System

Abstract

A system is provided.SOLUTION: This system includes a means for acquiring voice data, a means for converting the acquired voice data into character data, a means for analyzing the character data and inferring the intention of a user, a means for generating an operation procedure on the basis of an inference result, and a means for guiding the generated operation procedure to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] With the recent spread of smartphones, even the elderly are now required to operate them. However, many elderly people find it difficult to learn how to operate smartphones in traditional smartphone classes, and many feel that acquiring IT skills is a high hurdle. As a result, many elderly people are limited in their use of smartphones and are unable to make full use of them. Therefore, there is a need for a support system that allows elderly people to operate smartphones more intuitively. [Means for solving the problem]

[0005] The present invention provides a system for supporting elderly people to intuitively operate smartphones, which includes the following means:

[0006] 1. How to obtain audio data

[0007] 2. A means of converting acquired audio data into text data

[0008] 3. A method for analyzing text data and inferring user intent

[0009] 4. A method for generating operating procedures based on inference results

[0010] 5. Means of guiding the generated operation procedure to the user

[0011] Furthermore, by using image and video data for analysis, it is possible to more accurately understand the user's intentions and propose appropriate operating procedures. It also includes a means of providing voice guidance to the user, allowing elderly people to operate smartphones intuitively.

[0012] "Audio data" refers to data that records audio signals obtained from a user.

[0013] "Character data" is text-format data generated by analyzing voice data.

[0014] "Analysis" is the process of inferring the user's intentions and requirements based on the acquired data.

[0015] "User intent" refers to the actions or requests that a user wants to achieve using a smartphone.

[0016] "Inference" is the process of predicting a user's intentions and next actions from data and information obtained through analysis.

[0017] "Operational procedures" refer to the specific steps a user must take on a smartphone to achieve a specific goal.

[0018] "Voice guidance" refers to the system part that conveys the generated operating procedure to the user by voice.

[0019] "Image data" refers to data of photographs taken by the user or screen captures.

[0020] "Video data" refers to data that records a video taken by a user or actions recorded on the screen.

[0021] "Guidance" refers to the process of communicating appropriate operating procedures to users and guiding them through smartphone operation. [Brief explanation of the drawings]

[0022] [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

[0023] 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.

[0024] First, the terms used in the following description will be explained.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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."

[0030] [First embodiment]

[0031] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0032] 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.

[0033] 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).

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0039] 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.

[0040] 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.

[0041] 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.

[0042] 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."

[0043] The system of the present invention is intended to assist elderly people in intuitively operating smartphones, and specific embodiments thereof will be described below.

[0044] The system is mainly composed of two parts: a terminal and a server. The terminal is equipped with a voice input device and a camera, allowing users to input voice, image, and video data. The server analyzes the received data, infers the user's intention, and generates appropriate operating procedures.

[0045] User Interaction

[0046] The user speaks to the smartphone, saying, "I want to communicate with my grandchildren on SNS." This voice input is taken through the device's voice input device.

[0047] Terminal handling

[0048] The device uses natural language processing (NLP) technology to recognize voice data and convert it into text data, which is then sent from the device to the server.

[0049] Server Analysis

[0050] The server infers the user's intent based on the text data received from the device, which includes pre-processing data analysis and uses NLP technology to understand the user's needs.

[0051] Next, the server generates operational instructions based on the inferred intent. For example, instructions for installing a social networking app or creating an account are generated at this stage.

[0052] Providing operating instructions

[0053] The generated operating instructions are sent from the server to the device, which then plays them back as voice guidance. For example, the instructions might say, "First, open the app store, then search for the social networking app, and tap the install button."

[0054] User operations

[0055] The user follows the instructions to open the app store, search for the social networking app, and install it. After completing this series of operations, the device notifies the server that the installation is complete and obtains the next steps.

[0056] Continued guidance

[0057] After the installation is complete, the device will continue to play a voice prompt saying, "Next, open the app and begin creating your account." It will also provide specific instructions for each form field, providing detailed instructions such as, "Enter your name" and "Enter your email address."

[0058] Specific examples

[0059] As a concrete example, let us consider an online shopping scenario.

[0060] The user speaks, "I want to buy a new shirt." The device converts this speech into text data and sends it to the server. The server infers the user's intent and generates online shopping instructions. For example, it might generate instructions such as, "Open a shopping site and enter 'shirt' in the search bar," and send them to the device.

[0061] The terminal provides the received instructions to the user as voice guidance, and the user operates the shopping site according to the guidance. The voice guidance supports a series of operations, from searching for products and adding them to the cart to completing the purchase.

[0062] In this way, the present invention provides a system that allows elderly people to easily operate smartphones, significantly lowering the barrier to using smartphones.

[0063] The processing flow will be explained below.

[0064] Step 1: Getting voice input

[0065] The user speaks into their smartphone, saying, "I want to communicate with my grandchildren on social media."

[0066] Step 2: Convert the audio data

[0067] The device converts the captured voice data into text data, using voice recognition technology to convert the voice into text.

[0068] Step 3: Sending character data

[0069] The terminal transmits the converted character data to the server.

[0070] Step 4: Receiving the data

[0071] The server receives the character data sent from the terminal.

[0072] Step 5: Parsing intent

[0073] The server uses natural language processing to analyze the received text data and infer the user's intent. For example, if the request is "I want to communicate with my grandchildren on social media," it can determine that a social media app needs to be installed and an account created.

[0074] Step 6: Generate operating instructions

[0075] Based on the inference results, the server generates specific operation instructions, including how to open the app store, how to search for and install social networking apps, and how to create an account.

[0076] Step 7: Send instructions

[0077] The server sends the generated operation procedure to the terminal.

[0078] Step 8: Audio guidance to the user

[0079] Based on the received operating instructions, the device will provide voice guidance to the user, such as "First, open the app store, then search for the SNS app, and tap the install button."

[0080] Step 9: User execution

[0081] The user follows the voice prompts to open the app store, search for the social networking app, and tap the install button.

[0082] Step 10: Installation Complete Notification

[0083] The device notifies the server that the installation of the SNS app has been completed.

[0084] Step 11: Account creation instructions

[0085] The device receives additional operating instructions from the server and provides the user with a voice prompt saying, "Next, open the app and begin creating your account."

[0086] Step 12: Form Assistance

[0087] The device also provides specific input assistance within the account creation form, such as "Please enter your name" and "Please enter your email address."

[0088] Step 13: Complete your account creation

[0089] Users follow the voice prompts and enter the required information into the form to complete account creation.

[0090] This series of processes realizes a system that allows users to operate their smartphones intuitively and smoothly.

[0091] Example 1

[0092] 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."

[0093] Modern smartphones are multifunctional and often difficult to operate, especially for the elderly. Even with effective use of voice input, conversion to text data, and natural language processing, it is difficult for elderly people to intuitively and easily operate smartphones. This invention aims to solve this problem by providing a system that supports elderly people in operating smartphones more intuitively.

[0094] 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.

[0095] In this invention, the server includes means for acquiring voice data, means for converting the acquired voice data into character data, means for analyzing the character data and inferring the user's intention, means for generating operation procedures based on the inference result, means for providing the generated operation procedures to the user, and means for analyzing the user's intention and generating and providing the operation procedures by the terminal and the server operating in cooperation with each other, thereby enabling elderly people to operate smartphones intuitively and easily.

[0096] "Voice data" refers to data that has been recorded and stored in digital form of a user's speech.

[0097] "Character data" refers to data obtained by converting voice data into text format.

[0098] "Analysis" is the process of understanding the information contained in text data and interpreting its meaning.

[0099] "User intent" refers to the requests and desires expressed by the user through speech input.

[0100] "Operation steps" are instructions or guidelines for performing a desired action by a user.

[0101] "Providing" refers to the act of transmitting the generated operating procedure to the user by voice or display.

[0102] A "terminal" is a device that is directly operated by a user, such as a smartphone or tablet.

[0103] A "server" is a computer system that is installed on the cloud or within a network and works in conjunction with terminals to analyze and process data.

[0104] An "audio input device" is a device, such as a microphone, used to capture audio data.

[0105] "Natural language processing" refers to techniques and methods that allow computers to understand and process human language.

[0106] The system of the present invention assists elderly people in intuitively operating smartphones. This system is composed of a terminal and a server, and aims to simplify smartphone operation by automatically generating and providing operating procedures based on the user's voice input. Specific embodiments are described below.

[0107] System configuration

[0108] The system mainly consists of two parts: a terminal equipped with a voice input device and a server that performs data analysis and generates operating procedures.

[0109] Terminal

[0110] The terminal is a mobile device such as a smartphone or tablet, equipped with a voice input device (microphone), a camera, and a communication means. The terminal receives voice data from the user and converts it into text data. This conversion is performed using natural language processing (NLP) technology such as the Google speech recognition API.

[0111] server

[0112] The server, located in the cloud or within the network, receives and analyzes the text data sent from the device. Using an NLP library such as Python's NLTK or spaCy, the server tokenizes the text data, extracts key keywords, and infers the user's intent. Based on the inference results, the server then generates and sends operational instructions to the device.

[0113] Specific operation example

[0114] 1. User voice input:

[0115] The user speaks into their smartphone, saying, "I want to communicate with my grandchildren on social media." This voice is picked up through the device's microphone.

[0116] 2. Transcription of audio data:

[0117] The device converts the acquired voice data into text data using the Google speech recognition API or similar.

[0118] 3. Sending and parsing character data:

[0119] The device sends the converted text data in real time to the server, which then analyzes it and uses libraries such as Python's NLTK or spaCy to infer the user's intent.

[0120] 4. Operational Procedure Generation:

[0121] The server generates appropriate operation instructions based on the inference results, for example, "First, open the app store, then search for the social networking app, and tap the install button."

[0122] 5. Provide instructions:

[0123] The server sends the generated operation procedure to the terminal, which then provides it to the user as voice guidance.

[0124] Specific examples

[0125] Let's consider an online shopping scenario. A user voice-inputs, "I want to buy a new shirt." The device converts this voice into text data and sends it to the server. The server infers the user's intention, generates instructions such as, "Open the shopping site and enter 'shirt' in the search bar," and sends them to the device. The device then provides the received instructions to the user as voice guidance, and the user operates the shopping site according to the instructions.

[0126] Example prompts for generative AI models

[0127] You can simulate the system's processing by inputting prompts like the following into the generative AI model:

[0128] Please explain the sequence of steps that would occur if a user were to say, "I want to communicate with my grandchildren on social media," using voice input into a smartphone. Please include speech recognition, data analysis, generation of operating procedures, and voice guidance.

[0129] In this way, the system of the present invention enables elderly people to operate smartphones intuitively and easily, and supports their use of smartphones.

[0130] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0131] Step 1: User Speech Input

[0132] The user speaks into their smartphone, saying, "I want to communicate with my grandchildren on social media." The input is voice data, which is picked up by the device's microphone. The voice data is then prepared for use in the next processing step.

[0133] Step 2: Transcribe the audio data

[0134] The device converts the acquired voice data into text data using natural language processing (NLP) technology such as the Google speech recognition API. This conversion is a specific operation that takes voice data as input, analyzes it, and outputs text data. For example, the voice data "I want to communicate with my grandchildren on social media" is converted into text data "I want to communicate with my grandchildren on social media."

[0135] Step 3: Sending character data

[0136] The terminal transmits the converted text data to the server in real time. The input here is text data, and the output is data transmission to the server. Specifically, an HTTP request is sent from the terminal to the server, and the text data is included.

[0137] Step 4: Parsing character data

[0138] The server infers the user's intent based on the received text data. It uses an NLP library such as Python's NLTK or spaCy to tokenize the text data and extract key keywords. In this step, the input is the text data, and the output is the inferred user intent. Specifically, the server analyzes the text data and identifies keywords such as "grandchild," "SNS," and "interaction."

[0139] Step 5: Generate operating instructions

[0140] The server generates appropriate operating instructions based on the inferred intent. The input here is the user's intent, and the output is the operating instructions. Specifically, the server references predefined scenarios and procedure templates to create a guide such as "First, open the app store, then search for the social networking app, and tap the install button."

[0141] Step 6: Send instructions

[0142] The server sends the generated operation procedure to the terminal. The input is the generated operation procedure, and the output is data transmission to the terminal. A specific operation is an HTTP response sent from the server to the terminal, which includes the generated operation procedure.

[0143] Step 7: Provide operating instructions

[0144] The device receives the operation procedure from the server and provides it to the user as voice guidance. The input here is the generated operation procedure, and the output is the voice guidance. Specifically, the device uses voice synthesis technology to provide voice guidance such as, "First, open the app store, then search for the SNS app, and tap the install button."

[0145] Step 8: User interaction

[0146] The user operates the smartphone according to the provided voice guidance. The input is the voice guidance, and the output is the corresponding smartphone operation. Specifically, the user opens the app store, searches for the SNS app, and installs it.

[0147] Step 9: Installation Complete Notification

[0148] The device notifies the server that the user has completed installation of the SNS app. The input is the installation completion status, and the output is a notification to the server. Specifically, the device detects the completion of installation and sends the status to the server via an HTTP request.

[0149] Step 10: Next steps

[0150] The server receives notification that the installation is complete, generates next steps, and sends them to the device. The device then plays the next steps received from the server as voice guidance. The input here is the next steps, and the output is voice guidance. For example, the guidance may say, "Next, open the app and begin creating your account." Specific operations include providing detailed voice instructions for each input field in the form, such as "Please enter your name" or "Please enter your email address."

[0151] (Application example 1)

[0152] 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."

[0153] In traditional factory facilities and industrial automation environments, elderly and inexperienced workers face the challenge of efficiently operating sophisticated machinery and equipment. This can lead to operational errors and delays in maintenance work, resulting in concerns about reduced overall efficiency. Furthermore, the lack of intuitive and easy-to-understand operating guides means that training and education are time-consuming and costly.

[0154] 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.

[0155] In this invention, the server includes means for acquiring voice data, means for converting the voice data into character data, means for analyzing the character data and inferring a user's intention, means for generating an operating procedure based on the inference result, means for guiding the generated operating procedure to the user, and means for providing voice guidance and displaying visual guidance for operating the industrial automation device based on the user's intention, thereby enabling even elderly people and inexperienced workers to intuitively operate and maintain the industrial automation device.

[0156] "Means for acquiring voice data" refers to devices or software for collecting the voice uttered by the user as digital data.

[0157] "Means for converting voice data into text data" refers to technology or devices that analyze acquired voice data and convert it into corresponding text information.

[0158] "Means for analyzing character data and inferring user intent" refers to a system that analyzes character data entered by a user using natural language processing technology, etc., to understand what the user is trying to do.

[0159] "Means for generating operating procedures based on inference results" refers to a technology or mechanism that generates accurate and specific operating methods or work procedures according to the inferred user intentions.

[0160] The "means for guiding the generated operating procedure to the user" refers to a method or device for presenting the generated operating procedure to the user in an easy-to-understand manner.

[0161] "Means for providing audio guidance and displaying visual guidance for operating industrial automation equipment based on the user's intentions" refers to technology or devices that explain the appropriate procedures through audio and visual presentations when elderly or inexperienced workers operate industrial automation equipment.

[0162] "Means for using image data and video data" refers to technologies and systems for obtaining and analyzing useful information from static images and dynamic video.

[0163] "Means for generating and providing guidance on maintenance procedures for industrial automation equipment" refers to technology or mechanisms that generate specific methods for maintaining and repairing automated machinery used in factories, etc., and provide easy-to-understand guidance to workers.

[0164] The present invention provides a system that enables elderly or inexperienced workers to intuitively operate and maintain industrial automation equipment. The system aims to simplify complex operating procedures by combining voice input and visual guidance, thereby improving efficiency and safety.

[0165] Hardware and Software Configuration

[0166] The device uses smart glasses or head-mounted displays (e.g., Google Glass, Microsoft HoloLens) equipped with a voice input device and a camera, which can rapidly collect the user's voice and provide visual feedback.

[0167] The server uses advanced natural language processing (NLP) techniques to analyze the user's voice data. The voice data is converted into text data, and the user's intent is then inferred. Based on this inference, specific operating instructions are generated. The server uses the Google Speech-to-Text API and natural language processing libraries (e.g., spaCy, NLTK).

[0168] Data processing and calculation

[0169] The device captures the user's voice and converts it into text data in real time using the Google Speech-to-Text API. This text data is then sent to a server, where natural language processing technology is used to analyze the user's intent and generate appropriate operating instructions based on the analysis results. The generated instructions are then sent to the device as audio and visual guidance and provided to the user.

[0170] Specific examples

[0171] For example, if a user says "I want to start maintenance on the robot," the device collects the voice, converts the data into text, and sends it to the server. The server analyzes the text and generates specific maintenance instructions, such as "First, turn off the safety device, then open the panel." The generated instructions are sent to the device as audio and visual guidance, and the user is guided through them.

[0172] Example prompt sentence:

[0173] Imagine a scenario where a user uses smart glasses to say, "I want to start maintenance on the robot." Explain the process of converting this speech into text data, sending it to a server, generating appropriate maintenance instructions, and displaying and providing voice guidance on the smart glasses.

[0174] In this way, the system of the present invention realizes an environment in which elderly people and inexperienced workers can easily operate and maintain industrial automation equipment.

[0175] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0176] Step 1:

[0177] The user provides voice input

[0178] The user inputs "I want to start maintenance on the robot" through a voice input device on the smart glasses or head-mounted display. The input is voice data. The output is obtained as voice data.

[0179] Step 2:

[0180] The device converts the voice data into text data.

[0181] The device's internal processing converts acquired voice data into text data using the Google Speech-to-Text API. The input is voice data, and the output is the converted text data.

[0182] Step 3:

[0183] The terminal sends character data to the server

[0184] The converted character data is sent from the terminal to the server. The input is character data, and the output is character data sent to the server.

[0185] Step 4:

[0186] The server analyzes the text data and infers the user's intent.

[0187] On the server side, the received text data is analyzed using natural language processing (NLP) technology to infer the user's intent. The software used is an NLP library such as spaCy or NLTK. The input is text data, and the output is data indicating the user's intent.

[0188] Step 5:

[0189] The server generates an operating procedure based on the inference results.

[0190] The server generates specific operating procedures based on the inferred user intent. In this generation process, appropriate procedures are automatically generated using a generative AI model. The input is data indicating the user intent, and the output is operating procedure data.

[0191] Step 6:

[0192] Send the operation instructions generated by the server to the terminal

[0193] The generated operation procedure data is sent from the server to the terminal. The input is the operation procedure data, and the output is the data sent to the terminal.

[0194] Step 7:

[0195] The device guides the user through operation procedures both audibly and visually.

[0196] The terminal provides the received operation procedure data to the user as voice guidance and visual guidance. The voice guidance uses voice synthesis technology, and the visual guidance is displayed on the display of the smart glasses or head-mounted display. The input is the operation procedure data, and the output is the voice guidance and visual guidance.

[0197] Step 8:

[0198] The user performs the operation

[0199] The user operates and maintains the industrial automation equipment according to the voice and visual guidance provided by the terminal, where the input is the voice and visual guidance and the output is the operation performed.

[0200] The above steps allow the user to intuitively operate and maintain industrial automation equipment.

[0201] 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.

[0202] The present invention is a system that supports the elderly in intuitively operating smartphones, and in particular incorporates an emotion engine that recognizes the user's emotions and responds adaptively. Here, a specific embodiment incorporating the emotion engine will be described.

[0203] The system is composed of a terminal, a server, and an emotion engine working together. The terminal is equipped with a voice input device and a camera, allowing users to input voice, image, and video data. The emotion engine also analyzes the user's voice and image data to recognize the user's emotional state.

[0204] User Interaction

[0205] The user speaks to the smartphone, saying, "I want to communicate with my grandchildren on SNS." This voice input is taken through the device's voice input device.

[0206] Terminal handling

[0207] The device converts the captured voice data into text using voice recognition technology. If there is any voice data or image data, it also acquires it and sends it to the emotion engine.

[0208] Emotion engine processing

[0209] The emotion engine analyzes the acquired voice and image data to recognize the user's emotional state, for example, distinguishing between when the user is in trouble or when they are feeling anxious.

