system

Abstract

We provide the system. [Solution] A means of receiving voice input from a communication terminal available to the user and converting it into digital data, A means for analyzing the digital data and converting it into text data, A means for analyzing the text data using natural language processing to identify the user's intent, A means of authenticating a user using voice pattern recognition and a passphrase, A means to prevent duplicate actions by referring to the user's past action history, A means of detecting fraud risks and issuing warnings to users and their associates, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] With the progress of an aging society, the hurdles for the elderly to use digital technology have become apparent. In particular, it is difficult to access information in online shopping, life consultation, and health management, and there are concerns about the risks of duplicate orders and fraud due to incorrect operations. Therefore, there is a need for an interface that allows the elderly and information disadvantaged to safely and routinely use digital services and its operation method.

Means for Solving the Problems

[0005] This invention proposes a system that leverages the operability of classic communication devices while utilizing speech recognition technology and generative artificial intelligence to provide users with intuitive voice interaction. Specifically, it converts the user's voice into digital data and analyzes it to generate natural text dialogue. Furthermore, it implements strict user authentication using voice pattern recognition and passphrases, prevents duplicate orders by referring to past action history, and detects and warns of fraud risks, thereby enabling users to use the service safely.

[0006] A "communication terminal" refers to a device used by a user to send and receive voice and data.

[0007] "Voice input" refers to the process of capturing voice signals emitted by a user as digital data.

[0008] "Digital data" refers to audio, which is an analog signal, converted into a format that is easy to process electronically.

[0009] "Text data" refers to data obtained by converting analyzed speech input into text format.

[0010] "Natural language processing" refers to the technology that enables computers to understand human language and interpret its meaning.

[0011] "Speech pattern recognition" refers to a technology that analyzes the characteristics of speech signals to identify a specific speaker.

[0012] A "passphrase" refers to a security measure used to authenticate users by using a specific phrase.

[0013] "Authentication" refers to the process by which the system verifies the user's legitimacy and grants access.

[0014] "Action history" refers to a record of operations and activities that a user has performed within the system in the past.

[0015] "Fraud risk" refers to the possibility that a user may suffer damage due to illegal acts or unreliable information sources.

Brief Explanation of Drawings

[0016] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when combined with an emotion engine.

Embodiments for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0020] In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, a labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] As shown in Figure 1, the 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.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0030] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] This invention is a system that utilizes voice interaction via a user-friendly communication terminal, aiming to enable the elderly and those with limited access to information to easily utilize digital services. This system primarily includes functions for voice recognition, natural language processing, user authentication, history management, and fraud prevention.

[0038] The user provides voice input through a communication terminal. The terminal converts the user's voice into digital data and sends it to the server. The server converts the received voice into text data and analyzes the user's intent using natural language processing technology. Based on this analysis, the server generates an appropriate response and prepares to reply to the user.

[0039] For user authentication, the server utilizes voice pattern recognition technology and a passphrase to verify the user's identity based on their voice characteristics. After authentication is complete, the server checks the user's past action history to ensure there are no duplicate orders or inquiries. If necessary, the server asks the user confirmation questions.

[0040] Furthermore, the server continuously monitors communications and immediately warns users and registered parties if it detects a risk of fraud. This allows users to use digital services necessary for their daily lives with peace of mind.

[0041] As a concrete example, consider the case where a user wishes to order a product. When the user enters "I want to order a new supplement," the server checks the user's past order history to ensure there are no duplicates and then confirms with the user. This process prevents the user from repeatedly placing incorrect orders. Through this series of processes, the user can purchase products smoothly and safely through the system.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] The user gives voice commands to the communication terminal. For example, they might say, "I want to order supplements."

[0045] Step 2:

[0046] The device converts the user's voice into digital data. This converted digital data is then transmitted to a server via the network.

[0047] Step 3:

[0048] The server converts the received audio data into text data through a speech recognition process. This text data is then analyzed by a natural language processing module.

[0049] Step 4:

[0050] The server identifies the user's intent from the parsed text data. In this case, it understands the instruction, "I want to order supplements."

[0051] Step 5:

[0052] The server authenticates the user's identity using voice pattern recognition technology and a registered passphrase. If authentication is successful, the process proceeds to the next step.

[0053] Step 6:

[0054] The server retrieves the user's past order history from the database and compares it with the current instructions to check for duplicate orders.

[0055] Step 7:

[0056] If duplicates are detected, the server will generate an additional voice prompt to ask the user for confirmation.

[0057] Step 8:

[0058] After the user confirms, the server officially accepts the order and processes the order details. This includes checking the availability of the required items and arranging shipping.

[0059] Step 9:

[0060] The server constantly monitors the security of transactions, issues warnings if fraud is suspected, and sends notifications to pre-registered family members as needed.

[0061] Step 10:

[0062] As a final response, the terminal will notify the user of the order confirmation and the necessary next steps.

[0063] Therefore, users can securely place product orders through the system.

[0064] (Example 1)

[0065] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0066] This invention seeks to enable safe and easy access to digital services for the elderly and those with limited digital literacy, while reducing their anxiety about complex digital operations and fraud. Voice-based interfaces, in particular, are attracting attention as a means of achieving intuitive and natural communication, but unresolved issues remain regarding related authentication, fraud prevention, and order management.

[0067] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0068] In this invention, the server includes means for converting and analyzing voice data from the user into digital information, means for identifying the user's intent through natural language processing, and means for authenticating the user using voice recognition technology and a password. This enables users to safely and efficiently utilize digital services through natural voice interaction.

[0069] "Electronic device" refers to a device used by a user to input voice data, and includes devices such as smartphones and tablets.

[0070] "Digital information" refers to an electrical data format obtained as a result of processing analog audio data using electronic methods.

[0071] "Text information" refers to information in written form that is generated after audio data has been analyzed, and it expresses the user's intent in a way that is easier to understand.

[0072] "Language analysis technology" refers to a series of techniques used to understand user intent and emotions from text information, and it utilizes natural language processing methods.

[0073] "Voice recognition technology" is a technology used to identify or authenticate individuals using their voice, and it verifies the matching of voice characteristics.

[0074] A "password" is a string of characters that a user has set in advance as part of the authentication process, and it serves as an additional security measure for verifying the user's identity.

[0075] "Fraudulent activity" refers to actions that are inappropriate and contrary to the user's intentions, or actions that involve the risk of damaging the user's information or services through fraudulent means.

[0076] A "generative AI model" is an artificial intelligence model used to dynamically generate responses to user inquiries, and is a technology that automatically generates prompt text.

[0077] This invention provides a system that allows users to easily operate digital services using their voice. Users access the system by voice through electronic devices such as smartphones and tablets. When a user inputs voice into the device, the terminal converts that voice into digital information. Various technologies can be used for voice recognition, but for example, the conversion is performed through a voice recognition API.

[0078] This digital information is transmitted to a server via the network. The server processes the received digital information and converts it into text information. This makes the information obtained from the speech easier to analyze. The server is equipped with natural language processing software that utilizes language analysis technology to analyze the user's intent and identify the necessary actions. For example, a language analysis library is used as the software for this analysis.

[0079] The server also verifies the user's identity using voice recognition technology and a password. The voice recognition technology utilizes specific voice recognition software, which authenticates the user based on the characteristics of their voice. After authentication is complete, the server reviews the user's past activity history to check for duplicate actions. This helps prevent unintentional duplicate orders.

[0080] When the user provides new instructions, the server uses an AI model to generate prompts and ask questions or confirmations to the user. For example, it might ask, "You ordered this product before, would you like to order it again?" By utilizing dynamically generated prompts based on user input in this way, the interaction proceeds more smoothly.

[0081] The server also has a function to immediately warn the user and their associates when it detects fraudulent activity. This allows users to use digital services with peace of mind. Through this system, users are provided with an environment in which they can intuitively and safely use digital services on a daily basis.

[0082] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0083] Step 1:

[0084] The user speaks instructions into the microphone of the communication terminal. The input at this time is the user's voice. The terminal uses the microphone to capture the audio data and converts the analog audio signal into digital information. The output at this stage is audio data in digital format.

[0085] Step 2:

[0086] The terminal transmits digital audio data to the server via the network. The server receives this digital audio data. The server uses speech recognition software to convert the audio data into text information. The input is digital audio data, and the output is text information converted from the audio.

[0087] Step 3:

[0088] The server passes the converted text information to a natural language processing unit, which analyzes the user's intent. This process involves syntactically analyzing the text data and extracting keywords and phrases to understand the user's request. The input is text information, and the output is data related to the user's intent.

[0089] Step 4:

[0090] The server uses a voice authentication system to verify the user's identity. Input consists of the user's voice characteristics and a pre-set password, while output indicates the authentication success or failure status. Voice identification technology compares the voice data with registered information; authentication is complete if they match.

[0091] Step 5:

[0092] The server references the user's past behavior history to check for any actions that overlap with the newly received intent. The input for this step is the user's intent data, and the output is the result of the duplicate check. This prevents orders that duplicate past actions.

[0093] Step 6:

[0094] If necessary, the server uses a generative AI model to generate a prompt message that asks the user for confirmation. The input is the user's intent and past history information, and the output is the prompt message. For example, a prompt message such as "You have ordered this product before, would you like to order it again?" might be generated.

[0095] Step 7:

[0096] The server monitors communications to detect fraudulent activity. If a fraud risk is detected, the input is the detected suspicious pattern, and the output is a warning message to the user and their associates. Fraud detection algorithms are used to provide real-time notifications.

[0097] Step 8:

[0098] Finally, the server generates a response to the user and sends it to the terminal. The input is the confirmed user intent or the generated prompt, and the output is returned to the terminal as a voice response. The terminal synthesizes this into speech and sends it back to the user, completing the process.

[0099] (Application Example 1)

[0100] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0101] In modern society, elderly people and users unfamiliar with digital technology face the problem of complex operation when using online services. Furthermore, mechanisms to prevent fraud and erroneous orders are insufficient, creating a need for systems that these users can use with peace of mind. Additionally, there is a need for methods that allow for easy order confirmation and completion of orders solely through voice commands.

[0102] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0103] In this invention, the server includes means for receiving voice input from an information processing device available to the user and converting it into digital information, means for selecting products based on voice commands and confirming order details by voice, and means for detecting fraud risks and issuing warnings to the user and related parties. This enables simple and secure online ordering using voice.

[0104] An "information processing device" is a device that receives information as input and generates output by performing various calculations.

[0105] "Voice input" is a method of inputting instructions or information using the user's own voice.

[0106] "Digital information" refers to data that is processed by a computer and represented as an array of bits.

[0107] "Encoded information" refers to data that has been converted from natural language or speech and encoded into an analyzable format.

[0108] "Natural language processing" is a technology that enables computers to understand human language and analyze its meaning.

[0109] "Voice characteristic recognition" is a technology that detects unique features contained in a voice signal to identify an individual.

[0110] A "password" is a secret word or phrase used to grant authentication or access under specific conditions.

[0111] "Activity history" refers to information that stores a record of a user's past actions and operations.

[0112] "Fraud risk" refers to a situation in which there is a possibility of suffering financial or informational damage due to malicious acts.

[0113] A "warning" is a notification or signal that indicates the possibility of danger or a problem occurring.

[0114] "Voice commands" refer to instructions or commands that a user gives to a device using their voice.

[0115] "Order details" refer to information about the products or services that the user wishes to purchase or acquire.

[0116] The system implementing this invention is based on the user performing voice input from an information processing device, such as a smartphone. The voice input data is converted into digital information using the Google® Speech-to-Text API. This digital information is transferred to a server and converted into encoded information using natural language processing technology. It is preferable to use the Python NLTK library for natural language processing. The server analyzes this encoded information and identifies the user's purpose.

[0117] The server verifies and authenticates the user using voice characteristic recognition and a password. Voice authentication technologies such as Amazon Rekognition can be used as the authentication method, identifying the user from the voice data. In this process, the use of encryption technology is recommended to ensure the protection of the user's personal information.

[0118] The server also has a function to prevent duplicate actions by referring to the user's activity history. For example, it can detect duplicate orders for the same product on different dates and, if necessary, prompt the user with a voice confirmation. In addition, it applies anomaly detection algorithms such as Isolation Forest to detect fraud risks and warn of fraudulent activity in advance.

