated message on a chat user interface or outputs it as a voice.

[0364] The above is the specific processing flow in a system equipped with a generative AI model and an emotion engine.

[0365] Example 2

[0366] 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."

[0367] Conventional devices could only provide simple text responses and operations in response to user input, making it difficult to realize responses and operations that take the user's emotions into account. Furthermore, there were limited ways to provide additional functions, resulting in low user convenience. Furthermore, there was a lack of means to optimally provide specific functions, such as calendar reminders and email sending functions, based on the user's emotions.

[0368] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for displaying a chat user interface on a home screen, a means for converting a voice input from a user into text, a means for sending data to a generative AI model and having it analyze the data, a means for the generative AI model to determine a response or operation based on emotion data from the emotion engine, a means for notifying the user of the response, a means for downloading and installing additional functions or applications from an online store, a means for suggesting additional functions based on the user's emotional state, and a means for performing a calendar reminder function, an email sending function, and various setting changes on behalf of the user. This makes it possible to provide responses and operations that take the user's emotions into consideration, and to suggest additional functions.

[0369] A "generative AI model" is an artificial intelligence that analyzes user input data and generates appropriate responses and operations.

[0370] A "terminal" is a device that is equipped with a generative AI model and interacts with the user.

[0371] The "chat user interface" is an interface that is displayed on the home screen of the terminal and that accepts user input.

[0372] The "voice recognition function" is a function that converts a user's voice input into text.

[0373] The "emotion engine" is a function that recognizes emotions from user voice and text input and provides them to the generative AI model.

[0374] "Online Store" means a digital marketplace for offering additional features and applications.

[0375] The "Calendar reminder function" is a function that sets a reminder at a specified date and time and notifies you.

[0376] The "email sending function" is a function that creates and sends email based on user instructions.

[0377] The "means for changing various settings" is a function that automatically changes settings based on the user's request.

[0378] This invention relates to a system that combines a generative AI model and an emotion engine, and aims to improve convenience and user experience by analyzing user input data and providing appropriate responses and operations. This system is configured to install a generative AI model on a terminal and display a chat user interface on the home screen, allowing users to easily access it.

[0379] System Configuration

[0380] The main hardware and software components of the system are as follows:

[0381] 1. Device: A device that is equipped with a generative AI model and interacts with the user. Specific examples include smartphones and tablet PCs.

[0382] 2. Generative AI model: This is an artificial intelligence that analyzes user input data and generates appropriate responses and operations. It uses natural language processing (NLP) technology to accurately analyze user input.

[0383] 3. Chat user interface: An interface that appears on the device's home screen and accepts text or voice input from the user, allowing the user to easily communicate their requests to the system.

[0384] 4. Speech recognition function: This function converts the user's voice input into text. This conversion allows the voice input to be analyzed in the same way as text.

[0385] 5. Emotion Engine: A system that recognizes emotions from user voice and text inputs and provides the results to a generative AI model. This capability allows the system to understand the user's emotional state and optimize responses and suggestions.

[0386] 6. Online Store: A digital marketplace offering additional features and applications, allowing users to extend functionality as needed.

[0387] 7. APIs: Application Programming Interfaces are used to perform specific operations, such as setting a calendar reminder or sending an email.

[0388] Implementation method

[0389] When a user inputs commands into the chat user interface via text or voice, the data is received by the device. In the case of voice input, the data is converted into text using a speech recognition function. The text data is then sent to a generative AI model and analyzed using natural language processing technology. The generative AI model determines the appropriate response or action based on the analysis results, taking into account the emotional data provided by the emotion engine.

[0390] For example, if a user types, "Set a reminder for a meeting tomorrow at 10 AM," the system will parse this instruction and set a reminder for the specified date and time through the calendar API. Furthermore, if the emotion engine detects the user's stress, the generative AI model will generate a polite response such as, "Thank you for your hard work. Can you let me know what the meeting is about?"

[0391] Specific examples

[0392] Example 1: Emotion-recognition-based calendar reminder setting

[0393] User: "Set a reminder for a meeting tomorrow at 10 AM."

[0394] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[0395] Generative AI model: Analyzes the received text and asks the user for meeting details (content, location, etc.).

[0396] Emotion engine: Detects stress levels from the user's voice.

[0397] Generative AI models: Generate polite responses (e.g., "Good work. Can you tell me what the meeting was about?").

[0398] User: "Project X status review meeting in conference room A."

[0399] Generative AI model: Calls the calendar application API to set a reminder at the specified date and time.

[0400] On your device: Notify the user with the message "Your reminder has been set. Is there anything else we can help you with?"

[0401] Example 2: Emotion recognition in email sending

[0402] User: "Send me a new email."

[0403] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[0404] Generative AI model: Analyzes the received text and asks the user for the email address to send it to.

[0405] Emotion Engine: Detects gratitude from the user's voice.

[0406] Generative AI models: Generate responses tailored to the sentiment of gratitude (e.g., "Thank you. Can you give me your email address?").

[0407] User: "example@example.com"

[0408] Generative AI model: Ask for subject and body text.

[0409] User: "Subject: 'Meeting Announcement', Body: 'We have a meeting tomorrow at 10 AM.'"

[0410] Generative AI model: Calls the email sending API to send the email.

[0411] Terminal: Notify the user with the message "Your email has been sent. Is there anything else we can help you with?"

[0412] In this way, the system analyzes the user's input and provides appropriate responses and operations that take into account the emotion data. However, this embodiment is merely an example, and the present invention can be implemented in other ways without departing from the scope of the present invention.

[0413] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0414] Step 1:

[0415] The user provides input in the chat user interface

[0416] A user inputs instructions into a chat user interface using text or voice. The input data contains the user's intent or request. For example, "Set a reminder for a meeting tomorrow at 10 AM." The string of data (text or voice) is sent to the system.

[0417] Step 2:

[0418] The terminal receives input

[0419] The terminal receives text and voice data entered by the user. This is where the input data is first captured by the system. For example, when a user enters voice input, the voice data is stored in the terminal.

[0420] Step 3:

[0421] Your device converts your voice input into text

[0422] When voice input is made, the device uses speech recognition to convert the speech to text. The input is voice data, and the output is the equivalent text data. For example, voice data such as "Set a reminder for a meeting tomorrow at 10:00 AM" is converted to text such as "Set a reminder for a meeting tomorrow at 10:00 AM."

[0423] Step 4:

[0424] The device sends data to the generative AI model

[0425] The terminal sends the received or converted text data to the generative AI model. The input is text data, and the output is data waiting to be interpreted by the generative AI model. The data is sent to the generative AI model server using a communication protocol such as an HTTP request.

[0426] Step 5:

[0427] A generative AI model analyzes the input

[0428] The generative AI model analyzes the received text data. The input is text data, and the output is instructions or operational decisions based on the analysis results. The generative AI model uses natural language processing techniques to analyze the text and interpret the user's request. For example, it can understand the instruction "Set a meeting reminder."

[0429] Step 6:

[0430] The emotion engine provides emotion data to the generative AI model

[0431] The emotion engine analyzes emotions from the tone and content of a user's voice or text and provides that data to a generative AI model. The input is voice or text data, and the output is emotion data. For example, it can analyze a user's stress level from their tone of voice.

[0432] Step 7:

[0433] Generative AI models determine responses and actions

[0434] The generative AI model takes emotional data into account to determine the appropriate response or action. The input is the user's instructions and emotional data, and the output is the determined response or action. For example, it generates responses such as "Ask for reminder settings details" or "Confirm meeting details."

[0435] Step 8:

[0436] The terminal notifies the user of the response

[0437] The device notifies the user of the response from the generative AI model. The input is the response data from the generative AI model, and the output is the response that is displayed or spoken to the user. For example, a message such as "Thank you for your hard work. Could you please let me know the details of the meeting?" is displayed.

[0438] Step 9:

[0439] If necessary, the device calls the relevant API to perform the process.

[0440] When necessary, the device will call relevant application program interfaces such as a calendar API or email API to perform specific operations. The input is the user's instruction and the analysis result of the generative AI model, and the output is the result of the performed operation. For example, calling a calendar API to set a reminder.

[0441] (Application example 2)

[0442] 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."

[0443] Conventional systems using generative AI models and emotion recognition engines mainly respond to basic user operational requests, making it difficult to efficiently interact with customers in physical stores. In particular, they are insufficient when providing detailed information, such as responses based on the customer's emotional state, checking the stock of specific products, or guiding customers to their location. Therefore, in order to improve customer satisfaction in physical stores, it is necessary to provide more advanced information and responses that reflect emotions.

[0444] 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.

[0445] In this invention, the server is a terminal equipped with a generative AI model, and includes means for displaying a chat user interface on a home screen, means for receiving input from a user and converting the voice input into text, means for analyzing the received text and performing various operations, means for notifying the user of the operation results, means for analyzing the user's emotions using an emotion recognition engine, means for checking product inventory status, and means for providing the shelf location of a specific product. This allows for more advanced interaction with customers, making it possible to provide specific product information and inventory status, and to respond appropriately to the customer's emotional state.

[0446] ---

[0447] OK, now we'll create definitions for each of the key words in the rewritten claims.

[0448] definition statement

[0449] ---

[0450] A "generative AI model" is an artificial intelligence that analyzes user input and generates appropriate responses and operations.

[0451] A "chat user interface" is a user interface that is displayed on the home screen and accepts text and voice input.

[0452] A "means for converting speech input to text" is a technique for converting a user's speech input into text form.

[0453] The "means for performing various operations" is a system that performs the necessary operations based on the analyzed text.

[0454] The "means for notifying the user of the operation result" is a function for notifying the user of the result of the executed operation.

[0455] An "emotion recognition engine" is an algorithm that recognizes and analyzes emotions from the user's voice or text input.

[0456] The "means for checking product inventory status" is a system for checking whether a specific product is in stock.

[0457] The "means for providing the shelf location of a specific product" is a function that guides the user to the location where the product is stored.

[0458] ---

[0459] Understood. Now, let's create the detailed description based on the information we have provided so far.

[0460] MODE FOR CARRYING OUT THE INVENTION

[0461] ---

[0462] System Overview

[0463] This invention is a customer service system for brick-and-mortar stores that uses a terminal equipped with a generative AI model and an emotion recognition engine. This system displays a chat user interface on the screen and accepts voice and text input in response to questions and requests from customers in the store. The generative AI model analyzes these inputs and executes appropriate responses and operations. Furthermore, the emotion recognition engine can analyze customer emotions and provide responses that correspond to those emotions.

[0464] System configuration

[0465] The system includes the following main components:

[0466] 1. Device: A device that is equipped with a generative AI model and interacts with the user. Examples of devices that can be used include smartphones and tablets.

[0467] 2. Generative AI model: An artificial intelligence that analyzes user input and generates appropriate responses or actions. For example, natural language processing models (such as BERT and GPT-3) can be applied.

[0468] 3. Chat user interface: An interface that appears on the device's home screen and accepts text and voice input.

[0469] 4. Speech recognition: A function that converts user voice input into text. Examples of services that can be used include Google Cloud Speech-to-Text and Amazon Transcribe.

[0470] 5. Emotion Recognition Engine: An engine that recognizes emotions from the user's voice and text input and generates corresponding responses. For example, IBM Watson Tone Analyzer can be used.

[0471] 6. Various APIs: Application program interfaces for checking product inventory status and providing product shelf location information. RESTful APIs are commonly used for this purpose.

[0472] Operation flow

[0473] The system works as follows: First, a customer enters text into the chat user interface or issues a voice command. The input is received by the device, and in the case of voice input, it is converted into text using a speech recognition function. The text is then sent to a generative AI model for analysis. Based on the analysis results, the generative AI model determines the appropriate response or action.

[0474] The emotion recognition engine analyzes emotions from customer voice and text inputs and passes the results to a generative AI model. The generative AI model generates responses and actions taking emotional data into account. For example, if a customer's emotions indicate stress, the generative AI model will generate a more polite response. It can also provide relaxation-related information and suggestions based on their emotions.

[0475] Specific examples

[0476] Example 1: Checking inventory

[0477] User: "Can you tell me if this item is in stock?"

[0478] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[0479] Generative AI model: Analyzes the incoming text and recognizes it as an instruction to check inventory.

[0480] Emotion Recognition Engine: Analyzes emotions from user text.

[0481] Generative AI model: Calls the stock availability API to check the availability of the specified product.

[0482] Terminal: Notifies the user with the message "The product is in stock."

[0483] Example 2: Product location guidance

[0484] User: "Where is this item?"

[0485] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[0486] Generative AI model: Analyzes the received text and recognizes it as instructions to guide shelf locations.

[0487] Emotion Recognition Engine: Analyzes emotions from user text.

[0488] Generative AI model: Calls the product shelf location information API to obtain the location of the specified product.

[0489] Terminal: Notifies the user with the message "The product is located in the second section of the store."

[0490] Prompt Sentence Examples

[0491] Please let me know if you have this item in stock.

[0492] "Where is this item located?"

[0493] This will make customer service in physical stores more efficient and improve customer satisfaction.

[0494] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0495] Understood. Now, I will explain the processing flow of the system program that realizes the application example, broken down into specific processing steps.

[0496] Program processing steps

[0497] ---

[0498] Step 1:

[0499] The user provides voice or text input to the chat user interface.

[0500] What happens: The user says, "Tell me if this item is in stock."

[0501] Input: User's voice input.

[0502] Output: Audio data.

[0503] Step 2:

[0504] The device receives voice input and converts it into text using speech recognition.

[0505] How it works: The device receives the audio and uses Google Cloud Speech-to-Text to convert it into text: "Tell me if this item is in stock."

[0506] Input: Audio data.

[0507] Output: Text data ("Tell me if this item is in stock").

[0508] Step 3:

[0509] The received text is sent to a generative AI model for analysis.

[0510] How it works: The device sends text data to a generative AI model (e.g., GPT-3) and receives an analysis result, which determines that the text is a request for inventory check.

[0511] Input: Text data ("Tell me if this item is in stock").

[0512] Output: Analysis result data (command "check_inventory", item "requested_item").

[0513] Step 4:

[0514] Analyze user emotions using an emotion recognition engine.

[0515] How it works: The device sends text data to an emotion recognition engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotions. The analysis results indicate that the user has a neutral attitude.

[0516] Input: Text data ("Tell me if this item is in stock").

[0517] Output: Emotion data (neutral).

[0518] Step 5:

[0519] Call the inventory status API to check the product's inventory status.

[0520] Operation: The device sends a request to the stock confirmation API to obtain the stock status of the specified product. For example, a request is sent via the RESTful API to check the stock status of "requested_item".

[0521] Input: Analysis result data (command "check_inventory", item "requested_item").

[0522] Output: Inventory status data (in stock).

[0523] Step 6:

[0524] Generate appropriate responses based on analysis results and sentiment data.

[0525] How it works: The generative AI model takes into account the analysis results and sentiment data and generates a response message saying, "The item is in stock."

[0526] Input: Stock status data (in stock), Sentiment data (neutral).

[0527] Output: Response message ("The item is in stock.").

[0528] Step 7:

[0529] Notify the user of the operation result.

[0530] Operation: The terminal notifies the user of the reply message through the chat user interface.

[0531] Input: Response message ("Item is in stock.").

[0532] Output: A text message that is displayed to the user.

[0533] This will enable customers to smoothly request product information in-store and receive appropriate responses.

[0534] 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.

[0535] 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.

[0536] 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.

[0537] [Second embodiment]

[0538] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0539] 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.

[0540] 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).

[0541] 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.

[0542] 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.

[0543] 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).

[0544] 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.

[0545] 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.

[0546] 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.

[0547] 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.

[0548] 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.

[0549] 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."

[0550] This invention is a system that uses a terminal equipped with a generative AI model to provide operations and services according to user requests. This system displays a chat user interface on the home screen, receives input from the user, analyzes it, and executes appropriate responses and operations.

[0551] System configuration

[0552] The system includes the following major components:

[0553] 1. Terminal: A device that contains a generative AI model and interacts with the user.

[0554] 2. Generative AI model: Artificial intelligence that analyzes user input and generates appropriate responses or actions.

[0555] 3. Chat user interface: An interface that appears on the home screen and accepts text and voice input.

[0556] 4. Speech recognition function: The function that converts the user's voice input into text.

[0557] 5. Plugin Market: An online store offering additional features and applications.

[0558] 6. Various APIs: Application Program Interfaces for performing specific functions such as sending emails or calendar reminders.

[0559] Program processing

[0560] The program processing of this system is as follows: First, the user inputs text into the chat user interface or issues a voice command. The input is received by the device and converted into text using a speech recognition function as needed. Next, the text is sent to the generative AI model for analysis. Based on the analysis results, the generative AI model determines the appropriate response or operation.

[0561] For example, if a user types "send a new email," the generative AI model next asks the user for the necessary information (recipient, subject, and body) and receives each answer. It then calls the email sending API to send the email. The operation result is generated by the generative AI model and notified to the user via the device.

[0562] Specific examples

[0563] Example 1: Calendar reminder settings

[0564] User: "Set a reminder for a meeting tomorrow at 10 AM."

[0565] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[0566] Generative AI model: Analyzes the received text and asks the user for meeting details (content, location, etc.).

[0567] User: "Project X status review meeting in conference room A."

[0568] Generative AI model: Calls the calendar application API to set a reminder for the specified date and time.

[0569] On the device: The user is notified with the message "Reminder set."

[0570] Example 2: Sending email

[0571] User: "Send me a new email."

[0572] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[0573] Generative AI model: Analyzes the received text and asks the user for the email address to send it to.

[0574] User: "example@example.com"

[0575] Generative AI model: Ask for subject and body text.

[0576] User: "Subject: 'Meeting Announcement', Body: 'We have a meeting tomorrow at 10 AM.'"

[0577] Generative AI model: Calls the email sending API to send the email.

[0578] Terminal: Notify the user with the message "Email has been sent."

[0579] Extensions

[0580] This system uses a plugin market to allow users to download and install additional functions and applications. When a user instructs the system to "add a new plugin," the generative AI model accesses the plugin market and downloads and installs the specified plugin. Once the installation is complete, the device notifies the user.

[0581] In this way, the present invention is a system that utilizes generative AI models to respond to various user requests, simplifying smartphone operation and increasing user convenience.