[0210] Server Analysis

[0211] The server receives data sent from the device and emotion engine and infers the user's intention. Here, it also uses emotional information obtained from the emotion engine. For example, if it infers that the user is in trouble, it generates more detailed procedural instructions than usual.

[0212] Operation procedure generation and response

[0213] The server generates adaptive operation instructions based on the inference results and emotional information. For example, it generates specific instructions for installing a social networking app and creating an account. If the user feels anxious, it provides detailed instructions.

[0214] Sending and providing instructions

[0215] The generated operating instructions are sent from the server to the device, which then provides them to the user as voice guidance. Specific instructions include, "First, open the app store, then search for the SNS app, and tap the install button."

[0216] User operations

[0217] The user follows the voice prompts to open the app store, search for the social networking app, and tap the install button.

[0218] Continued guidance

[0219] Once the installation is complete, the device will receive instructions from the server, such as "Next, open the app and begin creating your account." The emotion engine continues to monitor the user's emotions and adjusts the level of detail of the instructions as needed.

[0220] Emotion-Based Feedback

[0221] The device will use the emotion engine again to recognize the user's emotions while they are operating the device, and provide feedback based on that information. For example, even if the user is feeling anxious, the device will respond with positive feedback such as "That went well" if the operation is successful.

[0222] In this way, the present invention provides a system that supports more adaptive and intuitive smartphone operation by taking into account the user's emotional state. Specifically, it analyzes voice and image data and combines an emotion engine to provide operation procedures and feedback that comprehensively consider the user's intentions and emotions. This allows elderly people to use smartphones smoothly and safely.

[0223] The processing flow will be explained below.

[0224] Step 1: Getting voice input

[0225] The user speaks into their smartphone, saying, "I want to communicate with my grandchildren on social media."

[0226] Step 2: Convert the audio data

[0227] The device converts the captured voice data into text data, using voice recognition technology to convert the voice into text.

[0228] Step 3: Sending character data

[0229] The terminal transmits the converted character data to the server.

[0230] Step 4: Obtaining emotion data

[0231] The device sends audio data and, if necessary, image and video data of the user to the emotion engine.

[0232] Step 5: Analyze the sentiment data

[0233] The emotion engine analyzes the acquired voice and image data to recognize the user's emotions, for example, determining whether the user is feeling anxious.

[0234] Step 6: Receiving Data

[0235] The server receives the character data sent from the terminal and the emotion data sent from the emotion engine.

[0236] Step 7: Parsing intent

[0237] The server uses natural language processing to analyze the text data and infer the user's intent. Based on the request, "I want to communicate with my grandchildren on social media," it infers that the user needs to install a social media app and create an account.

[0238] Step 8: Generate operating instructions

[0239] The server generates adaptive operating procedures based on the inference results and emotion data. If the server detects anxiety in the user, it adjusts the procedures to be more detailed and easy to understand.

[0240] Step 9: Send instructions

[0241] The server transmits the generated adaptive operation procedure to the terminal.

[0242] Step 10: Voice prompts to the user

[0243] Based on the received operating instructions, the device will provide voice guidance to the user, such as "First, open the app store, then search for the SNS app, and tap the install button."

[0244] Step 11: User execution

[0245] The user follows the voice prompts to open the app store, search for the social networking app, and tap the install button.

[0246] Step 12: Installation Complete Notification

[0247] The device notifies the server that the installation of the SNS app has been completed.

[0248] Step 13: Account creation instructions

[0249] The device receives additional instructions from the server and provides a voice prompt to the user saying, "Next, open the app and begin creating your account." The emotion engine continues to monitor the user's emotions and provides further detailed instructions if anxiety persists.

[0250] Step 14: Form Assistance

[0251] The device will provide specific instructions for each input field on the account creation form, providing detailed instructions aloud such as "Please enter your name" or "Please enter your email address."

[0252] Step 15: Emotional Feedback

[0253] The emotion engine continuously analyzes the user's emotions while filling out the form, and provides relaxing feedback such as "Take it easy, it's okay" when stress levels rise.

[0254] Step 16: Complete your account creation

[0255] Users follow the voice prompts and enter the required information into the form to complete account creation.

[0256] In this way, by combining emotion engines, it becomes possible to respond adaptively to the user's emotional state, realizing a system that allows elderly people to operate smartphones comfortably.

[0257] Example 2

[0258] 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."

[0259] For elderly people who have difficulty intuitively operating smartphones, conventional systems have had difficulty recognizing the user's emotional state and providing adaptive support. In particular, when the operating procedures are difficult or the user feels anxious, appropriate support is not provided, which can lead to operational errors and stress in the user. There is a need to solve this problem and provide a system that can support elderly people in using smartphones with confidence.

[0260] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0261] In this invention, the server includes means for acquiring user voice data, means for converting the acquired voice data into character data, means for acquiring image data and video data using a camera, means for analyzing the acquired voice data and image data to recognize the user's emotional state, means for inferring the user's intention based on the analysis results of the voice data and emotional state, means for generating operation procedures based on the inference results and emotional information, means for providing the generated operation procedures to the user as voice guidance, and means for re-monitoring the user's emotional state during operation and adjusting the guidance content as necessary. This allows the user to receive optimal support according to their emotional state, enabling elderly people to operate smartphones smoothly and safely.

[0262] The "means for acquiring user voice data" refers to a device or system that collects the user's voice through a microphone.

[0263] The "means for converting acquired voice data into text data" refers to a process or system that converts voice data into text data using voice recognition technology.

[0264] "Means for acquiring image data and video data using a camera" refers to a device or system that uses a camera to record a user's actions and expressions and collects them as image or video data.

[0265] "Means for analyzing acquired audio and image data to recognize a user's emotional state" refers to a process or system that analyzes the collected data to identify a user's emotions (e.g., anxiety, confusion, joy, etc.).

[0266] A "means for inferring user intent based on analysis of speech data and emotional state" is a process or system that uses the analysis to identify the user's wants and needs.

[0267] The "means for generating operating procedures based on inference results and emotional information" refers to a process or system that generates appropriate operating procedures or guidelines according to the user's intentions and emotional state.

[0268] The "means for providing the generated operating procedure to the user as voice guidance" refers to a process or system that converts the generated operating procedure into voice data format and provides voice guidance to the user.

[0269] "Means for re-monitoring the user's emotional state during operation and adjusting the guidance content as necessary" refers to a process or system that re-monitors the user's emotions during operation and adaptively changes the details and content of the guidance according to the user's state.

[0270] The present invention is a system that supports the elderly in intuitively operating smartphones, and in particular incorporates an emotion engine to provide guidance and feedback that is adapted to the user's emotional state. Specific embodiments of the present invention will be described below.

[0271] System configuration

[0272] This system works in cooperation with a terminal, a server, and an emotion engine. The terminal is equipped with a voice input device and a camera, allowing users to input voice, image, and video data. The emotion engine analyzes the user's voice data and image data to recognize the user's emotional state. The server infers the user's intentions based on this data, generates appropriate operating procedures, and provides voice guidance.

[0273] Hardware and software used

[0274] Device: A mobile device such as a smartphone or tablet, including a voice input device (microphone) and a camera.

[0275] Speech recognition technology: Common cloud-based speech recognition APIs (e.g., Google Speech-to-Text API).

[0276] Emotion engine: An API for analyzing user emotions (e.g., Microsoft Azure's Emotion API).

[0277] Server: A cloud server for performing inference and procedure generation.

[0278] Speech synthesis technology: Technology that converts the generated instructions into voice guidance (e.g., Amazon Polly).

[0279] Specific operation of the system

[0280] 1. User Interaction

[0281] The user speaks to the smartphone, saying, "I want to communicate with my grandchildren on SNS." This voice input is acquired through the device's voice input device.

[0282] 2. Transcription of audio data

[0283] The device uses voice recognition technology to convert the acquired voice data into text data. For example, an input such as "I want to communicate with my grandchildren on social media" is converted into text.

[0284] 3. Acquisition of image and video data

[0285] The device uses a camera to record the user's facial expressions and movements, capturing image and video data, which is then sent to the emotion engine along with audio data.

[0286] 4. Emotion analysis

[0287] The emotion engine analyzes the received voice and image data to recognize the user's emotional state, for example, identifying various emotions such as whether the user is distressed or anxious.

[0288] 5. Intention Inference

[0289] The server uses natural language processing technology to infer the user's intentions based on the data sent from the emotion engine. Emotional information is also used to determine if the user is having trouble and if more detailed guidance is needed.

[0290] 6. Operation procedure generation

[0291] The server generates adaptive operation instructions based on the inference results and emotional information. For example, when guiding a user through the steps of installing a social networking app, if the user feels anxious, the server will break down the steps into more detailed instructions.

[0292] 7. Audio guidance of procedures

[0293] The generated operating instructions are sent from the server to the device, which then uses speech synthesis technology to provide voice guidance to the user, such as "First, open the app store, then search for the SNS app, and tap the install button."

[0294] 8. User Operations

[0295] The user follows the voice guidance to operate the smartphone. If the user does not understand an operation, they can ask for help by voice input again.

[0296] 9. Emotion Monitoring and Feedback

[0297] The device will again use the emotion engine to monitor the user's emotions during operation, adjust the level of detail when guiding the user through the next steps as needed, and provide positive feedback such as "That was great, good job" when the user performs a successful operation.

[0298] Specific examples

[0299] Below are examples of typical user speech input and subsequent prompts for actions:

[0300] Prompt Sentence Examples

[0301] User: "I want to communicate with my grandchildren on social media."

[0302] The device recognizes the voice, and the emotion engine analyzes the user's emotions. If it determines that the user is in trouble, the server generates more detailed instructions.

[0303] Server: "First, open the app store. Then search for a social networking app. Tap the install button."

[0304] In this way, the system provides comprehensive support for elderly people to smoothly operate smartphones while taking into account the user's emotional state.

[0305] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0306] Step 1:

[0307] The user inputs voice data. Specifically, the user speaks into the smartphone, saying, "I want to communicate with my grandchildren on SNS." This voice data is input.

[0308] Input: User's voice data

[0309] Output: Audio data file (WAV, MP3, etc.)

[0310] Step 2:

[0311] The device converts the acquired voice data into text data using voice recognition technology, such as the Google Speech-to-Text API.

[0312] Input: Audio data file

[0313] Data processing: Speech-to-text conversion using speech recognition algorithms

[0314] Output: Character data (text format)

[0315] Step 3:

[0316] The terminal uses a camera to record the user's facial expressions and movements, and acquires image data and video data.

[0317] Input: Captured video data

[0318] Data processing: Creating and saving video files

[0319] Output: Image data (JPEG, PNG), video data (MP4, AVI)

[0320] Step 4:

[0321] The emotion engine analyzes audio and image data to recognize the user's emotional state, for example, using Microsoft Azure's Emotion API.

[0322] Input: Text data, image data, video data

[0323] Data processing: Application of emotion recognition algorithms through natural language processing and image analysis

[0324] Output: Emotional state data (e.g., confusion, anxiety, joy)

[0325] Step 5:

[0326] The server infers the user's intention based on the emotional state data and text data sent from the emotion engine, using natural language processing technology (e.g., OpenAI's GPT-3).

[0327] Input: Emotional state data, character data

[0328] Data processing: Intention inference using natural language processing

[0329] Output: User intent data (e.g., "I want to interact on social media")

[0330] Step 6:

[0331] The server generates operation instructions based on the inference results and the emotional state, such as instructions for installing a social networking app.

[0332] Input: User intent data, emotional state data

[0333] Data processing: Applying procedure generation algorithms and assembling detailed operational steps

[0334] Output: Specific operating instructions (e.g., "First, open the app store")

[0335] Step 7:

[0336] The server then sends the generated instructions to the device, which then provides them as voice prompts, for example by using Amazon Polly to convert text to speech.

[0337] Input: Operation procedure data

[0338] Data processing: Use of Text-to-Speech technology (TTS)

[0339] Output: Audio data (audio guide for operation procedures)

[0340] Step 8:

[0341] The user follows the voice prompts to open the app store, search for the social networking app, and tap the install button. As the user performs these actions, the system continues to monitor the user's reactions.

[0342] Input: Voice guidance

[0343] Output: User action

[0344] Step 9:

[0345] The device monitors the user's emotions using the emotion engine again during the user's operation, and provides guidance on the next steps, adjusting the level of detail of the guidance as necessary.

[0346] Input: Real-time video and audio data

[0347] Data processing: Updates with sentiment analysis

[0348] Output: Adjusted operating procedure voice guidance

[0349] Step 10:

[0350] The device provides feedback based on the emotions recognized during the user's operation, for example, giving positive feedback such as "That was great, good job!"

[0351] Input: Updated emotional state data, user action data

[0352] Data processing: Applying feedback generation algorithms

[0353] Output: Feedback audio data

[0354] (Application example 2)

[0355] 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."

[0356] Elderly people often find it difficult to use smartphones due to their complex operation. Furthermore, in order to provide appropriate support for their operation, it is necessary to understand the user's emotional state and respond adaptively. However, current systems have difficulty providing support that takes the user's emotions into account, which can result in users feeling anxious or confused. The purpose of this invention is to solve this problem and enable elderly people to use smartphones with peace of mind.

[0357] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring voice data, means for converting the acquired voice data into character data, means for analyzing the character data and inferring the user's intention, means for generating operation procedures based on the inference results, means for guiding the generated operation procedures to the user, and means for adaptively responding using an emotion engine that analyzes the user's emotional state. This makes it possible to provide adaptive and detailed operation procedures while taking the user's emotional state into consideration. It is also possible to provide positive feedback upon success so that the user can continue operating with peace of mind.

[0358] "Means for acquiring voice data" refers to a device or system for collecting voice input from a user.

[0359] The term "means for converting voice data into character data" refers to a technology for converting acquired voice data into character information, such as a voice recognition technology.

[0360] "Means for analyzing character data and inferring the user's intent" refers to algorithms or programs that use converted character data to infer what the user is looking for.

[0361] "Means for generating operating procedures based on inference results" refers to a program or system for automatically generating operating procedures according to the user's intentions.

[0362] The "means for guiding the generated operating procedure to the user" refers to a method for communicating the generated operating procedure to the user, such as voice guidance or screen display.

[0363] An "emotion engine that analyzes a user's emotional state" refers to software or a program that analyzes a user's voice data or image data to recognize the user's emotional state.

[0364] "Adaptive response means" refers to a system that adjusts the guidance content and operating procedures according to the user's emotional state.

[0365] "Using image data and video data as the subject of analysis" refers to analyzing not only audio data but also image data and video data that include the user's facial expressions and actions.

[0366] "Means for providing audio guidance to a user" refers to a system or technology for conveying information or instructions to a user by voice.

[0367] "Means for adjusting the level of detail of operation procedures" refers to a method for adjusting the level of detail of the operation procedures presented depending on the user's emotional state and skill level.

[0368] "Means for providing positive feedback for successful operations" refers to software or a system that provides positive feedback by voice or display when a user successfully performs an operation.

[0369] "Means for the server to generate a response based on the inference results" refers to the technology that enables the server to create a response based on the analysis results based on voice data and emotional data and provide it to the user.

[0370] "Means for generating and guiding operating procedures using a generative AI model and prompt sentences" refers to an algorithm or system that uses a generative AI model to generate appropriate prompt sentences and provides operating procedures to the user based on those prompt sentences.

[0371] The present invention relates to a system that uses an emotion engine to grasp the emotional state of elderly people when they use a smartphone to deliver food, and provides adaptive operating procedures and feedback.

[0372] System Overview

[0373] This system operates in cooperation with the terminal, server, and emotion engine.

[0374] Terminal: A mobile device such as a smartphone equipped with a voice input device and a camera. The terminal has the function of receiving voice data from the user and converting it into text data.

[0375] Server: Analyzes voice and image data to infer the user's intentions and emotions. Based on the analysis results, the server generates adaptive operating procedures and provides feedback.

[0376] Emotion engine: An algorithm that analyzes the user's emotional state based on their voice and image data.

[0377] Hardware and Software

[0378] Hardware

[0379] Smartphone (with voice input device and camera)

[0380] software

[0381] speech_recognition library: Used to convert speech input into text data.

[0382] emotion_recognition: A custom library for sentiment analysis.

[0383] server_communication: For server communication.

[0384] voice_assistant: A custom module for voice assistant functionality.

[0385] Specific processing examples

[0386] 1. Acquiring and recognizing voice input:

[0387] The device receives voice input from the user, such as "I would like to order sushi," and converts this into text data using the speech_recognition library.

[0388] 2. Emotion recognition using emotion engine:

[0389] The acquired voice data and image data are analyzed by an emotion engine to identify the user's emotional state, such as whether they are feeling anxious or distressed.

[0390] 3. Sending data to the server:

[0391] Emotional data and voice data are sent to the server, which then uses this data to infer the user's intentions. For example, a request such as "I want to order sushi" is received.

[0392] 4. Operational Procedure Generation:

[0393] The server generates adaptive operation instructions based on the inference results and emotion data. If detailed instructions are required, it generates specific instructions such as "First, open the app and tap the sushi category."

[0394] 5. Audio feedback:

[0395] The generated instructions are sent to the device, and the voice assistant uses "voice_assistant" to provide feedback to the user: "Next, open the app store, search for the social networking app, and tap the install button."

[0396] 6. Positive Feedback:

[0397] If the operation is successful, the emotion engine checks the status again and provides positive feedback such as "That worked."

[0398] Specific examples and prompts for the generative AI model

[0399] Examples:

[0400] If a user voice-inputs "I want to order sushi" and the emotion engine detects that the user is in a "troubled" state, the server will generate a prompt sentence like the following:

[0401] Example prompt sentence:

[0402] 1. "First, open your food delivery app."

[0403] 2. "Next, tap on the Sushi category from the menu."

[0404] 3. "Choose your favorite sushi item and add it to your cart."

[0405] 4. "Please confirm your order details and press the button to confirm your order."

[0406] In this way, the system allows users to use their smartphones and operate food delivery services with emotional security.

[0407] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0408] Step 1:

[0409] Acquiring voice input:

[0410] The user speaks into the smartphone, saying, "I'd like to order sushi." The terminal acquires this speech using a voice input device. The input data is the user's voice data. The terminal acquires this voice data and sends it to the next step.

[0411] Step 2:

[0412] Audio to text conversion:

[0413] The device uses the speech_recognition library to convert the acquired voice data into text data. The input data is voice data, and the output data is text data converted from this voice. Data conversion is performed using voice recognition technology.

[0414] Step 3:

[0415] Emotional State Analysis:

[0416] The device sends voice and image data to the emotion engine, which analyzes the user's emotional state. The input data is the converted text data and voice data, and the output data is the user's emotional state (for example, "I'm in trouble" or "I'm relieved"). The emotion engine analyzes this using a machine learning algorithm.

[0417] Step 4:

[0418] Sending data to the server:

[0419] The terminal transmits emotional data and text data to the server. The input data is the analyzed emotional state and text data, and the output data is the data received by the server. Here, data communication technology is used.

[0420] Step 5:

[0421] Intention inference by the server:

[0422] The server infers the user's intention based on the received text data and emotional data. The input data is the emotional state and text data, and the output data is the user's intention (e.g., "I want to order sushi"). The server uses natural language processing technology and inference algorithms.

[0423] Step 6:

[0424] Generate operating instructions:

[0425] The server generates adaptive operation instructions based on the user's intention and emotional state. The input data is the inferred user's intention and emotional state, and the output data is the specific operation instructions (e.g., "First, open the app and tap the sushi category"). The server then uses a generative AI model to create an appropriate prompt.

[0426] Step 7:

[0427] Sending instructions:

[0428] The server sends the generated operation procedure to the terminal. The input data is the generated operation procedure, and the output data is the operation procedure received by the terminal. Data communication technology is used.

[0429] Step 8:

[0430] Voice guidance for operation procedures:

[0431] The device uses a voice assistant to provide guidance to the user based on the received operating instructions. The input data is the operating instructions, and the output data is voice guidance to the user. Speech synthesis technology is used to audibly convey specific operating procedures to the user.