[0119] For order processing, users can select products based on voice commands and confirm their order details by voice. The system uses the Google Text-to-Speech API to provide voice feedback to the user.

[0120] For example, if a user says, "I want to order a recently popular health supplement," the system analyzes this request, retrieves a list of currently popular health supplements, and verbally communicates the options to the user. Once the order is confirmed, the server completes the transaction.

[0121] Examples of prompts for a generative AI model are as follows:

[0122] "A 50-year-old user is trying to order a new health supplement using voice input. Please provide voice guidance to the user at each step of the ordering process."

[0123] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0124] Step 1:

[0125] The user performs voice input through the device.

[0126] The input is the user's voice, which the device passes to the Google Speech-to-Text API. The API converts the voice into text data. This process makes the voice data available for transmission to the server as text data.

[0127] Step 2:

[0128] The server receives text data and performs natural language processing.

[0129] The input is text data, and the server uses Python's NLTK library for natural language processing. It analyzes the meaning and intent of the text and identifies corresponding instructions and inquiries. This process encapsulates the user's requests and prepares them for the next steps.

[0130] Step 3:

[0131] The server performs user authentication.

[0132] The input is the user's voice characteristics information. The server uses voice authentication technology such as Amazon Rekognition to detect the voice characteristics and compare them with a password. This prevents misrecognition and impersonation, and verifies the user's legitimacy.

[0133] Step 4:

[0134] The server checks the user's activity history to prevent duplicate orders.

[0135] The input consists of past order data, and the server compares it to the current request by referring to the database. If duplicates exist, such as orders for the same product on different dates, the server issues a warning. This process helps prevent incorrect orders.

[0136] Step 5:

[0137] The server processes orders based on voice commands.

[0138] The input is parsed text data that includes the user's intent. The server uses this to search for products in the product database and proceed with the order process. The selected products are provided to the user via voice feedback using the Google Text-to-Speech API. The user confirms the selection, and the final order is confirmed.

[0139] Step 6:

[0140] The server detects fraud risks and issues warnings if necessary.

[0141] The input is all transaction data for an anomaly detection algorithm, and the server applies Isolation Forest and other tools to assess the likelihood of fraud. If suspicious activity is detected, the server sends an alert to the user and their associates for further verification.

[0142] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0143] This invention provides a more user-friendly and secure environment by incorporating emotion recognition capabilities into a system that uses classic communication equipment to support the elderly and those who are digitally vulnerable. This system integrates an emotion engine in addition to voice recognition, natural language processing, identity verification, history management, and fraud prevention functions.

[0144] When a user gives a voice command through a communication terminal, the terminal converts the voice into digital data and sends it to the server. The server converts the voice data into text data and uses natural language processing to analyze the user's intent. In addition, an emotion engine identifies the user's emotions based on the characteristics of the voice. This information is used to dynamically adjust the content of the dialogue.

[0145] User authentication is performed using voice pattern recognition and a passphrase. If authentication is successful, the system checks for duplicate actions by referring to the user's past action history. The server constantly monitors for potential fraud and has a mechanism in place to immediately warn the user and their associates if a risk is detected.

[0146] For example, if a user expresses concern about a delayed delivery, the server uses an emotion engine to recognize the expression of anxiety and, in addition to providing a regular delivery status check, offers detailed explanations and solutions to alleviate reassurance. This allows the user to address the problem with emotional reassurance.

[0147] This system aims to provide users with a more comfortable user experience by enabling personalized responses that take emotions into consideration. Furthermore, by monitoring changes in the user's emotions and automatically notifying relevant parties as needed, it reduces the risks that elderly individuals may encounter in their daily lives.

[0148] The following describes the processing flow.

[0149] Step 1:

[0150] The user gives voice commands to the communication device. For example, they might say, "I want to order supplements."

[0151] Step 2:

[0152] The terminal captures the user's voice signal, converts it into digital data, and then sends it to the server.

[0153] Step 3:

[0154] The server converts the received audio data into text data using a speech recognition system. This text data is then passed to a natural language processing module.

[0155] Step 4:

[0156] The server analyzes text data using natural language processing to identify the user's intent. In this case, it understands the intent to "order supplements."

[0157] Step 5:

[0158] The server also uses an emotion engine to analyze the user's voice and identify emotional states such as feelings of security or anxiety.

[0159] Step 6:

[0160] The server performs authentication using voice pattern recognition and a registered passphrase, and if authentication is successful, it prepares to process the user's request.

[0161] Step 7:

[0162] The server retrieves past order history from the database and checks if there are any duplicate new orders.

[0163] Step 8:

[0164] If a duplicate order is found, or if the server determines that the user's emotional state is unstable, it will generate a response that reflects this. For example, it might suggest, "Would you like to place the same order as last time?" or "Please wait while we check the delivery status in detail."

[0165] Step 9:

[0166] The server assesses fraud risk as needed, issues a warning if fraud is suspected, and automatically notifies registered parties.

[0167] Step 10:

[0168] Once the process is complete, the user will be notified of the results via their device. This notification will include information to reassure the user and explanations of the necessary next steps.

[0169] This process allows users to receive a fast and safe service that is sensitive to their emotions.

[0170] (Example 2)

[0171] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0172] For the elderly and those with limited access to information, there is a need for a system that can establish a simple and secure communication environment through voice, while also providing the flexibility to respond to emotional needs. Existing technologies lack comprehensive integration of emotion recognition, identity verification, and fraud prevention, making it difficult to achieve both usability and security.

[0173] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0174] In this invention, the server includes means for receiving voice input from a communication device available to the user and converting it into numerical data, means for analyzing the numerical data and converting it into character data, and means for analyzing the character data by language processing and identifying the user's intent. This makes it intuitively usable even for the elderly and those with limited access to information, and also enables responses that take emotions into consideration.

[0175] A "communication device" is a device used by a user to input voice data and has the function of sending and receiving information with a server via a communication network.

[0176] "Numerical data" refers to data obtained by converting audio signals into a digital format, and is used for audio analysis.

[0177] "Character data" refers to text-formatted data obtained by analyzing numerical data, and is used in natural language processing.

[0178] "Language processing" is a technology that analyzes user intent based on text data, and includes natural language understanding.

[0179] "Identity verification" is the process of verifying a user's identity using voice patterns or passwords.

[0180] "Operation history" refers to a record of actions a user has taken in the past, which is managed by the system.

[0181] "Fraudulent activity risk" refers to unauthorized operations or fraud that may occur within the system, and is the target of monitoring to detect them.

[0182] "Emotional characteristics" refer to information about the user's emotional state, as determined from factors such as tone and rhythm of voice.

[0183] "Dynamic adjustment of dialogue" is the process of adapting the system's response based on the user's emotions and intentions.

[0184] This invention is a system that enables safe and user-friendly communication for the elderly and those with limited access to information. Specifically, it aims to analyze the user's intentions and emotions from voice input and provide appropriate responses. The following details each component and its operation.

[0185] The terminal receives voice input from the user. In this process, a microphone is used to convert the voice into numerical data, which is then transmitted to a server via a communication network. This conversion is performed using commonly available speech recognition software.

[0186] The server converts the numerical data of the received speech into text data and then uses a natural language processing engine to analyze the user's intent. For this purpose, it utilizes general language processing tools. During this process, an emotion recognition engine analyzes the characteristics of the speech and identifies the user's emotions. Based on this, the server dynamically adjusts its dialogue to provide a response that aligns with the user's emotions.

[0187] For example, if a user expresses anxiety such as "I'm worried because my delivery is delayed," the server will sense this anxiety through emotion recognition. As a result, it will respond in a way that is appropriate to the user's emotions by providing detailed information about the delivery status or sending reassuring messages.

[0188] An example of a prompt message to input into the generating AI model is: "Audio data has been received. The user appears worried. Please check the delivery status and provide reassuring information."

[0189] This invention will realize a safe and emotionally considerate communication system that can be used intuitively by the elderly and those with limited access to information.

[0190] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0191] Step 1:

[0192] The terminal receives voice input from the user. Specifically, the terminal uses a microphone to convert the voice from analog to digital numerical data. The input is an audio signal, and the output is digital numerical data. This data is sent to the server via the communication network for further processing.

[0193] Step 2:

[0194] The server converts received numerical data into character data. This is a process using speech recognition software, where the input is numerical data and the output is character data. Specifically, the server analyzes the numerical data and converts the speech patterns into corresponding strings.

[0195] Step 3:

[0196] The server analyzes text data using a natural language processing engine. The input is text data, and the output is identification data that indicates the user's intent. Specifically, the server performs grammatical analysis and semantic interpretation to identify the intent behind the user's requests and questions.

[0197] Step 4:

[0198] The server uses an emotion recognition engine to identify the user's emotions. Input is data including text data and voice characteristics, and output is data indicating the emotional state. Specifically, the server analyzes the tone and speed of the voice to determine what emotional state the user is in.

[0199] Step 5:

[0200] The server verifies the user's identity and checks the operation history. In this step, a voice pattern and a password are used as input, and the output is the authentication result. Specifically, the server compares the registered pattern with the input and refers to the operation history to detect duplicates and fraudulent activity.

[0201] Step 6:

[0202] The server generates an appropriate response considering the user's emotions and intentions and sends it to the terminal. The input is emotional state and identification data, and the output is a tailored response message. Specifically, the server creates a dialogue message adapted to the user's state and adds contextually relevant information using a generative AI model.

[0203] Step 7:

[0204] The terminal provides the user with received responses via audio or text display. Input is the response message from the server, and output is in a user-understandable format. Specifically, the terminal uses speakers and displays to convey information and support user accessibility.

[0205] (Application Example 2)

[0206] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0207] In brick-and-mortar retail settings, customer service requires flexible and appropriate responses that respond to customer emotions. However, current systems make it difficult to analyze emotions in real time and adjust service accordingly. Furthermore, detailed support for the elderly and those with limited access to information is insufficient. Therefore, a system that comprehensively addresses these issues is necessary.

[0208] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0209] In this invention, the server includes means for receiving voice input from an information terminal available to the user and converting it into digital data, means for analyzing the digital data and converting it into text data, and means for analyzing the emotions in the voice and providing optimal information in accordance with the customer's emotions. This makes it possible to grasp the customer's emotions in real time during customer service operations in physical stores and to provide appropriate information and customer service accordingly.

[0210] An "information terminal" is a device that receives voice input from a user and converts it into digital data.

[0211] "Digital data" refers to a data format converted from analog signals, which can be processed and analyzed by computers.

[0212] "Character data" refers to text-based data generated from digital data through natural language processing.

[0213] "Natural language processing" is a technology that enables computers to understand and analyze human language, allowing them to identify the user's intent.

[0214] "Voice pattern recognition" is a technology that analyzes the characteristics of speech to identify its source, and is used for identity verification.

[0215] A "password" is an encrypted phrase used for user authentication.

[0216] "Action history" refers to a record of actions a user has taken in the past, and is used to prevent future actions from being duplicated.

[0217] "Fraudulent activity" refers to any action or attempt that may deceive or maliciously harm a user.

[0218] "Emotion analysis" is a technology that infers a user's emotional state from their voice or text.

[0219] "Information provision" refers to the act of providing users with the data and explanations they need, tailored to their specific circumstances.

[0220] This invention is a system that highly supports customer service in physical stores. The user wears smart glasses and uses them as an information terminal to receive voice input. The terminal converts the voice spoken by the user into digital data, and this data is sent to a cloud server. The server uses the Google Cloud Speech-to-Text API to convert the digital data into text data.

[0221] The server then uses IBM Watson® natural language understanding services on the converted text data to analyze the user's intent and emotions. This analysis visualizes the emotions in the speech, enabling the provision of appropriate information. For example, if a customer says, "I'm worried about whether this product is easy to use," the server identifies the emotion of anxiety and, based on that, displays usage examples and detailed explanations on the smart glasses' display.

[0222] In this way, sales staff can receive optimal information tailored to the customer's real-time emotional state, enabling more effective customer service. Examples of specific prompt messages include the following:

[0223] Audio data: The customer said, "I'm worried about the usability of a particular product."

[0224] Emotional analysis: Anxiety and identification.