[0582] The processing flow will be explained below.

[0583] Email sending process

[0584] Step 1:

[0585] The user types or speaks "send a new email" in the chat user interface on the home screen.

[0586] Step 2:

[0587] The device receives input from the user, which, if spoken, is converted to text using speech recognition.

[0588] Step 3:

[0589] The device transfers the text data to the generative AI model.

[0590] Step 4:

[0591] The generative AI model analyzes the received text and recognizes that it is a request to "send a new email."

[0592] Step 5:

[0593] The generative AI model generates a message requesting the recipient's email address.

[0594] Step 6:

[0595] The terminal displays this message on the chat user interface or outputs it as a voice message.

[0596] Step 7:

[0597] The user inputs or speaks the email address of the recipient.

[0598] Step 8:

[0599] The device receives the recipient's email address and forwards it to the generative AI model.

[0600] Step 9:

[0601] A generative AI model generates a message with a desired subject and body.

[0602] Step 10:

[0603] The terminal displays this message on the chat user interface or outputs it as a voice message.

[0604] Step 11:

[0605] The user types or speaks the subject and body of the email.

[0606] Step 12:

[0607] The device receives this information and forwards it to the generative AI model.

[0608] Step 13:

[0609] The generative AI model prepares the data to call the email sending API.

[0610] Step 14:

[0611] The generative AI model passes the recipient address, subject, and message body to the email sending API.

[0612] Step 15:

[0613] The device calls the email sending API to send the email.

[0614] Step 16:

[0615] The device receives the transmission results and notifies the generative AI model of the results.

[0616] Step 17:

[0617] If the generative AI model is successful, it generates the message "Email sent" and if it fails, it generates an error message.

[0618] Step 18:

[0619] The terminal displays the generated message on a chat user interface or outputs it as a voice.

[0620] Calendar Reminder Setting Process

[0621] Step 1:

[0622] A user types or speaks into the chat user interface on the home screen, "Set a reminder for a meeting tomorrow at 10 AM."

[0623] Step 2:

[0624] The device receives input from the user, which, if spoken, is converted to text using speech recognition.

[0625] Step 3:

[0626] The device transfers the text data to the generative AI model.

[0627] Step 4:

[0628] The generative AI model analyzes the received text and recognizes it as a request to "set a reminder."

[0629] Step 5:

[0630] The generative AI model generates a message requesting meeting details (content, location, etc.).

[0631] Step 6:

[0632] The terminal displays this message on the chat user interface or outputs it as a voice message.

[0633] Step 7:

[0634] The user types or speaks meeting details.

[0635] Step 8:

[0636] The device receives the meeting details and forwards them to the generative AI model.

[0637] Step 9:

[0638] The generative AI model prepares the data to call the calendar application API.

[0639] Step 10:

[0640] The generative AI model passes the date, time, content, and location to the calendar application API.

[0641] Step 11:

[0642] The device calls the calendar application API to set the reminder.

[0643] Step 12:

[0644] The device receives the reminder setting results and notifies the generative AI model.

[0645] Step 13:

[0646] If the generative AI model is successful, it generates a message saying "Reminder set" and if it fails, it generates an error message.

[0647] Step 14:

[0648] The terminal displays the generated message on a chat user interface or outputs it as a voice.

[0649] Example 1

[0650] 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."

[0651] In conventional smart devices and virtual assistants, systems for quickly and accurately responding to user operation requests have not been fully established. Furthermore, it has been difficult to provide various functions in an integrated manner, resulting in reduced user convenience. The objective of this invention is to provide a system that utilizes generative AI models to quickly and accurately respond to various user requests and execute operations.

[0652] 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.

[0653] In this invention, the server uses a terminal equipped with a generative AI model and includes: means for displaying a chat user interface on a home screen; means for receiving input from a user and converting the voice input into text; means for sending the received text to the generative AI model and analyzing it; means for generating appropriate responses and operations and displaying them to the user; means for obtaining necessary additional information from the user; means for calling various APIs to execute operations; and means for notifying the user of the results of the operations. This enables prompt and accurate responses and operations to be executed in response to various user requests. A "generative AI model" is an artificial intelligence model that analyzes user input and generates appropriate responses and operations.

[0654] A "terminal" is a device that is equipped with a generative AI model and interacts with the user.

[0655] A "chat user interface" is an interface that is displayed on the home screen and accepts text and voice input from the user.

[0656] The "voice recognition function" is a function that converts a user's voice input into text.

[0657] An "API" is an application program interface for performing a specific function.

[0658] "Online Store" means a digital platform for providing additional features and applications.

[0659] The "calendar function" is a function for managing schedules and setting reminders.

[0660] The "email sending function" is a function for sending e-mail to a destination specified by the user.

[0661] The "means for changing various settings on behalf of the user" refers to a means for adjusting the system settings based on the user's instructions.

[0662] This invention is a system that uses a terminal equipped with a generative AI model to provide operations and services according to user requests. This system displays a chat user interface on the home screen, receives input from the user, analyzes it, and executes appropriate responses and operations.

[0663] System configuration

[0664] The system includes the following major components:

[0665] 1. Terminal: A device that contains a generative AI model and interacts with the user.

[0666] 2. Generative AI model: Artificial intelligence that analyzes user input and generates appropriate responses or actions.

[0667] 3. Chat user interface: An interface that appears on the home screen and accepts text and voice input.

[0668] 4. Speech recognition: A function that converts user voice input into text. For example, we use the Google Speech-to-Text API.

[0669] 5. Online Store: A platform that offers additional features and applications.

[0670] 6. Various APIs: Application Program Interfaces for performing specific functions, such as sending emails or calendar reminders.

[0671] Program processing

[0672] The program in this system operates in the following steps: First, the user inputs text into the chat user interface or issues a voice command. The input is received by the device and converted into text using a speech recognition function as needed. The text is then sent to the generative AI model for analysis. Based on the analysis results, the generative AI model determines and executes an appropriate response or operation.

[0673] For example, if a user instructs the model to "send a new email," the generative AI model will then ask the user for the necessary information (recipient, subject, and body) and receive each response. It will then call the email sending API and send the email. The operation result is generated by the generative AI model and notified to the user via the device.

[0674] Specific examples

[0675] Example 1: Calendar reminder settings

[0676] 1. User: "Set a reminder for a meeting tomorrow at 10 AM."

[0677] 2. Terminal: Receives user input and converts it to text using speech recognition if necessary.

[0678] 3. Generative AI model: Analyzes the received text and asks the user for meeting details (content, location, etc.).

[0679] 4. User: "Project X status review meeting. Location: Conference Room A."

[0680] 5. Generative AI model: Calls the calendar application API to set a reminder for the specified date and time.

[0681] 6. Device: Notify the user with the message "Reminder has been set."

[0682] Example 2: Sending email

[0683] 1. User: "Send me a new email."

[0684] 2. Terminal: Receives user input and converts it to text using speech recognition if necessary.

[0685] 3. Generative AI model: Analyzes the received text and asks the user for the email address to send it to.

[0686] 4. User: "example@example.com"

[0687] 5. Generative AI model: Ask for subject and body text.

[0688] 6. User: "Subject: 'Meeting Announcement', Body: 'We'll be meeting tomorrow at 10 AM.'"

[0689] 7. Generative AI model: Calls the email sending API and sends the email.

[0690] 8. Terminal: Notify the user with the message "Email has been sent."

[0691] Extensions

[0692] This system allows users to download and install additional features and applications using an online store. When a user requests "add a new plugin," the generative AI model accesses the online store, downloads, and installs the specified plugin. Once the installation is complete, the device notifies the user.

[0693] In this way, the present invention is a system that utilizes a generative AI model to respond to a variety of user requests, simplify terminal operation, and increase user convenience.

[0694] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0695] Step 1:

[0696] A user enters text into the chat user interface or issues a voice command, which generates input data. Text is received as input data, and voice is received as voice data.

[0697] Step 2:

[0698] The device receives user input. If it is voice input, it converts the voice data into text data using the speech recognition function. The input is voice data, and the output is text data. Specifically, it converts the voice into text using the Google Speech-to-Text API.

[0699] Step 3:

[0700] The text data received by the device is sent to the generative AI model. Here, the input data (text) is passed to the generative AI model, which then performs an analysis process. The generative AI model receives the input text and performs data calculations for analysis. This analysis clarifies the requested content.

[0701] Step 4:

[0702] The generative AI model analyzes the text data and determines the appropriate response or operation. Based on the analysis results, it generates a prompt to ask the user for the next required information (for example, recipient, subject, and body of an email when sending one). The input is the analyzed data, and the output is the prompt. The specific operation uses a natural language processing algorithm within the model.

[0703] Step 5:

[0704] The terminal will then generate a prompt and notify the user. If the user enters additional information or a response, that data will be sent back to the terminal. The input is the user's response data, and the output is the updated user data.

[0705] Step 6:

[0706] The generative AI model receives additional information from the user and executes operations by calling various APIs as necessary. For example, it calls an email sending API to send an email. In this procedure, the input is the updated user data, and the output is the result of executing the API call. As a specific operation, the actual operation is performed using the defined API interface.

[0707] Step 7:

[0708] The device notifies the user of the operation result. For example, a message such as "Email sent" or "Reminder set" is generated and provided to the user. The input is the result of the API call, and the output is the notification message. The device displays the message on the user's screen.

[0709] Through the above steps, a terminal system utilizing a generative AI model can respond quickly and accurately to user input and provide a variety of operations and services.

[0710] (Application example 1)

[0711] 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."

[0712] Autonomous vehicles require passengers to easily set their destinations and respond quickly in emergencies. However, current systems lack the high level of interactivity required for this, making it difficult for them to understand user instructions in real time and respond appropriately. Furthermore, complex systems with multiple functions can be difficult for users to use. Furthermore, there is a growing need for systems that can provide specific functions within autonomous vehicles and respond flexibly to situations.

[0713] 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.

[0714] In this invention, the server is a terminal equipped with a generative AI model and includes: means for displaying a chat user interface on a home screen; means for receiving input from a user and converting the voice input into text; means for analyzing the received text and performing various operations; means for notifying the user of the operation results; means for setting a destination in an autonomous vehicle; and means for sending notifications to contacts in the event of an emergency. This allows the user to easily set a destination and respond quickly to emergencies. Furthermore, by utilizing the generative AI model, the system becomes highly interactive and can respond appropriately to user instructions in real time.

[0715] A "generative AI model" is a type of artificial intelligence that analyzes user input and generates appropriate responses and operations.

[0716] "Terminal" refers to a device that is equipped with a generative AI model and interacts with the user.

[0717] A "chat user interface" is an interface that is displayed on the home screen and accepts text and voice input from the user.

[0718] The "means for converting speech input to text" is a processing function that recognizes the user's speech and converts it into text form.

[0719] "Means for analyzing received text and performing various operations" refers to a function that analyzes text received from a user using a generative AI model and performs specific operations based on the results.

[0720] "Means for notifying the user of the operation results" is a function for informing the user of the results of the operation performed by the generative AI model.

[0721] The "means for setting a destination in an autonomous vehicle" is a function that sets a destination based on user instructions within the autonomous vehicle system.

[0722] The "means for sending a notification to a contact in an emergency" is a function for quickly sending a notification to a designated contact in an emergency.

[0723] "Means to download and install from the Plug-in Market" refers to the ability to download and install additional features and applications from an online store.

[0724] "Means for providing plug-ins that optimize operation in an autonomous vehicle" refers to a function that provides additional plug-ins to optimize operation and functionality in an autonomous vehicle.

[0725] The "means for providing navigation information in real time" is a function for providing navigation information related to a destination or current location designated by the user in real time.

[0726] This invention relates to a system that automatically sets destinations and responds to emergencies based on user instructions in a device equipped with a generative AI model and in an autonomous vehicle. This system is highly interactive and provides operations and services that respond to user requests in real time.

[0727] Main components of the system

[0728] 1. Terminal: A device that is equipped with a generative AI model and interacts with the user. This terminal can be realized, for example, as a display installed in an autonomous vehicle or a smartphone held by the user.

[0729] 2. Generative AI models: These are artificial intelligence models that analyze user input and generate appropriate responses or actions. Examples include OpenAI's GPT-3.

[0730] 3. Chat user interface: This is the interface that appears on the home screen and accepts text and voice input from the user.

[0731] 4. Speech recognition function: This is a function that converts user voice input into text. For example, the speech_recognition module is used.

[0732] 5. Navigation module: This module allows users to set up navigation to a destination specified by the user. It uses map services such as Google Maps API.

[0733] 6. Emergency contact function: This function is used to send notifications to contacts in the event of an emergency. Email is typically sent using the SMTP protocol.

[0734] 7. Plug-in Market: An online store offering additional features and applications.

[0735] Program processing

[0736] The system works as follows: First, the device receives voice input from the user. The voice input is converted to text using the speech_recognition module. Next, the text is sent to a generative AI model (e.g., GPT-3) for analysis. Based on the results of this analysis, appropriate navigation settings and emergency contact operations are determined. For navigation, a route to the specified destination is set using the Google Maps API, and the results are notified to the user via the device. In the event of an emergency, a notification is sent to the specified contacts using SMTP.

[0737] Usage example

[0738] Example prompt 1:

[0739] User: "Please set your next destination to Tokyo Station."

[0740] The device converts the speech into text, and the generative AI model analyzes it to set navigation with "Tokyo Station" as the destination. It then calls the Google Maps API to start route guidance and notifies the user of the results.

[0741] Example prompt 2:

[0742] User: "Please contact your emergency contact."

[0743] The device converts the speech into text, which the generative AI model analyzes and sends a notification to the designated emergency contacts. An email is sent to the emergency contacts using the SMTP protocol.

[0744] In this way, the present invention provides a system that significantly improves passenger convenience in autonomous vehicles and also enables rapid response in emergencies.

[0745] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0746] Step 1:

[0747] The user inputs a command by voice, for example, "Please set the next destination to Tokyo Station."

[0748] Step 2:

[0749] The terminal receives the user's voice. The received voice data is converted into text data using a speech recognition module (speech_recognition). The input is voice data, and the output is text data. The specific operation of this conversion is to process the voice signal as digital data and analyze it using a language model.

[0750] Step 3:

[0751] The device sends the generated text to a generative AI model (e.g., GPT-3) for analysis. The input is the text data generated in step 2, and the output is the analysis results (including commands and specific operation instructions). Specifically, the process involves inputting text data into a generative AI model, analyzing the output, and determining the appropriate operation.

[0752] Step 4:

[0753] Based on the analysis results of the generative AI model, the navigation module (Google Maps API) is called. In this step, destination information is extracted from the analysis results and navigation settings are made. The input is the analysis results, and the output is the set route information. Specifically, the destination information is sent to the Google Maps API endpoint and route information is received.

[0754] Step 5:

[0755] The device notifies the user of navigation information obtained from the Google Maps API. The input is route information obtained from the Google Maps API, and the output is navigation instructions on the device's screen or via voice. Specifically, the device displays route information on the user interface and provides voice guidance if voice output is available.

[0756] Step 6:

[0757] In an emergency, the user may give instructions for emergency contact. For example, the user may give instructions by voice such as "Please contact the emergency contact." The input is voice data from the user.

[0758] Step 7:

[0759] As in step 2, the device receives the user's voice and converts it into text using speech recognition. The input is voice data and the output is text data.

[0760] Step 8:

[0761] The generative AI model analyzes the text data and identifies emergency contact instructions. The input is the text data, and the output is the emergency contact instructions.

[0762] Step 9:

[0763] The terminal uses the emergency contact function to send a notification to the specified contact. In this step, the input is the emergency contact instructions, and the output is the result of sending the notification using SMTP. The specific operation is to send an email containing the specified message to the emergency contact address.

[0764] In this way, a system is realized that performs navigation settings and emergency contact according to user instructions.

[0765] 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.

[0766] This invention is a system that uses a terminal equipped with a generative AI model to provide operations and services according to user requests. This system displays a chat user interface on the home screen, receives user input, analyzes it, and executes appropriate responses and operations. In addition, by incorporating an emotion engine, it recognizes the user's emotions and provides responses and operations according to the emotions.

[0767] System configuration

[0768] The system includes the following major components:

[0769] 1. Terminal: A device that contains a generative AI model and interacts with the user.

[0770] 2. Generative AI model: Artificial intelligence that analyzes user input and generates appropriate responses or actions.

[0771] 3. Chat user interface: An interface that appears on the home screen and accepts text and voice input.

[0772] 4. Speech recognition function: The function that converts the user's voice input into text.

[0773] 5. Plugin Market: An online store offering additional features and applications.

[0774] 6. APIs: Application Program Interfaces for performing specific functions such as sending emails or calendar reminders.

[0775] 7. Emotion Engine: Recognizes emotions from user voice and text inputs and generates corresponding responses.

[0776] Program processing

[0777] The program processing of this system is as follows: First, the user inputs text into the chat user interface or issues a voice command. The input is received by the device and converted into text using a speech recognition function as needed. Next, the text is sent to the generative AI model for analysis. Based on the analysis results, the generative AI model determines the appropriate response or operation.

[0778] The emotion engine analyzes emotions from the user's voice or text input and passes the results to the generative AI model, which then generates responses and actions taking the emotional data into account. For example, if the user is feeling stressed, the generative AI model will generate a more polite response. It can also suggest appropriate plugins based on the user's emotions.

[0779] Specific examples

[0780] Example 1: Emotion-recognition-based calendar reminder setting

[0781] User: "Set a reminder for a meeting tomorrow at 10 AM."

[0782] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[0783] Generative AI model: Analyzes the received text and asks the user for meeting details (content, location, etc.).

[0784] Emotion engine: Detects stress levels from the user's voice.

[0785] Generative AI models generate polite responses (e.g., "Good work. Can you tell me what the meeting was about?").

[0786] User: "Project X status review meeting in conference room A."

[0787] Generative AI model: Calls the calendar application API to set a reminder for the specified date and time.

[0788] On your device: Notify the user with the message "Your reminder has been set. Is there anything else we can help you with?"

[0789] Example 2: Emotion recognition in email sending

[0790] User: "Send me a new email."

[0791] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[0792] Generative AI model: Analyzes the received text and asks the user for the email address to send it to.

[0793] Emotion Engine: Detects gratitude from the user's voice.