[0432] Step 9:

[0433] User interaction and feedback:

[0434] The user follows the voice guidance to perform the operation. The device again uses the emotion engine to monitor the user's emotional state and provides positive feedback if the operation is successful. The input data is the user's operation result and new emotional data, and the output data is positive feedback. This allows the user to gain confidence in their operation and use the app with peace of mind.

[0435] 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.

[0436] 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.

[0437] 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.

[0438] [Second embodiment]

[0439] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0440] 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.

[0441] 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).

[0442] 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.

[0443] 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.

[0444] 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).

[0445] 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.

[0446] 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.

[0447] 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.

[0448] 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.

[0449] 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.

[0450] 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."

[0451] The system of the present invention is intended to assist elderly people in intuitively operating smartphones, and specific embodiments thereof will be described below.

[0452] The system is mainly composed of two parts: a terminal and a server. The terminal is equipped with a voice input device and a camera, allowing users to input voice, image, and video data. The server analyzes the received data, infers the user's intention, and generates appropriate operating procedures.

[0453] User Interaction

[0454] The user speaks to the smartphone, saying, "I want to communicate with my grandchildren on SNS." This voice input is taken through the device's voice input device.

[0455] Terminal handling

[0456] The device uses natural language processing (NLP) technology to recognize voice data and convert it into text data, which is then sent from the device to the server.

[0457] Server Analysis

[0458] The server infers the user's intent based on the text data received from the device, which includes pre-processing data analysis and uses NLP technology to understand the user's needs.

[0459] Next, the server generates operational instructions based on the inferred intent. For example, instructions for installing a social networking app or creating an account are generated at this stage.

[0460] Providing operating instructions

[0461] The generated operating instructions are sent from the server to the device, which then plays them back as voice guidance. For example, the instructions might say, "First, open the app store, then search for the social networking app, and tap the install button."

[0462] User operations

[0463] The user follows the instructions to open the app store, search for the social networking app, and install it. After completing this series of operations, the device notifies the server that the installation is complete and obtains the next steps.

[0464] Continued guidance

[0465] After the installation is complete, the device will continue to play a voice prompt saying, "Next, open the app and begin creating your account." It will also provide specific instructions for each form field, providing detailed instructions such as, "Enter your name" and "Enter your email address."

[0466] Specific examples

[0467] As a concrete example, let us consider an online shopping scenario.

[0468] The user speaks, "I want to buy a new shirt." The device converts this speech into text data and sends it to the server. The server infers the user's intent and generates online shopping instructions. For example, it might generate instructions such as, "Open a shopping site and enter 'shirt' in the search bar," and send them to the device.

[0469] The terminal provides the received instructions to the user as voice guidance, and the user operates the shopping site according to the guidance. The voice guidance supports a series of operations, from searching for products and adding them to the cart to completing the purchase.

[0470] In this way, the present invention provides a system that allows elderly people to easily operate smartphones, significantly lowering the barrier to using smartphones.

[0471] The processing flow will be explained below.

[0472] Step 1: Getting voice input

[0473] The user speaks into their smartphone, saying, "I want to communicate with my grandchildren on social media."

[0474] Step 2: Convert the audio data

[0475] The device converts the captured voice data into text data, using voice recognition technology to convert the voice into text.

[0476] Step 3: Sending character data

[0477] The terminal transmits the converted character data to the server.

[0478] Step 4: Receiving the data

[0479] The server receives the character data sent from the terminal.

[0480] Step 5: Parsing intent

[0481] The server uses natural language processing to analyze the received text data and infer the user's intent. For example, if the request is "I want to communicate with my grandchildren on social media," it can determine that a social media app needs to be installed and an account created.

[0482] Step 6: Generate operating instructions

[0483] Based on the inference results, the server generates specific operation instructions, including how to open the app store, how to search for and install social networking apps, and how to create an account.

[0484] Step 7: Send instructions

[0485] The server sends the generated operation procedure to the terminal.

[0486] Step 8: Audio guidance to the user

[0487] Based on the received operating instructions, the device will provide voice guidance to the user, such as "First, open the app store, then search for the SNS app, and tap the install button."

[0488] Step 9: User execution

[0489] The user follows the voice prompts to open the app store, search for the social networking app, and tap the install button.

[0490] Step 10: Installation Complete Notification

[0491] The device notifies the server that the installation of the SNS app has been completed.

[0492] Step 11: Account creation instructions

[0493] The device receives additional operating instructions from the server and provides the user with a voice prompt saying, "Next, open the app and begin creating your account."

[0494] Step 12: Form Assistance

[0495] The device also provides specific input assistance within the account creation form, such as "Please enter your name" and "Please enter your email address."

[0496] Step 13: Complete your account creation

[0497] Users follow the voice prompts and enter the required information into the form to complete account creation.

[0498] This series of processes realizes a system that allows users to operate their smartphones intuitively and smoothly.

[0499] Example 1

[0500] 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."

[0501] Modern smartphones are multifunctional and often difficult to operate, especially for the elderly. Even with effective use of voice input, conversion to text data, and natural language processing, it is difficult for elderly people to intuitively and easily operate smartphones. This invention aims to solve this problem by providing a system that supports elderly people in operating smartphones more intuitively.

[0502] 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.

[0503] In this invention, the server includes means for acquiring voice data, means for converting the acquired voice data into character data, means for analyzing the character data and inferring the user's intention, means for generating operation procedures based on the inference result, means for providing the generated operation procedures to the user, and means for analyzing the user's intention and generating and providing the operation procedures by the terminal and the server operating in cooperation with each other, thereby enabling elderly people to operate smartphones intuitively and easily.

[0504] "Voice data" refers to data that has been recorded and stored in digital form of a user's speech.

[0505] "Character data" refers to data obtained by converting voice data into text format.

[0506] "Analysis" is the process of understanding the information contained in text data and interpreting its meaning.

[0507] "User intent" refers to the requests and desires expressed by the user through speech input.

[0508] "Operation steps" are instructions or guidelines for performing a desired action by a user.

[0509] "Providing" refers to the act of transmitting the generated operating procedure to the user by voice or display.

[0510] A "terminal" is a device that is directly operated by a user, such as a smartphone or tablet.

[0511] A "server" is a computer system that is installed on the cloud or within a network and works in conjunction with terminals to analyze and process data.

[0512] An "audio input device" is a device, such as a microphone, used to capture audio data.

[0513] "Natural language processing" refers to techniques and methods that allow computers to understand and process human language.

[0514] The system of the present invention assists elderly people in intuitively operating smartphones. This system is composed of a terminal and a server, and aims to simplify smartphone operation by automatically generating and providing operating procedures based on the user's voice input. Specific embodiments are described below.

[0515] System configuration

[0516] The system mainly consists of two parts: a terminal equipped with a voice input device and a server that performs data analysis and generates operating procedures.

[0517] Terminal

[0518] The terminal is a mobile device such as a smartphone or tablet, equipped with a voice input device (microphone), a camera, and a communication means. The terminal receives voice data from the user and converts it into text data. This conversion is performed using natural language processing (NLP) technology such as the Google speech recognition API.

[0519] server

[0520] The server, located in the cloud or within the network, receives and analyzes the text data sent from the device. Using an NLP library such as Python's NLTK or spaCy, the server tokenizes the text data, extracts key keywords, and infers the user's intent. Based on the inference results, the server then generates and sends operational instructions to the device.

[0521] Specific operation example

[0522] 1. User voice input:

[0523] The user speaks into their smartphone, saying, "I want to communicate with my grandchildren on social media." This voice is picked up through the device's microphone.

[0524] 2. Transcription of audio data:

[0525] The device converts the acquired voice data into text data using the Google speech recognition API or similar.

[0526] 3. Sending and parsing character data:

[0527] The device sends the converted text data in real time to the server, which then analyzes it and uses libraries such as Python's NLTK or spaCy to infer the user's intent.

[0528] 4. Operational Procedure Generation:

[0529] The server generates appropriate operation instructions based on the inference results, for example, "First, open the app store, then search for the social networking app, and tap the install button."

[0530] 5. Provide instructions:

[0531] The server sends the generated operation procedure to the terminal, which then provides it to the user as voice guidance.

[0532] Specific examples

[0533] Let's consider an online shopping scenario. A user voice-inputs, "I want to buy a new shirt." The device converts this voice into text data and sends it to the server. The server infers the user's intention, generates instructions such as, "Open the shopping site and enter 'shirt' in the search bar," and sends them to the device. The device then provides the received instructions to the user as voice guidance, and the user operates the shopping site according to the instructions.

[0534] Example prompts for generative AI models

[0535] You can simulate the system's processing by inputting prompts like the following into the generative AI model:

[0536] Please explain the sequence of steps that would occur if a user were to say, "I want to communicate with my grandchildren on social media," using voice input into a smartphone. Please include speech recognition, data analysis, generation of operating procedures, and voice guidance.

[0537] In this way, the system of the present invention enables elderly people to operate smartphones intuitively and easily, and supports their use of smartphones.

[0538] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0539] Step 1: User Speech Input

[0540] The user speaks into their smartphone, saying, "I want to communicate with my grandchildren on social media." The input is voice data, which is picked up by the device's microphone. The voice data is then prepared for use in the next processing step.

[0541] Step 2: Transcribe the audio data

[0542] The device converts the acquired voice data into text data using natural language processing (NLP) technology such as the Google speech recognition API. This conversion is a specific operation that takes voice data as input, analyzes it, and outputs text data. For example, the voice data "I want to communicate with my grandchildren on social media" is converted into text data "I want to communicate with my grandchildren on social media."

[0543] Step 3: Sending character data

[0544] The terminal transmits the converted text data to the server in real time. The input here is text data, and the output is data transmission to the server. Specifically, an HTTP request is sent from the terminal to the server, and the text data is included.

[0545] Step 4: Parsing character data

[0546] The server infers the user's intent based on the received text data. It uses an NLP library such as Python's NLTK or spaCy to tokenize the text data and extract key keywords. In this step, the input is the text data, and the output is the inferred user intent. Specifically, the server analyzes the text data and identifies keywords such as "grandchild," "SNS," and "interaction."

[0547] Step 5: Generate operating instructions

[0548] The server generates appropriate operating instructions based on the inferred intent. The input here is the user's intent, and the output is the operating instructions. Specifically, the server references predefined scenarios and procedure templates to create a guide such as "First, open the app store, then search for the social networking app, and tap the install button."

[0549] Step 6: Send instructions

[0550] The server sends the generated operation procedure to the terminal. The input is the generated operation procedure, and the output is data transmission to the terminal. A specific operation is an HTTP response sent from the server to the terminal, which includes the generated operation procedure.

[0551] Step 7: Provide operating instructions

[0552] The device receives the operation procedure from the server and provides it to the user as voice guidance. The input here is the generated operation procedure, and the output is the voice guidance. Specifically, the device uses voice synthesis technology to provide voice guidance such as, "First, open the app store, then search for the SNS app, and tap the install button."

[0553] Step 8: User interaction

[0554] The user operates the smartphone according to the provided voice guidance. The input is the voice guidance, and the output is the corresponding smartphone operation. Specifically, the user opens the app store, searches for the SNS app, and installs it.

[0555] Step 9: Installation Complete Notification

[0556] The device notifies the server that the user has completed installation of the SNS app. The input is the installation completion status, and the output is a notification to the server. Specifically, the device detects the completion of installation and sends the status to the server via an HTTP request.

[0557] Step 10: Next steps

[0558] The server receives notification that the installation is complete, generates next steps, and sends them to the device. The device then plays the next steps received from the server as voice guidance. The input here is the next steps, and the output is voice guidance. For example, the guidance may say, "Next, open the app and begin creating your account." Specific operations include providing detailed voice instructions for each input field in the form, such as "Please enter your name" or "Please enter your email address."

[0559] (Application example 1)

[0560] 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."

[0561] In traditional factory facilities and industrial automation environments, elderly and inexperienced workers face the challenge of efficiently operating sophisticated machinery and equipment. This can lead to operational errors and delays in maintenance work, resulting in concerns about reduced overall efficiency. Furthermore, the lack of intuitive and easy-to-understand operating guides means that training and education are time-consuming and costly.

[0562] 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.

[0563] In this invention, the server includes means for acquiring voice data, means for converting the voice data into character data, means for analyzing the character data and inferring a user's intention, means for generating an operating procedure based on the inference result, means for guiding the generated operating procedure to the user, and means for providing voice guidance and displaying visual guidance for operating the industrial automation device based on the user's intention, thereby enabling even elderly people and inexperienced workers to intuitively operate and maintain the industrial automation device.

[0564] "Means for acquiring voice data" refers to devices or software for collecting the voice uttered by the user as digital data.

[0565] "Means for converting voice data into text data" refers to technology or devices that analyze acquired voice data and convert it into corresponding text information.

[0566] "Means for analyzing character data and inferring user intent" refers to a system that analyzes character data entered by a user using natural language processing technology, etc., to understand what the user is trying to do.

[0567] "Means for generating operating procedures based on inference results" refers to a technology or mechanism that generates accurate and specific operating methods or work procedures according to the inferred user intentions.

[0568] The "means for guiding the generated operating procedure to the user" refers to a method or device for presenting the generated operating procedure to the user in an easy-to-understand manner.

[0569] "Means for providing audio guidance and displaying visual guidance for operating industrial automation equipment based on the user's intentions" refers to technology or devices that explain the appropriate procedures through audio and visual presentations when elderly or inexperienced workers operate industrial automation equipment.

[0570] "Means for using image data and video data" refers to technologies and systems for obtaining and analyzing useful information from static images and dynamic video.

[0571] "Means for generating and providing guidance on maintenance procedures for industrial automation equipment" refers to technology or mechanisms that generate specific methods for maintaining and repairing automated machinery used in factories, etc., and provide easy-to-understand guidance to workers.

[0572] The present invention provides a system that enables elderly or inexperienced workers to intuitively operate and maintain industrial automation equipment. The system aims to simplify complex operating procedures by combining voice input and visual guidance, thereby improving efficiency and safety.

[0573] Hardware and Software Configuration

[0574] The device uses smart glasses or head-mounted displays (e.g., Google Glass, Microsoft HoloLens) equipped with a voice input device and a camera, which can rapidly collect the user's voice and provide visual feedback.

[0575] The server uses advanced natural language processing (NLP) techniques to analyze the user's voice data. The voice data is converted into text data, and the user's intent is then inferred. Based on this inference, specific operating instructions are generated. The server uses the Google Speech-to-Text API and natural language processing libraries (e.g., spaCy, NLTK).

[0576] Data processing and calculation

[0577] The device captures the user's voice and converts it into text data in real time using the Google Speech-to-Text API. This text data is then sent to a server, where natural language processing technology is used to analyze the user's intent and generate appropriate operating instructions based on the analysis results. The generated instructions are then sent to the device as audio and visual guidance and provided to the user.

[0578] Specific examples

[0579] For example, if a user says "I want to start maintenance on the robot," the device collects the voice, converts the data into text, and sends it to the server. The server analyzes the text and generates specific maintenance instructions, such as "First, turn off the safety device, then open the panel." The generated instructions are sent to the device as audio and visual guidance, and the user is guided through them.

[0580] Example prompt sentence:

[0581] Imagine a scenario where a user uses smart glasses to say, "I want to start maintenance on the robot." Explain the process of converting this speech into text data, sending it to a server, generating appropriate maintenance instructions, and displaying and providing voice guidance on the smart glasses.

[0582] In this way, the system of the present invention realizes an environment in which elderly people and inexperienced workers can easily operate and maintain industrial automation equipment.

[0583] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0584] Step 1:

[0585] The user provides voice input

[0586] The user inputs "I want to start maintenance on the robot" through a voice input device on the smart glasses or head-mounted display. The input is voice data. The output is obtained as voice data.

[0587] Step 2:

[0588] The device converts the voice data into text data.

[0589] The device's internal processing converts acquired voice data into text data using the Google Speech-to-Text API. The input is voice data, and the output is the converted text data.

[0590] Step 3:

[0591] The terminal sends character data to the server

[0592] The converted character data is sent from the terminal to the server. The input is character data, and the output is character data sent to the server.

[0593] Step 4:

[0594] The server analyzes the text data and infers the user's intent.

[0595] On the server side, the received text data is analyzed using natural language processing (NLP) technology to infer the user's intent. The software used is an NLP library such as spaCy or NLTK. The input is text data, and the output is data indicating the user's intent.

[0596] Step 5:

[0597] The server generates an operating procedure based on the inference results.

[0598] The server generates specific operating procedures based on the inferred user intent. In this generation process, appropriate procedures are automatically generated using a generative AI model. The input is data indicating the user intent, and the output is operating procedure data.

[0599] Step 6:

[0600] Send the operation instructions generated by the server to the terminal

[0601] The generated operation procedure data is sent from the server to the terminal. The input is the operation procedure data, and the output is the data sent to the terminal.

[0602] Step 7:

[0603] The device guides the user through operation procedures both audibly and visually.

[0604] The terminal provides the received operation procedure data to the user as voice guidance and visual guidance. The voice guidance uses voice synthesis technology, and the visual guidance is displayed on the display of the smart glasses or head-mounted display. The input is the operation procedure data, and the output is the voice guidance and visual guidance.

[0605] Step 8:

[0606] The user performs the operation

[0607] The user operates and maintains the industrial automation equipment according to the voice and visual guidance provided by the terminal, where the input is the voice and visual guidance and the output is the operation performed.

[0608] The above steps allow the user to intuitively operate and maintain industrial automation equipment.

[0609] 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.

[0610] The present invention is a system that supports the elderly in intuitively operating smartphones, and in particular incorporates an emotion engine that recognizes the user's emotions and responds adaptively. Here, a specific embodiment incorporating the emotion engine will be described.

[0611] The system is composed of a terminal, a server, and an emotion engine working together. The terminal is equipped with a voice input device and a camera, allowing users to input voice, image, and video data. The emotion engine also analyzes the user's voice and image data to recognize the user's emotional state.

[0612] User Interaction

[0613] The user speaks to the smartphone, saying, "I want to communicate with my grandchildren on SNS." This voice input is taken through the device's voice input device.

[0614] Terminal handling

[0615] The device converts the captured voice data into text using voice recognition technology. If there is any voice data or image data, it also acquires it and sends it to the emotion engine.

[0616] Emotion engine processing

[0617] The emotion engine analyzes the acquired voice and image data to recognize the user's emotional state, for example, distinguishing between when the user is in trouble or when they are feeling anxious.

[0618] Server Analysis

[0619] The server receives data sent from the device and emotion engine and infers the user's intention. Here, it also uses emotional information obtained from the emotion engine. For example, if it infers that the user is in trouble, it generates more detailed procedural instructions than usual.

[0620] Operation procedure generation and response

[0621] The server generates adaptive operation instructions based on the inference results and emotional information. For example, it generates specific instructions for installing a social networking app and creating an account. If the user feels anxious, it provides detailed instructions.

[0622] Sending and providing instructions

[0623] The generated operating instructions are sent from the server to the device, which then provides them to the user as voice guidance. Specific instructions include, "First, open the app store, then search for the SNS app, and tap the install button."

[0624] User operations

[0625] The user follows the voice prompts to open the app store, search for the social networking app, and tap the install button.

[0626] Continued guidance

[0627] Once the installation is complete, the device will receive instructions from the server, such as "Next, open the app and begin creating your account." The emotion engine continues to monitor the user's emotions and adjusts the level of detail of the instructions as needed.

[0628] Emotion-Based Feedback

[0629] The device will use the emotion engine again to recognize the user's emotions while they are operating the device, and provide feedback based on that information. For example, even if the user is feeling anxious, the device will respond with positive feedback such as "That went well" if the operation is successful.

[0630] In this way, the present invention provides a system that supports more adaptive and intuitive smartphone operation by taking into account the user's emotional state. Specifically, it analyzes voice and image data and combines an emotion engine to provide operation procedures and feedback that comprehensively consider the user's intentions and emotions. This allows elderly people to use smartphones smoothly and safely.

[0631] The processing flow will be explained below.

[0632] Step 1: Getting voice input

[0633] The user speaks into their smartphone, saying, "I want to communicate with my grandchildren on social media."