[0225] Recommendation: Display video tutorials on how to use the product on the smart glasses display to provide reassuring information.

[0226] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0227] Step 1:

[0228] The user collects customer voices through smart glasses. The voice input is converted into digital data using the device's microphone. This digital data is sent directly to the cloud server without any editing.

[0229] Step 2:

[0230] The server converts received digital data into text data using the Google Cloud Speech-to-Text API. It receives digital audio data as input and converts it to text using a speech recognition algorithm. The output is text data that accurately represents the audio content.

[0231] Step 3:

[0232] The server analyzes the converted character data using IBM Watson's natural language understanding service. Here, natural language processing is performed using the character data as input to identify the user's intent and emotions. The output generates data representing the identified intent and emotions.

[0233] Step 4:

[0234] The server generates information tailored to the customer's state based on intent and emotion data. It utilizes a generative AI model to create prompts that meet customer needs. For example, if anxiety is detected, it generates information including specific explanations and product usage examples to provide reassurance.

[0235] Step 5:

[0236] The server displays the generated information on the user's smart glasses display. This allows the terminal to receive information from the server as input, display appropriate information on the display based on that input, and create a situation where the user can provide the best possible service to the customer.

[0237] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0238] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0239] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0240] [Second Embodiment]

[0241] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0242] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0243] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0244] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0245] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0246] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0247] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0248] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0249] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0250] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0251] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0252] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0253] This invention is a system that utilizes voice interaction via a user-friendly communication terminal, aiming to enable the elderly and those with limited access to information to easily utilize digital services. This system primarily includes functions for voice recognition, natural language processing, user authentication, history management, and fraud prevention.

[0254] The user provides voice input through a communication terminal. The terminal converts the user's voice into digital data and sends it to the server. The server converts the received voice into text data and analyzes the user's intent using natural language processing technology. Based on this analysis, the server generates an appropriate response and prepares to reply to the user.

[0255] For user authentication, the server utilizes voice pattern recognition technology and a passphrase to verify the user's identity based on their voice characteristics. After authentication is complete, the server checks the user's past action history to ensure there are no duplicate orders or inquiries. If necessary, the server asks the user confirmation questions.

[0256] Furthermore, the server continuously monitors communications and immediately warns users and registered parties if it detects a risk of fraud. This allows users to use digital services necessary for their daily lives with peace of mind.

[0257] As a concrete example, consider the case where a user wishes to order a product. When the user enters "I want to order a new supplement," the server checks the user's past order history to ensure there are no duplicates and then confirms with the user. This process prevents the user from repeatedly placing incorrect orders. Through this series of processes, the user can purchase products smoothly and safely through the system.

[0258] The following describes the processing flow.

[0259] Step 1:

[0260] The user gives voice commands to the communication terminal. For example, they might say, "I want to order supplements."

[0261] Step 2:

[0262] The device converts the user's voice into digital data. This converted digital data is then transmitted to a server via the network.

[0263] Step 3:

[0264] The server converts the received audio data into text data through a speech recognition process. This text data is then analyzed by a natural language processing module.

[0265] Step 4:

[0266] The server identifies the user's intent from the parsed text data. In this case, it understands the instruction, "I want to order supplements."

[0267] Step 5:

[0268] The server authenticates the user's identity using voice pattern recognition technology and a registered passphrase. If authentication is successful, the process proceeds to the next step.

[0269] Step 6:

[0270] The server retrieves the user's past order history from the database and compares it with the current instructions to check for duplicate orders.

[0271] Step 7:

[0272] If duplicates are detected, the server will generate an additional voice prompt to ask the user for confirmation.

[0273] Step 8:

[0274] After the user confirms, the server officially accepts the order and processes the order details. This includes checking the availability of the required items and arranging shipping.

[0275] Step 9:

[0276] The server constantly monitors the security of transactions, issues warnings if fraud is suspected, and sends notifications to pre-registered family members as needed.

[0277] Step 10:

[0278] As a final response, the terminal will notify the user of the order confirmation and the necessary next steps.

[0279] As described above, users can safely place product orders through the system.

[0280] (Example 1)

[0281] Next, Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[0282] In the present invention, it is required to be able to use digital services safely and easily while reducing difficult digital operations for the elderly and those with poor information skills and anxiety about fraud victimization. In particular, an interface based on voice interaction has attracted attention as a means to realize intuitive and natural communication, but there are still unresolved issues regarding authentication, fraud prevention, and order management related to this.

[0283] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0284] In this invention, the server includes means for converting and analyzing voice data from a user into digital information, means for identifying the user's intention by natural language processing, and means for performing personal authentication using voice recognition technology and a passphrase. As a result, users can utilize digital services safely and efficiently through natural voice interaction.

[0285] An "electronic device" refers to a device used by a user to input voice data and includes devices such as smartphones and tablets.

[0286] "Digital information" refers to an electrical data format obtained as a result of processing analog voice data by electronic means.

[0287] "Text information" is the written form of information generated after voice data is analyzed and expresses the user's intention in a more understandable form.

[0288] "Language analysis technology" refers to a series of techniques used to understand user intent and emotions from text information, and it utilizes natural language processing methods.

[0289] "Voice recognition technology" is a technology used to identify or authenticate individuals using their voice, and it verifies the matching of voice characteristics.

[0290] A "password" is a string of characters that a user has set in advance as part of the authentication process, and it serves as an additional security measure for verifying the user's identity.

[0291] "Fraudulent activity" refers to actions that are inappropriate and contrary to the user's intentions, or actions that involve the risk of damaging the user's information or services through fraudulent means.

[0292] A "generative AI model" is an artificial intelligence model used to dynamically generate responses to user inquiries, and is a technology that automatically generates prompt text.

[0293] This invention provides a system that allows users to easily operate digital services using their voice. Users access the system by voice through electronic devices such as smartphones and tablets. When a user inputs voice into the device, the terminal converts that voice into digital information. Various technologies can be used for voice recognition, but for example, the conversion is performed through a voice recognition API.

[0294] This digital information is transmitted to a server via the network. The server processes the received digital information and converts it into text information. This makes the information obtained from the speech easier to analyze. The server is equipped with natural language processing software that utilizes language analysis technology to analyze the user's intent and identify the necessary actions. For example, a language analysis library is used as the software for this analysis.

[0295] The server also verifies the user's identity using voice recognition technology and a password. The voice recognition technology utilizes specific voice recognition software, which authenticates the user based on the characteristics of their voice. After authentication is complete, the server reviews the user's past activity history to check for duplicate actions. This helps prevent unintentional duplicate orders.

[0296] When the user provides new instructions, the server uses an AI model to generate prompts and ask questions or confirmations to the user. For example, it might ask, "You ordered this product before, would you like to order it again?" By utilizing dynamically generated prompts based on user input in this way, the interaction proceeds more smoothly.

[0297] The server also has a function to immediately warn the user and their associates when it detects fraudulent activity. This allows users to use digital services with peace of mind. Through this system, users are provided with an environment in which they can intuitively and safely use digital services on a daily basis.

[0298] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0299] Step 1:

[0300] The user speaks instructions into the microphone of the communication terminal. The input at this time is the user's voice. The terminal uses the microphone to capture the audio data and converts the analog audio signal into digital information. The output at this stage is audio data in digital format.

[0301] Step 2:

[0302] The terminal sends digital voice data to the server via the network. The server receives this digital voice data. The server uses speech recognition software to convert the voice data into text information. The input is digital voice data, and the output is the text information converted from the voice.

[0303] Step 3:

[0304] The server passes the converted text information to the natural language processing unit to analyze the user's intention. In this process, by parsing the text data and extracting keywords and phrases, the user's request is grasped. The input is text information, and the output is data related to the user's intention.

[0305] Step 4:

[0306] The server uses the voice authentication system to verify the user's identity. The input is the characteristics of the user's voice and the set passphrase, and the output is the status of authentication success or failure. Through voice recognition technology, the voice data is compared with the registered information, and the authentication is completed when they match.

[0307] Step 5:

[0308] The server refers to the user's past behavior history to check if there are any actions that overlap with the newly received intention. The input for this step is the user's intention data, and the output is the result of the duplicate check. This prevents duplicate orders with past actions.

[0309] Step 6:

[0310] If necessary, the server uses the generative AI model to generate a prompt sentence to ask the user for confirmation. The input is the user's intention and past history information, and the output is the prompt sentence. For example, a prompt sentence such as "You ordered this product before. Do you want to reorder?" is generated.

[0311] Step 7:

[0312] The server monitors communications to detect fraudulent activity. If a fraud risk is detected, the input is the detected suspicious pattern, and the output is a warning message to the user and their associates. Fraud detection algorithms are used to provide real-time notifications.

[0313] Step 8:

[0314] Finally, the server generates a response to the user and sends it to the terminal. The input is the confirmed user intent or the generated prompt, and the output is returned to the terminal as a voice response. The terminal synthesizes this into speech and sends it back to the user, completing the process.

[0315] (Application Example 1)

[0316] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0317] In modern society, elderly people and users unfamiliar with digital technology face the problem of complex operation when using online services. Furthermore, mechanisms to prevent fraud and erroneous orders are insufficient, creating a need for systems that these users can use with peace of mind. Additionally, there is a need for methods that allow for easy order confirmation and completion of orders solely through voice commands.

[0318] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0319] In this invention, the server includes means for receiving voice input from an information processing device available to the user and converting it into digital information, means for selecting products based on voice commands and confirming order details by voice, and means for detecting fraud risks and issuing warnings to the user and related parties. This enables simple and secure online ordering using voice.

[0320] An "information processing device" is a device that receives information as input and generates output by performing various calculations.

[0321] "Voice input" is a method of inputting instructions or information using the user's own voice.

[0322] "Digital information" refers to data that is processed by a computer and represented as an array of bits.

[0323] "Encoded information" refers to data that has been converted from natural language or speech and encoded into an analyzable format.

[0324] "Natural language processing" is a technology that enables computers to understand human language and analyze its meaning.

[0325] "Voice characteristic recognition" is a technology that detects unique features contained in a voice signal to identify an individual.

[0326] A "password" is a secret word or phrase used to grant authentication or access under specific conditions.

[0327] "Activity history" refers to information that stores a record of a user's past actions and operations.

[0328] "Fraud risk" refers to a situation in which there is a possibility of suffering financial or informational damage due to malicious acts.

[0329] A "warning" is a notification or signal that indicates the possibility of danger or a problem occurring.

[0330] "Voice commands" refer to instructions or commands that a user gives to a device using their voice.

[0331] "Order details" refer to information about the products or services that the user wishes to purchase or acquire.

[0332] The system implementing this invention is based on the user performing voice input from an information processing device, such as a smartphone. The voice input data is converted into digital information using the Google Speech-to-Text API. This digital information is transferred to a server and converted into encoded information using natural language processing technology. It is preferable to use the Python NLTK library for natural language processing. The server analyzes this encoded information to identify the user's purpose.

[0333] The server verifies and authenticates the user using voice characteristic recognition and a password. Voice authentication technologies such as Amazon Rekognition can be used as the authentication method, identifying the user from the voice data. In this process, the use of encryption technology is recommended to ensure the protection of the user's personal information.

[0334] The server also has a function to prevent duplicate actions by referring to the user's activity history. For example, it can detect duplicate orders for the same product on different dates and, if necessary, prompt the user with a voice confirmation. In addition, it applies anomaly detection algorithms such as Isolation Forest to detect fraud risks and warn of fraudulent activity in advance.

[0335] For order processing, users can select products based on voice commands and confirm their order details by voice. The system uses the Google Text-to-Speech API to provide voice feedback to the user.

[0336] For example, if a user says, "I want to order a recently popular health supplement," the system analyzes this request, retrieves a list of currently popular health supplements, and verbally communicates the options to the user. Once the order is confirmed, the server completes the transaction.

[0337] Examples of prompts for a generative AI model are as follows:

[0338] "A 50-year-old user is trying to order a new health supplement using voice input. Please provide voice guidance to the user at each step of the ordering process."

[0339] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0340] Step 1:

[0341] The user performs voice input through the device.

[0342] The input is the user's voice, which the device passes to the Google Speech-to-Text API. The API converts the voice into text data. This process makes the voice data available for transmission to the server as text data.