[0794] Generative AI models generate responses tailored to the sentiment of gratitude (e.g., "Thank you. Can you give me your email address?").

[0795] User: "example@example.com"

[0796] Generative AI model: Ask for subject and body text.

[0797] User: "Subject: 'Meeting Announcement', Body: 'We have a meeting tomorrow at 10 AM.'"

[0798] Generative AI model: Calls the email sending API to send the email.

[0799] Terminal: Notify the user with the message "Your email has been sent. Is there anything else we can help you with?"

[0800] Extensions

[0801] This system can download and install additional functions and applications using the plugin market. When the user instructs the system to "add a new plugin," the generative AI model accesses the plugin market and downloads and installs the specified plugin. It can also suggest appropriate plugins based on the analysis results of the emotion engine. For example, if the user is feeling stressed, it will suggest relaxation-related plugins.

[0802] In this way, by utilizing a generative AI model and an emotion engine, the present invention provides a system that responds to various user requests, simplifies smartphone operation, and improves user convenience. Furthermore, by executing appropriate responses and operations based on the user's emotional state, more human-like interactions can be achieved.

[0803] The processing flow will be explained below.

[0804] Email sending process including emotion recognition

[0805] Step 1:

[0806] The user types or speaks "send a new email" in the chat user interface on the home screen.

[0807] Step 2:

[0808] The device receives input from the user, which, if spoken, is converted to text using speech recognition.

[0809] Step 3:

[0810] The device transfers the text data to the generative AI model.

[0811] Step 4:

[0812] The generative AI model analyzes the received text and recognizes that it is a request to "send a new email."

[0813] Step 5:

[0814] The generative AI model generates a message requesting the recipient's email address.

[0815] Step 6:

[0816] The terminal displays this message on the chat user interface or outputs it as a voice message.

[0817] Step 7:

[0818] The user inputs or speaks the email address of the recipient.

[0819] Step 8:

[0820] The device receives the recipient's email address and forwards it to the generative AI model.

[0821] Step 9:

[0822] The emotion engine analyzes the user input (voice or text) up to this point and identifies the user's emotion.

[0823] Step 10:

[0824] The generative AI model takes into account the output of the emotion engine to determine the appropriate tone of the response. For example, if the user is nervous, the generative AI model will generate a message that responds in a calm tone.

[0825] Step 11:

[0826] A generative AI model generates a message with a desired subject and body.

[0827] Step 12:

[0828] The terminal displays this message on the chat user interface or outputs it as a voice message.

[0829] Step 13:

[0830] The user types or speaks the subject and body of the email.

[0831] Step 14:

[0832] The device receives this information and forwards it to the generative AI model.

[0833] Step 15:

[0834] The generative AI model prepares the data to call the email sending API.

[0835] Step 16:

[0836] The generative AI model passes the recipient address, subject, and message body to the email sending API.

[0837] Step 17:

[0838] The device calls the email sending API to send the email.

[0839] Step 18:

[0840] The device receives the transmission results and notifies the generative AI model of the results.

[0841] Step 19:

[0842] If the generative AI model is successful, it generates the message "Email sent" and if it fails, it generates an error message.

[0843] Step 20:

[0844] The terminal displays the generated message on a chat user interface or outputs it as a voice.

[0845] Calendar reminder setting process using emotion recognition

[0846] Step 1:

[0847] A user types or speaks into the chat user interface on the home screen, "Set a reminder for a meeting tomorrow at 10 AM."

[0848] Step 2:

[0849] The device receives input from the user, which, if spoken, is converted to text using speech recognition.

[0850] Step 3:

[0851] The device transfers the text data to the generative AI model.

[0852] Step 4:

[0853] The generative AI model analyzes the received text and recognizes it as a request to "set a reminder."

[0854] Step 5:

[0855] The emotion engine analyzes the user input (voice or text) up to this point and identifies the user's emotion.

[0856] Step 6:

[0857] The generative AI model takes into account the output of the emotion engine and asks the user for meeting details (content, location, etc.) in an appropriate tone.

[0858] Step 7:

[0859] The terminal displays the message generated by the generation AI model on the chat user interface or outputs it as audio.

[0860] Step 8:

[0861] The user types or speaks meeting details.

[0862] Step 9:

[0863] The device receives the meeting details and forwards them to the generative AI model.

[0864] Step 10:

[0865] The generative AI model prepares the data to call the calendar application API.

[0866] Step 11:

[0867] The generative AI model passes the date, time, content, and location to the calendar application API.

[0868] Step 12:

[0869] The device calls the calendar application API to set the reminder.

[0870] Step 13:

[0871] The device receives the reminder setting results and notifies the generative AI model.

[0872] Step 14:

[0873] If the generative AI model is successful, it generates a message saying "Reminder set" and if it fails, it generates an error message.

[0874] Step 15:

[0875] The terminal displays the generated message on a chat user interface or outputs it as a voice.

[0876] The above is the specific processing flow in a system equipped with a generative AI model and an emotion engine.

[0877] Example 2

[0878] 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."

[0879] Conventional devices could only provide simple text responses and operations in response to user input, making it difficult to realize responses and operations that take the user's emotions into account. Furthermore, there were limited ways to provide additional functions, resulting in low user convenience. Furthermore, there was a lack of means to optimally provide specific functions, such as calendar reminders and email sending functions, based on the user's emotions.

[0880] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for displaying a chat user interface on a home screen, a means for converting a voice input from a user into text, a means for sending data to a generative AI model and having it analyze the data, a means for the generative AI model to determine a response or operation based on emotion data from the emotion engine, a means for notifying the user of the response, a means for downloading and installing additional functions or applications from an online store, a means for suggesting additional functions based on the user's emotional state, and a means for performing a calendar reminder function, an email sending function, and various setting changes on behalf of the user. This makes it possible to provide responses and operations that take the user's emotions into consideration, and to suggest additional functions.

[0881] A "generative AI model" is an artificial intelligence that analyzes user input data and generates appropriate responses and operations.

[0882] A "terminal" is a device that is equipped with a generative AI model and interacts with the user.

[0883] The "chat user interface" is an interface that is displayed on the home screen of the terminal and that accepts user input.

[0884] The "voice recognition function" is a function that converts a user's voice input into text.

[0885] The "emotion engine" is a function that recognizes emotions from user voice and text input and provides them to the generative AI model.

[0886] "Online Store" means a digital marketplace for offering additional features and applications.

[0887] The "Calendar reminder function" is a function that sets a reminder at a specified date and time and notifies you.

[0888] The "email sending function" is a function that creates and sends email based on user instructions.

[0889] The "means for changing various settings" is a function that automatically changes settings based on the user's request.

[0890] This invention relates to a system that combines a generative AI model and an emotion engine, and aims to improve convenience and user experience by analyzing user input data and providing appropriate responses and operations. This system is configured to install a generative AI model on a terminal and display a chat user interface on the home screen, allowing users to easily access it.

[0891] System Configuration

[0892] The main hardware and software components of the system are as follows:

[0893] 1. Device: A device that is equipped with a generative AI model and interacts with the user. Specific examples include smartphones and tablet PCs.

[0894] 2. Generative AI model: This is an artificial intelligence that analyzes user input data and generates appropriate responses and operations. It uses natural language processing (NLP) technology to accurately analyze user input.

[0895] 3. Chat user interface: An interface that appears on the device's home screen and accepts text or voice input from the user, allowing the user to easily communicate their requests to the system.

[0896] 4. Speech recognition function: This function converts the user's voice input into text. This conversion allows the voice input to be analyzed in the same way as text.

[0897] 5. Emotion Engine: A system that recognizes emotions from user voice and text inputs and provides the results to a generative AI model. This capability allows the system to understand the user's emotional state and optimize responses and suggestions.

[0898] 6. Online Store: A digital marketplace offering additional features and applications, allowing users to extend functionality as needed.

[0899] 7. APIs: Application Programming Interfaces are used to perform specific operations, such as setting a calendar reminder or sending an email.

[0900] Implementation method

[0901] When a user inputs commands into the chat user interface via text or voice, the data is received by the device. In the case of voice input, the data is converted into text using a speech recognition function. The text data is then sent to a generative AI model and analyzed using natural language processing technology. The generative AI model determines the appropriate response or action based on the analysis results, taking into account the emotional data provided by the emotion engine.

[0902] For example, if a user types, "Set a reminder for a meeting tomorrow at 10 AM," the system will parse this instruction and set a reminder for the specified date and time through the calendar API. Furthermore, if the emotion engine detects the user's stress, the generative AI model will generate a polite response such as, "Thank you for your hard work. Can you let me know what the meeting is about?"

[0903] Specific examples

[0904] Example 1: Emotion-recognition-based calendar reminder setting

[0905] User: "Set a reminder for a meeting tomorrow at 10 AM."

[0906] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[0907] Generative AI model: Analyzes the received text and asks the user for meeting details (content, location, etc.).

[0908] Emotion engine: Detects stress levels from the user's voice.

[0909] Generative AI models: Generate polite responses (e.g., "Good work. Can you tell me what the meeting was about?").

[0910] User: "Project X status review meeting in conference room A."

[0911] Generative AI model: Calls the calendar application API to set a reminder at the specified date and time.

[0912] On your device: Notify the user with the message "Your reminder has been set. Is there anything else we can help you with?"

[0913] Example 2: Emotion recognition in email sending

[0914] User: "Send me a new email."

[0915] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[0916] Generative AI model: Analyzes the received text and asks the user for the email address to send it to.

[0917] Emotion Engine: Detects gratitude from the user's voice.

[0918] Generative AI models: Generate responses tailored to the sentiment of gratitude (e.g., "Thank you. Can you give me your email address?").

[0919] User: "example@example.com"

[0920] Generative AI model: Ask for subject and body text.

[0921] User: "Subject: 'Meeting Announcement', Body: 'We have a meeting tomorrow at 10 AM.'"

[0922] Generative AI model: Calls the email sending API to send the email.

[0923] Terminal: Notify the user with the message "Your email has been sent. Is there anything else we can help you with?"

[0924] In this way, the system analyzes the user's input and provides appropriate responses and operations that take into account the emotion data. However, this embodiment is merely an example, and the present invention can be implemented in other ways without departing from the scope of the present invention.

[0925] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0926] Step 1:

[0927] The user provides input in the chat user interface

[0928] A user inputs instructions into a chat user interface using text or voice. The input data contains the user's intent or request. For example, "Set a reminder for a meeting tomorrow at 10 AM." The string of data (text or voice) is sent to the system.

[0929] Step 2:

[0930] The terminal receives input

[0931] The terminal receives text and voice data entered by the user. This is where the input data is first captured by the system. For example, when a user enters voice input, the voice data is stored in the terminal.

[0932] Step 3:

[0933] Your device converts your voice input into text

[0934] When voice input is made, the device uses speech recognition to convert the speech to text. The input is voice data, and the output is the equivalent text data. For example, voice data such as "Set a reminder for a meeting tomorrow at 10:00 AM" is converted to text such as "Set a reminder for a meeting tomorrow at 10:00 AM."

[0935] Step 4:

[0936] The device sends data to the generative AI model

[0937] The terminal sends the received or converted text data to the generative AI model. The input is text data, and the output is data waiting to be interpreted by the generative AI model. The data is sent to the generative AI model server using a communication protocol such as an HTTP request.

[0938] Step 5:

[0939] A generative AI model analyzes the input

[0940] The generative AI model analyzes the received text data. The input is text data, and the output is instructions or operational decisions based on the analysis results. The generative AI model uses natural language processing techniques to analyze the text and interpret the user's request. For example, it can understand the instruction "Set a meeting reminder."

[0941] Step 6:

[0942] The emotion engine provides emotion data to the generative AI model

[0943] The emotion engine analyzes emotions from the tone and content of a user's voice or text and provides that data to a generative AI model. The input is voice or text data, and the output is emotion data. For example, it can analyze a user's stress level from their tone of voice.

[0944] Step 7:

[0945] Generative AI models determine responses and actions

[0946] The generative AI model takes emotional data into account to determine the appropriate response or action. The input is the user's instructions and emotional data, and the output is the determined response or action. For example, it generates responses such as "Ask for reminder settings details" or "Confirm meeting details."

[0947] Step 8:

[0948] The terminal notifies the user of the response

[0949] The device notifies the user of the response from the generative AI model. The input is the response data from the generative AI model, and the output is the response that is displayed or spoken to the user. For example, a message such as "Thank you for your hard work. Could you please let me know the details of the meeting?" is displayed.

[0950] Step 9:

[0951] If necessary, the device calls the relevant API to perform the process.

[0952] When necessary, the device will call relevant application program interfaces such as a calendar API or email API to perform specific operations. The input is the user's instruction and the analysis result of the generative AI model, and the output is the result of the performed operation. For example, calling a calendar API to set a reminder.

[0953] (Application example 2)

[0954] 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."

[0955] Conventional systems using generative AI models and emotion recognition engines mainly respond to basic user operational requests, making it difficult to efficiently interact with customers in physical stores. In particular, they are insufficient when providing detailed information, such as responses based on the customer's emotional state, checking the stock of specific products, or guiding customers to their location. Therefore, in order to improve customer satisfaction in physical stores, it is necessary to provide more advanced information and responses that reflect emotions.

[0956] 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.

[0957] In this invention, the server is a terminal equipped with a generative AI model, and includes means for displaying a chat user interface on a home screen, means for receiving input from a user and converting the voice input into text, means for analyzing the received text and performing various operations, means for notifying the user of the operation results, means for analyzing the user's emotions using an emotion recognition engine, means for checking product inventory status, and means for providing the shelf location of a specific product. This allows for more advanced interaction with customers, making it possible to provide specific product information and inventory status, and to respond appropriately to the customer's emotional state.

[0958] ---

[0959] OK, now we'll create definitions for each of the key words in the rewritten claims.

[0960] definition statement

[0961] ---

[0962] A "generative AI model" is an artificial intelligence that analyzes user input and generates appropriate responses and operations.

[0963] A "chat user interface" is a user interface that is displayed on the home screen and accepts text and voice input.

[0964] A "means for converting speech input to text" is a technique for converting a user's speech input into text form.

[0965] The "means for performing various operations" is a system that performs the necessary operations based on the analyzed text.

[0966] The "means for notifying the user of the operation result" is a function for notifying the user of the result of the executed operation.

[0967] An "emotion recognition engine" is an algorithm that recognizes and analyzes emotions from the user's voice or text input.

[0968] The "means for checking product inventory status" is a system for checking whether a specific product is in stock.

[0969] The "means for providing the shelf location of a specific product" is a function that guides the user to the location where the product is stored.

[0970] ---

[0971] Understood. Now, let's create the detailed description based on the information we have provided so far.

[0972] MODE FOR CARRYING OUT THE INVENTION

[0973] ---

[0974] System Overview

[0975] This invention is a customer service system for brick-and-mortar stores that uses a terminal equipped with a generative AI model and an emotion recognition engine. This system displays a chat user interface on the screen and accepts voice and text input in response to questions and requests from customers in the store. The generative AI model analyzes these inputs and executes appropriate responses and operations. Furthermore, the emotion recognition engine can analyze customer emotions and provide responses that correspond to those emotions.

[0976] System configuration

[0977] The system includes the following main components:

[0978] 1. Device: A device that is equipped with a generative AI model and interacts with the user. Examples of devices that can be used include smartphones and tablets.

[0979] 2. Generative AI model: An artificial intelligence that analyzes user input and generates appropriate responses or actions. For example, natural language processing models (such as BERT and GPT-3) can be applied.

[0980] 3. Chat user interface: An interface that appears on the device's home screen and accepts text and voice input.

[0981] 4. Speech recognition: A function that converts user voice input into text. Examples of services that can be used include Google Cloud Speech-to-Text and Amazon Transcribe.

[0982] 5. Emotion Recognition Engine: An engine that recognizes emotions from the user's voice and text input and generates corresponding responses. For example, IBM Watson Tone Analyzer can be used.

[0983] 6. Various APIs: Application program interfaces for checking product inventory status and providing product shelf location information. RESTful APIs are commonly used for this purpose.

[0984] Operation flow

[0985] The system works as follows: First, a customer enters text into the chat user interface or issues a voice command. The input is received by the device, and in the case of voice input, it is converted into text using a speech recognition function. The text is then sent to a generative AI model for analysis. Based on the analysis results, the generative AI model determines the appropriate response or action.

[0986] The emotion recognition engine analyzes emotions from customer voice and text inputs and passes the results to a generative AI model. The generative AI model generates responses and actions taking emotional data into account. For example, if a customer's emotions indicate stress, the generative AI model will generate a more polite response. It can also provide relaxation-related information and suggestions based on their emotions.

[0987] Specific examples

[0988] Example 1: Checking inventory

[0989] User: "Can you tell me if this item is in stock?"

[0990] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[0991] Generative AI model: Analyzes the incoming text and recognizes it as an instruction to check inventory.

[0992] Emotion Recognition Engine: Analyzes emotions from user text.

[0993] Generative AI model: Calls the stock availability API to check the availability of the specified product.

[0994] Terminal: Notifies the user with the message "The product is in stock."

[0995] Example 2: Product location guidance

[0996] User: "Where is this item?"

[0997] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[0998] Generative AI model: Analyzes the received text and recognizes it as instructions to guide shelf locations.

[0999] Emotion Recognition Engine: Analyzes emotions from user text.

[1000] Generative AI model: Calls the product shelf location information API to obtain the location of the specified product.

[1001] Terminal: Notifies the user with the message "The product is located in the second section of the store."

[1002] Prompt Sentence Examples

[1003] Please let me know if you have this item in stock.

[1004] "Where is this item located?"

[1005] This will make customer service in physical stores more efficient and improve customer satisfaction.

[1006] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1007] Understood. Now, I will explain the processing flow of the system program that realizes the application example, broken down into specific processing steps.

[1008] Program processing steps

[1009] ---

[1010] Step 1:

[1011] The user provides voice or text input to the chat user interface.

[1012] What happens: The user says, "Tell me if this item is in stock."

[1013] Input: User's voice input.

[1014] Output: Audio data.

[1015] Step 2:

[1016] The device receives voice input and converts it into text using speech recognition.

[1017] How it works: The device receives the audio and uses Google Cloud Speech-to-Text to convert it into text: "Tell me if this item is in stock."