[0634] Step 2: Convert the audio data

[0635] The device converts the captured voice data into text data, using voice recognition technology to convert the voice into text.

[0636] Step 3: Sending character data

[0637] The terminal transmits the converted character data to the server.

[0638] Step 4: Obtaining emotion data

[0639] The device sends audio data and, if necessary, image and video data of the user to the emotion engine.

[0640] Step 5: Analyze the sentiment data

[0641] The emotion engine analyzes the acquired voice and image data to recognize the user's emotions, for example, determining whether the user is feeling anxious.

[0642] Step 6: Receiving Data

[0643] The server receives the character data sent from the terminal and the emotion data sent from the emotion engine.

[0644] Step 7: Parsing intent

[0645] The server uses natural language processing to analyze the text data and infer the user's intent. Based on the request, "I want to communicate with my grandchildren on social media," it infers that the user needs to install a social media app and create an account.

[0646] Step 8: Generate operating instructions

[0647] The server generates adaptive operating procedures based on the inference results and emotion data. If the server detects anxiety in the user, it adjusts the procedures to be more detailed and easy to understand.

[0648] Step 9: Send instructions

[0649] The server transmits the generated adaptive operation procedure to the terminal.

[0650] Step 10: Voice prompts to the user

[0651] Based on the received operating instructions, the device will provide voice guidance to the user, such as "First, open the app store, then search for the SNS app, and tap the install button."

[0652] Step 11: User execution

[0653] The user follows the voice prompts to open the app store, search for the social networking app, and tap the install button.

[0654] Step 12: Installation Complete Notification

[0655] The device notifies the server that the installation of the SNS app has been completed.

[0656] Step 13: Account creation instructions

[0657] The device receives additional instructions from the server and provides a voice prompt to the user saying, "Next, open the app and begin creating your account." The emotion engine continues to monitor the user's emotions and provides further detailed instructions if anxiety persists.

[0658] Step 14: Form Assistance

[0659] The device will provide specific instructions for each input field on the account creation form, providing detailed instructions aloud such as "Please enter your name" or "Please enter your email address."

[0660] Step 15: Emotional Feedback

[0661] The emotion engine continuously analyzes the user's emotions while filling out the form, and provides relaxing feedback such as "Take it easy, it's okay" when stress levels rise.

[0662] Step 16: Complete your account creation

[0663] Users follow the voice prompts and enter the required information into the form to complete account creation.

[0664] In this way, by combining emotion engines, it becomes possible to respond adaptively to the user's emotional state, realizing a system that allows elderly people to operate smartphones comfortably.

[0665] Example 2

[0666] 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."

[0667] For elderly people who have difficulty intuitively operating smartphones, conventional systems have had difficulty recognizing the user's emotional state and providing adaptive support. In particular, when the operating procedures are difficult or the user feels anxious, appropriate support is not provided, which can lead to operational errors and stress in the user. There is a need to solve this problem and provide a system that can support elderly people in using smartphones with confidence.

[0668] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0669] In this invention, the server includes means for acquiring user voice data, means for converting the acquired voice data into character data, means for acquiring image data and video data using a camera, means for analyzing the acquired voice data and image data to recognize the user's emotional state, means for inferring the user's intention based on the analysis results of the voice data and emotional state, means for generating operation procedures based on the inference results and emotional information, means for providing the generated operation procedures to the user as voice guidance, and means for re-monitoring the user's emotional state during operation and adjusting the guidance content as necessary. This allows the user to receive optimal support according to their emotional state, enabling elderly people to operate smartphones smoothly and safely.

[0670] The "means for acquiring user voice data" refers to a device or system that collects the user's voice through a microphone.

[0671] The "means for converting acquired voice data into text data" refers to a process or system that converts voice data into text data using voice recognition technology.

[0672] "Means for acquiring image data and video data using a camera" refers to a device or system that uses a camera to record a user's actions and expressions and collects them as image or video data.

[0673] "Means for analyzing acquired audio and image data to recognize a user's emotional state" refers to a process or system that analyzes the collected data to identify a user's emotions (e.g., anxiety, confusion, joy, etc.).

[0674] A "means for inferring user intent based on analysis of speech data and emotional state" is a process or system that uses the analysis to identify the user's wants and needs.

[0675] The "means for generating operating procedures based on inference results and emotional information" refers to a process or system that generates appropriate operating procedures or guidelines according to the user's intentions and emotional state.

[0676] The "means for providing the generated operating procedure to the user as voice guidance" refers to a process or system that converts the generated operating procedure into voice data format and provides voice guidance to the user.

[0677] "Means for re-monitoring the user's emotional state during operation and adjusting the guidance content as necessary" refers to a process or system that re-monitors the user's emotions during operation and adaptively changes the details and content of the guidance according to the user's state.

[0678] The present invention is a system that supports the elderly in intuitively operating smartphones, and in particular incorporates an emotion engine to provide guidance and feedback that is adapted to the user's emotional state. Specific embodiments of the present invention will be described below.

[0679] System configuration

[0680] This system works in cooperation with a terminal, a server, and an emotion engine. The terminal is equipped with a voice input device and a camera, allowing users to input voice, image, and video data. The emotion engine analyzes the user's voice data and image data to recognize the user's emotional state. The server infers the user's intentions based on this data, generates appropriate operating procedures, and provides voice guidance.

[0681] Hardware and software used

[0682] Device: A mobile device such as a smartphone or tablet, including a voice input device (microphone) and a camera.

[0683] Speech recognition technology: Common cloud-based speech recognition APIs (e.g., Google Speech-to-Text API).

[0684] Emotion engine: An API for analyzing user emotions (e.g., Microsoft Azure's Emotion API).

[0685] Server: A cloud server for performing inference and procedure generation.

[0686] Speech synthesis technology: Technology that converts the generated instructions into voice guidance (e.g., Amazon Polly).

[0687] Specific operation of the system

[0688] 1. User Interaction

[0689] The user speaks to the smartphone, saying, "I want to communicate with my grandchildren on SNS." This voice input is acquired through the device's voice input device.

[0690] 2. Transcription of audio data

[0691] The device uses voice recognition technology to convert the acquired voice data into text data. For example, an input such as "I want to communicate with my grandchildren on social media" is converted into text.

[0692] 3. Acquisition of image and video data

[0693] The device uses a camera to record the user's facial expressions and movements, capturing image and video data, which is then sent to the emotion engine along with audio data.

[0694] 4. Emotion analysis

[0695] The emotion engine analyzes the received voice and image data to recognize the user's emotional state, for example, identifying various emotions such as whether the user is distressed or anxious.

[0696] 5. Intention Inference

[0697] The server uses natural language processing technology to infer the user's intentions based on the data sent from the emotion engine. Emotional information is also used to determine if the user is having trouble and if more detailed guidance is needed.

[0698] 6. Operation procedure generation

[0699] The server generates adaptive operation instructions based on the inference results and emotional information. For example, when guiding a user through the steps of installing a social networking app, if the user feels anxious, the server will break down the steps into more detailed instructions.

[0700] 7. Audio guidance of procedures

[0701] The generated operating instructions are sent from the server to the device, which then uses speech synthesis technology to provide voice guidance to the user, such as "First, open the app store, then search for the SNS app, and tap the install button."

[0702] 8. User Operations

[0703] The user follows the voice guidance to operate the smartphone. If the user does not understand an operation, they can ask for help by voice input again.

[0704] 9. Emotion Monitoring and Feedback

[0705] The device will again use the emotion engine to monitor the user's emotions during operation, adjust the level of detail when guiding the user through the next steps as needed, and provide positive feedback such as "That was great, good job" when the user performs a successful operation.

[0706] Specific examples

[0707] Below are examples of typical user speech input and subsequent prompts for actions:

[0708] Prompt Sentence Examples

[0709] User: "I want to communicate with my grandchildren on social media."

[0710] The device recognizes the voice, and the emotion engine analyzes the user's emotions. If it determines that the user is in trouble, the server generates more detailed instructions.

[0711] Server: "First, open the app store. Then search for a social networking app. Tap the install button."

[0712] In this way, the system provides comprehensive support for elderly people to smoothly operate smartphones while taking into account the user's emotional state.

[0713] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0714] Step 1:

[0715] The user inputs voice data. Specifically, the user speaks into the smartphone, saying, "I want to communicate with my grandchildren on SNS." This voice data is input.

[0716] Input: User's voice data

[0717] Output: Audio data file (WAV, MP3, etc.)

[0718] Step 2:

[0719] The device converts the acquired voice data into text data using voice recognition technology, such as the Google Speech-to-Text API.

[0720] Input: Audio data file

[0721] Data processing: Speech-to-text conversion using speech recognition algorithms

[0722] Output: Character data (text format)

[0723] Step 3:

[0724] The terminal uses a camera to record the user's facial expressions and movements, and acquires image data and video data.

[0725] Input: Captured video data

[0726] Data processing: Creating and saving video files

[0727] Output: Image data (JPEG, PNG), video data (MP4, AVI)

[0728] Step 4:

[0729] The emotion engine analyzes audio and image data to recognize the user's emotional state, for example, using Microsoft Azure's Emotion API.

[0730] Input: Text data, image data, video data

[0731] Data processing: Application of emotion recognition algorithms through natural language processing and image analysis

[0732] Output: Emotional state data (e.g., confusion, anxiety, joy)

[0733] Step 5:

[0734] The server infers the user's intention based on the emotional state data and text data sent from the emotion engine, using natural language processing technology (e.g., OpenAI's GPT-3).

[0735] Input: Emotional state data, character data

[0736] Data processing: Intention inference using natural language processing

[0737] Output: User intent data (e.g., "I want to interact on social media")

[0738] Step 6:

[0739] The server generates operation instructions based on the inference results and the emotional state, such as instructions for installing a social networking app.

[0740] Input: User intent data, emotional state data

[0741] Data processing: Applying procedure generation algorithms and assembling detailed operational steps

[0742] Output: Specific operating instructions (e.g., "First, open the app store")

[0743] Step 7:

[0744] The server then sends the generated instructions to the device, which then provides them as voice prompts, for example by using Amazon Polly to convert text to speech.

[0745] Input: Operation procedure data

[0746] Data processing: Use of Text-to-Speech technology (TTS)

[0747] Output: Audio data (audio guide for operation procedures)

[0748] Step 8:

[0749] The user follows the voice prompts to open the app store, search for the social networking app, and tap the install button. As the user performs these actions, the system continues to monitor the user's reactions.

[0750] Input: Voice guidance

[0751] Output: User action

[0752] Step 9:

[0753] The device monitors the user's emotions using the emotion engine again during the user's operation, and provides guidance on the next steps, adjusting the level of detail of the guidance as necessary.

[0754] Input: Real-time video and audio data

[0755] Data processing: Updates with sentiment analysis

[0756] Output: Adjusted operating procedure voice guidance

[0757] Step 10:

[0758] The device provides feedback based on the emotions recognized during the user's operation, for example, giving positive feedback such as "That was great, good job!"

[0759] Input: Updated emotional state data, user action data

[0760] Data processing: Applying feedback generation algorithms

[0761] Output: Feedback audio data

[0762] (Application example 2)

[0763] 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."

[0764] Elderly people often find it difficult to use smartphones due to their complex operation. Furthermore, in order to provide appropriate support for their operation, it is necessary to understand the user's emotional state and respond adaptively. However, current systems have difficulty providing support that takes the user's emotions into account, which can result in users feeling anxious or confused. The purpose of this invention is to solve this problem and enable elderly people to use smartphones with peace of mind.

[0765] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring voice data, means for converting the acquired voice data into character data, means for analyzing the character data and inferring the user's intention, means for generating operation procedures based on the inference results, means for guiding the generated operation procedures to the user, and means for adaptively responding using an emotion engine that analyzes the user's emotional state. This makes it possible to provide adaptive and detailed operation procedures while taking the user's emotional state into consideration. It is also possible to provide positive feedback upon success so that the user can continue operating with peace of mind.

[0766] "Means for acquiring voice data" refers to a device or system for collecting voice input from a user.

[0767] The term "means for converting voice data into character data" refers to a technology for converting acquired voice data into character information, such as a voice recognition technology.

[0768] "Means for analyzing character data and inferring the user's intent" refers to algorithms or programs that use converted character data to infer what the user is looking for.

[0769] "Means for generating operating procedures based on inference results" refers to a program or system for automatically generating operating procedures according to the user's intentions.

[0770] The "means for guiding the generated operating procedure to the user" refers to a method for communicating the generated operating procedure to the user, such as voice guidance or screen display.

[0771] An "emotion engine that analyzes a user's emotional state" refers to software or a program that analyzes a user's voice data or image data to recognize the user's emotional state.

[0772] "Adaptive response means" refers to a system that adjusts the guidance content and operating procedures according to the user's emotional state.

[0773] "Using image data and video data as the subject of analysis" refers to analyzing not only audio data but also image data and video data that include the user's facial expressions and actions.

[0774] "Means for providing audio guidance to a user" refers to a system or technology for conveying information or instructions to a user by voice.

[0775] "Means for adjusting the level of detail of operation procedures" refers to a method for adjusting the level of detail of the operation procedures presented depending on the user's emotional state and skill level.

[0776] "Means for providing positive feedback for successful operations" refers to software or a system that provides positive feedback by voice or display when a user successfully performs an operation.

[0777] "Means for the server to generate a response based on the inference results" refers to the technology that enables the server to create a response based on the analysis results based on voice data and emotional data and provide it to the user.

[0778] "Means for generating and guiding operating procedures using a generative AI model and prompt sentences" refers to an algorithm or system that uses a generative AI model to generate appropriate prompt sentences and provides operating procedures to the user based on those prompt sentences.

[0779] The present invention relates to a system that uses an emotion engine to grasp the emotional state of elderly people when they use a smartphone to deliver food, and provides adaptive operating procedures and feedback.

[0780] System Overview

[0781] This system operates in cooperation with the terminal, server, and emotion engine.

[0782] Terminal: A mobile device such as a smartphone equipped with a voice input device and a camera. The terminal has the function of receiving voice data from the user and converting it into text data.

[0783] Server: Analyzes voice and image data to infer the user's intentions and emotions. Based on the analysis results, the server generates adaptive operating procedures and provides feedback.

[0784] Emotion engine: An algorithm that analyzes the user's emotional state based on their voice and image data.

[0785] Hardware and Software

[0786] Hardware

[0787] Smartphone (with voice input device and camera)

[0788] software

[0789] speech_recognition library: Used to convert speech input into text data.

[0790] emotion_recognition: A custom library for sentiment analysis.

[0791] server_communication: For server communication.

[0792] voice_assistant: A custom module for voice assistant functionality.

[0793] Specific processing examples

[0794] 1. Acquiring and recognizing voice input:

[0795] The device receives voice input from the user, such as "I would like to order sushi," and converts this into text data using the speech_recognition library.

[0796] 2. Emotion recognition using emotion engine:

[0797] The acquired voice data and image data are analyzed by an emotion engine to identify the user's emotional state, such as whether they are feeling anxious or distressed.

[0798] 3. Sending data to the server:

[0799] Emotional data and voice data are sent to the server, which then uses this data to infer the user's intentions. For example, a request such as "I want to order sushi" is received.

[0800] 4. Operational Procedure Generation:

[0801] The server generates adaptive operation instructions based on the inference results and emotion data. If detailed instructions are required, it generates specific instructions such as "First, open the app and tap the sushi category."

[0802] 5. Audio feedback:

[0803] The generated instructions are sent to the device, and the voice assistant uses "voice_assistant" to provide feedback to the user: "Next, open the app store, search for the social networking app, and tap the install button."

[0804] 6. Positive Feedback:

[0805] If the operation is successful, the emotion engine checks the status again and provides positive feedback such as "That worked."

[0806] Specific examples and prompts for the generative AI model

[0807] Examples:

[0808] If a user voice-inputs "I want to order sushi" and the emotion engine detects that the user is in a "troubled" state, the server will generate a prompt sentence like the following:

[0809] Example prompt sentence:

[0810] 1. "First, open your food delivery app."

[0811] 2. "Next, tap on the Sushi category from the menu."

[0812] 3. "Choose your favorite sushi item and add it to your cart."

[0813] 4. "Please confirm your order details and press the button to confirm your order."

[0814] In this way, the system allows users to use their smartphones and operate food delivery services with emotional security.

[0815] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0816] Step 1:

[0817] Acquiring voice input:

[0818] The user speaks into the smartphone, saying, "I'd like to order sushi." The terminal acquires this speech using a voice input device. The input data is the user's voice data. The terminal acquires this voice data and sends it to the next step.

[0819] Step 2:

[0820] Audio to text conversion:

[0821] The device uses the speech_recognition library to convert the acquired voice data into text data. The input data is voice data, and the output data is text data converted from this voice. Data conversion is performed using voice recognition technology.

[0822] Step 3:

[0823] Emotional State Analysis:

[0824] The device sends voice and image data to the emotion engine, which analyzes the user's emotional state. The input data is the converted text data and voice data, and the output data is the user's emotional state (for example, "I'm in trouble" or "I'm relieved"). The emotion engine analyzes this using a machine learning algorithm.

[0825] Step 4:

[0826] Sending data to the server:

[0827] The terminal transmits emotional data and text data to the server. The input data is the analyzed emotional state and text data, and the output data is the data received by the server. Here, data communication technology is used.

[0828] Step 5:

[0829] Intention inference by the server:

[0830] The server infers the user's intention based on the received text data and emotional data. The input data is the emotional state and text data, and the output data is the user's intention (e.g., "I want to order sushi"). The server uses natural language processing technology and inference algorithms.

[0831] Step 6:

[0832] Generate operating instructions:

[0833] The server generates adaptive operation instructions based on the user's intention and emotional state. The input data is the inferred user's intention and emotional state, and the output data is the specific operation instructions (e.g., "First, open the app and tap the sushi category"). The server then uses a generative AI model to create an appropriate prompt.

[0834] Step 7:

[0835] Sending instructions:

[0836] The server sends the generated operation procedure to the terminal. The input data is the generated operation procedure, and the output data is the operation procedure received by the terminal. Data communication technology is used.

[0837] Step 8:

[0838] Voice guidance for operation procedures:

[0839] The device uses a voice assistant to provide guidance to the user based on the received operating instructions. The input data is the operating instructions, and the output data is voice guidance to the user. Speech synthesis technology is used to audibly convey specific operating procedures to the user.

[0840] Step 9:

[0841] User interaction and feedback:

[0842] The user follows the voice guidance to perform the operation. The device again uses the emotion engine to monitor the user's emotional state and provides positive feedback if the operation is successful. The input data is the user's operation result and new emotional data, and the output data is positive feedback. This allows the user to gain confidence in their operation and use the app with peace of mind.

[0843] 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.

[0844] 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.

[0845] 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.

[0846] [Third embodiment]

[0847] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0848] 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.

[0849] 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).

[0850] 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.

[0851] 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.

[0852] 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).

[0853] 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.

[0854] 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.

[0855] 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.

[0856] 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.

[0857] 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.

[0858] 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."

[0859] The system of the present invention is intended to assist elderly people in intuitively operating smartphones, and specific embodiments thereof will be described below.

[0860] The system is mainly composed of two parts: a terminal and a server. The terminal is equipped with a voice input device and a camera, allowing users to input voice, image, and video data. The server analyzes the received data, infers the user's intention, and generates appropriate operating procedures.

[0861] User Interaction

[0862] The user speaks to the smartphone, saying, "I want to communicate with my grandchildren on SNS." This voice input is taken through the device's voice input device.

[0863] Terminal handling

[0864] The device uses natural language processing (NLP) technology to recognize voice data and convert it into text data, which is then sent from the device to the server.

[0865] Server Analysis

[0866] The server infers the user's intent based on the text data received from the device, which includes pre-processing data analysis and uses NLP technology to understand the user's needs.

[0867] Next, the server generates operational instructions based on the inferred intent. For example, instructions for installing a social networking app or creating an account are generated at this stage.

[0868] Providing operating instructions

[0869] The generated operating instructions are sent from the server to the device, which then plays them back as voice guidance. For example, the instructions might say, "First, open the app store, then search for the social networking app, and tap the install button."