[0343] Step 2:

[0344] The server receives text data and performs natural language processing.

[0345] The input is text data, and the server uses Python's NLTK library for natural language processing. It analyzes the meaning and intent of the text and identifies corresponding instructions and inquiries. This process encapsulates the user's requests and prepares them for the next steps.

[0346] Step 3:

[0347] The server performs user authentication.

[0348] The input is the user's voice characteristics information. The server uses voice authentication technology such as Amazon Rekognition to detect the voice characteristics and compare them with a password. This prevents misrecognition and impersonation, and verifies the user's legitimacy.

[0349] Step 4:

[0350] The server checks the user's activity history to prevent duplicate orders.

[0351] The input consists of past order data, and the server compares it to the current request by referring to the database. If duplicates exist, such as orders for the same product on different dates, the server issues a warning. This process helps prevent incorrect orders.

[0352] Step 5:

[0353] The server processes orders based on voice commands.

[0354] The input is parsed text data that includes the user's intent. The server uses this to search for products in the product database and proceed with the order process. The selected products are provided to the user via voice feedback using the Google Text-to-Speech API. The user confirms the selection, and the final order is confirmed.

[0355] Step 6:

[0356] The server detects fraud risks and issues warnings if necessary.

[0357] The input is all transaction data for an anomaly detection algorithm, and the server applies Isolation Forest and other tools to assess the likelihood of fraud. If suspicious activity is detected, the server sends an alert to the user and their associates for further verification.

[0358] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0359] This invention provides a more user-friendly and secure environment by incorporating emotion recognition capabilities into a system that uses classic communication equipment to support the elderly and those who are digitally vulnerable. This system integrates an emotion engine in addition to voice recognition, natural language processing, identity verification, history management, and fraud prevention functions.

[0360] When a user gives a voice command through a communication terminal, the terminal converts the voice into digital data and sends it to the server. The server converts the voice data into text data and uses natural language processing to analyze the user's intent. In addition, an emotion engine identifies the user's emotions based on the characteristics of the voice. This information is used to dynamically adjust the content of the dialogue.

[0361] User authentication is performed using voice pattern recognition and a passphrase. If authentication is successful, the system checks for duplicate actions by referring to the user's past action history. The server constantly monitors for potential fraud and has a mechanism in place to immediately warn the user and their associates if a risk is detected.

[0362] For example, if a user expresses concern about a delayed delivery, the server uses an emotion engine to recognize the expression of anxiety and, in addition to providing a regular delivery status check, offers detailed explanations and solutions to alleviate reassurance. This allows the user to address the problem with emotional reassurance.

[0363] This system aims to provide users with a more comfortable user experience by enabling personalized responses that take emotions into consideration. Furthermore, by monitoring changes in the user's emotions and automatically notifying relevant parties as needed, it reduces the risks that elderly individuals may encounter in their daily lives.

[0364] The following describes the processing flow.

[0365] Step 1:

[0366] The user gives voice commands to the communication device. For example, they might say, "I want to order supplements."

[0367] Step 2:

[0368] The terminal captures the user's voice signal, converts it into digital data, and then sends it to the server.

[0369] Step 3:

[0370] The server converts the received audio data into text data using a speech recognition system. This text data is then passed to a natural language processing module.

[0371] Step 4:

[0372] The server analyzes text data using natural language processing to identify the user's intent. In this case, it understands the intent to "order supplements."

[0373] Step 5:

[0374] The server also uses an emotion engine to analyze the user's voice and identify emotional states such as feelings of security or anxiety.

[0375] Step 6:

[0376] The server performs authentication using voice pattern recognition and a registered passphrase, and if authentication is successful, it prepares to process the user's request.

[0377] Step 7:

[0378] The server retrieves past order history from the database and checks if there are any duplicate new orders.

[0379] Step 8:

[0380] If a duplicate order is found, or if the server determines that the user's emotional state is unstable, it will generate a response that reflects this. For example, it might suggest, "Would you like to place the same order as last time?" or "Please wait while we check the delivery status in detail."

[0381] Step 9:

[0382] The server assesses fraud risk as needed, issues a warning if fraud is suspected, and automatically notifies registered parties.

[0383] Step 10:

[0384] Once the process is complete, the user will be notified of the results via their device. This notification will include information to reassure the user and explanations of the necessary next steps.

[0385] This process allows users to receive a fast and safe service that is sensitive to their emotions.

[0386] (Example 2)

[0387] Next, we will describe Example 2. 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".

[0388] For the elderly and those with limited access to information, there is a need for a system that can establish a simple and secure communication environment through voice, while also providing the flexibility to respond to emotional needs. Existing technologies lack comprehensive integration of emotion recognition, identity verification, and fraud prevention, making it difficult to achieve both usability and security.

[0389] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0390] In this invention, the server includes means for receiving voice input from a communication device available to the user and converting it into numerical data, means for analyzing the numerical data and converting it into character data, and means for analyzing the character data by language processing and identifying the user's intent. This makes it intuitively usable even for the elderly and those with limited access to information, and also enables responses that take emotions into consideration.

[0391] A "communication device" is a device used by a user to input voice data and has the function of sending and receiving information with a server via a communication network.

[0392] "Numerical data" refers to data obtained by converting audio signals into a digital format, and is used for audio analysis.

[0393] "Character data" refers to text-formatted data obtained by analyzing numerical data, and is used in natural language processing.

[0394] "Language processing" is a technology that analyzes user intent based on text data, and includes natural language understanding.

[0395] "Identity verification" is the process of verifying a user's identity using voice patterns or passwords.

[0396] "Operation history" refers to a record of actions a user has taken in the past, which is managed by the system.

[0397] "Fraudulent activity risk" refers to unauthorized operations or fraud that may occur within the system, and is the target of monitoring to detect them.

[0398] "Emotional characteristics" refer to information about the user's emotional state, as determined from factors such as tone and rhythm of voice.

[0399] "Dynamic adjustment of dialogue" is the process of adapting the system's response based on the user's emotions and intentions.

[0400] This invention is a system that enables safe and user-friendly communication for the elderly and those with limited access to information. Specifically, it aims to analyze the user's intentions and emotions from voice input and provide appropriate responses. The following details each component and its operation.

[0401] The terminal receives voice input from the user. In this process, a microphone is used to convert the voice into numerical data, which is then transmitted to a server via a communication network. This conversion is performed using commonly available speech recognition software.

[0402] The server converts the numerical data of the received speech into text data and then uses a natural language processing engine to analyze the user's intent. For this purpose, it utilizes general language processing tools. During this process, an emotion recognition engine analyzes the characteristics of the speech and identifies the user's emotions. Based on this, the server dynamically adjusts its dialogue to provide a response that aligns with the user's emotions.

[0403] For example, if a user expresses anxiety such as "I'm worried because my delivery is delayed," the server will sense this anxiety through emotion recognition. As a result, it will respond in a way that is appropriate to the user's emotions by providing detailed information about the delivery status or sending reassuring messages.

[0404] An example of a prompt message to input into the generating AI model is: "Audio data has been received. The user appears worried. Please check the delivery status and provide reassuring information."

[0405] This invention will realize a safe and emotionally considerate communication system that can be used intuitively by the elderly and those with limited access to information.

[0406] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0407] Step 1:

[0408] The terminal receives voice input from the user. Specifically, the terminal uses a microphone to convert the voice from analog to digital numerical data. The input is an audio signal, and the output is digital numerical data. This data is sent to the server via the communication network for further processing.

[0409] Step 2:

[0410] The server converts received numerical data into character data. This is a process using speech recognition software, where the input is numerical data and the output is character data. Specifically, the server analyzes the numerical data and converts the speech patterns into corresponding strings.

[0411] Step 3:

[0412] The server analyzes text data using a natural language processing engine. The input is text data, and the output is identification data that indicates the user's intent. Specifically, the server performs grammatical analysis and semantic interpretation to identify the intent behind the user's requests and questions.

[0413] Step 4:

[0414] The server uses an emotion recognition engine to identify the user's emotions. Input is data including text data and voice characteristics, and output is data indicating the emotional state. Specifically, the server analyzes the tone and speed of the voice to determine what emotional state the user is in.

[0415] Step 5:

[0416] The server verifies the user's identity and checks the operation history. In this step, a voice pattern and a password are used as input, and the output is the authentication result. Specifically, the server compares the registered pattern with the input and refers to the operation history to detect duplicates and fraudulent activity.

[0417] Step 6:

[0418] The server generates an appropriate response considering the user's emotions and intentions and sends it to the terminal. The input is emotional state and identification data, and the output is a tailored response message. Specifically, the server creates a dialogue message adapted to the user's state and adds contextually relevant information using a generative AI model.

[0419] Step 7:

[0420] The terminal provides the user with received responses via audio or text display. Input is the response message from the server, and output is in a user-understandable format. Specifically, the terminal uses speakers and displays to convey information and support user accessibility.

[0421] (Application Example 2)

[0422] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0423] In brick-and-mortar retail settings, customer service requires flexible and appropriate responses that respond to customer emotions. However, current systems make it difficult to analyze emotions in real time and adjust service accordingly. Furthermore, detailed support for the elderly and those with limited access to information is insufficient. Therefore, a system that comprehensively addresses these issues is necessary.

[0424] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0425] In this invention, the server includes means for receiving voice input from an information terminal available to the user and converting it into digital data, means for analyzing the digital data and converting it into text data, and means for analyzing the emotions in the voice and providing optimal information in accordance with the customer's emotions. This makes it possible to grasp the customer's emotions in real time during customer service operations in physical stores and to provide appropriate information and customer service accordingly.

[0426] An "information terminal" is a device that receives voice input from a user and converts it into digital data.

[0427] "Digital data" refers to a data format converted from analog signals, which can be processed and analyzed by computers.

[0428] "Character data" refers to text-based data generated from digital data through natural language processing.

[0429] "Natural language processing" is a technology that enables computers to understand and analyze human language, allowing them to identify the user's intent.

[0430] "Voice pattern recognition" is a technology that analyzes the characteristics of speech to identify its source, and is used for identity verification.

[0431] A "password" is an encrypted phrase used for user authentication.

[0432] "Action history" refers to a record of actions a user has taken in the past, and is used to prevent future actions from being duplicated.

[0433] "Fraudulent activity" refers to any action or attempt that may deceive or maliciously harm a user.

[0434] "Emotion analysis" is a technology that infers a user's emotional state from their voice or text.

[0435] "Information provision" refers to the act of providing users with the data and explanations they need, tailored to their specific circumstances.

[0436] This invention is a system that highly supports customer service in physical stores. The user wears smart glasses and uses them as an information terminal to receive voice input. The terminal converts the voice spoken by the user into digital data, and this data is sent to a cloud server. The server uses the Google Cloud Speech-to-Text API to convert the digital data into text data.

[0437] The server then uses IBM Watson's natural language understanding service on the converted text data to analyze the user's intent and emotions. This analysis visualizes the emotions in the speech, enabling the provision of appropriate information. For example, if a customer says, "I'm worried about whether this product is easy to use," the server identifies the emotion of anxiety and, based on that, displays usage examples and detailed explanations on the smart glasses' display.

[0438] In this way, sales staff can receive optimal information tailored to the customer's real-time emotional state, enabling more effective customer service. Examples of specific prompt messages include the following:

[0439] Audio data: The customer said, "I'm worried about the usability of a particular product."

[0440] Emotional analysis: Anxiety and identification.

[0441] Recommendation: Display video tutorials on how to use the product on the smart glasses display to provide reassuring information.

[0442] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0443] Step 1:

[0444] The user collects customer voices through smart glasses. The voice input is converted into digital data using the device's microphone. This digital data is sent directly to the cloud server without any editing.

[0445] Step 2:

[0446] The server converts received digital data into text data using the Google Cloud Speech-to-Text API. It receives digital audio data as input and converts it to text using a speech recognition algorithm. The output is text data that accurately represents the audio content.

[0447] Step 3:

[0448] The server analyzes the converted character data using IBM Watson's natural language understanding service. Here, natural language processing is performed using the character data as input to identify the user's intent and emotions. The output generates data representing the identified intent and emotions.