[1018] Input: Audio data.

[1019] Output: Text data ("Tell me if this item is in stock").

[1020] Step 3:

[1021] The received text is sent to a generative AI model for analysis.

[1022] How it works: The device sends text data to a generative AI model (e.g., GPT-3) and receives an analysis result, which determines that the text is a request for inventory check.

[1023] Input: Text data ("Tell me if this item is in stock").

[1024] Output: Analysis result data (command "check_inventory", item "requested_item").

[1025] Step 4:

[1026] Analyze user emotions using an emotion recognition engine.

[1027] How it works: The device sends text data to an emotion recognition engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotions. The analysis results indicate that the user has a neutral attitude.

[1028] Input: Text data ("Tell me if this item is in stock").

[1029] Output: Emotion data (neutral).

[1030] Step 5:

[1031] Call the inventory status API to check the product's inventory status.

[1032] Operation: The device sends a request to the stock confirmation API to obtain the stock status of the specified product. For example, a request is sent via the RESTful API to check the stock status of "requested_item".

[1033] Input: Analysis result data (command "check_inventory", item "requested_item").

[1034] Output: Inventory status data (in stock).

[1035] Step 6:

[1036] Generate appropriate responses based on analysis results and sentiment data.

[1037] How it works: The generative AI model takes into account the analysis results and sentiment data and generates a response message saying, "The item is in stock."

[1038] Input: Stock status data (in stock), Sentiment data (neutral).

[1039] Output: Response message ("The item is in stock.").

[1040] Step 7:

[1041] Notify the user of the operation result.

[1042] Operation: The terminal notifies the user of the reply message through the chat user interface.

[1043] Input: Response message ("Item is in stock.").

[1044] Output: A text message that is displayed to the user.

[1045] This will enable customers to smoothly request product information in-store and receive appropriate responses.

[1046] 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.

[1047] 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.

[1048] 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.

[1049] [Third embodiment]

[1050] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1051] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1052] 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).

[1053] 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.

[1054] 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.

[1055] 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).

[1056] 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.

[1057] 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.

[1058] 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.

[1059] 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.

[1060] 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.

[1061] 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."

[1062] This invention is a system that uses a terminal equipped with a generative AI model to provide operations and services according to user requests. This system displays a chat user interface on the home screen, receives input from the user, analyzes it, and executes appropriate responses and operations.

[1063] System configuration

[1064] The system includes the following major components:

[1065] 1. Terminal: A device that contains a generative AI model and interacts with the user.

[1066] 2. Generative AI model: Artificial intelligence that analyzes user input and generates appropriate responses or actions.

[1067] 3. Chat user interface: An interface that appears on the home screen and accepts text and voice input.

[1068] 4. Speech recognition function: The function that converts the user's voice input into text.

[1069] 5. Plugin Market: An online store offering additional features and applications.

[1070] 6. Various APIs: Application Program Interfaces for performing specific functions such as sending emails or calendar reminders.

[1071] Program processing

[1072] The program processing of this system is as follows: First, the user inputs text into the chat user interface or issues a voice command. The input is received by the device and converted into text using a speech recognition function as needed. Next, the text is sent to the generative AI model for analysis. Based on the analysis results, the generative AI model determines the appropriate response or operation.

[1073] For example, if a user types "send a new email," the generative AI model next asks the user for the necessary information (recipient, subject, and body) and receives each answer. It then calls the email sending API to send the email. The operation result is generated by the generative AI model and notified to the user via the device.

[1074] Specific examples

[1075] Example 1: Calendar reminder settings

[1076] User: "Set a reminder for a meeting tomorrow at 10 AM."

[1077] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[1078] Generative AI model: Analyzes the received text and asks the user for meeting details (content, location, etc.).

[1079] User: "Project X status review meeting in conference room A."

[1080] Generative AI model: Calls the calendar application API to set a reminder for the specified date and time.

[1081] On the device: The user is notified with the message "Reminder set."

[1082] Example 2: Sending email

[1083] User: "Send me a new email."

[1084] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[1085] Generative AI model: Analyzes the received text and asks the user for the email address to send it to.

[1086] User: "example@example.com"

[1087] Generative AI model: Ask for subject and body text.

[1088] User: "Subject: 'Meeting Announcement', Body: 'We have a meeting tomorrow at 10 AM.'"

[1089] Generative AI model: Calls the email sending API to send the email.

[1090] Terminal: Notify the user with the message "Email has been sent."

[1091] Extensions

[1092] This system uses a plugin market to allow users to download and install additional functions and applications. When a user instructs the system to "add a new plugin," the generative AI model accesses the plugin market and downloads and installs the specified plugin. Once the installation is complete, the device notifies the user.

[1093] In this way, the present invention is a system that utilizes generative AI models to respond to various user requests, simplifying smartphone operation and increasing user convenience.

[1094] The processing flow will be explained below.

[1095] Email sending process

[1096] Step 1:

[1097] The user types or speaks "send a new email" in the chat user interface on the home screen.

[1098] Step 2:

[1099] The device receives input from the user, which, if spoken, is converted to text using speech recognition.

[1100] Step 3:

[1101] The device transfers the text data to the generative AI model.

[1102] Step 4:

[1103] The generative AI model analyzes the received text and recognizes that it is a request to "send a new email."

[1104] Step 5:

[1105] The generative AI model generates a message requesting the recipient's email address.

[1106] Step 6:

[1107] The terminal displays this message on the chat user interface or outputs it as a voice message.

[1108] Step 7:

[1109] The user inputs or speaks the email address of the recipient.

[1110] Step 8:

[1111] The device receives the recipient's email address and forwards it to the generative AI model.

[1112] Step 9:

[1113] A generative AI model generates a message with a desired subject and body.

[1114] Step 10:

[1115] The terminal displays this message on the chat user interface or outputs it as a voice message.

[1116] Step 11:

[1117] The user types or speaks the subject and body of the email.

[1118] Step 12:

[1119] The device receives this information and forwards it to the generative AI model.

[1120] Step 13:

[1121] The generative AI model prepares the data to call the email sending API.

[1122] Step 14:

[1123] The generative AI model passes the recipient address, subject, and message body to the email sending API.

[1124] Step 15:

[1125] The device calls the email sending API to send the email.

[1126] Step 16:

[1127] The device receives the transmission results and notifies the generative AI model of the results.

[1128] Step 17:

[1129] If the generative AI model is successful, it generates the message "Email sent" and if it fails, it generates an error message.

[1130] Step 18:

[1131] The terminal displays the generated message on a chat user interface or outputs it as a voice.

[1132] Calendar Reminder Setting Process

[1133] Step 1:

[1134] A user types or speaks into the chat user interface on the home screen, "Set a reminder for a meeting tomorrow at 10 AM."

[1135] Step 2:

[1136] The device receives input from the user, which, if spoken, is converted to text using speech recognition.

[1137] Step 3:

[1138] The device transfers the text data to the generative AI model.

[1139] Step 4:

[1140] The generative AI model analyzes the received text and recognizes it as a request to "set a reminder."

[1141] Step 5:

[1142] The generative AI model generates a message requesting meeting details (content, location, etc.).

[1143] Step 6:

[1144] The terminal displays this message on the chat user interface or outputs it as a voice message.

[1145] Step 7:

[1146] The user types or speaks meeting details.

[1147] Step 8:

[1148] The device receives the meeting details and forwards them to the generative AI model.

[1149] Step 9:

[1150] The generative AI model prepares the data to call the calendar application API.

[1151] Step 10:

[1152] The generative AI model passes the date, time, content, and location to the calendar application API.

[1153] Step 11:

[1154] The device calls the calendar application API to set the reminder.

[1155] Step 12:

[1156] The device receives the reminder setting results and notifies the generative AI model.

[1157] Step 13:

[1158] If the generative AI model is successful, it generates a message saying "Reminder set" and if it fails, it generates an error message.

[1159] Step 14:

[1160] The terminal displays the generated message on a chat user interface or outputs it as a voice.

[1161] Example 1

[1162] 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."

[1163] In conventional smart devices and virtual assistants, systems for quickly and accurately responding to user operation requests have not been fully established. Furthermore, it has been difficult to provide various functions in an integrated manner, resulting in reduced user convenience. The objective of this invention is to provide a system that utilizes generative AI models to quickly and accurately respond to various user requests and execute operations.

[1164] 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.

[1165] In this invention, the server uses a terminal equipped with a generative AI model and includes: means for displaying a chat user interface on a home screen; means for receiving input from a user and converting the voice input into text; means for sending the received text to the generative AI model and analyzing it; means for generating appropriate responses and operations and displaying them to the user; means for obtaining necessary additional information from the user; means for calling various APIs to execute operations; and means for notifying the user of the results of the operations. This enables prompt and accurate responses and operations to be executed in response to various user requests. A "generative AI model" is an artificial intelligence model that analyzes user input and generates appropriate responses and operations.

[1166] A "terminal" is a device that is equipped with a generative AI model and interacts with the user.

[1167] A "chat user interface" is an interface that is displayed on the home screen and accepts text and voice input from the user.

[1168] The "voice recognition function" is a function that converts a user's voice input into text.

[1169] An "API" is an application program interface for performing a specific function.

[1170] "Online Store" means a digital platform for providing additional features and applications.

[1171] The "calendar function" is a function for managing schedules and setting reminders.

[1172] The "email sending function" is a function for sending e-mail to a destination specified by the user.

[1173] The "means for changing various settings on behalf of the user" refers to a means for adjusting the system settings based on the user's instructions.

[1174] This invention is a system that uses a terminal equipped with a generative AI model to provide operations and services according to user requests. This system displays a chat user interface on the home screen, receives input from the user, analyzes it, and executes appropriate responses and operations.

[1175] System configuration

[1176] The system includes the following major components:

[1177] 1. Terminal: A device that contains a generative AI model and interacts with the user.

[1178] 2. Generative AI model: Artificial intelligence that analyzes user input and generates appropriate responses or actions.

[1179] 3. Chat user interface: An interface that appears on the home screen and accepts text and voice input.

[1180] 4. Speech recognition: A function that converts user voice input into text. For example, we use the Google Speech-to-Text API.

[1181] 5. Online Store: A platform that offers additional features and applications.

[1182] 6. Various APIs: Application Program Interfaces for performing specific functions, such as sending emails or calendar reminders.

[1183] Program processing

[1184] The program in this system operates in the following steps: First, the user inputs text into the chat user interface or issues a voice command. The input is received by the device and converted into text using a speech recognition function as needed. The text is then sent to the generative AI model for analysis. Based on the analysis results, the generative AI model determines and executes an appropriate response or operation.

[1185] For example, if a user instructs the model to "send a new email," the generative AI model will then ask the user for the necessary information (recipient, subject, and body) and receive each response. It will then call the email sending API and send the email. The operation result is generated by the generative AI model and notified to the user via the device.

[1186] Specific examples

[1187] Example 1: Calendar reminder settings

[1188] 1. User: "Set a reminder for a meeting tomorrow at 10 AM."

[1189] 2. Terminal: Receives user input and converts it to text using speech recognition if necessary.

[1190] 3. Generative AI model: Analyzes the received text and asks the user for meeting details (content, location, etc.).

[1191] 4. User: "Project X status review meeting. Location: Conference Room A."

[1192] 5. Generative AI model: Calls the calendar application API to set a reminder for the specified date and time.

[1193] 6. Device: Notify the user with the message "Reminder has been set."

[1194] Example 2: Sending email

[1195] 1. User: "Send me a new email."

[1196] 2. Terminal: Receives user input and converts it to text using speech recognition if necessary.

[1197] 3. Generative AI model: Analyzes the received text and asks the user for the email address to send it to.

[1198] 4. User: "example@example.com"

[1199] 5. Generative AI model: Ask for subject and body text.

[1200] 6. User: "Subject: 'Meeting Announcement', Body: 'We'll be meeting tomorrow at 10 AM.'"

[1201] 7. Generative AI model: Calls the email sending API and sends the email.

[1202] 8. Terminal: Notify the user with the message "Email has been sent."

[1203] Extensions

[1204] This system allows users to download and install additional features and applications using an online store. When a user requests "add a new plugin," the generative AI model accesses the online store, downloads, and installs the specified plugin. Once the installation is complete, the device notifies the user.

[1205] In this way, the present invention is a system that utilizes a generative AI model to respond to a variety of user requests, simplify terminal operation, and increase user convenience.

[1206] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1207] Step 1:

[1208] A user enters text into the chat user interface or issues a voice command, which generates input data. Text is received as input data, and voice is received as voice data.

[1209] Step 2:

[1210] The device receives user input. If it is voice input, it converts the voice data into text data using the speech recognition function. The input is voice data, and the output is text data. Specifically, it converts the voice into text using the Google Speech-to-Text API.

[1211] Step 3:

[1212] The text data received by the device is sent to the generative AI model. Here, the input data (text) is passed to the generative AI model, which then performs an analysis process. The generative AI model receives the input text and performs data calculations for analysis. This analysis clarifies the requested content.

[1213] Step 4:

[1214] The generative AI model analyzes the text data and determines the appropriate response or operation. Based on the analysis results, it generates a prompt to ask the user for the next required information (for example, recipient, subject, and body of an email when sending one). The input is the analyzed data, and the output is the prompt. The specific operation uses a natural language processing algorithm within the model.

[1215] Step 5:

[1216] The terminal will then generate a prompt and notify the user. If the user enters additional information or a response, that data will be sent back to the terminal. The input is the user's response data, and the output is the updated user data.

[1217] Step 6:

[1218] The generative AI model receives additional information from the user and executes operations by calling various APIs as necessary. For example, it calls an email sending API to send an email. In this procedure, the input is the updated user data, and the output is the result of executing the API call. As a specific operation, the actual operation is performed using the defined API interface.

[1219] Step 7:

[1220] The device notifies the user of the operation result. For example, a message such as "Email sent" or "Reminder set" is generated and provided to the user. The input is the result of the API call, and the output is the notification message. The device displays the message on the user's screen.

[1221] Through the above steps, a terminal system utilizing a generative AI model can respond quickly and accurately to user input and provide a variety of operations and services.

[1222] (Application example 1)

[1223] 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."

[1224] Autonomous vehicles require passengers to easily set their destinations and respond quickly in emergencies. However, current systems lack the high level of interactivity required for this, making it difficult for them to understand user instructions in real time and respond appropriately. Furthermore, complex systems with multiple functions can be difficult for users to use. Furthermore, there is a growing need for systems that can provide specific functions within autonomous vehicles and respond flexibly to situations.

[1225] 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.

[1226] In this invention, the server is a terminal equipped with a generative AI model and includes: means for displaying a chat user interface on a home screen; means for receiving input from a user and converting the voice input into text; means for analyzing the received text and performing various operations; means for notifying the user of the operation results; means for setting a destination in an autonomous vehicle; and means for sending notifications to contacts in the event of an emergency. This allows the user to easily set a destination and respond quickly to emergencies. Furthermore, by utilizing the generative AI model, the system becomes highly interactive and can respond appropriately to user instructions in real time.

[1227] A "generative AI model" is a type of artificial intelligence that analyzes user input and generates appropriate responses and operations.

[1228] "Terminal" refers to a device that is equipped with a generative AI model and interacts with the user.

[1229] A "chat user interface" is an interface that is displayed on the home screen and accepts text and voice input from the user.

[1230] The "means for converting speech input to text" is a processing function that recognizes the user's speech and converts it into text form.

[1231] "Means for analyzing received text and performing various operations" refers to a function that analyzes text received from a user using a generative AI model and performs specific operations based on the results.

[1232] "Means for notifying the user of the operation results" is a function for informing the user of the results of the operation performed by the generative AI model.

[1233] The "means for setting a destination in an autonomous vehicle" is a function that sets a destination based on user instructions within the autonomous vehicle system.

[1234] The "means for sending a notification to a contact in an emergency" is a function for quickly sending a notification to a designated contact in an emergency.

[1235] "Means to download and install from the Plug-in Market" refers to the ability to download and install additional features and applications from an online store.

[1236] "Means for providing plug-ins that optimize operation in an autonomous vehicle" refers to a function that provides additional plug-ins to optimize operation and functionality in an autonomous vehicle.

[1237] The "means for providing navigation information in real time" is a function for providing navigation information related to a destination or current location designated by the user in real time.

[1238] This invention relates to a system that automatically sets destinations and responds to emergencies based on user instructions in a device equipped with a generative AI model and in an autonomous vehicle. This system is highly interactive and provides operations and services that respond to user requests in real time.

[1239] Main components of the system

[1240] 1. Terminal: A device that is equipped with a generative AI model and interacts with the user. This terminal can be realized, for example, as a display installed in an autonomous vehicle or a smartphone held by the user.

[1241] 2. Generative AI models: These are artificial intelligence models that analyze user input and generate appropriate responses or actions. Examples include OpenAI's GPT-3.

[1242] 3. Chat user interface: This is the interface that appears on the home screen and accepts text and voice input from the user.

[1243] 4. Speech recognition function: This is a function that converts user voice input into text. For example, the speech_recognition module is used.

[1244] 5. Navigation module: This module allows users to set up navigation to a destination specified by the user. It uses map services such as Google Maps API.

[1245] 6. Emergency contact function: This function is used to send notifications to contacts in the event of an emergency. Email is typically sent using the SMTP protocol.

[1246] 7. Plug-in Market: An online store offering additional features and applications.

[1247] Program processing

[1248] The system works as follows: First, the device receives voice input from the user. The voice input is converted to text using the speech_recognition module. Next, the text is sent to a generative AI model (e.g., GPT-3) for analysis. Based on the results of this analysis, appropriate navigation settings and emergency contact operations are determined. For navigation, a route to the specified destination is set using the Google Maps API, and the results are notified to the user via the device. In the event of an emergency, a notification is sent to the specified contacts using SMTP.

[1249] Usage example

[1250] Example prompt 1:

[1251] User: "Please set your next destination to Tokyo Station."

[1252] The device converts the speech into text, and the generative AI model analyzes it to set navigation with "Tokyo Station" as the destination. It then calls the Google Maps API to start route guidance and notifies the user of the results.

[1253] Example prompt 2:

[1254] User: "Please contact your emergency contact."