[0870] User operations

[0871] The user follows the instructions to open the app store, search for the social networking app, and install it. After completing this series of operations, the device notifies the server that the installation is complete and obtains the next steps.

[0872] Continued guidance

[0873] After the installation is complete, the device will continue to play a voice prompt saying, "Next, open the app and begin creating your account." It will also provide specific instructions for each form field, providing detailed instructions such as, "Enter your name" and "Enter your email address."

[0874] Specific examples

[0875] As a concrete example, let us consider an online shopping scenario.

[0876] The user speaks, "I want to buy a new shirt." The device converts this speech into text data and sends it to the server. The server infers the user's intent and generates online shopping instructions. For example, it might generate instructions such as, "Open a shopping site and enter 'shirt' in the search bar," and send them to the device.

[0877] The terminal provides the received instructions to the user as voice guidance, and the user operates the shopping site according to the guidance. The voice guidance supports a series of operations, from searching for products and adding them to the cart to completing the purchase.

[0878] In this way, the present invention provides a system that allows elderly people to easily operate smartphones, significantly lowering the barrier to using smartphones.

[0879] The processing flow will be explained below.

[0880] Step 1: Getting voice input

[0881] The user speaks into their smartphone, saying, "I want to communicate with my grandchildren on social media."

[0882] Step 2: Convert the audio data

[0883] The device converts the captured voice data into text data, using voice recognition technology to convert the voice into text.

[0884] Step 3: Sending character data

[0885] The terminal transmits the converted character data to the server.

[0886] Step 4: Receiving the data

[0887] The server receives the character data sent from the terminal.

[0888] Step 5: Parsing intent

[0889] The server uses natural language processing to analyze the received text data and infer the user's intent. For example, if the request is "I want to communicate with my grandchildren on social media," it can determine that a social media app needs to be installed and an account created.

[0890] Step 6: Generate operating instructions

[0891] Based on the inference results, the server generates specific operation instructions, including how to open the app store, how to search for and install social networking apps, and how to create an account.

[0892] Step 7: Send instructions

[0893] The server sends the generated operation procedure to the terminal.

[0894] Step 8: Audio guidance to the user

[0895] Based on the received operating instructions, the device will provide voice guidance to the user, such as "First, open the app store, then search for the SNS app, and tap the install button."

[0896] Step 9: User execution

[0897] The user follows the voice prompts to open the app store, search for the social networking app, and tap the install button.

[0898] Step 10: Installation Complete Notification

[0899] The device notifies the server that the installation of the SNS app has been completed.

[0900] Step 11: Account creation instructions

[0901] The device receives additional operating instructions from the server and provides the user with a voice prompt saying, "Next, open the app and begin creating your account."

[0902] Step 12: Form Assistance

[0903] The device also provides specific input assistance within the account creation form, such as "Please enter your name" and "Please enter your email address."

[0904] Step 13: Complete your account creation

[0905] Users follow the voice prompts and enter the required information into the form to complete account creation.

[0906] This series of processes realizes a system that allows users to operate their smartphones intuitively and smoothly.

[0907] Example 1

[0908] 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."

[0909] Modern smartphones are multifunctional and often difficult to operate, especially for the elderly. Even with effective use of voice input, conversion to text data, and natural language processing, it is difficult for elderly people to intuitively and easily operate smartphones. This invention aims to solve this problem by providing a system that supports elderly people in operating smartphones more intuitively.

[0910] 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.

[0911] In this invention, the server includes means for acquiring voice data, means for converting the acquired voice data into character data, means for analyzing the character data and inferring the user's intention, means for generating operation procedures based on the inference result, means for providing the generated operation procedures to the user, and means for analyzing the user's intention and generating and providing the operation procedures by the terminal and the server operating in cooperation with each other, thereby enabling elderly people to operate smartphones intuitively and easily.

[0912] "Voice data" refers to data that has been recorded and stored in digital form of a user's speech.

[0913] "Character data" refers to data obtained by converting voice data into text format.

[0914] "Analysis" is the process of understanding the information contained in text data and interpreting its meaning.

[0915] "User intent" refers to the requests and desires expressed by the user through speech input.

[0916] "Operation steps" are instructions or guidelines for performing a desired action by a user.

[0917] "Providing" refers to the act of transmitting the generated operating procedure to the user by voice or display.

[0918] A "terminal" is a device that is directly operated by a user, such as a smartphone or tablet.

[0919] A "server" is a computer system that is installed on the cloud or within a network and works in conjunction with terminals to analyze and process data.

[0920] An "audio input device" is a device, such as a microphone, used to capture audio data.

[0921] "Natural language processing" refers to techniques and methods that allow computers to understand and process human language.

[0922] The system of the present invention assists elderly people in intuitively operating smartphones. This system is composed of a terminal and a server, and aims to simplify smartphone operation by automatically generating and providing operating procedures based on the user's voice input. Specific embodiments are described below.

[0923] System configuration

[0924] The system mainly consists of two parts: a terminal equipped with a voice input device and a server that performs data analysis and generates operating procedures.

[0925] Terminal

[0926] The terminal is a mobile device such as a smartphone or tablet, equipped with a voice input device (microphone), a camera, and a communication means. The terminal receives voice data from the user and converts it into text data. This conversion is performed using natural language processing (NLP) technology such as the Google speech recognition API.

[0927] server

[0928] The server, located in the cloud or within the network, receives and analyzes the text data sent from the device. Using an NLP library such as Python's NLTK or spaCy, the server tokenizes the text data, extracts key keywords, and infers the user's intent. Based on the inference results, the server then generates and sends operational instructions to the device.

[0929] Specific operation example

[0930] 1. User voice input:

[0931] The user speaks into their smartphone, saying, "I want to communicate with my grandchildren on social media." This voice is picked up through the device's microphone.

[0932] 2. Transcription of audio data:

[0933] The device converts the acquired voice data into text data using the Google speech recognition API or similar.

[0934] 3. Sending and parsing character data:

[0935] The device sends the converted text data in real time to the server, which then analyzes it and uses libraries such as Python's NLTK or spaCy to infer the user's intent.

[0936] 4. Operational Procedure Generation:

[0937] The server generates appropriate operation instructions based on the inference results, for example, "First, open the app store, then search for the social networking app, and tap the install button."

[0938] 5. Provide instructions:

[0939] The server sends the generated operation procedure to the terminal, which then provides it to the user as voice guidance.

[0940] Specific examples

[0941] Let's consider an online shopping scenario. A user voice-inputs, "I want to buy a new shirt." The device converts this voice into text data and sends it to the server. The server infers the user's intention, generates instructions such as, "Open the shopping site and enter 'shirt' in the search bar," and sends them to the device. The device then provides the received instructions to the user as voice guidance, and the user operates the shopping site according to the instructions.

[0942] Example prompts for generative AI models

[0943] You can simulate the system's processing by inputting prompts like the following into the generative AI model:

[0944] Please explain the sequence of steps that would occur if a user were to say, "I want to communicate with my grandchildren on social media," using voice input into a smartphone. Please include speech recognition, data analysis, generation of operating procedures, and voice guidance.

[0945] In this way, the system of the present invention enables elderly people to operate smartphones intuitively and easily, and supports their use of smartphones.

[0946] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0947] Step 1: User Speech Input

[0948] The user speaks into their smartphone, saying, "I want to communicate with my grandchildren on social media." The input is voice data, which is picked up by the device's microphone. The voice data is then prepared for use in the next processing step.

[0949] Step 2: Transcribe the audio data

[0950] The device converts the acquired voice data into text data using natural language processing (NLP) technology such as the Google speech recognition API. This conversion is a specific operation that takes voice data as input, analyzes it, and outputs text data. For example, the voice data "I want to communicate with my grandchildren on social media" is converted into text data "I want to communicate with my grandchildren on social media."

[0951] Step 3: Sending character data

[0952] The terminal transmits the converted text data to the server in real time. The input here is text data, and the output is data transmission to the server. Specifically, an HTTP request is sent from the terminal to the server, and the text data is included.

[0953] Step 4: Parsing character data

[0954] The server infers the user's intent based on the received text data. It uses an NLP library such as Python's NLTK or spaCy to tokenize the text data and extract key keywords. In this step, the input is the text data, and the output is the inferred user intent. Specifically, the server analyzes the text data and identifies keywords such as "grandchild," "SNS," and "interaction."

[0955] Step 5: Generate operating instructions

[0956] The server generates appropriate operating instructions based on the inferred intent. The input here is the user's intent, and the output is the operating instructions. Specifically, the server references predefined scenarios and procedure templates to create a guide such as "First, open the app store, then search for the social networking app, and tap the install button."

[0957] Step 6: Send instructions

[0958] The server sends the generated operation procedure to the terminal. The input is the generated operation procedure, and the output is data transmission to the terminal. A specific operation is an HTTP response sent from the server to the terminal, which includes the generated operation procedure.

[0959] Step 7: Provide operating instructions

[0960] The device receives the operation procedure from the server and provides it to the user as voice guidance. The input here is the generated operation procedure, and the output is the voice guidance. Specifically, the device uses voice synthesis technology to provide voice guidance such as, "First, open the app store, then search for the SNS app, and tap the install button."

[0961] Step 8: User interaction

[0962] The user operates the smartphone according to the provided voice guidance. The input is the voice guidance, and the output is the corresponding smartphone operation. Specifically, the user opens the app store, searches for the SNS app, and installs it.

[0963] Step 9: Installation Complete Notification

[0964] The device notifies the server that the user has completed installation of the SNS app. The input is the installation completion status, and the output is a notification to the server. Specifically, the device detects the completion of installation and sends the status to the server via an HTTP request.

[0965] Step 10: Next steps

[0966] The server receives notification that the installation is complete, generates next steps, and sends them to the device. The device then plays the next steps received from the server as voice guidance. The input here is the next steps, and the output is voice guidance. For example, the guidance may say, "Next, open the app and begin creating your account." Specific operations include providing detailed voice instructions for each input field in the form, such as "Please enter your name" or "Please enter your email address."

[0967] (Application example 1)

[0968] 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."

[0969] In traditional factory facilities and industrial automation environments, elderly and inexperienced workers face the challenge of efficiently operating sophisticated machinery and equipment. This can lead to operational errors and delays in maintenance work, resulting in concerns about reduced overall efficiency. Furthermore, the lack of intuitive and easy-to-understand operating guides means that training and education are time-consuming and costly.

[0970] 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.

[0971] In this invention, the server includes means for acquiring voice data, means for converting the voice data into character data, means for analyzing the character data and inferring a user's intention, means for generating an operating procedure based on the inference result, means for guiding the generated operating procedure to the user, and means for providing voice guidance and displaying visual guidance for operating the industrial automation device based on the user's intention, thereby enabling even elderly people and inexperienced workers to intuitively operate and maintain the industrial automation device.

[0972] "Means for acquiring voice data" refers to devices or software for collecting the voice uttered by the user as digital data.

[0973] "Means for converting voice data into text data" refers to technology or devices that analyze acquired voice data and convert it into corresponding text information.

[0974] "Means for analyzing character data and inferring user intent" refers to a system that analyzes character data entered by a user using natural language processing technology, etc., to understand what the user is trying to do.

[0975] "Means for generating operating procedures based on inference results" refers to a technology or mechanism that generates accurate and specific operating methods or work procedures according to the inferred user intentions.

[0976] The "means for guiding the generated operating procedure to the user" refers to a method or device for presenting the generated operating procedure to the user in an easy-to-understand manner.

[0977] "Means for providing audio guidance and displaying visual guidance for operating industrial automation equipment based on the user's intentions" refers to technology or devices that explain the appropriate procedures through audio and visual presentations when elderly or inexperienced workers operate industrial automation equipment.

[0978] "Means for using image data and video data" refers to technologies and systems for obtaining and analyzing useful information from static images and dynamic video.

[0979] "Means for generating and providing guidance on maintenance procedures for industrial automation equipment" refers to technology or mechanisms that generate specific methods for maintaining and repairing automated machinery used in factories, etc., and provide easy-to-understand guidance to workers.

[0980] The present invention provides a system that enables elderly or inexperienced workers to intuitively operate and maintain industrial automation equipment. The system aims to simplify complex operating procedures by combining voice input and visual guidance, thereby improving efficiency and safety.

[0981] Hardware and Software Configuration

[0982] The device uses smart glasses or head-mounted displays (e.g., Google Glass, Microsoft HoloLens) equipped with a voice input device and a camera, which can rapidly collect the user's voice and provide visual feedback.

[0983] The server uses advanced natural language processing (NLP) techniques to analyze the user's voice data. The voice data is converted into text data, and the user's intent is then inferred. Based on this inference, specific operating instructions are generated. The server uses the Google Speech-to-Text API and natural language processing libraries (e.g., spaCy, NLTK).

[0984] Data processing and calculation

[0985] The device captures the user's voice and converts it into text data in real time using the Google Speech-to-Text API. This text data is then sent to a server, where natural language processing technology is used to analyze the user's intent and generate appropriate operating instructions based on the analysis results. The generated instructions are then sent to the device as audio and visual guidance and provided to the user.

[0986] Specific examples

[0987] For example, if a user says "I want to start maintenance on the robot," the device collects the voice, converts the data into text, and sends it to the server. The server analyzes the text and generates specific maintenance instructions, such as "First, turn off the safety device, then open the panel." The generated instructions are sent to the device as audio and visual guidance, and the user is guided through them.

[0988] Example prompt sentence:

[0989] Imagine a scenario where a user uses smart glasses to say, "I want to start maintenance on the robot." Explain the process of converting this speech into text data, sending it to a server, generating appropriate maintenance instructions, and displaying and providing voice guidance on the smart glasses.

[0990] In this way, the system of the present invention realizes an environment in which elderly people and inexperienced workers can easily operate and maintain industrial automation equipment.

[0991] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0992] Step 1:

[0993] The user provides voice input

[0994] The user inputs "I want to start maintenance on the robot" through a voice input device on the smart glasses or head-mounted display. The input is voice data. The output is obtained as voice data.

[0995] Step 2:

[0996] The device converts the voice data into text data.

[0997] The device's internal processing converts acquired voice data into text data using the Google Speech-to-Text API. The input is voice data, and the output is the converted text data.

[0998] Step 3:

[0999] The terminal sends character data to the server

[1000] The converted character data is sent from the terminal to the server. The input is character data, and the output is character data sent to the server.

[1001] Step 4:

[1002] The server analyzes the text data and infers the user's intent.

[1003] On the server side, the received text data is analyzed using natural language processing (NLP) technology to infer the user's intent. The software used is an NLP library such as spaCy or NLTK. The input is text data, and the output is data indicating the user's intent.

[1004] Step 5:

[1005] The server generates an operating procedure based on the inference results.

[1006] The server generates specific operating procedures based on the inferred user intent. In this generation process, appropriate procedures are automatically generated using a generative AI model. The input is data indicating the user intent, and the output is operating procedure data.

[1007] Step 6:

[1008] Send the operation instructions generated by the server to the terminal

[1009] The generated operation procedure data is sent from the server to the terminal. The input is the operation procedure data, and the output is the data sent to the terminal.

[1010] Step 7:

[1011] The device guides the user through operation procedures both audibly and visually.

[1012] The terminal provides the received operation procedure data to the user as voice guidance and visual guidance. The voice guidance uses voice synthesis technology, and the visual guidance is displayed on the display of the smart glasses or head-mounted display. The input is the operation procedure data, and the output is the voice guidance and visual guidance.

[1013] Step 8:

[1014] The user performs the operation

[1015] The user operates and maintains the industrial automation equipment according to the voice and visual guidance provided by the terminal, where the input is the voice and visual guidance and the output is the operation performed.

[1016] The above steps allow the user to intuitively operate and maintain industrial automation equipment.

[1017] 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.

[1018] The present invention is a system that supports the elderly in intuitively operating smartphones, and in particular incorporates an emotion engine that recognizes the user's emotions and responds adaptively. Here, a specific embodiment incorporating the emotion engine will be described.

[1019] The system is composed of a terminal, a server, and an emotion engine working together. The terminal is equipped with a voice input device and a camera, allowing users to input voice, image, and video data. The emotion engine also analyzes the user's voice and image data to recognize the user's emotional state.

[1020] User Interaction

[1021] The user speaks to the smartphone, saying, "I want to communicate with my grandchildren on SNS." This voice input is taken through the device's voice input device.

[1022] Terminal handling

[1023] The device converts the captured voice data into text using voice recognition technology. If there is any voice data or image data, it also acquires it and sends it to the emotion engine.

[1024] Emotion engine processing

[1025] The emotion engine analyzes the acquired voice and image data to recognize the user's emotional state, for example, distinguishing between when the user is in trouble or when they are feeling anxious.

[1026] Server Analysis

[1027] The server receives data sent from the device and emotion engine and infers the user's intention. Here, it also uses emotional information obtained from the emotion engine. For example, if it infers that the user is in trouble, it generates more detailed procedural instructions than usual.

[1028] Operation procedure generation and response

[1029] The server generates adaptive operation instructions based on the inference results and emotional information. For example, it generates specific instructions for installing a social networking app and creating an account. If the user feels anxious, it provides detailed instructions.

[1030] Sending and providing instructions

[1031] The generated operating instructions are sent from the server to the device, which then provides them to the user as voice guidance. Specific instructions include, "First, open the app store, then search for the SNS app, and tap the install button."

[1032] User operations

[1033] The user follows the voice prompts to open the app store, search for the social networking app, and tap the install button.

[1034] Continued guidance

[1035] Once the installation is complete, the device will receive instructions from the server, such as "Next, open the app and begin creating your account." The emotion engine continues to monitor the user's emotions and adjusts the level of detail of the instructions as needed.

[1036] Emotion-Based Feedback

[1037] The device will use the emotion engine again to recognize the user's emotions while they are operating the device, and provide feedback based on that information. For example, even if the user is feeling anxious, the device will respond with positive feedback such as "That went well" if the operation is successful.

[1038] In this way, the present invention provides a system that supports more adaptive and intuitive smartphone operation by taking into account the user's emotional state. Specifically, it analyzes voice and image data and combines an emotion engine to provide operation procedures and feedback that comprehensively consider the user's intentions and emotions. This allows elderly people to use smartphones smoothly and safely.

[1039] The processing flow will be explained below.

[1040] Step 1: Getting voice input

[1041] The user speaks into their smartphone, saying, "I want to communicate with my grandchildren on social media."

[1042] Step 2: Convert the audio data

[1043] The device converts the captured voice data into text data, using voice recognition technology to convert the voice into text.

[1044] Step 3: Sending character data

[1045] The terminal transmits the converted character data to the server.

[1046] Step 4: Obtaining emotion data

[1047] The device sends audio data and, if necessary, image and video data of the user to the emotion engine.

[1048] Step 5: Analyze the sentiment data

[1049] The emotion engine analyzes the acquired voice and image data to recognize the user's emotions, for example, determining whether the user is feeling anxious.

[1050] Step 6: Receiving Data

[1051] The server receives the character data sent from the terminal and the emotion data sent from the emotion engine.

[1052] Step 7: Parsing intent

[1053] The server uses natural language processing to analyze the text data and infer the user's intent. Based on the request, "I want to communicate with my grandchildren on social media," it infers that the user needs to install a social media app and create an account.

[1054] Step 8: Generate operating instructions

[1055] The server generates adaptive operating procedures based on the inference results and emotion data. If the server detects anxiety in the user, it adjusts the procedures to be more detailed and easy to understand.

[1056] Step 9: Send instructions

[1057] The server transmits the generated adaptive operation procedure to the terminal.

[1058] Step 10: Voice prompts to the user

[1059] Based on the received operating instructions, the device will provide voice guidance to the user, such as "First, open the app store, then search for the SNS app, and tap the install button."

[1060] Step 11: User execution

[1061] The user follows the voice prompts to open the app store, search for the social networking app, and tap the install button.

[1062] Step 12: Installation Complete Notification

[1063] The device notifies the server that the installation of the SNS app has been completed.

[1064] Step 13: Account creation instructions

[1065] The device receives additional instructions from the server and provides a voice prompt to the user saying, "Next, open the app and begin creating your account." The emotion engine continues to monitor the user's emotions and provides further detailed instructions if anxiety persists.