[0449] Step 4:

[0450] The server generates information tailored to the customer's state based on intent and emotion data. It utilizes a generative AI model to create prompts that meet customer needs. For example, if anxiety is detected, it generates information including specific explanations and product usage examples to provide reassurance.

[0451] Step 5:

[0452] The server displays the generated information on the user's smart glasses display. This allows the terminal to receive information from the server as input, display appropriate information on the display based on that input, and create a situation where the user can provide the best possible service to the customer.

[0453] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0454] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0455] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0456] [Third Embodiment]

[0457] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0458] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0459] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0460] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0461] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0462] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0463] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0464] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0465] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0466] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0467] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0468] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0469] This invention is a system that utilizes voice interaction via a user-friendly communication terminal, aiming to enable the elderly and those with limited access to information to easily utilize digital services. This system primarily includes functions for voice recognition, natural language processing, user authentication, history management, and fraud prevention.

[0470] The user provides voice input through a communication terminal. The terminal converts the user's voice into digital data and sends it to the server. The server converts the received voice into text data and analyzes the user's intent using natural language processing technology. Based on this analysis, the server generates an appropriate response and prepares to reply to the user.

[0471] For user authentication, the server utilizes voice pattern recognition technology and a passphrase to verify the user's identity based on their voice characteristics. After authentication is complete, the server checks the user's past action history to ensure there are no duplicate orders or inquiries. If necessary, the server asks the user confirmation questions.

[0472] Furthermore, the server continuously monitors communications and immediately warns users and registered parties if it detects a risk of fraud. This allows users to use digital services necessary for their daily lives with peace of mind.

[0473] As a concrete example, consider the case where a user wishes to order a product. When the user enters "I want to order a new supplement," the server checks the user's past order history to ensure there are no duplicates and then confirms with the user. This process prevents the user from repeatedly placing incorrect orders. Through this series of processes, the user can purchase products smoothly and safely through the system.

[0474] The following describes the processing flow.

[0475] Step 1:

[0476] The user gives voice commands to the communication terminal. For example, they might say, "I want to order supplements."

[0477] Step 2:

[0478] The device converts the user's voice into digital data. This converted digital data is then transmitted to a server via the network.

[0479] Step 3:

[0480] The server converts the received audio data into text data through a speech recognition process. This text data is then analyzed by a natural language processing module.

[0481] Step 4:

[0482] The server identifies the user's intent from the parsed text data. In this case, it understands the instruction, "I want to order supplements."

[0483] Step 5:

[0484] The server authenticates the user's identity using voice pattern recognition technology and a registered passphrase. If authentication is successful, the process proceeds to the next step.

[0485] Step 6:

[0486] The server retrieves the user's past order history from the database and compares it with the current instructions to check for duplicate orders.

[0487] Step 7:

[0488] If duplicates are detected, the server will generate an additional voice prompt to ask the user for confirmation.

[0489] Step 8:

[0490] After the user confirms, the server officially accepts the order and processes the order details. This includes checking the availability of the required items and arranging shipping.

[0491] Step 9:

[0492] The server constantly monitors the security of transactions, issues warnings if fraud is suspected, and sends notifications to pre-registered family members as needed.

[0493] Step 10:

[0494] As a final response, the terminal will notify the user of the order confirmation and the necessary next steps.

[0495] Therefore, users can securely place product orders through the system.

[0496] (Example 1)

[0497] Next, we will describe Example 1. 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."

[0498] This invention seeks to enable safe and easy access to digital services for the elderly and those with limited digital literacy, while reducing their anxiety about complex digital operations and fraud. Voice-based interfaces, in particular, are attracting attention as a means of achieving intuitive and natural communication, but unresolved issues remain regarding related authentication, fraud prevention, and order management.

[0499] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0500] In this invention, the server includes means for converting and analyzing voice data from the user into digital information, means for identifying the user's intent through natural language processing, and means for authenticating the user using voice recognition technology and a password. This enables users to safely and efficiently utilize digital services through natural voice interaction.

[0501] "Electronic device" refers to a device used by a user to input voice data, and includes devices such as smartphones and tablets.

[0502] "Digital information" refers to an electrical data format obtained as a result of processing analog audio data using electronic methods.

[0503] "Text information" refers to information in written form that is generated after audio data has been analyzed, and it expresses the user's intent in a way that is easier to understand.

[0504] "Language analysis technology" refers to a series of techniques used to understand user intent and emotions from text information, and it utilizes natural language processing methods.

[0505] "Voice recognition technology" is a technology used to identify or authenticate individuals using their voice, and it verifies the matching of voice characteristics.

[0506] A "password" is a string of characters that a user has set in advance as part of the authentication process, and it serves as an additional security measure for verifying the user's identity.

[0507] "Fraudulent activity" refers to actions that are inappropriate and contrary to the user's intentions, or actions that involve the risk of damaging the user's information or services through fraudulent means.

[0508] A "generative AI model" is an artificial intelligence model used to dynamically generate responses to user inquiries, and is a technology that automatically generates prompt text.

[0509] This invention provides a system that allows users to easily operate digital services using their voice. Users access the system by voice through electronic devices such as smartphones and tablets. When a user inputs voice into the device, the terminal converts that voice into digital information. Various technologies can be used for voice recognition, but for example, the conversion is performed through a voice recognition API.

[0510] This digital information is transmitted to a server via the network. The server processes the received digital information and converts it into text information. This makes the information obtained from the speech easier to analyze. The server is equipped with natural language processing software that utilizes language analysis technology to analyze the user's intent and identify the necessary actions. For example, a language analysis library is used as the software for this analysis.

[0511] The server also verifies the user's identity using voice recognition technology and a password. The voice recognition technology utilizes specific voice recognition software, which authenticates the user based on the characteristics of their voice. After authentication is complete, the server reviews the user's past activity history to check for duplicate actions. This helps prevent unintentional duplicate orders.

[0512] When the user provides new instructions, the server uses an AI model to generate prompts and ask questions or confirmations to the user. For example, it might ask, "You ordered this product before, would you like to order it again?" By utilizing dynamically generated prompts based on user input in this way, the interaction proceeds more smoothly.

[0513] The server also has a function to immediately warn the user and their associates when it detects fraudulent activity. This allows users to use digital services with peace of mind. Through this system, users are provided with an environment in which they can intuitively and safely use digital services on a daily basis.

[0514] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0515] Step 1:

[0516] The user speaks instructions into the microphone of the communication terminal. The input at this time is the user's voice. The terminal uses the microphone to capture the audio data and converts the analog audio signal into digital information. The output at this stage is audio data in digital format.

[0517] Step 2:

[0518] The terminal transmits digital audio data to the server via the network. The server receives this digital audio data. The server uses speech recognition software to convert the audio data into text information. The input is digital audio data, and the output is text information converted from the audio.

[0519] Step 3:

[0520] The server passes the converted text information to a natural language processing unit, which analyzes the user's intent. This process involves syntactically analyzing the text data and extracting keywords and phrases to understand the user's request. The input is text information, and the output is data related to the user's intent.

[0521] Step 4:

[0522] The server uses a voice authentication system to verify the user's identity. Input consists of the user's voice characteristics and a pre-set password, while output indicates the authentication success or failure status. Voice identification technology compares the voice data with registered information; authentication is complete if they match.

[0523] Step 5:

[0524] The server references the user's past behavior history to check for any actions that overlap with the newly received intent. The input for this step is the user's intent data, and the output is the result of the duplicate check. This prevents orders that duplicate past actions.

[0525] Step 6:

[0526] If necessary, the server uses a generative AI model to generate a prompt message that asks the user for confirmation. The input is the user's intent and past history information, and the output is the prompt message. For example, a prompt message such as "You have ordered this product before, would you like to order it again?" might be generated.

[0527] Step 7:

[0528] The server monitors communications to detect fraudulent activity. If a fraud risk is detected, the input is the detected suspicious pattern, and the output is a warning message to the user and their associates. Fraud detection algorithms are used to provide real-time notifications.

[0529] Step 8:

[0530] Finally, the server generates a response to the user and sends it to the terminal. The input is the confirmed user intent or the generated prompt, and the output is returned to the terminal as a voice response. The terminal synthesizes this into speech and sends it back to the user, completing the process.

[0531] (Application Example 1)

[0532] Next, we will explain Application Example 1. In the following explanation, 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."

[0533] In modern society, elderly people and users unfamiliar with digital technology face the problem of complex operation when using online services. Furthermore, mechanisms to prevent fraud and erroneous orders are insufficient, creating a need for systems that these users can use with peace of mind. Additionally, there is a need for methods that allow for easy order confirmation and completion of orders solely through voice commands.

[0534] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0535] In this invention, the server includes means for receiving voice input from an information processing device available to the user and converting it into digital information, means for selecting products based on voice commands and confirming order details by voice, and means for detecting fraud risks and issuing warnings to the user and related parties. This enables simple and secure online ordering using voice.

[0536] An "information processing device" is a device that receives information as input and generates output by performing various calculations.

[0537] "Voice input" is a method of inputting instructions or information using the user's own voice.

[0538] "Digital information" refers to data that is processed by a computer and represented as an array of bits.

[0539] "Encoded information" refers to data that has been converted from natural language or speech and encoded into an analyzable format.

[0540] "Natural language processing" is a technology that enables computers to understand human language and analyze its meaning.

[0541] "Voice characteristic recognition" is a technology that detects unique features contained in a voice signal to identify an individual.

[0542] A "password" is a secret word or phrase used to grant authentication or access under specific conditions.

[0543] "Activity history" refers to information that stores a record of a user's past actions and operations.

[0544] "Fraud risk" refers to a situation in which there is a possibility of suffering financial or informational damage due to malicious acts.

[0545] A "warning" is a notification or signal that indicates the possibility of danger or a problem occurring.

[0546] "Voice commands" refer to instructions or commands that a user gives to a device using their voice.

[0547] "Order details" refer to information about the products or services that the user wishes to purchase or acquire.

[0548] The system implementing this invention is based on the user performing voice input from an information processing device, such as a smartphone. The voice input data is converted into digital information using the Google Speech-to-Text API. This digital information is transferred to a server and converted into encoded information using natural language processing technology. It is preferable to use the Python NLTK library for natural language processing. The server analyzes this encoded information to identify the user's purpose.

[0549] The server verifies and authenticates the user using voice characteristic recognition and a password. Voice authentication technologies such as Amazon Rekognition can be used as the authentication method, identifying the user from the voice data. In this process, the use of encryption technology is recommended to ensure the protection of the user's personal information.

[0550] The server also has a function to prevent duplicate actions by referring to the user's activity history. For example, it can detect duplicate orders for the same product on different dates and, if necessary, prompt the user with a voice confirmation. In addition, it applies anomaly detection algorithms such as Isolation Forest to detect fraud risks and warn of fraudulent activity in advance.

[0551] For order processing, users can select products based on voice commands and confirm their order details by voice. The system uses the Google Text-to-Speech API to provide voice feedback to the user.

[0552] For example, if a user says, "I want to order a recently popular health supplement," the system analyzes this request, retrieves a list of currently popular health supplements, and verbally communicates the options to the user. Once the order is confirmed, the server completes the transaction.

[0553] Examples of prompts for a generative AI model are as follows:

[0554] "A 50-year-old user is trying to order a new health supplement using voice input. Please provide voice guidance to the user at each step of the ordering process."

[0555] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0556] Step 1:

[0557] The user performs voice input through the device.

[0558] The input is the user's voice, which the device passes to the Google Speech-to-Text API. The API converts the voice into text data. This process makes the voice data available for transmission to the server as text data.

[0559] Step 2:

[0560] The server receives text data and performs natural language processing.

[0561] The input is text data, and the server uses Python's NLTK library for natural language processing. It analyzes the meaning and intent of the text and identifies corresponding instructions and inquiries. This process encapsulates the user's requests and prepares them for the next steps.

[0562] Step 3:

[0563] The server performs user authentication.

[0564] The input is the user's voice characteristics information. The server uses voice authentication technology such as Amazon Rekognition to detect the voice characteristics and compare them with a password. This prevents misrecognition and impersonation, and verifies the user's legitimacy.

[0565] Step 4:

[0566] The server checks the user's activity history to prevent duplicate orders.