[1255] The device converts the speech into text, which the generative AI model analyzes and sends a notification to the designated emergency contacts. An email is sent to the emergency contacts using the SMTP protocol.

[1256] In this way, the present invention provides a system that significantly improves passenger convenience in autonomous vehicles and also enables rapid response in emergencies.

[1257] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1258] Step 1:

[1259] The user inputs a command by voice, for example, "Please set the next destination to Tokyo Station."

[1260] Step 2:

[1261] The terminal receives the user's voice. The received voice data is converted into text data using a speech recognition module (speech_recognition). The input is voice data, and the output is text data. The specific operation of this conversion is to process the voice signal as digital data and analyze it using a language model.

[1262] Step 3:

[1263] The device sends the generated text to a generative AI model (e.g., GPT-3) for analysis. The input is the text data generated in step 2, and the output is the analysis results (including commands and specific operation instructions). Specifically, the process involves inputting text data into a generative AI model, analyzing the output, and determining the appropriate operation.

[1264] Step 4:

[1265] Based on the analysis results of the generative AI model, the navigation module (Google Maps API) is called. In this step, destination information is extracted from the analysis results and navigation settings are made. The input is the analysis results, and the output is the set route information. Specifically, the destination information is sent to the Google Maps API endpoint and route information is received.

[1266] Step 5:

[1267] The device notifies the user of navigation information obtained from the Google Maps API. The input is route information obtained from the Google Maps API, and the output is navigation instructions on the device's screen or via voice. Specifically, the device displays route information on the user interface and provides voice guidance if voice output is available.

[1268] Step 6:

[1269] In an emergency, the user may give instructions for emergency contact. For example, the user may give instructions by voice such as "Please contact the emergency contact." The input is voice data from the user.

[1270] Step 7:

[1271] As in step 2, the device receives the user's voice and converts it into text using speech recognition. The input is voice data and the output is text data.

[1272] Step 8:

[1273] The generative AI model analyzes the text data and identifies emergency contact instructions. The input is the text data, and the output is the emergency contact instructions.

[1274] Step 9:

[1275] The terminal uses the emergency contact function to send a notification to the specified contact. In this step, the input is the emergency contact instructions, and the output is the result of sending the notification using SMTP. The specific operation is to send an email containing the specified message to the emergency contact address.

[1276] In this way, a system is realized that performs navigation settings and emergency contact according to user instructions.

[1277] 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.

[1278] This invention is a system that uses a terminal equipped with a generative AI model to provide operations and services according to user requests. This system displays a chat user interface on the home screen, receives user input, analyzes it, and executes appropriate responses and operations. In addition, by incorporating an emotion engine, it recognizes the user's emotions and provides responses and operations according to the emotions.

[1279] System configuration

[1280] The system includes the following major components:

[1281] 1. Terminal: A device that contains a generative AI model and interacts with the user.

[1282] 2. Generative AI model: Artificial intelligence that analyzes user input and generates appropriate responses or actions.

[1283] 3. Chat user interface: An interface that appears on the home screen and accepts text and voice input.

[1284] 4. Speech recognition function: The function that converts the user's voice input into text.

[1285] 5. Plugin Market: An online store offering additional features and applications.

[1286] 6. APIs: Application Program Interfaces for performing specific functions such as sending emails or calendar reminders.

[1287] 7. Emotion Engine: Recognizes emotions from user voice and text inputs and generates corresponding responses.

[1288] Program processing

[1289] The program processing of this system is as follows: First, the user inputs text into the chat user interface or issues a voice command. The input is received by the device and converted into text using a speech recognition function as needed. Next, the text is sent to the generative AI model for analysis. Based on the analysis results, the generative AI model determines the appropriate response or operation.

[1290] The emotion engine analyzes emotions from the user's voice or text input and passes the results to the generative AI model, which then generates responses and actions taking the emotional data into account. For example, if the user is feeling stressed, the generative AI model will generate a more polite response. It can also suggest appropriate plugins based on the user's emotions.

[1291] Specific examples

[1292] Example 1: Emotion-recognition-based calendar reminder setting

[1293] User: "Set a reminder for a meeting tomorrow at 10 AM."

[1294] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[1295] Generative AI model: Analyzes the received text and asks the user for meeting details (content, location, etc.).

[1296] Emotion engine: Detects stress levels from the user's voice.

[1297] Generative AI models generate polite responses (e.g., "Good work. Can you tell me what the meeting was about?").

[1298] User: "Project X status review meeting in conference room A."

[1299] Generative AI model: Calls the calendar application API to set a reminder for the specified date and time.

[1300] On your device: Notify the user with the message "Your reminder has been set. Is there anything else we can help you with?"

[1301] Example 2: Emotion recognition in email sending

[1302] User: "Send me a new email."

[1303] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[1304] Generative AI model: Analyzes the received text and asks the user for the email address to send it to.

[1305] Emotion Engine: Detects gratitude from the user's voice.

[1306] Generative AI models generate responses tailored to the sentiment of gratitude (e.g., "Thank you. Can you give me your email address?").

[1307] User: "example@example.com"

[1308] Generative AI model: Ask for subject and body text.

[1309] User: "Subject: 'Meeting Announcement', Body: 'We have a meeting tomorrow at 10 AM.'"

[1310] Generative AI model: Calls the email sending API to send the email.

[1311] Terminal: Notify the user with the message "Your email has been sent. Is there anything else we can help you with?"

[1312] Extensions

[1313] This system can download and install additional functions and applications using the plugin market. When the user instructs the system to "add a new plugin," the generative AI model accesses the plugin market and downloads and installs the specified plugin. It can also suggest appropriate plugins based on the analysis results of the emotion engine. For example, if the user is feeling stressed, it will suggest relaxation-related plugins.

[1314] In this way, by utilizing a generative AI model and an emotion engine, the present invention provides a system that responds to various user requests, simplifies smartphone operation, and improves user convenience. Furthermore, by executing appropriate responses and operations based on the user's emotional state, more human-like interactions can be achieved.

[1315] The processing flow will be explained below.

[1316] Email sending process including emotion recognition

[1317] Step 1:

[1318] The user types or speaks "send a new email" in the chat user interface on the home screen.

[1319] Step 2:

[1320] The device receives input from the user, which, if spoken, is converted to text using speech recognition.

[1321] Step 3:

[1322] The device transfers the text data to the generative AI model.

[1323] Step 4:

[1324] The generative AI model analyzes the received text and recognizes that it is a request to "send a new email."

[1325] Step 5:

[1326] The generative AI model generates a message requesting the recipient's email address.

[1327] Step 6:

[1328] The terminal displays this message on the chat user interface or outputs it as a voice message.

[1329] Step 7:

[1330] The user inputs or speaks the email address of the recipient.

[1331] Step 8:

[1332] The device receives the recipient's email address and forwards it to the generative AI model.

[1333] Step 9:

[1334] The emotion engine analyzes the user input (voice or text) up to this point and identifies the user's emotion.

[1335] Step 10:

[1336] The generative AI model takes into account the output of the emotion engine to determine the appropriate tone of the response. For example, if the user is nervous, the generative AI model will generate a message that responds in a calm tone.

[1337] Step 11:

[1338] A generative AI model generates a message with a desired subject and body.

[1339] Step 12:

[1340] The terminal displays this message on the chat user interface or outputs it as a voice message.

[1341] Step 13:

[1342] The user types or speaks the subject and body of the email.

[1343] Step 14:

[1344] The device receives this information and forwards it to the generative AI model.

[1345] Step 15:

[1346] The generative AI model prepares the data to call the email sending API.

[1347] Step 16:

[1348] The generative AI model passes the recipient address, subject, and message body to the email sending API.

[1349] Step 17:

[1350] The device calls the email sending API to send the email.

[1351] Step 18:

[1352] The device receives the transmission results and notifies the generative AI model of the results.

[1353] Step 19:

[1354] If the generative AI model is successful, it generates the message "Email sent" and if it fails, it generates an error message.

[1355] Step 20:

[1356] The terminal displays the generated message on a chat user interface or outputs it as a voice.

[1357] Calendar reminder setting process using emotion recognition

[1358] Step 1:

[1359] A user types or speaks into the chat user interface on the home screen, "Set a reminder for a meeting tomorrow at 10 AM."

[1360] Step 2:

[1361] The device receives input from the user, which, if spoken, is converted to text using speech recognition.

[1362] Step 3:

[1363] The device transfers the text data to the generative AI model.

[1364] Step 4:

[1365] The generative AI model analyzes the received text and recognizes it as a request to "set a reminder."

[1366] Step 5:

[1367] The emotion engine analyzes the user input (voice or text) up to this point and identifies the user's emotion.

[1368] Step 6:

[1369] The generative AI model takes into account the output of the emotion engine and asks the user for meeting details (content, location, etc.) in an appropriate tone.

[1370] Step 7:

[1371] The terminal displays the message generated by the generation AI model on the chat user interface or outputs it as audio.

[1372] Step 8:

[1373] The user types or speaks meeting details.

[1374] Step 9:

[1375] The device receives the meeting details and forwards them to the generative AI model.

[1376] Step 10:

[1377] The generative AI model prepares the data to call the calendar application API.

[1378] Step 11:

[1379] The generative AI model passes the date, time, content, and location to the calendar application API.

[1380] Step 12:

[1381] The device calls the calendar application API to set the reminder.

[1382] Step 13:

[1383] The device receives the reminder setting results and notifies the generative AI model.

[1384] Step 14:

[1385] If the generative AI model is successful, it generates a message saying "Reminder set" and if it fails, it generates an error message.

[1386] Step 15:

[1387] The terminal displays the generated message on a chat user interface or outputs it as a voice.

[1388] The above is the specific processing flow in a system equipped with a generative AI model and an emotion engine.

[1389] Example 2

[1390] 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."

[1391] Conventional devices could only provide simple text responses and operations in response to user input, making it difficult to realize responses and operations that take the user's emotions into account. Furthermore, there were limited ways to provide additional functions, resulting in low user convenience. Furthermore, there was a lack of means to optimally provide specific functions, such as calendar reminders and email sending functions, based on the user's emotions.

[1392] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for displaying a chat user interface on a home screen, a means for converting a voice input from a user into text, a means for sending data to a generative AI model and having it analyze the data, a means for the generative AI model to determine a response or operation based on emotion data from the emotion engine, a means for notifying the user of the response, a means for downloading and installing additional functions or applications from an online store, a means for suggesting additional functions based on the user's emotional state, and a means for performing a calendar reminder function, an email sending function, and various setting changes on behalf of the user. This makes it possible to provide responses and operations that take the user's emotions into consideration, and to suggest additional functions.

[1393] A "generative AI model" is an artificial intelligence that analyzes user input data and generates appropriate responses and operations.

[1394] A "terminal" is a device that is equipped with a generative AI model and interacts with the user.

[1395] The "chat user interface" is an interface that is displayed on the home screen of the terminal and that accepts user input.

[1396] The "voice recognition function" is a function that converts a user's voice input into text.

[1397] The "emotion engine" is a function that recognizes emotions from user voice and text input and provides them to the generative AI model.

[1398] "Online Store" means a digital marketplace for offering additional features and applications.

[1399] The "Calendar reminder function" is a function that sets a reminder at a specified date and time and notifies you.

[1400] The "email sending function" is a function that creates and sends email based on user instructions.

[1401] The "means for changing various settings" is a function that automatically changes settings based on the user's request.

[1402] This invention relates to a system that combines a generative AI model and an emotion engine, and aims to improve convenience and user experience by analyzing user input data and providing appropriate responses and operations. This system is configured to install a generative AI model on a terminal and display a chat user interface on the home screen, allowing users to easily access it.

[1403] System Configuration

[1404] The main hardware and software components of the system are as follows:

[1405] 1. Device: A device that is equipped with a generative AI model and interacts with the user. Specific examples include smartphones and tablet PCs.

[1406] 2. Generative AI model: This is an artificial intelligence that analyzes user input data and generates appropriate responses and operations. It uses natural language processing (NLP) technology to accurately analyze user input.

[1407] 3. Chat user interface: An interface that appears on the device's home screen and accepts text or voice input from the user, allowing the user to easily communicate their requests to the system.

[1408] 4. Speech recognition function: This function converts the user's voice input into text. This conversion allows the voice input to be analyzed in the same way as text.

[1409] 5. Emotion Engine: A system that recognizes emotions from user voice and text inputs and provides the results to a generative AI model. This capability allows the system to understand the user's emotional state and optimize responses and suggestions.

[1410] 6. Online Store: A digital marketplace offering additional features and applications, allowing users to extend functionality as needed.

[1411] 7. APIs: Application Programming Interfaces are used to perform specific operations, such as setting a calendar reminder or sending an email.

[1412] Implementation method

[1413] When a user inputs commands into the chat user interface via text or voice, the data is received by the device. In the case of voice input, the data is converted into text using a speech recognition function. The text data is then sent to a generative AI model and analyzed using natural language processing technology. The generative AI model determines the appropriate response or action based on the analysis results, taking into account the emotional data provided by the emotion engine.

[1414] For example, if a user types, "Set a reminder for a meeting tomorrow at 10 AM," the system will parse this instruction and set a reminder for the specified date and time through the calendar API. Furthermore, if the emotion engine detects the user's stress, the generative AI model will generate a polite response such as, "Thank you for your hard work. Can you let me know what the meeting is about?"

[1415] Specific examples

[1416] Example 1: Emotion-recognition-based calendar reminder setting

[1417] User: "Set a reminder for a meeting tomorrow at 10 AM."

[1418] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[1419] Generative AI model: Analyzes the received text and asks the user for meeting details (content, location, etc.).

[1420] Emotion engine: Detects stress levels from the user's voice.

[1421] Generative AI models: Generate polite responses (e.g., "Good work. Can you tell me what the meeting was about?").

[1422] User: "Project X status review meeting in conference room A."

[1423] Generative AI model: Calls the calendar application API to set a reminder at the specified date and time.

[1424] On your device: Notify the user with the message "Your reminder has been set. Is there anything else we can help you with?"

[1425] Example 2: Emotion recognition in email sending

[1426] User: "Send me a new email."

[1427] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[1428] Generative AI model: Analyzes the received text and asks the user for the email address to send it to.

[1429] Emotion Engine: Detects gratitude from the user's voice.

[1430] Generative AI models: Generate responses tailored to the sentiment of gratitude (e.g., "Thank you. Can you give me your email address?").

[1431] User: "example@example.com"

[1432] Generative AI model: Ask for subject and body text.

[1433] User: "Subject: 'Meeting Announcement', Body: 'We have a meeting tomorrow at 10 AM.'"

[1434] Generative AI model: Calls the email sending API to send the email.

[1435] Terminal: Notify the user with the message "Your email has been sent. Is there anything else we can help you with?"

[1436] In this way, the system analyzes the user's input and provides appropriate responses and operations that take into account the emotion data. However, this embodiment is merely an example, and the present invention can be implemented in other ways without departing from the scope of the present invention.

[1437] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1438] Step 1:

[1439] The user provides input in the chat user interface

[1440] A user inputs instructions into a chat user interface using text or voice. The input data contains the user's intent or request. For example, "Set a reminder for a meeting tomorrow at 10 AM." The string of data (text or voice) is sent to the system.

[1441] Step 2:

[1442] The terminal receives input

[1443] The terminal receives text and voice data entered by the user. This is where the input data is first captured by the system. For example, when a user enters voice input, the voice data is stored in the terminal.

[1444] Step 3:

[1445] Your device converts your voice input into text

[1446] When voice input is made, the device uses speech recognition to convert the speech to text. The input is voice data, and the output is the equivalent text data. For example, voice data such as "Set a reminder for a meeting tomorrow at 10:00 AM" is converted to text such as "Set a reminder for a meeting tomorrow at 10:00 AM."

[1447] Step 4:

[1448] The device sends data to the generative AI model

[1449] The terminal sends the received or converted text data to the generative AI model. The input is text data, and the output is data waiting to be interpreted by the generative AI model. The data is sent to the generative AI model server using a communication protocol such as an HTTP request.

[1450] Step 5:

[1451] A generative AI model analyzes the input

[1452] The generative AI model analyzes the received text data. The input is text data, and the output is instructions or operational decisions based on the analysis results. The generative AI model uses natural language processing techniques to analyze the text and interpret the user's request. For example, it can understand the instruction "Set a meeting reminder."

[1453] Step 6:

[1454] The emotion engine provides emotion data to the generative AI model

[1455] The emotion engine analyzes emotions from the tone and content of a user's voice or text and provides that data to a generative AI model. The input is voice or text data, and the output is emotion data. For example, it can analyze a user's stress level from their tone of voice.

[1456] Step 7:

[1457] Generative AI models determine responses and actions

[1458] The generative AI model takes emotional data into account to determine the appropriate response or action. The input is the user's instructions and emotional data, and the output is the determined response or action. For example, it generates responses such as "Ask for reminder settings details" or "Confirm meeting details."

[1459] Step 8:

[1460] The terminal notifies the user of the response

[1461] The device notifies the user of the response from the generative AI model. The input is the response data from the generative AI model, and the output is the response that is displayed or spoken to the user. For example, a message such as "Thank you for your hard work. Could you please let me know the details of the meeting?" is displayed.

[1462] Step 9:

[1463] If necessary, the device calls the relevant API to perform the process.

[1464] When necessary, the device will call relevant application program interfaces such as a calendar API or email API to perform specific operations. The input is the user's instruction and the analysis result of the generative AI model, and the output is the result of the performed operation. For example, calling a calendar API to set a reminder.

[1465] (Application example 2)

[1466] 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."

[1467] Conventional systems using generative AI models and emotion recognition engines mainly respond to basic user operational requests, making it difficult to efficiently interact with customers in physical stores. In particular, they are insufficient when providing detailed information, such as responses based on the customer's emotional state, checking the stock of specific products, or guiding customers to their location. Therefore, in order to improve customer satisfaction in physical stores, it is necessary to provide more advanced information and responses that reflect emotions.

[1468] 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.

[1469] In this invention, the server is a terminal equipped with a generative AI model, and includes means for displaying a chat user interface on a home screen, means for receiving input from a user and converting the voice input into text, means for analyzing the received text and performing various operations, means for notifying the user of the operation results, means for analyzing the user's emotions using an emotion recognition engine, means for checking product inventory status, and means for providing the shelf location of a specific product. This allows for more advanced interaction with customers, making it possible to provide specific product information and inventory status, and to respond appropriately to the customer's emotional state.