[1066] Step 14: Form Assistance

[1067] The device will provide specific instructions for each input field on the account creation form, providing detailed instructions aloud such as "Please enter your name" or "Please enter your email address."

[1068] Step 15: Emotional Feedback

[1069] The emotion engine continuously analyzes the user's emotions while filling out the form, and provides relaxing feedback such as "Take it easy, it's okay" when stress levels rise.

[1070] Step 16: Complete your account creation

[1071] Users follow the voice prompts and enter the required information into the form to complete account creation.

[1072] In this way, by combining emotion engines, it becomes possible to respond adaptively to the user's emotional state, realizing a system that allows elderly people to operate smartphones comfortably.

[1073] Example 2

[1074] 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."

[1075] For elderly people who have difficulty intuitively operating smartphones, conventional systems have had difficulty recognizing the user's emotional state and providing adaptive support. In particular, when the operating procedures are difficult or the user feels anxious, appropriate support is not provided, which can lead to operational errors and stress in the user. There is a need to solve this problem and provide a system that can support elderly people in using smartphones with confidence.

[1076] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1077] In this invention, the server includes means for acquiring user voice data, means for converting the acquired voice data into character data, means for acquiring image data and video data using a camera, means for analyzing the acquired voice data and image data to recognize the user's emotional state, means for inferring the user's intention based on the analysis results of the voice data and emotional state, means for generating operation procedures based on the inference results and emotional information, means for providing the generated operation procedures to the user as voice guidance, and means for re-monitoring the user's emotional state during operation and adjusting the guidance content as necessary. This allows the user to receive optimal support according to their emotional state, enabling elderly people to operate smartphones smoothly and safely.

[1078] The "means for acquiring user voice data" refers to a device or system that collects the user's voice through a microphone.

[1079] The "means for converting acquired voice data into text data" refers to a process or system that converts voice data into text data using voice recognition technology.

[1080] "Means for acquiring image data and video data using a camera" refers to a device or system that uses a camera to record a user's actions and expressions and collects them as image or video data.

[1081] "Means for analyzing acquired audio and image data to recognize a user's emotional state" refers to a process or system that analyzes the collected data to identify a user's emotions (e.g., anxiety, confusion, joy, etc.).

[1082] A "means for inferring user intent based on analysis of speech data and emotional state" is a process or system that uses the analysis to identify the user's wants and needs.

[1083] The "means for generating operating procedures based on inference results and emotional information" refers to a process or system that generates appropriate operating procedures or guidelines according to the user's intentions and emotional state.

[1084] The "means for providing the generated operating procedure to the user as voice guidance" refers to a process or system that converts the generated operating procedure into voice data format and provides voice guidance to the user.

[1085] "Means for re-monitoring the user's emotional state during operation and adjusting the guidance content as necessary" refers to a process or system that re-monitors the user's emotions during operation and adaptively changes the details and content of the guidance according to the user's state.

[1086] The present invention is a system that supports the elderly in intuitively operating smartphones, and in particular incorporates an emotion engine to provide guidance and feedback that is adapted to the user's emotional state. Specific embodiments of the present invention will be described below.

[1087] System configuration

[1088] This system works in cooperation with a terminal, a server, and an emotion engine. The terminal is equipped with a voice input device and a camera, allowing users to input voice, image, and video data. The emotion engine analyzes the user's voice data and image data to recognize the user's emotional state. The server infers the user's intentions based on this data, generates appropriate operating procedures, and provides voice guidance.

[1089] Hardware and software used

[1090] Device: A mobile device such as a smartphone or tablet, including a voice input device (microphone) and a camera.

[1091] Speech recognition technology: Common cloud-based speech recognition APIs (e.g., Google Speech-to-Text API).

[1092] Emotion engine: An API for analyzing user emotions (e.g., Microsoft Azure's Emotion API).

[1093] Server: A cloud server for performing inference and procedure generation.

[1094] Speech synthesis technology: Technology that converts the generated instructions into voice guidance (e.g., Amazon Polly).

[1095] Specific operation of the system

[1096] 1. User Interaction

[1097] The user speaks to the smartphone, saying, "I want to communicate with my grandchildren on SNS." This voice input is acquired through the device's voice input device.

[1098] 2. Transcription of audio data

[1099] The device uses voice recognition technology to convert the acquired voice data into text data. For example, an input such as "I want to communicate with my grandchildren on social media" is converted into text.

[1100] 3. Acquisition of image and video data

[1101] The device uses a camera to record the user's facial expressions and movements, capturing image and video data, which is then sent to the emotion engine along with audio data.

[1102] 4. Emotion analysis

[1103] The emotion engine analyzes the received voice and image data to recognize the user's emotional state, for example, identifying various emotions such as whether the user is distressed or anxious.

[1104] 5. Intention Inference

[1105] The server uses natural language processing technology to infer the user's intentions based on the data sent from the emotion engine. Emotional information is also used to determine if the user is having trouble and if more detailed guidance is needed.

[1106] 6. Operation procedure generation

[1107] The server generates adaptive operation instructions based on the inference results and emotional information. For example, when guiding a user through the steps of installing a social networking app, if the user feels anxious, the server will break down the steps into more detailed instructions.

[1108] 7. Audio guidance of procedures

[1109] The generated operating instructions are sent from the server to the device, which then uses speech synthesis technology to provide voice guidance to the user, such as "First, open the app store, then search for the SNS app, and tap the install button."

[1110] 8. User Operations

[1111] The user follows the voice guidance to operate the smartphone. If the user does not understand an operation, they can ask for help by voice input again.

[1112] 9. Emotion Monitoring and Feedback

[1113] The device will again use the emotion engine to monitor the user's emotions during operation, adjust the level of detail when guiding the user through the next steps as needed, and provide positive feedback such as "That was great, good job" when the user performs a successful operation.

[1114] Specific examples

[1115] Below are examples of typical user speech input and subsequent prompts for actions:

[1116] Prompt Sentence Examples

[1117] User: "I want to communicate with my grandchildren on social media."

[1118] The device recognizes the voice, and the emotion engine analyzes the user's emotions. If it determines that the user is in trouble, the server generates more detailed instructions.

[1119] Server: "First, open the app store. Then search for a social networking app. Tap the install button."

[1120] In this way, the system provides comprehensive support for elderly people to smoothly operate smartphones while taking into account the user's emotional state.

[1121] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1122] Step 1:

[1123] The user inputs voice data. Specifically, the user speaks into the smartphone, saying, "I want to communicate with my grandchildren on SNS." This voice data is input.

[1124] Input: User's voice data

[1125] Output: Audio data file (WAV, MP3, etc.)

[1126] Step 2:

[1127] The device converts the acquired voice data into text data using voice recognition technology, such as the Google Speech-to-Text API.

[1128] Input: Audio data file

[1129] Data processing: Speech-to-text conversion using speech recognition algorithms

[1130] Output: Character data (text format)

[1131] Step 3:

[1132] The terminal uses a camera to record the user's facial expressions and movements, and acquires image data and video data.

[1133] Input: Captured video data

[1134] Data processing: Creating and saving video files

[1135] Output: Image data (JPEG, PNG), video data (MP4, AVI)

[1136] Step 4:

[1137] The emotion engine analyzes audio and image data to recognize the user's emotional state, for example, using Microsoft Azure's Emotion API.

[1138] Input: Text data, image data, video data

[1139] Data processing: Application of emotion recognition algorithms through natural language processing and image analysis

[1140] Output: Emotional state data (e.g., confusion, anxiety, joy)

[1141] Step 5:

[1142] The server infers the user's intention based on the emotional state data and text data sent from the emotion engine, using natural language processing technology (e.g., OpenAI's GPT-3).

[1143] Input: Emotional state data, character data

[1144] Data processing: Intention inference using natural language processing

[1145] Output: User intent data (e.g., "I want to interact on social media")

[1146] Step 6:

[1147] The server generates operation instructions based on the inference results and the emotional state, such as instructions for installing a social networking app.

[1148] Input: User intent data, emotional state data

[1149] Data processing: Applying procedure generation algorithms and assembling detailed operational steps

[1150] Output: Specific operating instructions (e.g., "First, open the app store")

[1151] Step 7:

[1152] The server then sends the generated instructions to the device, which then provides them as voice prompts, for example by using Amazon Polly to convert text to speech.

[1153] Input: Operation procedure data

[1154] Data processing: Use of Text-to-Speech technology (TTS)

[1155] Output: Audio data (audio guide for operation procedures)

[1156] Step 8:

[1157] The user follows the voice prompts to open the app store, search for the social networking app, and tap the install button. As the user performs these actions, the system continues to monitor the user's reactions.

[1158] Input: Voice guidance

[1159] Output: User action

[1160] Step 9:

[1161] The device monitors the user's emotions using the emotion engine again during the user's operation, and provides guidance on the next steps, adjusting the level of detail of the guidance as necessary.

[1162] Input: Real-time video and audio data

[1163] Data processing: Updates with sentiment analysis

[1164] Output: Adjusted operating procedure voice guidance

[1165] Step 10:

[1166] The device provides feedback based on the emotions recognized during the user's operation, for example, giving positive feedback such as "That was great, good job!"

[1167] Input: Updated emotional state data, user action data

[1168] Data processing: Applying feedback generation algorithms

[1169] Output: Feedback audio data

[1170] (Application example 2)

[1171] 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."

[1172] Elderly people often find it difficult to use smartphones due to their complex operation. Furthermore, in order to provide appropriate support for their operation, it is necessary to understand the user's emotional state and respond adaptively. However, current systems have difficulty providing support that takes the user's emotions into account, which can result in users feeling anxious or confused. The purpose of this invention is to solve this problem and enable elderly people to use smartphones with peace of mind.

[1173] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring voice data, means for converting the acquired voice data into character data, means for analyzing the character data and inferring the user's intention, means for generating operation procedures based on the inference results, means for guiding the generated operation procedures to the user, and means for adaptively responding using an emotion engine that analyzes the user's emotional state. This makes it possible to provide adaptive and detailed operation procedures while taking the user's emotional state into consideration. It is also possible to provide positive feedback upon success so that the user can continue operating with peace of mind.

[1174] "Means for acquiring voice data" refers to a device or system for collecting voice input from a user.

[1175] The term "means for converting voice data into character data" refers to a technology for converting acquired voice data into character information, such as a voice recognition technology.

[1176] "Means for analyzing character data and inferring the user's intent" refers to algorithms or programs that use converted character data to infer what the user is looking for.

[1177] "Means for generating operating procedures based on inference results" refers to a program or system for automatically generating operating procedures according to the user's intentions.

[1178] The "means for guiding the generated operating procedure to the user" refers to a method for communicating the generated operating procedure to the user, such as voice guidance or screen display.

[1179] An "emotion engine that analyzes a user's emotional state" refers to software or a program that analyzes a user's voice data or image data to recognize the user's emotional state.

[1180] "Adaptive response means" refers to a system that adjusts the guidance content and operating procedures according to the user's emotional state.

[1181] "Using image data and video data as the subject of analysis" refers to analyzing not only audio data but also image data and video data that include the user's facial expressions and actions.

[1182] "Means for providing audio guidance to a user" refers to a system or technology for conveying information or instructions to a user by voice.

[1183] "Means for adjusting the level of detail of operation procedures" refers to a method for adjusting the level of detail of the operation procedures presented depending on the user's emotional state and skill level.

[1184] "Means for providing positive feedback for successful operations" refers to software or a system that provides positive feedback by voice or display when a user successfully performs an operation.

[1185] "Means for the server to generate a response based on the inference results" refers to the technology that enables the server to create a response based on the analysis results based on voice data and emotional data and provide it to the user.

[1186] "Means for generating and guiding operating procedures using a generative AI model and prompt sentences" refers to an algorithm or system that uses a generative AI model to generate appropriate prompt sentences and provides operating procedures to the user based on those prompt sentences.

[1187] The present invention relates to a system that uses an emotion engine to grasp the emotional state of elderly people when they use a smartphone to deliver food, and provides adaptive operating procedures and feedback.

[1188] System Overview

[1189] This system operates in cooperation with the terminal, server, and emotion engine.

[1190] Terminal: A mobile device such as a smartphone equipped with a voice input device and a camera. The terminal has the function of receiving voice data from the user and converting it into text data.

[1191] Server: Analyzes voice and image data to infer the user's intentions and emotions. Based on the analysis results, the server generates adaptive operating procedures and provides feedback.

[1192] Emotion engine: An algorithm that analyzes the user's emotional state based on their voice and image data.

[1193] Hardware and Software

[1194] Hardware

[1195] Smartphone (with voice input device and camera)

[1196] software

[1197] speech_recognition library: Used to convert speech input into text data.

[1198] emotion_recognition: A custom library for sentiment analysis.

[1199] server_communication: For server communication.

[1200] voice_assistant: A custom module for voice assistant functionality.

[1201] Specific processing examples

[1202] 1. Acquiring and recognizing voice input:

[1203] The device receives voice input from the user, such as "I would like to order sushi," and converts this into text data using the speech_recognition library.

[1204] 2. Emotion recognition using emotion engine:

[1205] The acquired voice data and image data are analyzed by an emotion engine to identify the user's emotional state, such as whether they are feeling anxious or distressed.

[1206] 3. Sending data to the server:

[1207] Emotional data and voice data are sent to the server, which then uses this data to infer the user's intentions. For example, a request such as "I want to order sushi" is received.

[1208] 4. Operational Procedure Generation:

[1209] The server generates adaptive operation instructions based on the inference results and emotion data. If detailed instructions are required, it generates specific instructions such as "First, open the app and tap the sushi category."

[1210] 5. Audio feedback:

[1211] The generated instructions are sent to the device, and the voice assistant uses "voice_assistant" to provide feedback to the user: "Next, open the app store, search for the social networking app, and tap the install button."

[1212] 6. Positive Feedback:

[1213] If the operation is successful, the emotion engine checks the status again and provides positive feedback such as "That worked."

[1214] Specific examples and prompts for the generative AI model

[1215] Examples:

[1216] If a user voice-inputs "I want to order sushi" and the emotion engine detects that the user is in a "troubled" state, the server will generate a prompt sentence like the following:

[1217] Example prompt sentence:

[1218] 1. "First, open your food delivery app."

[1219] 2. "Next, tap on the Sushi category from the menu."

[1220] 3. "Choose your favorite sushi item and add it to your cart."

[1221] 4. "Please confirm your order details and press the button to confirm your order."

[1222] In this way, the system allows users to use their smartphones and operate food delivery services with emotional security.

[1223] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1224] Step 1:

[1225] Acquiring voice input:

[1226] The user speaks into the smartphone, saying, "I'd like to order sushi." The terminal acquires this speech using a voice input device. The input data is the user's voice data. The terminal acquires this voice data and sends it to the next step.

[1227] Step 2:

[1228] Audio to text conversion:

[1229] The device uses the speech_recognition library to convert the acquired voice data into text data. The input data is voice data, and the output data is text data converted from this voice. Data conversion is performed using voice recognition technology.

[1230] Step 3:

[1231] Emotional State Analysis:

[1232] The device sends voice and image data to the emotion engine, which analyzes the user's emotional state. The input data is the converted text data and voice data, and the output data is the user's emotional state (for example, "I'm in trouble" or "I'm relieved"). The emotion engine analyzes this using a machine learning algorithm.

[1233] Step 4:

[1234] Sending data to the server:

[1235] The terminal transmits emotional data and text data to the server. The input data is the analyzed emotional state and text data, and the output data is the data received by the server. Here, data communication technology is used.

[1236] Step 5:

[1237] Intention inference by the server:

[1238] The server infers the user's intention based on the received text data and emotional data. The input data is the emotional state and text data, and the output data is the user's intention (e.g., "I want to order sushi"). The server uses natural language processing technology and inference algorithms.

[1239] Step 6:

[1240] Generate operating instructions:

[1241] The server generates adaptive operation instructions based on the user's intention and emotional state. The input data is the inferred user's intention and emotional state, and the output data is the specific operation instructions (e.g., "First, open the app and tap the sushi category"). The server then uses a generative AI model to create an appropriate prompt.

[1242] Step 7:

[1243] Sending instructions:

[1244] The server sends the generated operation procedure to the terminal. The input data is the generated operation procedure, and the output data is the operation procedure received by the terminal. Data communication technology is used.

[1245] Step 8:

[1246] Voice guidance for operation procedures:

[1247] The device uses a voice assistant to provide guidance to the user based on the received operating instructions. The input data is the operating instructions, and the output data is voice guidance to the user. Speech synthesis technology is used to audibly convey specific operating procedures to the user.

[1248] Step 9:

[1249] User interaction and feedback:

[1250] The user follows the voice guidance to perform the operation. The device again uses the emotion engine to monitor the user's emotional state and provides positive feedback if the operation is successful. The input data is the user's operation result and new emotional data, and the output data is positive feedback. This allows the user to gain confidence in their operation and use the app with peace of mind.

[1251] 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.

[1252] 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.

[1253] 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.

[1254] [Fourth embodiment]

[1255] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1256] 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.

[1257] 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).

[1258] 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.

[1259] 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.

[1260] 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).

[1261] 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.

[1262] 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.

[1263] 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.

[1264] 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.

[1265] 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.

[1266] 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.

[1267] 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."

[1268] The system of the present invention is intended to assist elderly people in intuitively operating smartphones, and specific embodiments thereof will be described below.

[1269] The system is mainly composed of two parts: a terminal and a server. The terminal is equipped with a voice input device and a camera, allowing users to input voice, image, and video data. The server analyzes the received data, infers the user's intention, and generates appropriate operating procedures.

[1270] User Interaction

[1271] The user speaks to the smartphone, saying, "I want to communicate with my grandchildren on SNS." This voice input is taken through the device's voice input device.

[1272] Terminal handling

[1273] The device uses natural language processing (NLP) technology to recognize voice data and convert it into text data, which is then sent from the device to the server.

[1274] Server Analysis

[1275] The server infers the user's intent based on the text data received from the device, which includes pre-processing data analysis and uses NLP technology to understand the user's needs.

[1276] Next, the server generates operational instructions based on the inferred intent. For example, instructions for installing a social networking app or creating an account are generated at this stage.

[1277] Providing operating instructions

[1278] The generated operating instructions are sent from the server to the device, which then plays them back as voice guidance. For example, the instructions might say, "First, open the app store, then search for the social networking app, and tap the install button."

[1279] User operations

[1280] The user follows the instructions to open the app store, search for the social networking app, and install it. After completing this series of operations, the device notifies the server that the installation is complete and obtains the next steps.

[1281] Continued guidance

[1282] After the installation is complete, the device will continue to play a voice prompt saying, "Next, open the app and begin creating your account." It will also provide specific instructions for each form field, providing detailed instructions such as, "Enter your name" and "Enter your email address."

[1283] Specific examples

[1284] As a concrete example, let us consider an online shopping scenario.

[1285] The user speaks, "I want to buy a new shirt." The device converts this speech into text data and sends it to the server. The server infers the user's intent and generates online shopping instructions. For example, it might generate instructions such as, "Open a shopping site and enter 'shirt' in the search bar," and send them to the device.

[1286] The terminal provides the received instructions to the user as voice guidance, and the user operates the shopping site according to the guidance. The voice guidance supports a series of operations, from searching for products and adding them to the cart to completing the purchase.

[1287] In this way, the present invention provides a system that allows elderly people to easily operate smartphones, significantly lowering the barrier to using smartphones.

[1288] The processing flow will be explained below.

[1289] Step 1: Getting voice input

[1290] The user speaks into their smartphone, saying, "I want to communicate with my grandchildren on social media."

[1291] Step 2: Convert the audio data

[1292] The device converts the captured voice data into text data, using voice recognition technology to convert the voice into text.

[1293] Step 3: Sending character data

[1294] The terminal transmits the converted character data to the server.

[1295] Step 4: Receiving the data

[1296] The server receives the character data sent from the terminal.

[1297] Step 5: Parsing intent

[1298] The server uses natural language processing to analyze the received text data and infer the user's intent. For example, if the request is "I want to communicate with my grandchildren on social media," it can determine that a social media app needs to be installed and an account created.