[0567] The input consists of past order data, and the server compares it to the current request by referring to the database. If duplicates exist, such as orders for the same product on different dates, the server issues a warning. This process helps prevent incorrect orders.

[0568] Step 5:

[0569] The server processes orders based on voice commands.

[0570] The input is parsed text data that includes the user's intent. The server uses this to search for products in the product database and proceed with the order process. The selected products are provided to the user via voice feedback using the Google Text-to-Speech API. The user confirms the selection, and the final order is confirmed.

[0571] Step 6:

[0572] The server detects fraud risks and issues warnings if necessary.

[0573] The input is all transaction data for an anomaly detection algorithm, and the server applies Isolation Forest and other tools to assess the likelihood of fraud. If suspicious activity is detected, the server sends an alert to the user and their associates for further verification.

[0574] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0575] This invention provides a more user-friendly and secure environment by incorporating emotion recognition capabilities into a system that uses classic communication equipment to support the elderly and those who are digitally vulnerable. This system integrates an emotion engine in addition to voice recognition, natural language processing, identity verification, history management, and fraud prevention functions.

[0576] When a user gives a voice command through a communication terminal, the terminal converts the voice into digital data and sends it to the server. The server converts the voice data into text data and uses natural language processing to analyze the user's intent. In addition, an emotion engine identifies the user's emotions based on the characteristics of the voice. This information is used to dynamically adjust the content of the dialogue.

[0577] User authentication is performed using voice pattern recognition and a passphrase. If authentication is successful, the system checks for duplicate actions by referring to the user's past action history. The server constantly monitors for potential fraud and has a mechanism in place to immediately warn the user and their associates if a risk is detected.

[0578] For example, if a user expresses concern about a delayed delivery, the server uses an emotion engine to recognize the expression of anxiety and, in addition to providing a regular delivery status check, offers detailed explanations and solutions to alleviate reassurance. This allows the user to address the problem with emotional reassurance.

[0579] This system aims to provide users with a more comfortable user experience by enabling personalized responses that take emotions into consideration. Furthermore, by monitoring changes in the user's emotions and automatically notifying relevant parties as needed, it reduces the risks that elderly individuals may encounter in their daily lives.

[0580] The following describes the processing flow.

[0581] Step 1:

[0582] The user gives voice commands to the communication device. For example, they might say, "I want to order supplements."

[0583] Step 2:

[0584] The terminal captures the user's voice signal, converts it into digital data, and then sends it to the server.

[0585] Step 3:

[0586] The server converts the received audio data into text data using a speech recognition system. This text data is then passed to a natural language processing module.

[0587] Step 4:

[0588] The server analyzes text data using natural language processing to identify the user's intent. In this case, it understands the intent to "order supplements."

[0589] Step 5:

[0590] The server also uses an emotion engine to analyze the user's voice and identify emotional states such as feelings of security or anxiety.

[0591] Step 6:

[0592] The server performs authentication using voice pattern recognition and a registered passphrase, and if authentication is successful, it prepares to process the user's request.

[0593] Step 7:

[0594] The server retrieves past order history from the database and checks if there are any duplicate new orders.

[0595] Step 8:

[0596] If a duplicate order is found, or if the server determines that the user's emotional state is unstable, it will generate a response that reflects this. For example, it might suggest, "Would you like to place the same order as last time?" or "Please wait while we check the delivery status in detail."

[0597] Step 9:

[0598] The server assesses fraud risk as needed, issues a warning if fraud is suspected, and automatically notifies registered parties.

[0599] Step 10:

[0600] Once the process is complete, the user will be notified of the results via their device. This notification will include information to reassure the user and explanations of the necessary next steps.

[0601] This process allows users to receive a fast and safe service that is sensitive to their emotions.

[0602] (Example 2)

[0603] Next, we will describe Example 2. 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."

[0604] For the elderly and those with limited access to information, there is a need for a system that can establish a simple and secure communication environment through voice, while also providing the flexibility to respond to emotional needs. Existing technologies lack comprehensive integration of emotion recognition, identity verification, and fraud prevention, making it difficult to achieve both usability and security.

[0605] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0606] In this invention, the server includes means for receiving voice input from a communication device available to the user and converting it into numerical data, means for analyzing the numerical data and converting it into character data, and means for analyzing the character data by language processing and identifying the user's intent. This makes it intuitively usable even for the elderly and those with limited access to information, and also enables responses that take emotions into consideration.

[0607] A "communication device" is a device used by a user to input voice data and has the function of sending and receiving information with a server via a communication network.

[0608] "Numerical data" refers to data obtained by converting audio signals into a digital format, and is used for audio analysis.

[0609] "Character data" refers to text-formatted data obtained by analyzing numerical data, and is used in natural language processing.

[0610] "Language processing" is a technology that analyzes user intent based on text data, and includes natural language understanding.

[0611] "Identity verification" is the process of verifying a user's identity using voice patterns or passwords.

[0612] "Operation history" refers to a record of actions a user has taken in the past, which is managed by the system.

[0613] "Fraudulent activity risk" refers to unauthorized operations or fraud that may occur within the system, and is the target of monitoring to detect them.

[0614] "Emotional characteristics" refer to information about the user's emotional state, as determined from factors such as tone and rhythm of voice.

[0615] "Dynamic adjustment of dialogue" is the process of adapting the system's response based on the user's emotions and intentions.

[0616] This invention is a system that enables safe and user-friendly communication for the elderly and those with limited access to information. Specifically, it aims to analyze the user's intentions and emotions from voice input and provide appropriate responses. The following details each component and its operation.

[0617] The terminal receives voice input from the user. In this process, a microphone is used to convert the voice into numerical data, which is then transmitted to a server via a communication network. This conversion is performed using commonly available speech recognition software.

[0618] The server converts the numerical data of the received speech into text data and then uses a natural language processing engine to analyze the user's intent. For this purpose, it utilizes general language processing tools. During this process, an emotion recognition engine analyzes the characteristics of the speech and identifies the user's emotions. Based on this, the server dynamically adjusts its dialogue to provide a response that aligns with the user's emotions.

[0619] For example, if a user expresses anxiety such as "I'm worried because my delivery is delayed," the server will sense this anxiety through emotion recognition. As a result, it will respond in a way that is appropriate to the user's emotions by providing detailed information about the delivery status or sending reassuring messages.

[0620] An example of a prompt message to input into the generating AI model is: "Audio data has been received. The user appears worried. Please check the delivery status and provide reassuring information."

[0621] This invention will realize a safe and emotionally considerate communication system that can be used intuitively by the elderly and those with limited access to information.

[0622] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0623] Step 1:

[0624] The terminal receives voice input from the user. Specifically, the terminal uses a microphone to convert the voice from analog to digital numerical data. The input is an audio signal, and the output is digital numerical data. This data is sent to the server via the communication network for further processing.

[0625] Step 2:

[0626] The server converts received numerical data into character data. This is a process using speech recognition software, where the input is numerical data and the output is character data. Specifically, the server analyzes the numerical data and converts the speech patterns into corresponding strings.

[0627] Step 3:

[0628] The server analyzes text data using a natural language processing engine. The input is text data, and the output is identification data that indicates the user's intent. Specifically, the server performs grammatical analysis and semantic interpretation to identify the intent behind the user's requests and questions.

[0629] Step 4:

[0630] The server uses an emotion recognition engine to identify the user's emotions. Input is data including text data and voice characteristics, and output is data indicating the emotional state. Specifically, the server analyzes the tone and speed of the voice to determine what emotional state the user is in.

[0631] Step 5:

[0632] The server verifies the user's identity and checks the operation history. In this step, a voice pattern and a password are used as input, and the output is the authentication result. Specifically, the server compares the registered pattern with the input and refers to the operation history to detect duplicates and fraudulent activity.

[0633] Step 6:

[0634] The server generates an appropriate response considering the user's emotions and intentions and sends it to the terminal. The input is emotional state and identification data, and the output is a tailored response message. Specifically, the server creates a dialogue message adapted to the user's state and adds contextually relevant information using a generative AI model.

[0635] Step 7:

[0636] The terminal provides the user with received responses via audio or text display. Input is the response message from the server, and output is in a user-understandable format. Specifically, the terminal uses speakers and displays to convey information and support user accessibility.

[0637] (Application Example 2)

[0638] Next, we will explain application example 2. In the following explanation, 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."

[0639] In brick-and-mortar retail settings, customer service requires flexible and appropriate responses that respond to customer emotions. However, current systems make it difficult to analyze emotions in real time and adjust service accordingly. Furthermore, detailed support for the elderly and those with limited access to information is insufficient. Therefore, a system that comprehensively addresses these issues is necessary.

[0640] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0641] In this invention, the server includes means for receiving voice input from an information terminal available to the user and converting it into digital data, means for analyzing the digital data and converting it into text data, and means for analyzing the emotions in the voice and providing optimal information in accordance with the customer's emotions. This makes it possible to grasp the customer's emotions in real time during customer service operations in physical stores and to provide appropriate information and customer service accordingly.

[0642] An "information terminal" is a device that receives voice input from a user and converts it into digital data.

[0643] "Digital data" refers to a data format converted from analog signals, which can be processed and analyzed by computers.

[0644] "Character data" refers to text-based data generated from digital data through natural language processing.

[0645] "Natural language processing" is a technology that enables computers to understand and analyze human language, allowing them to identify the user's intent.

[0646] "Voice pattern recognition" is a technology that analyzes the characteristics of speech to identify its source, and is used for identity verification.

[0647] A "password" is an encrypted phrase used for user authentication.

[0648] "Action history" refers to a record of actions a user has taken in the past, and is used to prevent future actions from being duplicated.

[0649] "Fraudulent activity" refers to any action or attempt that may deceive or maliciously harm a user.

[0650] "Emotion analysis" is a technology that infers a user's emotional state from their voice or text.

[0651] "Information provision" refers to the act of providing users with the data and explanations they need, tailored to their specific circumstances.

[0652] This invention is a system that highly supports customer service in physical stores. The user wears smart glasses and uses them as an information terminal to receive voice input. The terminal converts the voice spoken by the user into digital data, and this data is sent to a cloud server. The server uses the Google Cloud Speech-to-Text API to convert the digital data into text data.

[0653] The server then uses IBM Watson's natural language understanding service on the converted text data to analyze the user's intent and emotions. This analysis visualizes the emotions in the speech, enabling the provision of appropriate information. For example, if a customer says, "I'm worried about whether this product is easy to use," the server identifies the emotion of anxiety and, based on that, displays usage examples and detailed explanations on the smart glasses' display.

[0654] In this way, sales staff can receive optimal information tailored to the customer's real-time emotional state, enabling more effective customer service. Examples of specific prompt messages include the following:

[0655] Audio data: The customer said, "I'm worried about the usability of a particular product."

[0656] Emotional analysis: Anxiety and identification.

[0657] Recommendation: Display video tutorials on how to use the product on the smart glasses display to provide reassuring information.

[0658] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0659] Step 1:

[0660] The user collects customer voices through smart glasses. The voice input is converted into digital data using the device's microphone. This digital data is sent directly to the cloud server without any editing.

[0661] Step 2:

[0662] The server converts received digital data into text data using the Google Cloud Speech-to-Text API. It receives digital audio data as input and converts it to text using a speech recognition algorithm. The output is text data that accurately represents the audio content.

[0663] Step 3:

[0664] The server analyzes the converted character data using IBM Watson's natural language understanding service. Here, natural language processing is performed using the character data as input to identify the user's intent and emotions. The output generates data representing the identified intent and emotions.

[0665] Step 4:

[0666] The server generates information tailored to the customer's state based on intent and emotion data. It utilizes a generative AI model to create prompts that meet customer needs. For example, if anxiety is detected, it generates information including specific explanations and product usage examples to provide reassurance.

[0667] Step 5:

[0668] The server displays the generated information on the user's smart glasses display. This allows the terminal to receive information from the server as input, display appropriate information on the display based on that input, and create a situation where the user can provide the best possible service to the customer.

[0669] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0670] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0671] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0672] [Fourth Embodiment]

[0673] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0674] As shown in Figure 7, the 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.