[1470] ---

[1471] OK, now we'll create definitions for each of the key words in the rewritten claims.

[1472] definition statement

[1473] ---

[1474] A "generative AI model" is an artificial intelligence that analyzes user input and generates appropriate responses and operations.

[1475] A "chat user interface" is a user interface that is displayed on the home screen and accepts text and voice input.

[1476] A "means for converting speech input to text" is a technique for converting a user's speech input into text form.

[1477] The "means for performing various operations" is a system that performs the necessary operations based on the analyzed text.

[1478] The "means for notifying the user of the operation result" is a function for notifying the user of the result of the executed operation.

[1479] An "emotion recognition engine" is an algorithm that recognizes and analyzes emotions from the user's voice or text input.

[1480] The "means for checking product inventory status" is a system for checking whether a specific product is in stock.

[1481] The "means for providing the shelf location of a specific product" is a function that guides the user to the location where the product is stored.

[1482] ---

[1483] Understood. Now, let's create the detailed description based on the information we have provided so far.

[1484] MODE FOR CARRYING OUT THE INVENTION

[1485] ---

[1486] System Overview

[1487] This invention is a customer service system for brick-and-mortar stores that uses a terminal equipped with a generative AI model and an emotion recognition engine. This system displays a chat user interface on the screen and accepts voice and text input in response to questions and requests from customers in the store. The generative AI model analyzes these inputs and executes appropriate responses and operations. Furthermore, the emotion recognition engine can analyze customer emotions and provide responses that correspond to those emotions.

[1488] System configuration

[1489] The system includes the following main components:

[1490] 1. Device: A device that is equipped with a generative AI model and interacts with the user. Examples of devices that can be used include smartphones and tablets.

[1491] 2. Generative AI model: An artificial intelligence that analyzes user input and generates appropriate responses or actions. For example, natural language processing models (such as BERT and GPT-3) can be applied.

[1492] 3. Chat user interface: An interface that appears on the device's home screen and accepts text and voice input.

[1493] 4. Speech recognition: A function that converts user voice input into text. Examples of services that can be used include Google Cloud Speech-to-Text and Amazon Transcribe.

[1494] 5. Emotion Recognition Engine: An engine that recognizes emotions from the user's voice and text input and generates corresponding responses. For example, IBM Watson Tone Analyzer can be used.

[1495] 6. Various APIs: Application program interfaces for checking product inventory status and providing product shelf location information. RESTful APIs are commonly used for this purpose.

[1496] Operation flow

[1497] The system works as follows: First, a customer enters text into the chat user interface or issues a voice command. The input is received by the device, and in the case of voice input, it is converted into text using a speech recognition function. The text is then sent to a generative AI model for analysis. Based on the analysis results, the generative AI model determines the appropriate response or action.

[1498] The emotion recognition engine analyzes emotions from customer voice and text inputs and passes the results to a generative AI model. The generative AI model generates responses and actions taking emotional data into account. For example, if a customer's emotions indicate stress, the generative AI model will generate a more polite response. It can also provide relaxation-related information and suggestions based on their emotions.

[1499] Specific examples

[1500] Example 1: Checking inventory

[1501] User: "Can you tell me if this item is in stock?"

[1502] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[1503] Generative AI model: Analyzes the incoming text and recognizes it as an instruction to check inventory.

[1504] Emotion Recognition Engine: Analyzes emotions from user text.

[1505] Generative AI model: Calls the stock availability API to check the availability of the specified product.

[1506] Terminal: Notifies the user with the message "The product is in stock."

[1507] Example 2: Product location guidance

[1508] User: "Where is this item?"

[1509] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[1510] Generative AI model: Analyzes the received text and recognizes it as instructions to guide shelf locations.

[1511] Emotion Recognition Engine: Analyzes emotions from user text.

[1512] Generative AI model: Calls the product shelf location information API to obtain the location of the specified product.

[1513] Terminal: Notifies the user with the message "The product is located in the second section of the store."

[1514] Prompt Sentence Examples

[1515] Please let me know if you have this item in stock.

[1516] "Where is this item located?"

[1517] This will make customer service in physical stores more efficient and improve customer satisfaction.

[1518] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1519] Understood. Now, I will explain the processing flow of the system program that realizes the application example, broken down into specific processing steps.

[1520] Program processing steps

[1521] ---

[1522] Step 1:

[1523] The user provides voice or text input to the chat user interface.

[1524] What happens: The user says, "Tell me if this item is in stock."

[1525] Input: User's voice input.

[1526] Output: Audio data.

[1527] Step 2:

[1528] The device receives voice input and converts it into text using speech recognition.

[1529] How it works: The device receives the audio and uses Google Cloud Speech-to-Text to convert it into text: "Tell me if this item is in stock."

[1530] Input: Audio data.

[1531] Output: Text data ("Tell me if this item is in stock").

[1532] Step 3:

[1533] The received text is sent to a generative AI model for analysis.

[1534] How it works: The device sends text data to a generative AI model (e.g., GPT-3) and receives an analysis result, which determines that the text is a request for inventory check.

[1535] Input: Text data ("Tell me if this item is in stock").

[1536] Output: Analysis result data (command "check_inventory", item "requested_item").

[1537] Step 4:

[1538] Analyze user emotions using an emotion recognition engine.

[1539] How it works: The device sends text data to an emotion recognition engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotions. The analysis results indicate that the user has a neutral attitude.

[1540] Input: Text data ("Tell me if this item is in stock").

[1541] Output: Emotion data (neutral).

[1542] Step 5:

[1543] Call the inventory status API to check the product's inventory status.

[1544] Operation: The device sends a request to the stock confirmation API to obtain the stock status of the specified product. For example, a request is sent via the RESTful API to check the stock status of "requested_item".

[1545] Input: Analysis result data (command "check_inventory", item "requested_item").

[1546] Output: Inventory status data (in stock).

[1547] Step 6:

[1548] Generate appropriate responses based on analysis results and sentiment data.

[1549] How it works: The generative AI model takes into account the analysis results and sentiment data and generates a response message saying, "The item is in stock."

[1550] Input: Stock status data (in stock), Sentiment data (neutral).

[1551] Output: Response message ("The item is in stock.").

[1552] Step 7:

[1553] Notify the user of the operation result.

[1554] Operation: The terminal notifies the user of the reply message through the chat user interface.

[1555] Input: Response message ("Item is in stock.").

[1556] Output: A text message that is displayed to the user.

[1557] This will enable customers to smoothly request product information in-store and receive appropriate responses.

[1558] 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.

[1559] 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.

[1560] 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.

[1561] [Fourth embodiment]

[1562] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1563] 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.

[1564] 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).

[1565] 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.

[1566] 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.

[1567] 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).

[1568] 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.

[1569] 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.

[1570] 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.

[1571] 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.

[1572] 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.

[1573] 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.

[1574] 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."

[1575] This invention is a system that uses a terminal equipped with a generative AI model to provide operations and services according to user requests. This system displays a chat user interface on the home screen, receives input from the user, analyzes it, and executes appropriate responses and operations.

[1576] System configuration

[1577] The system includes the following major components:

[1578] 1. Terminal: A device that contains a generative AI model and interacts with the user.

[1579] 2. Generative AI model: Artificial intelligence that analyzes user input and generates appropriate responses or actions.

[1580] 3. Chat user interface: An interface that appears on the home screen and accepts text and voice input.

[1581] 4. Speech recognition function: The function that converts the user's voice input into text.

[1582] 5. Plugin Market: An online store offering additional features and applications.

[1583] 6. Various APIs: Application Program Interfaces for performing specific functions such as sending emails or calendar reminders.

[1584] Program processing

[1585] The program processing of this system is as follows: First, the user inputs text into the chat user interface or issues a voice command. The input is received by the device and converted into text using a speech recognition function as needed. Next, the text is sent to the generative AI model for analysis. Based on the analysis results, the generative AI model determines the appropriate response or operation.

[1586] For example, if a user types "send a new email," the generative AI model next asks the user for the necessary information (recipient, subject, and body) and receives each answer. It then calls the email sending API to send the email. The operation result is generated by the generative AI model and notified to the user via the device.

[1587] Specific examples

[1588] Example 1: Calendar reminder settings

[1589] User: "Set a reminder for a meeting tomorrow at 10 AM."

[1590] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[1591] Generative AI model: Analyzes the received text and asks the user for meeting details (content, location, etc.).

[1592] User: "Project X status review meeting in conference room A."

[1593] Generative AI model: Calls the calendar application API to set a reminder for the specified date and time.

[1594] On the device: The user is notified with the message "Reminder set."

[1595] Example 2: Sending email

[1596] User: "Send me a new email."

[1597] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[1598] Generative AI model: Analyzes the received text and asks the user for the email address to send it to.

[1599] User: "example@example.com"

[1600] Generative AI model: Ask for subject and body text.

[1601] User: "Subject: 'Meeting Announcement', Body: 'We have a meeting tomorrow at 10 AM.'"

[1602] Generative AI model: Calls the email sending API to send the email.

[1603] Terminal: Notify the user with the message "Email has been sent."

[1604] Extensions

[1605] This system uses a plugin market to allow users to download and install additional functions and applications. When a user instructs the system to "add a new plugin," the generative AI model accesses the plugin market and downloads and installs the specified plugin. Once the installation is complete, the device notifies the user.

[1606] In this way, the present invention is a system that utilizes generative AI models to respond to various user requests, simplifying smartphone operation and increasing user convenience.

[1607] The processing flow will be explained below.

[1608] Email sending process

[1609] Step 1:

[1610] The user types or speaks "send a new email" in the chat user interface on the home screen.

[1611] Step 2:

[1612] The device receives input from the user, which, if spoken, is converted to text using speech recognition.

[1613] Step 3:

[1614] The device transfers the text data to the generative AI model.

[1615] Step 4:

[1616] The generative AI model analyzes the received text and recognizes that it is a request to "send a new email."

[1617] Step 5:

[1618] The generative AI model generates a message requesting the recipient's email address.

[1619] Step 6:

[1620] The terminal displays this message on the chat user interface or outputs it as a voice message.

[1621] Step 7:

[1622] The user inputs or speaks the email address of the recipient.

[1623] Step 8:

[1624] The device receives the recipient's email address and forwards it to the generative AI model.

[1625] Step 9:

[1626] A generative AI model generates a message with a desired subject and body.

[1627] Step 10:

[1628] The terminal displays this message on the chat user interface or outputs it as a voice message.

[1629] Step 11:

[1630] The user types or speaks the subject and body of the email.

[1631] Step 12:

[1632] The device receives this information and forwards it to the generative AI model.

[1633] Step 13:

[1634] The generative AI model prepares the data to call the email sending API.

[1635] Step 14:

[1636] The generative AI model passes the recipient address, subject, and message body to the email sending API.

[1637] Step 15:

[1638] The device calls the email sending API to send the email.

[1639] Step 16:

[1640] The device receives the transmission results and notifies the generative AI model of the results.

[1641] Step 17:

[1642] If the generative AI model is successful, it generates the message "Email sent" and if it fails, it generates an error message.

[1643] Step 18:

[1644] The terminal displays the generated message on a chat user interface or outputs it as a voice.

[1645] Calendar Reminder Setting Process

[1646] Step 1:

[1647] A user types or speaks into the chat user interface on the home screen, "Set a reminder for a meeting tomorrow at 10 AM."

[1648] Step 2:

[1649] The device receives input from the user, which, if spoken, is converted to text using speech recognition.

[1650] Step 3:

[1651] The device transfers the text data to the generative AI model.

[1652] Step 4:

[1653] The generative AI model analyzes the received text and recognizes it as a request to "set a reminder."

[1654] Step 5:

[1655] The generative AI model generates a message requesting meeting details (content, location, etc.).

[1656] Step 6:

[1657] The terminal displays this message on the chat user interface or outputs it as a voice message.

[1658] Step 7:

[1659] The user types or speaks meeting details.

[1660] Step 8:

[1661] The device receives the meeting details and forwards them to the generative AI model.

[1662] Step 9:

[1663] The generative AI model prepares the data to call the calendar application API.

[1664] Step 10:

[1665] The generative AI model passes the date, time, content, and location to the calendar application API.

[1666] Step 11:

[1667] The device calls the calendar application API to set the reminder.

[1668] Step 12:

[1669] The device receives the reminder setting results and notifies the generative AI model.

[1670] Step 13:

[1671] If the generative AI model is successful, it generates a message saying "Reminder set" and if it fails, it generates an error message.

[1672] Step 14:

[1673] The terminal displays the generated message on a chat user interface or outputs it as a voice.

[1674] Example 1

[1675] 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."

[1676] In conventional smart devices and virtual assistants, systems for quickly and accurately responding to user operation requests have not been fully established. Furthermore, it has been difficult to provide various functions in an integrated manner, resulting in reduced user convenience. The objective of this invention is to provide a system that utilizes generative AI models to quickly and accurately respond to various user requests and execute operations.

[1677] 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.

[1678] In this invention, the server uses a terminal equipped with a generative AI model and includes: means for displaying a chat user interface on a home screen; means for receiving input from a user and converting the voice input into text; means for sending the received text to the generative AI model and analyzing it; means for generating appropriate responses and operations and displaying them to the user; means for obtaining necessary additional information from the user; means for calling various APIs to execute operations; and means for notifying the user of the results of the operations. This enables prompt and accurate responses and operations to be executed in response to various user requests. A "generative AI model" is an artificial intelligence model that analyzes user input and generates appropriate responses and operations.

[1679] A "terminal" is a device that is equipped with a generative AI model and interacts with the user.

[1680] A "chat user interface" is an interface that is displayed on the home screen and accepts text and voice input from the user.

[1681] The "voice recognition function" is a function that converts a user's voice input into text.

[1682] An "API" is an application program interface for performing a specific function.

[1683] "Online Store" means a digital platform for providing additional features and applications.

[1684] The "calendar function" is a function for managing schedules and setting reminders.

[1685] The "email sending function" is a function for sending e-mail to a destination specified by the user.

[1686] The "means for changing various settings on behalf of the user" refers to a means for adjusting the system settings based on the user's instructions.

[1687] This invention is a system that uses a terminal equipped with a generative AI model to provide operations and services according to user requests. This system displays a chat user interface on the home screen, receives input from the user, analyzes it, and executes appropriate responses and operations.

[1688] System configuration

[1689] The system includes the following major components:

[1690] 1. Terminal: A device that contains a generative AI model and interacts with the user.

[1691] 2. Generative AI model: Artificial intelligence that analyzes user input and generates appropriate responses or actions.

[1692] 3. Chat user interface: An interface that appears on the home screen and accepts text and voice input.

[1693] 4. Speech recognition: A function that converts user voice input into text. For example, we use the Google Speech-to-Text API.

[1694] 5. Online Store: A platform that offers additional features and applications.

[1695] 6. Various APIs: Application Program Interfaces for performing specific functions, such as sending emails or calendar reminders.

[1696] Program processing

[1697] The program in this system operates in the following steps: First, the user inputs text into the chat user interface or issues a voice command. The input is received by the device and converted into text using a speech recognition function as needed. The text is then sent to the generative AI model for analysis. Based on the analysis results, the generative AI model determines and executes an appropriate response or operation.

[1698] For example, if a user instructs the model to "send a new email," the generative AI model will then ask the user for the necessary information (recipient, subject, and body) and receive each response. It will then call the email sending API and send the email. The operation result is generated by the generative AI model and notified to the user via the device.

[1699] Specific examples

[1700] Example 1: Calendar reminder settings

[1701] 1. User: "Set a reminder for a meeting tomorrow at 10 AM."

[1702] 2. Terminal: Receives user input and converts it to text using speech recognition if necessary.

[1703] 3. Generative AI model: Analyzes the received text and asks the user for meeting details (content, location, etc.).

[1704] 4. User: "Project X status review meeting. Location: Conference Room A."

[1705] 5. Generative AI model: Calls the calendar application API to set a reminder for the specified date and time.

[1706] 6. Device: Notify the user with the message "Reminder has been set."

[1707] Example 2: Sending email

[1708] 1. User: "Send me a new email."

[1709] 2. Terminal: Receives user input and converts it to text using speech recognition if necessary.

[1710] 3. Generative AI model: Analyzes the received text and asks the user for the email address to send it to.

[1711] 4. User: "example@example.com"

[1712] 5. Generative AI model: Ask for subject and body text.

[1713] 6. User: "Subject: 'Meeting Announcement', Body: 'We'll be meeting tomorrow at 10 AM.'"

[1714] 7. Generative AI model: Calls the email sending API and sends the email.

[1715] 8. Terminal: Notify the user with the message "Email has been sent."

[1716] Extensions

[1717] This system allows users to download and install additional features and applications using an online store. When a user requests "add a new plugin," the generative AI model accesses the online store, downloads, and installs the specified plugin. Once the installation is complete, the device notifies the user.

[1718] In this way, the present invention is a system that utilizes a generative AI model to respond to a variety of user requests, simplify terminal operation, and increase user convenience.

[1719] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1720] Step 1:

[1721] A user enters text into the chat user interface or issues a voice command, which generates input data. Text is received as input data, and voice is received as voice data.

[1722] Step 2:

[1723] The device receives user input. If it is voice input, it converts the voice data into text data using the speech recognition function. The input is voice data, and the output is text data. Specifically, it converts the voice into text using the Google Speech-to-Text API.

[1724] Step 3:

[1725] The text data received by the device is sent to the generative AI model. Here, the input data (text) is passed to the generative AI model, which then performs an analysis process. The generative AI model receives the input text and performs data calculations for analysis. This analysis clarifies the requested content.

[1726] Step 4:

[1727] The generative AI model analyzes the text data and determines the appropriate response or operation. Based on the analysis results, it generates a prompt to ask the user for the next required information (for example, recipient, subject, and body of an email when sending one). The input is the analyzed data, and the output is the prompt. The specific operation uses a natural language processing algorithm within the model.

[1728] Step 5:

[1729] The terminal will then generate a prompt and notify the user. If the user enters additional information or a response, that data will be sent back to the terminal. The input is the user's response data, and the output is the updated user data.