[1299] Step 6: Generate operating instructions

[1300] Based on the inference results, the server generates specific operation instructions, including how to open the app store, how to search for and install social networking apps, and how to create an account.

[1301] Step 7: Send instructions

[1302] The server sends the generated operation procedure to the terminal.

[1303] Step 8: Audio guidance to the user

[1304] Based on the received operating instructions, the device will provide voice guidance to the user, such as "First, open the app store, then search for the SNS app, and tap the install button."

[1305] Step 9: User execution

[1306] The user follows the voice prompts to open the app store, search for the social networking app, and tap the install button.

[1307] Step 10: Installation Complete Notification

[1308] The device notifies the server that the installation of the SNS app has been completed.

[1309] Step 11: Account creation instructions

[1310] The device receives additional operating instructions from the server and provides the user with a voice prompt saying, "Next, open the app and begin creating your account."

[1311] Step 12: Form Assistance

[1312] The device also provides specific input assistance within the account creation form, such as "Please enter your name" and "Please enter your email address."

[1313] Step 13: Complete your account creation

[1314] Users follow the voice prompts and enter the required information into the form to complete account creation.

[1315] This series of processes realizes a system that allows users to operate their smartphones intuitively and smoothly.

[1316] Example 1

[1317] 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."

[1318] Modern smartphones are multifunctional and often difficult to operate, especially for the elderly. Even with effective use of voice input, conversion to text data, and natural language processing, it is difficult for elderly people to intuitively and easily operate smartphones. This invention aims to solve this problem by providing a system that supports elderly people in operating smartphones more intuitively.

[1319] 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.

[1320] In this invention, the server includes means for acquiring voice data, means for converting the acquired voice data into character data, means for analyzing the character data and inferring the user's intention, means for generating operation procedures based on the inference result, means for providing the generated operation procedures to the user, and means for analyzing the user's intention and generating and providing the operation procedures by the terminal and the server operating in cooperation with each other, thereby enabling elderly people to operate smartphones intuitively and easily.

[1321] "Voice data" refers to data that has been recorded and stored in digital form of a user's speech.

[1322] "Character data" refers to data obtained by converting voice data into text format.

[1323] "Analysis" is the process of understanding the information contained in text data and interpreting its meaning.

[1324] "User intent" refers to the requests and desires expressed by the user through speech input.

[1325] "Operation steps" are instructions or guidelines for performing a desired action by a user.

[1326] "Providing" refers to the act of transmitting the generated operating procedure to the user by voice or display.

[1327] A "terminal" is a device that is directly operated by a user, such as a smartphone or tablet.

[1328] A "server" is a computer system that is installed on the cloud or within a network and works in conjunction with terminals to analyze and process data.

[1329] An "audio input device" is a device, such as a microphone, used to capture audio data.

[1330] "Natural language processing" refers to techniques and methods that allow computers to understand and process human language.

[1331] The system of the present invention assists elderly people in intuitively operating smartphones. This system is composed of a terminal and a server, and aims to simplify smartphone operation by automatically generating and providing operating procedures based on the user's voice input. Specific embodiments are described below.

[1332] System configuration

[1333] The system mainly consists of two parts: a terminal equipped with a voice input device and a server that performs data analysis and generates operating procedures.

[1334] Terminal

[1335] The terminal is a mobile device such as a smartphone or tablet, equipped with a voice input device (microphone), a camera, and a communication means. The terminal receives voice data from the user and converts it into text data. This conversion is performed using natural language processing (NLP) technology such as the Google speech recognition API.

[1336] server

[1337] The server, located in the cloud or within the network, receives and analyzes the text data sent from the device. Using an NLP library such as Python's NLTK or spaCy, the server tokenizes the text data, extracts key keywords, and infers the user's intent. Based on the inference results, the server then generates and sends operational instructions to the device.

[1338] Specific operation example

[1339] 1. User voice input:

[1340] The user speaks into their smartphone, saying, "I want to communicate with my grandchildren on social media." This voice is picked up through the device's microphone.

[1341] 2. Transcription of audio data:

[1342] The device converts the acquired voice data into text data using the Google speech recognition API or similar.

[1343] 3. Sending and parsing character data:

[1344] The device sends the converted text data in real time to the server, which then analyzes it and uses libraries such as Python's NLTK or spaCy to infer the user's intent.

[1345] 4. Operational Procedure Generation:

[1346] The server generates appropriate operation instructions based on the inference results, for example, "First, open the app store, then search for the social networking app, and tap the install button."

[1347] 5. Provide instructions:

[1348] The server sends the generated operation procedure to the terminal, which then provides it to the user as voice guidance.

[1349] Specific examples

[1350] Let's consider an online shopping scenario. A user voice-inputs, "I want to buy a new shirt." The device converts this voice into text data and sends it to the server. The server infers the user's intention, generates instructions such as, "Open the shopping site and enter 'shirt' in the search bar," and sends them to the device. The device then provides the received instructions to the user as voice guidance, and the user operates the shopping site according to the instructions.

[1351] Example prompts for generative AI models

[1352] You can simulate the system's processing by inputting prompts like the following into the generative AI model:

[1353] Please explain the sequence of steps that would occur if a user were to say, "I want to communicate with my grandchildren on social media," using voice input into a smartphone. Please include speech recognition, data analysis, generation of operating procedures, and voice guidance.

[1354] In this way, the system of the present invention enables elderly people to operate smartphones intuitively and easily, and supports their use of smartphones.

[1355] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1356] Step 1: User Speech Input

[1357] The user speaks into their smartphone, saying, "I want to communicate with my grandchildren on social media." The input is voice data, which is picked up by the device's microphone. The voice data is then prepared for use in the next processing step.

[1358] Step 2: Transcribe the audio data

[1359] The device converts the acquired voice data into text data using natural language processing (NLP) technology such as the Google speech recognition API. This conversion is a specific operation that takes voice data as input, analyzes it, and outputs text data. For example, the voice data "I want to communicate with my grandchildren on social media" is converted into text data "I want to communicate with my grandchildren on social media."

[1360] Step 3: Sending character data

[1361] The terminal transmits the converted text data to the server in real time. The input here is text data, and the output is data transmission to the server. Specifically, an HTTP request is sent from the terminal to the server, and the text data is included.

[1362] Step 4: Parsing character data

[1363] The server infers the user's intent based on the received text data. It uses an NLP library such as Python's NLTK or spaCy to tokenize the text data and extract key keywords. In this step, the input is the text data, and the output is the inferred user intent. Specifically, the server analyzes the text data and identifies keywords such as "grandchild," "SNS," and "interaction."

[1364] Step 5: Generate operating instructions

[1365] The server generates appropriate operating instructions based on the inferred intent. The input here is the user's intent, and the output is the operating instructions. Specifically, the server references predefined scenarios and procedure templates to create a guide such as "First, open the app store, then search for the social networking app, and tap the install button."

[1366] Step 6: Send instructions

[1367] The server sends the generated operation procedure to the terminal. The input is the generated operation procedure, and the output is data transmission to the terminal. A specific operation is an HTTP response sent from the server to the terminal, which includes the generated operation procedure.

[1368] Step 7: Provide operating instructions

[1369] The device receives the operation procedure from the server and provides it to the user as voice guidance. The input here is the generated operation procedure, and the output is the voice guidance. Specifically, the device uses voice synthesis technology to provide voice guidance such as, "First, open the app store, then search for the SNS app, and tap the install button."

[1370] Step 8: User interaction

[1371] The user operates the smartphone according to the provided voice guidance. The input is the voice guidance, and the output is the corresponding smartphone operation. Specifically, the user opens the app store, searches for the SNS app, and installs it.

[1372] Step 9: Installation Complete Notification

[1373] The device notifies the server that the user has completed installation of the SNS app. The input is the installation completion status, and the output is a notification to the server. Specifically, the device detects the completion of installation and sends the status to the server via an HTTP request.

[1374] Step 10: Next steps

[1375] The server receives notification that the installation is complete, generates next steps, and sends them to the device. The device then plays the next steps received from the server as voice guidance. The input here is the next steps, and the output is voice guidance. For example, the guidance may say, "Next, open the app and begin creating your account." Specific operations include providing detailed voice instructions for each input field in the form, such as "Please enter your name" or "Please enter your email address."

[1376] (Application example 1)

[1377] 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."

[1378] In traditional factory facilities and industrial automation environments, elderly and inexperienced workers face the challenge of efficiently operating sophisticated machinery and equipment. This can lead to operational errors and delays in maintenance work, resulting in concerns about reduced overall efficiency. Furthermore, the lack of intuitive and easy-to-understand operating guides means that training and education are time-consuming and costly.

[1379] 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.

[1380] In this invention, the server includes means for acquiring voice data, means for converting the voice data into character data, means for analyzing the character data and inferring a user's intention, means for generating an operating procedure based on the inference result, means for guiding the generated operating procedure to the user, and means for providing voice guidance and displaying visual guidance for operating the industrial automation device based on the user's intention, thereby enabling even elderly people and inexperienced workers to intuitively operate and maintain the industrial automation device.

[1381] "Means for acquiring voice data" refers to devices or software for collecting the voice uttered by the user as digital data.

[1382] "Means for converting voice data into text data" refers to technology or devices that analyze acquired voice data and convert it into corresponding text information.

[1383] "Means for analyzing character data and inferring user intent" refers to a system that analyzes character data entered by a user using natural language processing technology, etc., to understand what the user is trying to do.

[1384] "Means for generating operating procedures based on inference results" refers to a technology or mechanism that generates accurate and specific operating methods or work procedures according to the inferred user intentions.

[1385] The "means for guiding the generated operating procedure to the user" refers to a method or device for presenting the generated operating procedure to the user in an easy-to-understand manner.

[1386] "Means for providing audio guidance and displaying visual guidance for operating industrial automation equipment based on the user's intentions" refers to technology or devices that explain the appropriate procedures through audio and visual presentations when elderly or inexperienced workers operate industrial automation equipment.

[1387] "Means for using image data and video data" refers to technologies and systems for obtaining and analyzing useful information from static images and dynamic video.

[1388] "Means for generating and providing guidance on maintenance procedures for industrial automation equipment" refers to technology or mechanisms that generate specific methods for maintaining and repairing automated machinery used in factories, etc., and provide easy-to-understand guidance to workers.

[1389] The present invention provides a system that enables elderly or inexperienced workers to intuitively operate and maintain industrial automation equipment. The system aims to simplify complex operating procedures by combining voice input and visual guidance, thereby improving efficiency and safety.

[1390] Hardware and Software Configuration

[1391] The device uses smart glasses or head-mounted displays (e.g., Google Glass, Microsoft HoloLens) equipped with a voice input device and a camera, which can rapidly collect the user's voice and provide visual feedback.

[1392] The server uses advanced natural language processing (NLP) techniques to analyze the user's voice data. The voice data is converted into text data, and the user's intent is then inferred. Based on this inference, specific operating instructions are generated. The server uses the Google Speech-to-Text API and natural language processing libraries (e.g., spaCy, NLTK).

[1393] Data processing and calculation

[1394] The device captures the user's voice and converts it into text data in real time using the Google Speech-to-Text API. This text data is then sent to a server, where natural language processing technology is used to analyze the user's intent and generate appropriate operating instructions based on the analysis results. The generated instructions are then sent to the device as audio and visual guidance and provided to the user.

[1395] Specific examples

[1396] For example, if a user says "I want to start maintenance on the robot," the device collects the voice, converts the data into text, and sends it to the server. The server analyzes the text and generates specific maintenance instructions, such as "First, turn off the safety device, then open the panel." The generated instructions are sent to the device as audio and visual guidance, and the user is guided through them.

[1397] Example prompt sentence:

[1398] Imagine a scenario where a user uses smart glasses to say, "I want to start maintenance on the robot." Explain the process of converting this speech into text data, sending it to a server, generating appropriate maintenance instructions, and displaying and providing voice guidance on the smart glasses.

[1399] In this way, the system of the present invention realizes an environment in which elderly people and inexperienced workers can easily operate and maintain industrial automation equipment.

[1400] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1401] Step 1:

[1402] The user provides voice input

[1403] The user inputs "I want to start maintenance on the robot" through a voice input device on the smart glasses or head-mounted display. The input is voice data. The output is obtained as voice data.

[1404] Step 2:

[1405] The device converts the voice data into text data.

[1406] The device's internal processing converts acquired voice data into text data using the Google Speech-to-Text API. The input is voice data, and the output is the converted text data.

[1407] Step 3:

[1408] The terminal sends character data to the server

[1409] The converted character data is sent from the terminal to the server. The input is character data, and the output is character data sent to the server.

[1410] Step 4:

[1411] The server analyzes the text data and infers the user's intent.

[1412] On the server side, the received text data is analyzed using natural language processing (NLP) technology to infer the user's intent. The software used is an NLP library such as spaCy or NLTK. The input is text data, and the output is data indicating the user's intent.

[1413] Step 5:

[1414] The server generates an operating procedure based on the inference results.

[1415] The server generates specific operating procedures based on the inferred user intent. In this generation process, appropriate procedures are automatically generated using a generative AI model. The input is data indicating the user intent, and the output is operating procedure data.

[1416] Step 6:

[1417] Send the operation instructions generated by the server to the terminal

[1418] The generated operation procedure data is sent from the server to the terminal. The input is the operation procedure data, and the output is the data sent to the terminal.

[1419] Step 7:

[1420] The device guides the user through operation procedures both audibly and visually.

[1421] The terminal provides the received operation procedure data to the user as voice guidance and visual guidance. The voice guidance uses voice synthesis technology, and the visual guidance is displayed on the display of the smart glasses or head-mounted display. The input is the operation procedure data, and the output is the voice guidance and visual guidance.

[1422] Step 8:

[1423] The user performs the operation

[1424] The user operates and maintains the industrial automation equipment according to the voice and visual guidance provided by the terminal, where the input is the voice and visual guidance and the output is the operation performed.

[1425] The above steps allow the user to intuitively operate and maintain industrial automation equipment.

[1426] 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.

[1427] The present invention is a system that supports the elderly in intuitively operating smartphones, and in particular incorporates an emotion engine that recognizes the user's emotions and responds adaptively. Here, a specific embodiment incorporating the emotion engine will be described.

[1428] The system is composed of a terminal, a server, and an emotion engine working together. The terminal is equipped with a voice input device and a camera, allowing users to input voice, image, and video data. The emotion engine also analyzes the user's voice and image data to recognize the user's emotional state.

[1429] User Interaction

[1430] The user speaks to the smartphone, saying, "I want to communicate with my grandchildren on SNS." This voice input is taken through the device's voice input device.

[1431] Terminal handling

[1432] The device converts the captured voice data into text using voice recognition technology. If there is any voice data or image data, it also acquires it and sends it to the emotion engine.

[1433] Emotion engine processing

[1434] The emotion engine analyzes the acquired voice and image data to recognize the user's emotional state, for example, distinguishing between when the user is in trouble or when they are feeling anxious.

[1435] Server Analysis

[1436] The server receives data sent from the device and emotion engine and infers the user's intention. Here, it also uses emotional information obtained from the emotion engine. For example, if it infers that the user is in trouble, it generates more detailed procedural instructions than usual.

[1437] Operation procedure generation and response

[1438] The server generates adaptive operation instructions based on the inference results and emotional information. For example, it generates specific instructions for installing a social networking app and creating an account. If the user feels anxious, it provides detailed instructions.

[1439] Sending and providing instructions

[1440] The generated operating instructions are sent from the server to the device, which then provides them to the user as voice guidance. Specific instructions include, "First, open the app store, then search for the SNS app, and tap the install button."

[1441] User operations

[1442] The user follows the voice prompts to open the app store, search for the social networking app, and tap the install button.

[1443] Continued guidance

[1444] Once the installation is complete, the device will receive instructions from the server, such as "Next, open the app and begin creating your account." The emotion engine continues to monitor the user's emotions and adjusts the level of detail of the instructions as needed.

[1445] Emotion-Based Feedback

[1446] The device will use the emotion engine again to recognize the user's emotions while they are operating the device, and provide feedback based on that information. For example, even if the user is feeling anxious, the device will respond with positive feedback such as "That went well" if the operation is successful.

[1447] In this way, the present invention provides a system that supports more adaptive and intuitive smartphone operation by taking into account the user's emotional state. Specifically, it analyzes voice and image data and combines an emotion engine to provide operation procedures and feedback that comprehensively consider the user's intentions and emotions. This allows elderly people to use smartphones smoothly and safely.

[1448] The processing flow will be explained below.

[1449] Step 1: Getting voice input

[1450] The user speaks into their smartphone, saying, "I want to communicate with my grandchildren on social media."

[1451] Step 2: Convert the audio data

[1452] The device converts the captured voice data into text data, using voice recognition technology to convert the voice into text.

[1453] Step 3: Sending character data

[1454] The terminal transmits the converted character data to the server.

[1455] Step 4: Obtaining emotion data

[1456] The device sends audio data and, if necessary, image and video data of the user to the emotion engine.

[1457] Step 5: Analyze the sentiment data

[1458] The emotion engine analyzes the acquired voice and image data to recognize the user's emotions, for example, determining whether the user is feeling anxious.

[1459] Step 6: Receiving Data

[1460] The server receives the character data sent from the terminal and the emotion data sent from the emotion engine.

[1461] Step 7: Parsing intent

[1462] The server uses natural language processing to analyze the text data and infer the user's intent. Based on the request, "I want to communicate with my grandchildren on social media," it infers that the user needs to install a social media app and create an account.

[1463] Step 8: Generate operating instructions

[1464] The server generates adaptive operating procedures based on the inference results and emotion data. If the server detects anxiety in the user, it adjusts the procedures to be more detailed and easy to understand.

[1465] Step 9: Send instructions

[1466] The server transmits the generated adaptive operation procedure to the terminal.

[1467] Step 10: Voice prompts to the user

[1468] Based on the received operating instructions, the device will provide voice guidance to the user, such as "First, open the app store, then search for the SNS app, and tap the install button."

[1469] Step 11: User execution

[1470] The user follows the voice prompts to open the app store, search for the social networking app, and tap the install button.

[1471] Step 12: Installation Complete Notification

[1472] The device notifies the server that the installation of the SNS app has been completed.

[1473] Step 13: Account creation instructions

[1474] The device receives additional instructions from the server and provides a voice prompt to the user saying, "Next, open the app and begin creating your account." The emotion engine continues to monitor the user's emotions and provides further detailed instructions if anxiety persists.

[1475] Step 14: Form Assistance

[1476] The device will provide specific instructions for each input field on the account creation form, providing detailed instructions aloud such as "Please enter your name" or "Please enter your email address."

[1477] Step 15: Emotional Feedback

[1478] The emotion engine continuously analyzes the user's emotions while filling out the form, and provides relaxing feedback such as "Take it easy, it's okay" when stress levels rise.

[1479] Step 16: Complete your account creation

[1480] Users follow the voice prompts and enter the required information into the form to complete account creation.

[1481] In this way, by combining emotion engines, it becomes possible to respond adaptively to the user's emotional state, realizing a system that allows elderly people to operate smartphones comfortably.

[1482] Example 2

[1483] 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."

[1484] For elderly people who have difficulty intuitively operating smartphones, conventional systems have had difficulty recognizing the user's emotional state and providing adaptive support. In particular, when the operating procedures are difficult or the user feels anxious, appropriate support is not provided, which can lead to operational errors and stress in the user. There is a need to solve this problem and provide a system that can support elderly people in using smartphones with confidence.

[1485] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1486] In this invention, the server includes means for acquiring user voice data, means for converting the acquired voice data into character data, means for acquiring image data and video data using a camera, means for analyzing the acquired voice data and image data to recognize the user's emotional state, means for inferring the user's intention based on the analysis results of the voice data and emotional state, means for generating operation procedures based on the inference results and emotional information, means for providing the generated operation procedures to the user as voice guidance, and means for re-monitoring the user's emotional state during operation and adjusting the guidance content as necessary. This allows the user to receive optimal support according to their emotional state, enabling elderly people to operate smartphones smoothly and safely.

[1487] The "means for acquiring user voice data" refers to a device or system that collects the user's voice through a microphone.