[0675] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0676] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0677] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0678] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0679] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0680] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0681] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0682] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0683] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0684] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0685] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0686] This invention is a system that utilizes voice interaction via a user-friendly communication terminal, aiming to enable the elderly and those with limited access to information to easily utilize digital services. This system primarily includes functions for voice recognition, natural language processing, user authentication, history management, and fraud prevention.

[0687] The user provides voice input through a communication terminal. The terminal converts the user's voice into digital data and sends it to the server. The server converts the received voice into text data and analyzes the user's intent using natural language processing technology. Based on this analysis, the server generates an appropriate response and prepares to reply to the user.

[0688] For user authentication, the server utilizes voice pattern recognition technology and a passphrase to verify the user's identity based on their voice characteristics. After authentication is complete, the server checks the user's past action history to ensure there are no duplicate orders or inquiries. If necessary, the server asks the user confirmation questions.

[0689] Furthermore, the server continuously monitors communications and immediately warns users and registered parties if it detects a risk of fraud. This allows users to use digital services necessary for their daily lives with peace of mind.

[0690] As a concrete example, consider the case where a user wishes to order a product. When the user enters "I want to order a new supplement," the server checks the user's past order history to ensure there are no duplicates and then confirms with the user. This process prevents the user from repeatedly placing incorrect orders. Through this series of processes, the user can purchase products smoothly and safely through the system.

[0691] The following describes the processing flow.

[0692] Step 1:

[0693] The user gives voice commands to the communication terminal. For example, they might say, "I want to order supplements."

[0694] Step 2:

[0695] The device converts the user's voice into digital data. This converted digital data is then transmitted to a server via the network.

[0696] Step 3:

[0697] The server converts the received audio data into text data through a speech recognition process. This text data is then analyzed by a natural language processing module.

[0698] Step 4:

[0699] The server identifies the user's intent from the parsed text data. In this case, it understands the instruction, "I want to order supplements."

[0700] Step 5:

[0701] The server authenticates the user's identity using voice pattern recognition technology and a registered passphrase. If authentication is successful, the process proceeds to the next step.

[0702] Step 6:

[0703] The server retrieves the user's past order history from the database and compares it with the current instructions to check for duplicate orders.

[0704] Step 7:

[0705] If duplicates are detected, the server will generate an additional voice prompt to ask the user for confirmation.

[0706] Step 8:

[0707] After the user confirms, the server officially accepts the order and processes the order details. This includes checking the availability of the required items and arranging shipping.

[0708] Step 9:

[0709] The server constantly monitors the security of transactions, issues warnings if fraud is suspected, and sends notifications to pre-registered family members as needed.

[0710] Step 10:

[0711] As a final response, the terminal will notify the user of the order confirmation and the necessary next steps.

[0712] Therefore, users can securely place product orders through the system.

[0713] (Example 1)

[0714] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0715] This invention seeks to enable safe and easy access to digital services for the elderly and those with limited digital literacy, while reducing their anxiety about complex digital operations and fraud. Voice-based interfaces, in particular, are attracting attention as a means of achieving intuitive and natural communication, but unresolved issues remain regarding related authentication, fraud prevention, and order management.

[0716] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0717] In this invention, the server includes means for converting and analyzing voice data from the user into digital information, means for identifying the user's intent through natural language processing, and means for authenticating the user using voice recognition technology and a password. This enables users to safely and efficiently utilize digital services through natural voice interaction.

[0718] "Electronic device" refers to a device used by a user to input voice data, and includes devices such as smartphones and tablets.

[0719] "Digital information" refers to an electrical data format obtained as a result of processing analog audio data using electronic methods.

[0720] "Text information" refers to information in written form that is generated after audio data has been analyzed, and it expresses the user's intent in a way that is easier to understand.

[0721] "Language analysis technology" refers to a series of techniques used to understand user intent and emotions from text information, and it utilizes natural language processing methods.

[0722] "Voice recognition technology" is a technology used to identify or authenticate individuals using their voice, and it verifies the matching of voice characteristics.

[0723] A "password" is a string of characters that a user has set in advance as part of the authentication process, and it serves as an additional security measure for verifying the user's identity.

[0724] "Fraudulent activity" refers to actions that are inappropriate and contrary to the user's intentions, or actions that involve the risk of damaging the user's information or services through fraudulent means.

[0725] A "generative AI model" is an artificial intelligence model used to dynamically generate responses to user inquiries, and is a technology that automatically generates prompt text.

[0726] This invention provides a system that allows users to easily operate digital services using their voice. Users access the system by voice through electronic devices such as smartphones and tablets. When a user inputs voice into the device, the terminal converts that voice into digital information. Various technologies can be used for voice recognition, but for example, the conversion is performed through a voice recognition API.

[0727] This digital information is transmitted to a server via the network. The server processes the received digital information and converts it into text information. This makes the information obtained from the speech easier to analyze. The server is equipped with natural language processing software that utilizes language analysis technology to analyze the user's intent and identify the necessary actions. For example, a language analysis library is used as the software for this analysis.

[0728] The server also verifies the user's identity using voice recognition technology and a password. The voice recognition technology utilizes specific voice recognition software, which authenticates the user based on the characteristics of their voice. After authentication is complete, the server reviews the user's past activity history to check for duplicate actions. This helps prevent unintentional duplicate orders.

[0729] When the user provides new instructions, the server uses an AI model to generate prompts and ask questions or confirmations to the user. For example, it might ask, "You ordered this product before, would you like to order it again?" By utilizing dynamically generated prompts based on user input in this way, the interaction proceeds more smoothly.

[0730] The server also has a function to immediately warn the user and their associates when it detects fraudulent activity. This allows users to use digital services with peace of mind. Through this system, users are provided with an environment in which they can intuitively and safely use digital services on a daily basis.

[0731] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0732] Step 1:

[0733] The user speaks instructions into the microphone of the communication terminal. The input at this time is the user's voice. The terminal uses the microphone to capture the audio data and converts the analog audio signal into digital information. The output at this stage is audio data in digital format.

[0734] Step 2:

[0735] The terminal transmits digital audio data to the server via the network. The server receives this digital audio data. The server uses speech recognition software to convert the audio data into text information. The input is digital audio data, and the output is text information converted from the audio.

[0736] Step 3:

[0737] The server passes the converted text information to a natural language processing unit, which analyzes the user's intent. This process involves syntactically analyzing the text data and extracting keywords and phrases to understand the user's request. The input is text information, and the output is data related to the user's intent.

[0738] Step 4:

[0739] The server uses a voice authentication system to verify the user's identity. Input consists of the user's voice characteristics and a pre-set password, while output indicates the authentication success or failure status. Voice identification technology compares the voice data with registered information; authentication is complete if they match.

[0740] Step 5:

[0741] The server references the user's past behavior history to check for any actions that overlap with the newly received intent. The input for this step is the user's intent data, and the output is the result of the duplicate check. This prevents orders that duplicate past actions.

[0742] Step 6:

[0743] If necessary, the server uses a generative AI model to generate a prompt message that asks the user for confirmation. The input is the user's intent and past history information, and the output is the prompt message. For example, a prompt message such as "You have ordered this product before, would you like to order it again?" might be generated.

[0744] Step 7:

[0745] The server monitors communications to detect fraudulent activity. If a fraud risk is detected, the input is the detected suspicious pattern, and the output is a warning message to the user and their associates. Fraud detection algorithms are used to provide real-time notifications.

[0746] Step 8:

[0747] Finally, the server generates a response to the user and sends it to the terminal. The input is the confirmed user intent or the generated prompt, and the output is returned to the terminal as a voice response. The terminal synthesizes this into speech and sends it back to the user, completing the process.

[0748] (Application Example 1)

[0749] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0750] In modern society, elderly people and users unfamiliar with digital technology face the problem of complex operation when using online services. Furthermore, mechanisms to prevent fraud and erroneous orders are insufficient, creating a need for systems that these users can use with peace of mind. Additionally, there is a need for methods that allow for easy order confirmation and completion of orders solely through voice commands.

[0751] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0752] In this invention, the server includes means for receiving voice input from an information processing device available to the user and converting it into digital information, means for selecting products based on voice commands and confirming order details by voice, and means for detecting fraud risks and issuing warnings to the user and related parties. This enables simple and secure online ordering using voice.

[0753] An "information processing device" is a device that receives information as input and generates output by performing various calculations.

[0754] "Voice input" is a method of inputting instructions or information using the user's own voice.

[0755] "Digital information" refers to data that is processed by a computer and represented as an array of bits.

[0756] "Encoded information" refers to data that has been converted from natural language or speech and encoded into an analyzable format.

[0757] "Natural language processing" is a technology that enables computers to understand human language and analyze its meaning.

[0758] "Voice characteristic recognition" is a technology that detects unique features contained in a voice signal to identify an individual.

[0759] A "password" is a secret word or phrase used to grant authentication or access under specific conditions.

[0760] "Activity history" refers to information that stores a record of a user's past actions and operations.

[0761] "Fraud risk" refers to a situation in which there is a possibility of suffering financial or informational damage due to malicious acts.

[0762] A "warning" is a notification or signal that indicates the possibility of danger or a problem occurring.

[0763] "Voice commands" refer to instructions or commands that a user gives to a device using their voice.

[0764] "Order details" refer to information about the products or services that the user wishes to purchase or acquire.

[0765] The system implementing this invention is based on the user performing voice input from an information processing device, such as a smartphone. The voice input data is converted into digital information using the Google Speech-to-Text API. This digital information is transferred to a server and converted into encoded information using natural language processing technology. It is preferable to use the Python NLTK library for natural language processing. The server analyzes this encoded information to identify the user's purpose.

[0766] The server verifies and authenticates the user using voice characteristic recognition and a password. Voice authentication technologies such as Amazon Rekognition can be used as the authentication method, identifying the user from the voice data. In this process, the use of encryption technology is recommended to ensure the protection of the user's personal information.

[0767] The server also has a function to prevent duplicate actions by referring to the user's activity history. For example, it can detect duplicate orders for the same product on different dates and, if necessary, prompt the user with a voice confirmation. In addition, it applies anomaly detection algorithms such as Isolation Forest to detect fraud risks and warn of fraudulent activity in advance.

[0768] For order processing, users can select products based on voice commands and confirm their order details by voice. The system uses the Google Text-to-Speech API to provide voice feedback to the user.

[0769] For example, if a user says, "I want to order a recently popular health supplement," the system analyzes this request, retrieves a list of currently popular health supplements, and verbally communicates the options to the user. Once the order is confirmed, the server completes the transaction.

[0770] Examples of prompts for a generative AI model are as follows:

[0771] "A 50-year-old user is trying to order a new health supplement using voice input. Please provide voice guidance to the user at each step of the ordering process."

[0772] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0773] Step 1:

[0774] The user performs voice input through the device.

[0775] The input is the user's voice, which the device passes to the Google Speech-to-Text API. The API converts the voice into text data. This process makes the voice data available for transmission to the server as text data.

[0776] Step 2:

[0777] The server receives text data and performs natural language processing.

[0778] The input is text data, and the server uses Python's NLTK library for natural language processing. It analyzes the meaning and intent of the text and identifies corresponding instructions and inquiries. This process encapsulates the user's requests and prepares them for the next steps.

[0779] Step 3:

[0780] The server performs user authentication.

[0781] The input is the user's voice characteristics information. The server uses voice authentication technology such as Amazon Rekognition to detect the voice characteristics and compare them with a password. This prevents misrecognition and impersonation, and verifies the user's legitimacy.

[0782] Step 4:

[0783] The server checks the user's activity history to prevent duplicate orders.

[0784] The input consists of past order data, and the server compares it to the current request by referring to the database. If duplicates exist, such as orders for the same product on different dates, the server issues a warning. This process helps prevent incorrect orders.

[0785] Step 5:

[0786] The server processes orders based on voice commands.

[0787] The input is parsed text data that includes the user's intent. The server uses this to search for products in the product database and proceed with the order process. The selected products are provided to the user via voice feedback using the Google Text-to-Speech API. The user confirms the selection, and the final order is confirmed.

[0788] Step 6:

[0789] The server detects fraud risks and issues warnings if necessary.

[0790] The input is all transaction data for an anomaly detection algorithm, and the server applies Isolation Forest and other tools to assess the likelihood of fraud. If suspicious activity is detected, the server sends an alert to the user and their associates for further verification.