[1730] Step 6:

[1731] The generative AI model receives additional information from the user and executes operations by calling various APIs as necessary. For example, it calls an email sending API to send an email. In this procedure, the input is the updated user data, and the output is the result of executing the API call. As a specific operation, the actual operation is performed using the defined API interface.

[1732] Step 7:

[1733] The device notifies the user of the operation result. For example, a message such as "Email sent" or "Reminder set" is generated and provided to the user. The input is the result of the API call, and the output is the notification message. The device displays the message on the user's screen.

[1734] Through the above steps, a terminal system utilizing a generative AI model can respond quickly and accurately to user input and provide a variety of operations and services.

[1735] (Application example 1)

[1736] 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."

[1737] Autonomous vehicles require passengers to easily set their destinations and respond quickly in emergencies. However, current systems lack the high level of interactivity required for this, making it difficult for them to understand user instructions in real time and respond appropriately. Furthermore, complex systems with multiple functions can be difficult for users to use. Furthermore, there is a growing need for systems that can provide specific functions within autonomous vehicles and respond flexibly to situations.

[1738] 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.

[1739] In this invention, the server is a terminal equipped with a generative AI model and includes: means for displaying a chat user interface on a home screen; means for receiving input from a user and converting the voice input into text; means for analyzing the received text and performing various operations; means for notifying the user of the operation results; means for setting a destination in an autonomous vehicle; and means for sending notifications to contacts in the event of an emergency. This allows the user to easily set a destination and respond quickly to emergencies. Furthermore, by utilizing the generative AI model, the system becomes highly interactive and can respond appropriately to user instructions in real time.

[1740] A "generative AI model" is a type of artificial intelligence that analyzes user input and generates appropriate responses and operations.

[1741] "Terminal" refers to a device that is equipped with a generative AI model and interacts with the user.

[1742] A "chat user interface" is an interface that is displayed on the home screen and accepts text and voice input from the user.

[1743] The "means for converting speech input to text" is a processing function that recognizes the user's speech and converts it into text form.

[1744] "Means for analyzing received text and performing various operations" refers to a function that analyzes text received from a user using a generative AI model and performs specific operations based on the results.

[1745] "Means for notifying the user of the operation results" is a function for informing the user of the results of the operation performed by the generative AI model.

[1746] The "means for setting a destination in an autonomous vehicle" is a function that sets a destination based on user instructions within the autonomous vehicle system.

[1747] The "means for sending a notification to a contact in an emergency" is a function for quickly sending a notification to a designated contact in an emergency.

[1748] "Means to download and install from the Plug-in Market" refers to the ability to download and install additional features and applications from an online store.

[1749] "Means for providing plug-ins that optimize operation in an autonomous vehicle" refers to a function that provides additional plug-ins to optimize operation and functionality in an autonomous vehicle.

[1750] The "means for providing navigation information in real time" is a function for providing navigation information related to a destination or current location designated by the user in real time.

[1751] This invention relates to a system that automatically sets destinations and responds to emergencies based on user instructions in a device equipped with a generative AI model and in an autonomous vehicle. This system is highly interactive and provides operations and services that respond to user requests in real time.

[1752] Main components of the system

[1753] 1. Terminal: A device that is equipped with a generative AI model and interacts with the user. This terminal can be realized, for example, as a display installed in an autonomous vehicle or a smartphone held by the user.

[1754] 2. Generative AI models: These are artificial intelligence models that analyze user input and generate appropriate responses or actions. Examples include OpenAI's GPT-3.

[1755] 3. Chat user interface: This is the interface that appears on the home screen and accepts text and voice input from the user.

[1756] 4. Speech recognition function: This is a function that converts user voice input into text. For example, the speech_recognition module is used.

[1757] 5. Navigation module: This module allows users to set up navigation to a destination specified by the user. It uses map services such as Google Maps API.

[1758] 6. Emergency contact function: This function is used to send notifications to contacts in the event of an emergency. Email is typically sent using the SMTP protocol.

[1759] 7. Plug-in Market: An online store offering additional features and applications.

[1760] Program processing

[1761] The system works as follows: First, the device receives voice input from the user. The voice input is converted to text using the speech_recognition module. Next, the text is sent to a generative AI model (e.g., GPT-3) for analysis. Based on the results of this analysis, appropriate navigation settings and emergency contact operations are determined. For navigation, a route to the specified destination is set using the Google Maps API, and the results are notified to the user via the device. In the event of an emergency, a notification is sent to the specified contacts using SMTP.

[1762] Usage example

[1763] Example prompt 1:

[1764] User: "Please set your next destination to Tokyo Station."

[1765] The device converts the speech into text, and the generative AI model analyzes it to set navigation with "Tokyo Station" as the destination. It then calls the Google Maps API to start route guidance and notifies the user of the results.

[1766] Example prompt 2:

[1767] User: "Please contact your emergency contact."

[1768] The device converts the speech into text, which the generative AI model analyzes and sends a notification to the designated emergency contacts. An email is sent to the emergency contacts using the SMTP protocol.

[1769] In this way, the present invention provides a system that significantly improves passenger convenience in autonomous vehicles and also enables rapid response in emergencies.

[1770] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1771] Step 1:

[1772] The user inputs a command by voice, for example, "Please set the next destination to Tokyo Station."

[1773] Step 2:

[1774] The terminal receives the user's voice. The received voice data is converted into text data using a speech recognition module (speech_recognition). The input is voice data, and the output is text data. The specific operation of this conversion is to process the voice signal as digital data and analyze it using a language model.

[1775] Step 3:

[1776] The device sends the generated text to a generative AI model (e.g., GPT-3) for analysis. The input is the text data generated in step 2, and the output is the analysis results (including commands and specific operation instructions). Specifically, the process involves inputting text data into a generative AI model, analyzing the output, and determining the appropriate operation.

[1777] Step 4:

[1778] Based on the analysis results of the generative AI model, the navigation module (Google Maps API) is called. In this step, destination information is extracted from the analysis results and navigation settings are made. The input is the analysis results, and the output is the set route information. Specifically, the destination information is sent to the Google Maps API endpoint and route information is received.

[1779] Step 5:

[1780] The device notifies the user of navigation information obtained from the Google Maps API. The input is route information obtained from the Google Maps API, and the output is navigation instructions on the device's screen or via voice. Specifically, the device displays route information on the user interface and provides voice guidance if voice output is available.

[1781] Step 6:

[1782] In an emergency, the user may give instructions for emergency contact. For example, the user may give instructions by voice such as "Please contact the emergency contact." The input is voice data from the user.

[1783] Step 7:

[1784] As in step 2, the device receives the user's voice and converts it into text using speech recognition. The input is voice data and the output is text data.

[1785] Step 8:

[1786] The generative AI model analyzes the text data and identifies emergency contact instructions. The input is the text data, and the output is the emergency contact instructions.

[1787] Step 9:

[1788] The terminal uses the emergency contact function to send a notification to the specified contact. In this step, the input is the emergency contact instructions, and the output is the result of sending the notification using SMTP. The specific operation is to send an email containing the specified message to the emergency contact address.

[1789] In this way, a system is realized that performs navigation settings and emergency contact according to user instructions.

[1790] 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.

[1791] This invention is a system that uses a terminal equipped with a generative AI model to provide operations and services according to user requests. This system displays a chat user interface on the home screen, receives user input, analyzes it, and executes appropriate responses and operations. In addition, by incorporating an emotion engine, it recognizes the user's emotions and provides responses and operations according to the emotions.

[1792] System configuration

[1793] The system includes the following major components:

[1794] 1. Terminal: A device that contains a generative AI model and interacts with the user.

[1795] 2. Generative AI model: Artificial intelligence that analyzes user input and generates appropriate responses or actions.

[1796] 3. Chat user interface: An interface that appears on the home screen and accepts text and voice input.

[1797] 4. Speech recognition function: The function that converts the user's voice input into text.

[1798] 5. Plugin Market: An online store offering additional features and applications.

[1799] 6. APIs: Application Program Interfaces for performing specific functions such as sending emails or calendar reminders.

[1800] 7. Emotion Engine: Recognizes emotions from user voice and text inputs and generates corresponding responses.

[1801] Program processing

[1802] The program processing of this system is as follows: First, the user inputs text into the chat user interface or issues a voice command. The input is received by the device and converted into text using a speech recognition function as needed. Next, the text is sent to the generative AI model for analysis. Based on the analysis results, the generative AI model determines the appropriate response or operation.

[1803] The emotion engine analyzes emotions from the user's voice or text input and passes the results to the generative AI model, which then generates responses and actions taking the emotional data into account. For example, if the user is feeling stressed, the generative AI model will generate a more polite response. It can also suggest appropriate plugins based on the user's emotions.

[1804] Specific examples

[1805] Example 1: Emotion-recognition-based calendar reminder setting

[1806] User: "Set a reminder for a meeting tomorrow at 10 AM."

[1807] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[1808] Generative AI model: Analyzes the received text and asks the user for meeting details (content, location, etc.).

[1809] Emotion engine: Detects stress levels from the user's voice.

[1810] Generative AI models generate polite responses (e.g., "Good work. Can you tell me what the meeting was about?").

[1811] User: "Project X status review meeting in conference room A."

[1812] Generative AI model: Calls the calendar application API to set a reminder for the specified date and time.

[1813] On your device: Notify the user with the message "Your reminder has been set. Is there anything else we can help you with?"

[1814] Example 2: Emotion recognition in email sending

[1815] User: "Send me a new email."

[1816] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[1817] Generative AI model: Analyzes the received text and asks the user for the email address to send it to.

[1818] Emotion Engine: Detects gratitude from the user's voice.

[1819] Generative AI models generate responses tailored to the sentiment of gratitude (e.g., "Thank you. Can you give me your email address?").

[1820] User: "example@example.com"

[1821] Generative AI model: Ask for subject and body text.

[1822] User: "Subject: 'Meeting Announcement', Body: 'We have a meeting tomorrow at 10 AM.'"

[1823] Generative AI model: Calls the email sending API to send the email.

[1824] Terminal: Notify the user with the message "Your email has been sent. Is there anything else we can help you with?"

[1825] Extensions

[1826] This system can download and install additional functions and applications using the plugin market. When the user instructs the system to "add a new plugin," the generative AI model accesses the plugin market and downloads and installs the specified plugin. It can also suggest appropriate plugins based on the analysis results of the emotion engine. For example, if the user is feeling stressed, it will suggest relaxation-related plugins.

[1827] In this way, by utilizing a generative AI model and an emotion engine, the present invention provides a system that responds to various user requests, simplifies smartphone operation, and improves user convenience. Furthermore, by executing appropriate responses and operations based on the user's emotional state, more human-like interactions can be achieved.

[1828] The processing flow will be explained below.

[1829] Email sending process including emotion recognition

[1830] Step 1:

[1831] The user types or speaks "send a new email" in the chat user interface on the home screen.

[1832] Step 2:

[1833] The device receives input from the user, which, if spoken, is converted to text using speech recognition.

[1834] Step 3:

[1835] The device transfers the text data to the generative AI model.

[1836] Step 4:

[1837] The generative AI model analyzes the received text and recognizes that it is a request to "send a new email."

[1838] Step 5:

[1839] The generative AI model generates a message requesting the recipient's email address.

[1840] Step 6:

[1841] The terminal displays this message on the chat user interface or outputs it as a voice message.

[1842] Step 7:

[1843] The user inputs or speaks the email address of the recipient.

[1844] Step 8:

[1845] The device receives the recipient's email address and forwards it to the generative AI model.

[1846] Step 9:

[1847] The emotion engine analyzes the user input (voice or text) up to this point and identifies the user's emotion.

[1848] Step 10:

[1849] The generative AI model takes into account the output of the emotion engine to determine the appropriate tone of the response. For example, if the user is nervous, the generative AI model will generate a message that responds in a calm tone.

[1850] Step 11:

[1851] A generative AI model generates a message with a desired subject and body.

[1852] Step 12:

[1853] The terminal displays this message on the chat user interface or outputs it as a voice message.

[1854] Step 13:

[1855] The user types or speaks the subject and body of the email.

[1856] Step 14:

[1857] The device receives this information and forwards it to the generative AI model.

[1858] Step 15:

[1859] The generative AI model prepares the data to call the email sending API.

[1860] Step 16:

[1861] The generative AI model passes the recipient address, subject, and message body to the email sending API.

[1862] Step 17:

[1863] The device calls the email sending API to send the email.

[1864] Step 18:

[1865] The device receives the transmission results and notifies the generative AI model of the results.

[1866] Step 19:

[1867] If the generative AI model is successful, it generates the message "Email sent" and if it fails, it generates an error message.

[1868] Step 20:

[1869] The terminal displays the generated message on a chat user interface or outputs it as a voice.

[1870] Calendar reminder setting process using emotion recognition

[1871] Step 1:

[1872] A user types or speaks into the chat user interface on the home screen, "Set a reminder for a meeting tomorrow at 10 AM."

[1873] Step 2:

[1874] The device receives input from the user, which, if spoken, is converted to text using speech recognition.

[1875] Step 3:

[1876] The device transfers the text data to the generative AI model.

[1877] Step 4:

[1878] The generative AI model analyzes the received text and recognizes it as a request to "set a reminder."

[1879] Step 5:

[1880] The emotion engine analyzes the user input (voice or text) up to this point and identifies the user's emotion.

[1881] Step 6:

[1882] The generative AI model takes into account the output of the emotion engine and asks the user for meeting details (content, location, etc.) in an appropriate tone.

[1883] Step 7:

[1884] The terminal displays the message generated by the generation AI model on the chat user interface or outputs it as audio.

[1885] Step 8:

[1886] The user types or speaks meeting details.

[1887] Step 9:

[1888] The device receives the meeting details and forwards them to the generative AI model.

[1889] Step 10:

[1890] The generative AI model prepares the data to call the calendar application API.

[1891] Step 11:

[1892] The generative AI model passes the date, time, content, and location to the calendar application API.

[1893] Step 12:

[1894] The device calls the calendar application API to set the reminder.

[1895] Step 13:

[1896] The device receives the reminder setting results and notifies the generative AI model.

[1897] Step 14:

[1898] If the generative AI model is successful, it generates a message saying "Reminder set" and if it fails, it generates an error message.

[1899] Step 15:

[1900] The terminal displays the generated message on a chat user interface or outputs it as a voice.

[1901] The above is the specific processing flow in a system equipped with a generative AI model and an emotion engine.

[1902] Example 2

[1903] 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."

[1904] Conventional devices could only provide simple text responses and operations in response to user input, making it difficult to realize responses and operations that take the user's emotions into account. Furthermore, there were limited ways to provide additional functions, resulting in low user convenience. Furthermore, there was a lack of means to optimally provide specific functions, such as calendar reminders and email sending functions, based on the user's emotions.

[1905] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for displaying a chat user interface on a home screen, a means for converting a voice input from a user into text, a means for sending data to a generative AI model and having it analyze the data, a means for the generative AI model to determine a response or operation based on emotion data from the emotion engine, a means for notifying the user of the response, a means for downloading and installing additional functions or applications from an online store, a means for suggesting additional functions based on the user's emotional state, and a means for performing a calendar reminder function, an email sending function, and various setting changes on behalf of the user. This makes it possible to provide responses and operations that take the user's emotions into consideration, and to suggest additional functions.

[1906] A "generative AI model" is an artificial intelligence that analyzes user input data and generates appropriate responses and operations.

[1907] A "terminal" is a device that is equipped with a generative AI model and interacts with the user.

[1908] The "chat user interface" is an interface that is displayed on the home screen of the terminal and that accepts user input.

[1909] The "voice recognition function" is a function that converts a user's voice input into text.

[1910] The "emotion engine" is a function that recognizes emotions from user voice and text input and provides them to the generative AI model.

[1911] "Online Store" means a digital marketplace for offering additional features and applications.

[1912] The "Calendar reminder function" is a function that sets a reminder at a specified date and time and notifies you.

[1913] The "email sending function" is a function that creates and sends email based on user instructions.

[1914] The "means for changing various settings" is a function that automatically changes settings based on the user's request.

[1915] This invention relates to a system that combines a generative AI model and an emotion engine, and aims to improve convenience and user experience by analyzing user input data and providing appropriate responses and operations. This system is configured to install a generative AI model on a terminal and display a chat user interface on the home screen, allowing users to easily access it.

[1916] System Configuration

[1917] The main hardware and software components of the system are as follows:

[1918] 1. Device: A device that is equipped with a generative AI model and interacts with the user. Specific examples include smartphones and tablet PCs.

[1919] 2. Generative AI model: This is an artificial intelligence that analyzes user input data and generates appropriate responses and operations. It uses natural language processing (NLP) technology to accurately analyze user input.

[1920] 3. Chat user interface: An interface that appears on the device's home screen and accepts text or voice input from the user, allowing the user to easily communicate their requests to the system.

[1921] 4. Speech recognition function: This function converts the user's voice input into text. This conversion allows the voice input to be analyzed in the same way as text.

[1922] 5. Emotion Engine: A system that recognizes emotions from user voice and text inputs and provides the results to a generative AI model. This capability allows the system to understand the user's emotional state and optimize responses and suggestions.

[1923] 6. Online Store: A digital marketplace offering additional features and applications, allowing users to extend functionality as needed.

[1924] 7. APIs: Application Programming Interfaces are used to perform specific operations, such as setting a calendar reminder or sending an email.

[1925] Implementation method

[1926] When a user inputs commands into the chat user interface via text or voice, the data is received by the device. In the case of voice input, the data is converted into text using a speech recognition function. The text data is then sent to a generative AI model and analyzed using natural language processing technology. The generative AI model determines the appropriate response or action based on the analysis results, taking into account the emotional data provided by the emotion engine.

[1927] For example, if a user types, "Set a reminder for a meeting tomorrow at 10 AM," the system will parse this instruction and set a reminder for the specified date and time through the calendar API. Furthermore, if the emotion engine detects the user's stress, the generative AI model will generate a polite response such as, "Thank you for your hard work. Can you let me know what the meeting is about?"

[1928] Specific examples

[1929] Example 1: Emotion-recognition-based calendar reminder setting

[1930] User: "Set a reminder for a meeting tomorrow at 10 AM."

[1931] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[1932] Generative AI model: Analyzes the received text and asks the user for meeting details (content, location, etc.).