[1488] The "means for converting acquired voice data into text data" refers to a process or system that converts voice data into text data using voice recognition technology.

[1489] "Means for acquiring image data and video data using a camera" refers to a device or system that uses a camera to record a user's actions and expressions and collects them as image or video data.

[1490] "Means for analyzing acquired audio and image data to recognize a user's emotional state" refers to a process or system that analyzes the collected data to identify a user's emotions (e.g., anxiety, confusion, joy, etc.).

[1491] A "means for inferring user intent based on analysis of speech data and emotional state" is a process or system that uses the analysis to identify the user's wants and needs.

[1492] The "means for generating operating procedures based on inference results and emotional information" refers to a process or system that generates appropriate operating procedures or guidelines according to the user's intentions and emotional state.

[1493] The "means for providing the generated operating procedure to the user as voice guidance" refers to a process or system that converts the generated operating procedure into voice data format and provides voice guidance to the user.

[1494] "Means for re-monitoring the user's emotional state during operation and adjusting the guidance content as necessary" refers to a process or system that re-monitors the user's emotions during operation and adaptively changes the details and content of the guidance according to the user's state.

[1495] The present invention is a system that supports the elderly in intuitively operating smartphones, and in particular incorporates an emotion engine to provide guidance and feedback that is adapted to the user's emotional state. Specific embodiments of the present invention will be described below.

[1496] System configuration

[1497] This system works in cooperation with a terminal, a server, and an emotion engine. The terminal is equipped with a voice input device and a camera, allowing users to input voice, image, and video data. The emotion engine analyzes the user's voice data and image data to recognize the user's emotional state. The server infers the user's intentions based on this data, generates appropriate operating procedures, and provides voice guidance.

[1498] Hardware and software used

[1499] Device: A mobile device such as a smartphone or tablet, including a voice input device (microphone) and a camera.

[1500] Speech recognition technology: Common cloud-based speech recognition APIs (e.g., Google Speech-to-Text API).

[1501] Emotion engine: An API for analyzing user emotions (e.g., Microsoft Azure's Emotion API).

[1502] Server: A cloud server for performing inference and procedure generation.

[1503] Speech synthesis technology: Technology that converts the generated instructions into voice guidance (e.g., Amazon Polly).

[1504] Specific operation of the system

[1505] 1. User Interaction

[1506] The user speaks to the smartphone, saying, "I want to communicate with my grandchildren on SNS." This voice input is acquired through the device's voice input device.

[1507] 2. Transcription of audio data

[1508] The device uses voice recognition technology to convert the acquired voice data into text data. For example, an input such as "I want to communicate with my grandchildren on social media" is converted into text.

[1509] 3. Acquisition of image and video data

[1510] The device uses a camera to record the user's facial expressions and movements, capturing image and video data, which is then sent to the emotion engine along with audio data.

[1511] 4. Emotion analysis

[1512] The emotion engine analyzes the received voice and image data to recognize the user's emotional state, for example, identifying various emotions such as whether the user is distressed or anxious.

[1513] 5. Intention Inference

[1514] The server uses natural language processing technology to infer the user's intentions based on the data sent from the emotion engine. Emotional information is also used to determine if the user is having trouble and if more detailed guidance is needed.

[1515] 6. Operation procedure generation

[1516] The server generates adaptive operation instructions based on the inference results and emotional information. For example, when guiding a user through the steps of installing a social networking app, if the user feels anxious, the server will break down the steps into more detailed instructions.

[1517] 7. Audio guidance of procedures

[1518] The generated operating instructions are sent from the server to the device, which then uses speech synthesis technology to provide voice guidance to the user, such as "First, open the app store, then search for the SNS app, and tap the install button."

[1519] 8. User Operations

[1520] The user follows the voice guidance to operate the smartphone. If the user does not understand an operation, they can ask for help by voice input again.

[1521] 9. Emotion Monitoring and Feedback

[1522] The device will again use the emotion engine to monitor the user's emotions during operation, adjust the level of detail when guiding the user through the next steps as needed, and provide positive feedback such as "That was great, good job" when the user performs a successful operation.

[1523] Specific examples

[1524] Below are examples of typical user speech input and subsequent prompts for actions:

[1525] Prompt Sentence Examples

[1526] User: "I want to communicate with my grandchildren on social media."

[1527] The device recognizes the voice, and the emotion engine analyzes the user's emotions. If it determines that the user is in trouble, the server generates more detailed instructions.

[1528] Server: "First, open the app store. Then search for a social networking app. Tap the install button."

[1529] In this way, the system provides comprehensive support for elderly people to smoothly operate smartphones while taking into account the user's emotional state.

[1530] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1531] Step 1:

[1532] The user inputs voice data. Specifically, the user speaks into the smartphone, saying, "I want to communicate with my grandchildren on SNS." This voice data is input.

[1533] Input: User's voice data

[1534] Output: Audio data file (WAV, MP3, etc.)

[1535] Step 2:

[1536] The device converts the acquired voice data into text data using voice recognition technology, such as the Google Speech-to-Text API.

[1537] Input: Audio data file

[1538] Data processing: Speech-to-text conversion using speech recognition algorithms

[1539] Output: Character data (text format)

[1540] Step 3:

[1541] The terminal uses a camera to record the user's facial expressions and movements, and acquires image data and video data.

[1542] Input: Captured video data

[1543] Data processing: Creating and saving video files

[1544] Output: Image data (JPEG, PNG), video data (MP4, AVI)

[1545] Step 4:

[1546] The emotion engine analyzes audio and image data to recognize the user's emotional state, for example, using Microsoft Azure's Emotion API.

[1547] Input: Text data, image data, video data

[1548] Data processing: Application of emotion recognition algorithms through natural language processing and image analysis

[1549] Output: Emotional state data (e.g., confusion, anxiety, joy)

[1550] Step 5:

[1551] The server infers the user's intention based on the emotional state data and text data sent from the emotion engine, using natural language processing technology (e.g., OpenAI's GPT-3).

[1552] Input: Emotional state data, character data

[1553] Data processing: Intention inference using natural language processing

[1554] Output: User intent data (e.g., "I want to interact on social media")

[1555] Step 6:

[1556] The server generates operation instructions based on the inference results and the emotional state, such as instructions for installing a social networking app.

[1557] Input: User intent data, emotional state data

[1558] Data processing: Applying procedure generation algorithms and assembling detailed operational steps

[1559] Output: Specific operating instructions (e.g., "First, open the app store")

[1560] Step 7:

[1561] The server then sends the generated instructions to the device, which then provides them as voice prompts, for example by using Amazon Polly to convert text to speech.

[1562] Input: Operation procedure data

[1563] Data processing: Use of Text-to-Speech technology (TTS)

[1564] Output: Audio data (audio guide for operation procedures)

[1565] Step 8:

[1566] The user follows the voice prompts to open the app store, search for the social networking app, and tap the install button. As the user performs these actions, the system continues to monitor the user's reactions.

[1567] Input: Voice guidance

[1568] Output: User action

[1569] Step 9:

[1570] The device monitors the user's emotions using the emotion engine again during the user's operation, and provides guidance on the next steps, adjusting the level of detail of the guidance as necessary.

[1571] Input: Real-time video and audio data

[1572] Data processing: Updates with sentiment analysis

[1573] Output: Adjusted operating procedure voice guidance

[1574] Step 10:

[1575] The device provides feedback based on the emotions recognized during the user's operation, for example, giving positive feedback such as "That was great, good job!"

[1576] Input: Updated emotional state data, user action data

[1577] Data processing: Applying feedback generation algorithms

[1578] Output: Feedback audio data

[1579] (Application example 2)

[1580] 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."

[1581] Elderly people often find it difficult to use smartphones due to their complex operation. Furthermore, in order to provide appropriate support for their operation, it is necessary to understand the user's emotional state and respond adaptively. However, current systems have difficulty providing support that takes the user's emotions into account, which can result in users feeling anxious or confused. The purpose of this invention is to solve this problem and enable elderly people to use smartphones with peace of mind.

[1582] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring voice data, means for converting the acquired voice data into character data, means for analyzing the character data and inferring the user's intention, means for generating operation procedures based on the inference results, means for guiding the generated operation procedures to the user, and means for adaptively responding using an emotion engine that analyzes the user's emotional state. This makes it possible to provide adaptive and detailed operation procedures while taking the user's emotional state into consideration. It is also possible to provide positive feedback upon success so that the user can continue operating with peace of mind.

[1583] "Means for acquiring voice data" refers to a device or system for collecting voice input from a user.

[1584] The term "means for converting voice data into character data" refers to a technology for converting acquired voice data into character information, such as a voice recognition technology.

[1585] "Means for analyzing character data and inferring the user's intent" refers to algorithms or programs that use converted character data to infer what the user is looking for.

[1586] "Means for generating operating procedures based on inference results" refers to a program or system for automatically generating operating procedures according to the user's intentions.

[1587] The "means for guiding the generated operating procedure to the user" refers to a method for communicating the generated operating procedure to the user, such as voice guidance or screen display.

[1588] An "emotion engine that analyzes a user's emotional state" refers to software or a program that analyzes a user's voice data or image data to recognize the user's emotional state.

[1589] "Adaptive response means" refers to a system that adjusts the guidance content and operating procedures according to the user's emotional state.

[1590] "Using image data and video data as the subject of analysis" refers to analyzing not only audio data but also image data and video data that include the user's facial expressions and actions.

[1591] "Means for providing audio guidance to a user" refers to a system or technology for conveying information or instructions to a user by voice.

[1592] "Means for adjusting the level of detail of operation procedures" refers to a method for adjusting the level of detail of the operation procedures presented depending on the user's emotional state and skill level.

[1593] "Means for providing positive feedback for successful operations" refers to software or a system that provides positive feedback by voice or display when a user successfully performs an operation.

[1594] "Means for the server to generate a response based on the inference results" refers to the technology that enables the server to create a response based on the analysis results based on voice data and emotional data and provide it to the user.

[1595] "Means for generating and guiding operating procedures using a generative AI model and prompt sentences" refers to an algorithm or system that uses a generative AI model to generate appropriate prompt sentences and provides operating procedures to the user based on those prompt sentences.

[1596] The present invention relates to a system that uses an emotion engine to grasp the emotional state of elderly people when they use a smartphone to deliver food, and provides adaptive operating procedures and feedback.

[1597] System Overview

[1598] This system operates in cooperation with the terminal, server, and emotion engine.

[1599] Terminal: A mobile device such as a smartphone equipped with a voice input device and a camera. The terminal has the function of receiving voice data from the user and converting it into text data.

[1600] Server: Analyzes voice and image data to infer the user's intentions and emotions. Based on the analysis results, the server generates adaptive operating procedures and provides feedback.

[1601] Emotion engine: An algorithm that analyzes the user's emotional state based on their voice and image data.

[1602] Hardware and Software

[1603] Hardware

[1604] Smartphone (with voice input device and camera)

[1605] software

[1606] speech_recognition library: Used to convert speech input into text data.

[1607] emotion_recognition: A custom library for sentiment analysis.

[1608] server_communication: For server communication.

[1609] voice_assistant: A custom module for voice assistant functionality.

[1610] Specific processing examples

[1611] 1. Acquiring and recognizing voice input:

[1612] The device receives voice input from the user, such as "I would like to order sushi," and converts this into text data using the speech_recognition library.

[1613] 2. Emotion recognition using emotion engine:

[1614] The acquired voice data and image data are analyzed by an emotion engine to identify the user's emotional state, such as whether they are feeling anxious or distressed.

[1615] 3. Sending data to the server:

[1616] Emotional data and voice data are sent to the server, which then uses this data to infer the user's intentions. For example, a request such as "I want to order sushi" is received.

[1617] 4. Operational Procedure Generation:

[1618] The server generates adaptive operation instructions based on the inference results and emotion data. If detailed instructions are required, it generates specific instructions such as "First, open the app and tap the sushi category."

[1619] 5. Audio feedback:

[1620] The generated instructions are sent to the device, and the voice assistant uses "voice_assistant" to provide feedback to the user: "Next, open the app store, search for the social networking app, and tap the install button."

[1621] 6. Positive Feedback:

[1622] If the operation is successful, the emotion engine checks the status again and provides positive feedback such as "That worked."

[1623] Specific examples and prompts for the generative AI model

[1624] Examples:

[1625] If a user voice-inputs "I want to order sushi" and the emotion engine detects that the user is in a "troubled" state, the server will generate a prompt sentence like the following:

[1626] Example prompt sentence:

[1627] 1. "First, open your food delivery app."

[1628] 2. "Next, tap on the Sushi category from the menu."

[1629] 3. "Choose your favorite sushi item and add it to your cart."

[1630] 4. "Please confirm your order details and press the button to confirm your order."

[1631] In this way, the system allows users to use their smartphones and operate food delivery services with emotional security.

[1632] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1633] Step 1:

[1634] Acquiring voice input:

[1635] The user speaks into the smartphone, saying, "I'd like to order sushi." The terminal acquires this speech using a voice input device. The input data is the user's voice data. The terminal acquires this voice data and sends it to the next step.

[1636] Step 2:

[1637] Audio to text conversion:

[1638] The device uses the speech_recognition library to convert the acquired voice data into text data. The input data is voice data, and the output data is text data converted from this voice. Data conversion is performed using voice recognition technology.

[1639] Step 3:

[1640] Emotional State Analysis:

[1641] The device sends voice and image data to the emotion engine, which analyzes the user's emotional state. The input data is the converted text data and voice data, and the output data is the user's emotional state (for example, "I'm in trouble" or "I'm relieved"). The emotion engine analyzes this using a machine learning algorithm.

[1642] Step 4:

[1643] Sending data to the server:

[1644] The terminal transmits emotional data and text data to the server. The input data is the analyzed emotional state and text data, and the output data is the data received by the server. Here, data communication technology is used.

[1645] Step 5:

[1646] Intention inference by the server:

[1647] The server infers the user's intention based on the received text data and emotional data. The input data is the emotional state and text data, and the output data is the user's intention (e.g., "I want to order sushi"). The server uses natural language processing technology and inference algorithms.

[1648] Step 6:

[1649] Generate operating instructions:

[1650] The server generates adaptive operation instructions based on the user's intention and emotional state. The input data is the inferred user's intention and emotional state, and the output data is the specific operation instructions (e.g., "First, open the app and tap the sushi category"). The server then uses a generative AI model to create an appropriate prompt.

[1651] Step 7:

[1652] Sending instructions:

[1653] The server sends the generated operation procedure to the terminal. The input data is the generated operation procedure, and the output data is the operation procedure received by the terminal. Data communication technology is used.

[1654] Step 8:

[1655] Voice guidance for operation procedures:

[1656] The device uses a voice assistant to provide guidance to the user based on the received operating instructions. The input data is the operating instructions, and the output data is voice guidance to the user. Speech synthesis technology is used to audibly convey specific operating procedures to the user.

[1657] Step 9:

[1658] User interaction and feedback:

[1659] The user follows the voice guidance to perform the operation. The device again uses the emotion engine to monitor the user's emotional state and provides positive feedback if the operation is successful. The input data is the user's operation result and new emotional data, and the output data is positive feedback. This allows the user to gain confidence in their operation and use the app with peace of mind.

[1660] 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.

[1661] 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.

[1662] 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.

[1663] 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.

[1664] 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.

[1665] 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.

[1666] 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).

[1667] 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.

[1668] 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."

[1669] 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.

[1670] 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).

[1671] 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.

[1672] 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.

[1673] 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.

[1674] 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.

[1675] 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.

[1676] 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.

[1677] 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.

[1678] 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.

[1679] 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.

[1680] 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.

[1681] The following is further disclosed regarding the above embodiment.

[1682] (Claim 1)

[1683] means for acquiring audio data;

[1684] A means for converting the acquired voice data into text data;

[1685] means for analyzing character data and inferring user intent;

[1686] means for generating an operating procedure based on the inference result;

[1687] means for guiding the generated operation procedure to a user;

[1688] A system including:

[1689] (Claim 2)

[1690] 2. The system according to claim 1, wherein image data and video data are used as the analysis target.

[1691] (Claim 3)

[1692] 10. The system of claim 1, further comprising means for providing audio prompts to the user.

[1693] "Example 1"

[1694] (Claim 1)

[1695] means for acquiring audio data;

[1696] A means for converting the acquired voice data into text data;

[1697] means for analyzing character data and inferring user intent;

[1698] means for generating an operating procedure based on the inference result;

[1699] means for providing the generated operating procedure to a user;

[1700] A means for analyzing a user's intention and generating and providing an operation procedure by the terminal and the server operating in cooperation with each other;

[1701] A system including:

[1702] (Claim 2)

[1703] 2. The system according to claim 1, wherein image data and video data are used as the analysis target.

[1704] (Claim 3)

[1705] 10. The system of claim 1, further comprising means for providing audio prompts.

[1706] "Application Example 1"

[1707] (Claim 1)

[1708] means for acquiring audio data;

[1709] A means for converting the acquired voice data into text data;

[1710] means for analyzing character data and inferring user intent;

[1711] means for generating an operating procedure based on the inference result;

[1712] means for guiding the generated operation procedure to a user;

[1713] means for providing audio prompts and displaying visual guidance for operating the industrial automation device based on the user's intentions;

[1714] A system including:

[1715] (Claim 2)

[1716] 2. The system according to claim 1, wherein image data and video data are used as the analysis target.

[1717] (Claim 3)

[1718] 10. The system of claim 1, further comprising means for providing audio prompts to the user.

[1719] (Claim 4)

[1720] 10. The system of claim 1, for generating and guiding maintenance procedures for industrial automation equipment.

[1721] "Example 2: Combining Emotion Engines"

[1722] (Claim 1)

[1723] means for acquiring user voice data;

[1724] A means for converting the acquired voice data into text data;

[1725] means for acquiring image data and video data using a camera;

[1726] means for analyzing the acquired voice data and image data to recognize the emotional state of the user;

[1727] means for inferring a user's intention based on the analysis of the voice data and the emotional state;

[1728] a means for generating an operation procedure based on the inference result and the emotion information;

[1729] means for providing the generated operation procedure to a user as voice guidance;

[1730] means for re-monitoring the user's emotional state during operation and adjusting the guidance content as necessary;

[1731] A system including:

[1732] (Claim 2)

[1733] 2. The system according to claim 1, further comprising means for using image data and video data as the subject of analysis and providing audio guidance.

[1734] (Claim 3)

[1735] 10. The system of claim 1, further comprising means for monitoring a user's emotional state during operation and providing feedback.

[1736] "Application example 2 when combining emotion engines"

[1737] (Claim 1)

[1738] means for acquiring audio data;

[1739] A means for converting the acquired voice data into text data;

[1740] means for analyzing character data and inferring user intent;

[1741] means for generating an operating procedure based on the inference result;

[1742] means for guiding the generated operation procedure to a user;

[1743] a means for adaptively responding using an emotion engine that analyzes the user's emotional state;

[1744] A system including:

[1745] (Claim 2)

[1746] 2. The system according to claim 1, wherein image data and video data are used as the analysis target.

[1747] (Claim 3)

[1748] 10. The system of claim 1, further comprising means for providing audio prompts to the user.

[1749] (Claim 4)

[1750] 10. The system of claim 1, further comprising means for adjusting the level of detail of the operating instructions based on the emotional state of the user.

[1751] (Claim 5)

[1752] 10. The system of claim 1, further comprising means for providing positive feedback to the user upon successful operation.

[1753] (Claim 6)

[1754] 2. The system of claim 1, further comprising means for transmitting the analysis results to a server, the server generating a response based on the inference results.

[1755] (Claim 7)

[1756] The system of claim 1, further comprising means for generating and guiding operating procedures based on the user's intentions and emotions using a generative AI model and prompt sentences. [Explanation of symbols]

[1757] 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. means for acquiring audio data; A means for converting the acquired voice data into text data; means for analyzing character data and inferring user intent; means for generating an operating procedure based on the inference result; means for guiding the generated operation procedure to a user; A system including:

2. 2. The system according to claim 1, wherein image data and video data are used as the analysis target.

3. 10. The system of claim 1, further comprising means for providing audio prompts to the user.

Images