[1933] Emotion engine: Detects stress levels from the user's voice.

[1934] Generative AI models: Generate polite responses (e.g., "Good work. Can you tell me what the meeting was about?").

[1935] User: "Project X status review meeting in conference room A."

[1936] Generative AI model: Calls the calendar application API to set a reminder at the specified date and time.

[1937] On your device: Notify the user with the message "Your reminder has been set. Is there anything else we can help you with?"

[1938] Example 2: Emotion recognition in email sending

[1939] User: "Send me a new email."

[1940] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[1941] Generative AI model: Analyzes the received text and asks the user for the email address to send it to.

[1942] Emotion Engine: Detects gratitude from the user's voice.

[1943] Generative AI models: Generate responses tailored to the sentiment of gratitude (e.g., "Thank you. Can you give me your email address?").

[1944] User: "example@example.com"

[1945] Generative AI model: Ask for subject and body text.

[1946] User: "Subject: 'Meeting Announcement', Body: 'We have a meeting tomorrow at 10 AM.'"

[1947] Generative AI model: Calls the email sending API to send the email.

[1948] Terminal: Notify the user with the message "Your email has been sent. Is there anything else we can help you with?"

[1949] In this way, the system analyzes the user's input and provides appropriate responses and operations that take into account the emotion data. However, this embodiment is merely an example, and the present invention can be implemented in other ways without departing from the scope of the present invention.

[1950] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1951] Step 1:

[1952] The user provides input in the chat user interface

[1953] A user inputs instructions into a chat user interface using text or voice. The input data contains the user's intent or request. For example, "Set a reminder for a meeting tomorrow at 10 AM." The string of data (text or voice) is sent to the system.

[1954] Step 2:

[1955] The terminal receives input

[1956] The terminal receives text and voice data entered by the user. This is where the input data is first captured by the system. For example, when a user enters voice input, the voice data is stored in the terminal.

[1957] Step 3:

[1958] Your device converts your voice input into text

[1959] When voice input is made, the device uses speech recognition to convert the speech to text. The input is voice data, and the output is the equivalent text data. For example, voice data such as "Set a reminder for a meeting tomorrow at 10:00 AM" is converted to text such as "Set a reminder for a meeting tomorrow at 10:00 AM."

[1960] Step 4:

[1961] The device sends data to the generative AI model

[1962] The terminal sends the received or converted text data to the generative AI model. The input is text data, and the output is data waiting to be interpreted by the generative AI model. The data is sent to the generative AI model server using a communication protocol such as an HTTP request.

[1963] Step 5:

[1964] A generative AI model analyzes the input

[1965] The generative AI model analyzes the received text data. The input is text data, and the output is instructions or operational decisions based on the analysis results. The generative AI model uses natural language processing techniques to analyze the text and interpret the user's request. For example, it can understand the instruction "Set a meeting reminder."

[1966] Step 6:

[1967] The emotion engine provides emotion data to the generative AI model

[1968] The emotion engine analyzes emotions from the tone and content of a user's voice or text and provides that data to a generative AI model. The input is voice or text data, and the output is emotion data. For example, it can analyze a user's stress level from their tone of voice.

[1969] Step 7:

[1970] Generative AI models determine responses and actions

[1971] The generative AI model takes emotional data into account to determine the appropriate response or action. The input is the user's instructions and emotional data, and the output is the determined response or action. For example, it generates responses such as "Ask for reminder settings details" or "Confirm meeting details."

[1972] Step 8:

[1973] The terminal notifies the user of the response

[1974] The device notifies the user of the response from the generative AI model. The input is the response data from the generative AI model, and the output is the response that is displayed or spoken to the user. For example, a message such as "Thank you for your hard work. Could you please let me know the details of the meeting?" is displayed.

[1975] Step 9:

[1976] If necessary, the device calls the relevant API to perform the process.

[1977] When necessary, the device will call relevant application program interfaces such as a calendar API or email API to perform specific operations. The input is the user's instruction and the analysis result of the generative AI model, and the output is the result of the performed operation. For example, calling a calendar API to set a reminder.

[1978] (Application example 2)

[1979] 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."

[1980] Conventional systems using generative AI models and emotion recognition engines mainly respond to basic user operational requests, making it difficult to efficiently interact with customers in physical stores. In particular, they are insufficient when providing detailed information, such as responses based on the customer's emotional state, checking the stock of specific products, or guiding customers to their location. Therefore, in order to improve customer satisfaction in physical stores, it is necessary to provide more advanced information and responses that reflect emotions.

[1981] 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.

[1982] In this invention, the server is a terminal equipped with a generative AI model, and includes means for displaying a chat user interface on a home screen, means for receiving input from a user and converting the voice input into text, means for analyzing the received text and performing various operations, means for notifying the user of the operation results, means for analyzing the user's emotions using an emotion recognition engine, means for checking product inventory status, and means for providing the shelf location of a specific product. This allows for more advanced interaction with customers, making it possible to provide specific product information and inventory status, and to respond appropriately to the customer's emotional state.

[1983] ---

[1984] OK, now we'll create definitions for each of the key words in the rewritten claims.

[1985] definition statement

[1986] ---

[1987] A "generative AI model" is an artificial intelligence that analyzes user input and generates appropriate responses and operations.

[1988] A "chat user interface" is a user interface that is displayed on the home screen and accepts text and voice input.

[1989] A "means for converting speech input to text" is a technique for converting a user's speech input into text form.

[1990] The "means for performing various operations" is a system that performs the necessary operations based on the analyzed text.

[1991] The "means for notifying the user of the operation result" is a function for notifying the user of the result of the executed operation.

[1992] An "emotion recognition engine" is an algorithm that recognizes and analyzes emotions from the user's voice or text input.

[1993] The "means for checking product inventory status" is a system for checking whether a specific product is in stock.

[1994] The "means for providing the shelf location of a specific product" is a function that guides the user to the location where the product is stored.

[1995] ---

[1996] Understood. Now, let's create the detailed description based on the information we have provided so far.

[1997] MODE FOR CARRYING OUT THE INVENTION

[1998] ---

[1999] System Overview

[2000] This invention is a customer service system for brick-and-mortar stores that uses a terminal equipped with a generative AI model and an emotion recognition engine. This system displays a chat user interface on the screen and accepts voice and text input in response to questions and requests from customers in the store. The generative AI model analyzes these inputs and executes appropriate responses and operations. Furthermore, the emotion recognition engine can analyze customer emotions and provide responses that correspond to those emotions.

[2001] System configuration

[2002] The system includes the following main components:

[2003] 1. Device: A device that is equipped with a generative AI model and interacts with the user. Examples of devices that can be used include smartphones and tablets.

[2004] 2. Generative AI model: An artificial intelligence that analyzes user input and generates appropriate responses or actions. For example, natural language processing models (such as BERT and GPT-3) can be applied.

[2005] 3. Chat user interface: An interface that appears on the device's home screen and accepts text and voice input.

[2006] 4. Speech recognition: A function that converts user voice input into text. Examples of services that can be used include Google Cloud Speech-to-Text and Amazon Transcribe.

[2007] 5. Emotion Recognition Engine: An engine that recognizes emotions from the user's voice and text input and generates corresponding responses. For example, IBM Watson Tone Analyzer can be used.

[2008] 6. Various APIs: Application program interfaces for checking product inventory status and providing product shelf location information. RESTful APIs are commonly used for this purpose.

[2009] Operation flow

[2010] The system works as follows: First, a customer enters text into the chat user interface or issues a voice command. The input is received by the device, and in the case of voice input, it is converted into text using a speech recognition function. The text is then sent to a generative AI model for analysis. Based on the analysis results, the generative AI model determines the appropriate response or action.

[2011] The emotion recognition engine analyzes emotions from customer voice and text inputs and passes the results to a generative AI model. The generative AI model generates responses and actions taking emotional data into account. For example, if a customer's emotions indicate stress, the generative AI model will generate a more polite response. It can also provide relaxation-related information and suggestions based on their emotions.

[2012] Specific examples

[2013] Example 1: Checking inventory

[2014] User: "Can you tell me if this item is in stock?"

[2015] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[2016] Generative AI model: Analyzes the incoming text and recognizes it as an instruction to check inventory.

[2017] Emotion Recognition Engine: Analyzes emotions from user text.

[2018] Generative AI model: Calls the stock availability API to check the availability of the specified product.

[2019] Terminal: Notifies the user with the message "The product is in stock."

[2020] Example 2: Product location guidance

[2021] User: "Where is this item?"

[2022] Terminal: Receives user input and converts it to text using speech recognition if necessary.

[2023] Generative AI model: Analyzes the received text and recognizes it as instructions to guide shelf locations.

[2024] Emotion Recognition Engine: Analyzes emotions from user text.

[2025] Generative AI model: Calls the product shelf location information API to obtain the location of the specified product.

[2026] Terminal: Notifies the user with the message "The product is located in the second section of the store."

[2027] Prompt Sentence Examples

[2028] Please let me know if you have this item in stock.

[2029] "Where is this item located?"

[2030] This will make customer service in physical stores more efficient and improve customer satisfaction.

[2031] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2032] Understood. Now, I will explain the processing flow of the system program that realizes the application example, broken down into specific processing steps.

[2033] Program processing steps

[2034] ---

[2035] Step 1:

[2036] The user provides voice or text input to the chat user interface.

[2037] What happens: The user says, "Tell me if this item is in stock."

[2038] Input: User's voice input.

[2039] Output: Audio data.

[2040] Step 2:

[2041] The device receives voice input and converts it into text using speech recognition.

[2042] How it works: The device receives the audio and uses Google Cloud Speech-to-Text to convert it into text: "Tell me if this item is in stock."

[2043] Input: Audio data.

[2044] Output: Text data ("Tell me if this item is in stock").

[2045] Step 3:

[2046] The received text is sent to a generative AI model for analysis.

[2047] How it works: The device sends text data to a generative AI model (e.g., GPT-3) and receives an analysis result, which determines that the text is a request for inventory check.

[2048] Input: Text data ("Tell me if this item is in stock").

[2049] Output: Analysis result data (command "check_inventory", item "requested_item").

[2050] Step 4:

[2051] Analyze user emotions using an emotion recognition engine.

[2052] How it works: The device sends text data to an emotion recognition engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotions. The analysis results indicate that the user has a neutral attitude.

[2053] Input: Text data ("Tell me if this item is in stock").

[2054] Output: Emotion data (neutral).

[2055] Step 5:

[2056] Call the inventory status API to check the product's inventory status.

[2057] Operation: The device sends a request to the stock confirmation API to obtain the stock status of the specified product. For example, a request is sent via the RESTful API to check the stock status of "requested_item".

[2058] Input: Analysis result data (command "check_inventory", item "requested_item").

[2059] Output: Inventory status data (in stock).

[2060] Step 6:

[2061] Generate appropriate responses based on analysis results and sentiment data.

[2062] How it works: The generative AI model takes into account the analysis results and sentiment data and generates a response message saying, "The item is in stock."

[2063] Input: Stock status data (in stock), Sentiment data (neutral).

[2064] Output: Response message ("The item is in stock.").

[2065] Step 7:

[2066] Notify the user of the operation result.

[2067] Operation: The terminal notifies the user of the reply message through the chat user interface.

[2068] Input: Response message ("Item is in stock.").

[2069] Output: A text message that is displayed to the user.

[2070] This will enable customers to smoothly request product information in-store and receive appropriate responses.

[2071] 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.

[2072] 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.

[2073] 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.

[2074] 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.

[2075] 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.

[2076] 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.

[2077] 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).

[2078] 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.

[2079] 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."

[2080] 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.

[2081] 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).

[2082] 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.

[2083] 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.

[2084] 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.

[2085] 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.

[2086] 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.

[2087] 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.

[2088] 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.

[2089] 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.

[2090] 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.

[2091] 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.

[2092] The following is further disclosed regarding the above embodiment.

[2093] (Claim 1)

[2094] A terminal equipped with a generative AI model,

[2095] means for displaying a chat user interface on a home screen;

[2096] means for receiving input from a user and converting speech input to text;

[2097] means for analyzing the received text and performing various operations;

[2098] means for notifying a user of an operation result;

[2099] A system including:

[2100] (Claim 2)

[2101] A means to download and install additional features and applications from the Plug-in Market,

[2102] A means to extend existing functionality based on user requests;

[2103] The system of claim 1 further comprising:

[2104] (Claim 3)

[2105] a means for providing calendar reminders;

[2106] A means for providing an email sending function;

[2107] A means of changing various settings on your behalf,

[2108] The system of claim 1 further comprising:

[2109] (Claim 4)

[2110] means for receiving audio instructions and providing audio feedback;

[2111] A means for downloading and installing from the Plugin Market via voice commands;

[2112] The system of claim 2 further comprising:

[2113] (Claim 5)

[2114] A means for analyzing the request content and calling a calendar application API and an email sending API;

[2115] A means to notify the user of the results of reminder settings and email sending,

[2116] The system of claim 3 further comprising:

[2117] "Example 1" (Claim 1)

[2118] A terminal equipped with a generative AI model,

[2119] means for displaying a chat user interface on a home screen;

[2120] means for receiving input from a user and converting speech input to text;

[2121] A means for transmitting the received text to a generative AI model for analysis;

[2122] means for generating and displaying an appropriate response or action to the user;

[2123] a means for obtaining any additional information required from the user;

[2124] A means of calling various APIs to perform operations;

[2125] means for notifying a user of an operation result;

[2126] A system including:

[2127] (Claim 2)

[2128] A means to download and install additional features and applications from online stores;

[2129] A means to extend existing functionality based on user requests;

[2130] The system of claim 1 further comprising:

[2131] (Claim 3)

[2132] a means for providing a calendar function;

[2133] means for providing an email sending function;

[2134] A means of changing various settings on your behalf,

[2135] The system of claim 1 further comprising:

[2136] "Application Example 1"

[2137] (Claim 1)

[2138] A terminal equipped with a generative AI model,

[2139] means for displaying a chat user interface on a home screen;

[2140] means for receiving input from a user and converting speech input to text;

[2141] means for analyzing the received text and performing various operations;

[2142] means for notifying a user of an operation result;

[2143] a means for setting a destination in an autonomous vehicle;

[2144] a means of sending notifications to contacts in the event of an emergency;

[2145] A system including:

[2146] (Claim 2)

[2147] A means to download and install additional features and applications from the Plug-in Market,

[2148] A means to extend existing functionality based on user requests;

[2149] a means for providing plug-ins that optimize operation in an autonomous vehicle; and

[2150] The system of claim 1 further comprising:

[2151] (Claim 3)

[2152] a means for providing calendar reminders;

[2153] A means for providing an email sending function;

[2154] A means of changing various settings on your behalf,

[2155] a means for providing real-time navigation information;

[2156] The system of claim 1 further comprising:

[2157] "Example 2: Combining Emotion Engines"

[2158] (Claim 1)

[2159] A terminal equipped with a generative AI model,

[2160] means for displaying a chat user interface on a home screen;

[2161] means for receiving input from a user and converting speech input to text;

[2162] a means for transmitting the received text to a generative AI model;

[2163] A means for the generative AI model to analyze the text and determine the appropriate response or action based on the emotional data from the emotion engine;

[2164] A means for notifying the user of a response or operation result;

[2165] A system including:

[2166] (Claim 2)

[2167] A means to download and install additional features and applications from online stores;

[2168] means for suggesting additional features based on the emotional state of the user;

[2169] The system of claim 1 further comprising:

[2170] (Claim 3)

[2171] a means for providing calendar reminders;

[2172] A means for providing an email sending function;

[2173] A means of changing various settings on your behalf,

[2174] The system of claim 1 further comprising:

[2175] "Application Example 2 when combining emotion engines" Scope of original patent claims

[2176] ---

[2177] (Claim 1)

[2178] A terminal equipped with a generative AI model,

[2179] means for displaying a chat user interface on a home screen;

[2180] means for receiving input from a user and converting speech input to text;

[2181] means for analyzing the received text and performing various operations;

[2182] means for notifying a user of an operation result;

[2183] A system including:

[2184] (Claim 2)

[2185] A means to download and install additional features and applications from the Plug-in Market,

[2186] A means to extend existing functionality based on user requests;

[2187] The system of claim 1 further comprising:

[2188] (Claim 3)

[2189] a means for providing calendar reminders;

[2190] A means for providing an email sending function;

[2191] A means of changing various settings on your behalf,

[2192] The system of claim 1 further comprising:

[2193] ---

[2194] New Claims

[2195] ---

[2196] (Claim 1)

[2197] A terminal equipped with a generative AI model,

[2198] means for displaying a chat user interface on a home screen;

[2199] means for receiving input from a user and converting speech input to text;

[2200] means for analyzing the received text and performing various operations;

[2201] means for notifying a user of an operation result;

[2202] means for analyzing a user's emotions using an emotion recognition engine;

[2203] A way to check product availability,

[2204] a means for providing the shelf location of a particular product;

[2205] A system including:

[2206] (Claim 2)

[2207] A means to download and install additional features and applications from the Plug-in Market,

[2208] A means to extend existing functionality based on user requests;

[2209] The system of claim 1 further comprising:

[2210] (Claim 3)

[2211] a means for providing calendar reminders;

[2212] A means for providing an email sending function;

[2213] A means of changing various settings on your behalf,

[2214] a means for tailoring responses based on the customer's emotional state;

[2215] The system of claim 1 further comprising:

[2216] --- [Explanation of symbols]

[2217] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A terminal equipped with a generative AI model, means for displaying a chat user interface on a home screen; means for receiving input from a user and converting speech input to text; means for analyzing the received text and performing various operations; means for notifying a user of an operation result; A system including:

2. A means to download and install additional features and applications from the Plug-in Market, A means to extend existing functionality based on user requests; The system of claim 1 further comprising:

3. a means for providing calendar reminders; A means for providing an email sending function; A means of changing various settings on your behalf, The system of claim 1 further comprising:

4. means for receiving audio instructions and providing audio feedback; A means for downloading and installing from the Plugin Market via voice commands; The system of claim 2 further comprising:

5. A means for analyzing the request content and calling a calendar application API and an email sending API; A means to notify the user of the results of reminder settings and email sending, The system of claim 3 further comprising:

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