[0791] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0792] This invention provides a more user-friendly and secure environment by incorporating emotion recognition capabilities into a system that uses classic communication equipment to support the elderly and those who are digitally vulnerable. This system integrates an emotion engine in addition to voice recognition, natural language processing, identity verification, history management, and fraud prevention functions.

[0793] When a user gives a voice command through a communication terminal, the terminal converts the voice into digital data and sends it to the server. The server converts the voice data into text data and uses natural language processing to analyze the user's intent. In addition, an emotion engine identifies the user's emotions based on the characteristics of the voice. This information is used to dynamically adjust the content of the dialogue.

[0794] User authentication is performed using voice pattern recognition and a passphrase. If authentication is successful, the system checks for duplicate actions by referring to the user's past action history. The server constantly monitors for potential fraud and has a mechanism in place to immediately warn the user and their associates if a risk is detected.

[0795] For example, if a user expresses concern about a delayed delivery, the server uses an emotion engine to recognize the expression of anxiety and, in addition to providing a regular delivery status check, offers detailed explanations and solutions to alleviate reassurance. This allows the user to address the problem with emotional reassurance.

[0796] This system aims to provide users with a more comfortable user experience by enabling personalized responses that take emotions into consideration. Furthermore, by monitoring changes in the user's emotions and automatically notifying relevant parties as needed, it reduces the risks that elderly individuals may encounter in their daily lives.

[0797] The following describes the processing flow.

[0798] Step 1:

[0799] The user gives voice commands to the communication device. For example, they might say, "I want to order supplements."

[0800] Step 2:

[0801] The terminal captures the user's voice signal, converts it into digital data, and then sends it to the server.

[0802] Step 3:

[0803] The server converts the received audio data into text data using a speech recognition system. This text data is then passed to a natural language processing module.

[0804] Step 4:

[0805] The server analyzes text data using natural language processing to identify the user's intent. In this case, it understands the intent to "order supplements."

[0806] Step 5:

[0807] The server also uses an emotion engine to analyze the user's voice and identify emotional states such as feelings of security or anxiety.

[0808] Step 6:

[0809] The server performs authentication using voice pattern recognition and a registered passphrase, and if authentication is successful, it prepares to process the user's request.

[0810] Step 7:

[0811] The server retrieves past order history from the database and checks if there are any duplicate new orders.

[0812] Step 8:

[0813] If a duplicate order is found, or if the server determines that the user's emotional state is unstable, it will generate a response that reflects this. For example, it might suggest, "Would you like to place the same order as last time?" or "Please wait while we check the delivery status in detail."

[0814] Step 9:

[0815] The server assesses fraud risk as needed, issues a warning if fraud is suspected, and automatically notifies registered parties.

[0816] Step 10:

[0817] Once the process is complete, the user will be notified of the results via their device. This notification will include information to reassure the user and explanations of the necessary next steps.

[0818] This process allows users to receive a fast and safe service that is sensitive to their emotions.

[0819] (Example 2)

[0820] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0821] For the elderly and those with limited access to information, there is a need for a system that can establish a simple and secure communication environment through voice, while also providing the flexibility to respond to emotional needs. Existing technologies lack comprehensive integration of emotion recognition, identity verification, and fraud prevention, making it difficult to achieve both usability and security.

[0822] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0823] In this invention, the server includes means for receiving voice input from a communication device available to the user and converting it into numerical data, means for analyzing the numerical data and converting it into character data, and means for analyzing the character data by language processing and identifying the user's intent. This makes it intuitively usable even for the elderly and those with limited access to information, and also enables responses that take emotions into consideration.

[0824] A "communication device" is a device used by a user to input voice data and has the function of sending and receiving information with a server via a communication network.

[0825] "Numerical data" refers to data obtained by converting audio signals into a digital format, and is used for audio analysis.

[0826] "Character data" refers to text-formatted data obtained by analyzing numerical data, and is used in natural language processing.

[0827] "Language processing" is a technology that analyzes user intent based on text data, and includes natural language understanding.

[0828] "Identity verification" is the process of verifying a user's identity using voice patterns or passwords.

[0829] "Operation history" refers to a record of actions a user has taken in the past, which is managed by the system.

[0830] "Fraudulent activity risk" refers to unauthorized operations or fraud that may occur within the system, and is the target of monitoring to detect them.

[0831] "Emotional characteristics" refer to information about the user's emotional state, as determined from factors such as tone and rhythm of voice.

[0832] "Dynamic adjustment of dialogue" is the process of adapting the system's response based on the user's emotions and intentions.

[0833] This invention is a system that enables safe and user-friendly communication for the elderly and those with limited access to information. Specifically, it aims to analyze the user's intentions and emotions from voice input and provide appropriate responses. The following details each component and its operation.

[0834] The terminal receives voice input from the user. In this process, a microphone is used to convert the voice into numerical data, which is then transmitted to a server via a communication network. This conversion is performed using commonly available speech recognition software.

[0835] The server converts the numerical data of the received speech into text data and then uses a natural language processing engine to analyze the user's intent. For this purpose, it utilizes general language processing tools. During this process, an emotion recognition engine analyzes the characteristics of the speech and identifies the user's emotions. Based on this, the server dynamically adjusts its dialogue to provide a response that aligns with the user's emotions.

[0836] For example, if a user expresses anxiety such as "I'm worried because my delivery is delayed," the server will sense this anxiety through emotion recognition. As a result, it will respond in a way that is appropriate to the user's emotions by providing detailed information about the delivery status or sending reassuring messages.

[0837] An example of a prompt message to input into the generating AI model is: "Audio data has been received. The user appears worried. Please check the delivery status and provide reassuring information."

[0838] This invention will realize a safe and emotionally considerate communication system that can be used intuitively by the elderly and those with limited access to information.

[0839] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0840] Step 1:

[0841] The terminal receives voice input from the user. Specifically, the terminal uses a microphone to convert the voice from analog to digital numerical data. The input is an audio signal, and the output is digital numerical data. This data is sent to the server via the communication network for further processing.

[0842] Step 2:

[0843] The server converts received numerical data into character data. This is a process using speech recognition software, where the input is numerical data and the output is character data. Specifically, the server analyzes the numerical data and converts the speech patterns into corresponding strings.

[0844] Step 3:

[0845] The server analyzes text data using a natural language processing engine. The input is text data, and the output is identification data that indicates the user's intent. Specifically, the server performs grammatical analysis and semantic interpretation to identify the intent behind the user's requests and questions.

[0846] Step 4:

[0847] The server uses an emotion recognition engine to identify the user's emotions. Input is data including text data and voice characteristics, and output is data indicating the emotional state. Specifically, the server analyzes the tone and speed of the voice to determine what emotional state the user is in.

[0848] Step 5:

[0849] The server verifies the user's identity and checks the operation history. In this step, a voice pattern and a password are used as input, and the output is the authentication result. Specifically, the server compares the registered pattern with the input and refers to the operation history to detect duplicates and fraudulent activity.

[0850] Step 6:

[0851] The server generates an appropriate response considering the user's emotions and intentions and sends it to the terminal. The input is emotional state and identification data, and the output is a tailored response message. Specifically, the server creates a dialogue message adapted to the user's state and adds contextually relevant information using a generative AI model.

[0852] Step 7:

[0853] The terminal provides the user with received responses via audio or text display. Input is the response message from the server, and output is in a user-understandable format. Specifically, the terminal uses speakers and displays to convey information and support user accessibility.

[0854] (Application Example 2)

[0855] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0856] In brick-and-mortar retail settings, customer service requires flexible and appropriate responses that respond to customer emotions. However, current systems make it difficult to analyze emotions in real time and adjust service accordingly. Furthermore, detailed support for the elderly and those with limited access to information is insufficient. Therefore, a system that comprehensively addresses these issues is necessary.

[0857] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0858] In this invention, the server includes means for receiving voice input from an information terminal available to the user and converting it into digital data, means for analyzing the digital data and converting it into text data, and means for analyzing the emotions in the voice and providing optimal information in accordance with the customer's emotions. This makes it possible to grasp the customer's emotions in real time during customer service operations in physical stores and to provide appropriate information and customer service accordingly.

[0859] An "information terminal" is a device that receives voice input from a user and converts it into digital data.

[0860] "Digital data" refers to a data format converted from analog signals, which can be processed and analyzed by computers.

[0861] "Character data" refers to text-based data generated from digital data through natural language processing.

[0862] "Natural language processing" is a technology that enables computers to understand and analyze human language, allowing them to identify the user's intent.

[0863] "Voice pattern recognition" is a technology that analyzes the characteristics of speech to identify its source, and is used for identity verification.

[0864] A "password" is an encrypted phrase used for user authentication.

[0865] "Action history" refers to a record of actions a user has taken in the past, and is used to prevent future actions from being duplicated.

[0866] "Fraudulent activity" refers to any action or attempt that may deceive or maliciously harm a user.

[0867] "Emotion analysis" is a technology that infers a user's emotional state from their voice or text.

[0868] "Information provision" refers to the act of providing users with the data and explanations they need, tailored to their specific circumstances.

[0869] This invention is a system that highly supports customer service in physical stores. The user wears smart glasses and uses them as an information terminal to receive voice input. The terminal converts the voice spoken by the user into digital data, and this data is sent to a cloud server. The server uses the Google Cloud Speech-to-Text API to convert the digital data into text data.

[0870] The server then uses IBM Watson's natural language understanding service on the converted text data to analyze the user's intent and emotions. This analysis visualizes the emotions in the speech, enabling the provision of appropriate information. For example, if a customer says, "I'm worried about whether this product is easy to use," the server identifies the emotion of anxiety and, based on that, displays usage examples and detailed explanations on the smart glasses' display.

[0871] In this way, sales staff can receive optimal information tailored to the customer's real-time emotional state, enabling more effective customer service. Examples of specific prompt messages include the following:

[0872] Audio data: The customer said, "I'm worried about the usability of a particular product."

[0873] Emotional analysis: Anxiety and identification.

[0874] Recommendation: Display video tutorials on how to use the product on the smart glasses display to provide reassuring information.

[0875] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0876] Step 1:

[0877] The user collects customer voices through smart glasses. The voice input is converted into digital data using the device's microphone. This digital data is sent directly to the cloud server without any editing.

[0878] Step 2:

[0879] The server converts received digital data into text data using the Google Cloud Speech-to-Text API. It receives digital audio data as input and converts it to text using a speech recognition algorithm. The output is text data that accurately represents the audio content.

[0880] Step 3:

[0881] The server analyzes the converted character data using IBM Watson's natural language understanding service. Here, natural language processing is performed using the character data as input to identify the user's intent and emotions. The output generates data representing the identified intent and emotions.

[0882] Step 4:

[0883] The server generates information tailored to the customer's state based on intent and emotion data. It utilizes a generative AI model to create prompts that meet customer needs. For example, if anxiety is detected, it generates information including specific explanations and product usage examples to provide reassurance.

[0884] Step 5:

[0885] The server displays the generated information on the user's smart glasses display. This allows the terminal to receive information from the server as input, display appropriate information on the display based on that input, and create a situation where the user can provide the best possible service to the customer.

[0886] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0887] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0888] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0889] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0890] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0891] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0892] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0893] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0894] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0895] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0896] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0897] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0898] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0899] 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.

[0900] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0901] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0902] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0903] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0904] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0905] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0906] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0907] The following is further disclosed regarding the embodiments described above.

[0908] (Claim 1)

[0909] A means of receiving voice input from a communication terminal available to the user and converting it into digital data,

[0910] A means for analyzing the digital data and converting it into text data,

[0911] A means for analyzing the text data using natural language processing to identify the user's intent,

[0912] A means of authenticating a user using voice pattern recognition and a passphrase,

[0913] A means to prevent duplicate actions by referring to the user's past action history,

[0914] A means of detecting fraud risks and issuing warnings to users and their associates,

[0915] A system that includes this.

[0916] (Claim 2)

[0917] The system according to claim 1, further comprising means for managing orders for goods and services, and for checking and notifying users of the status of those orders.

[0918] (Claim 3)

[0919] The system according to claim 1, further comprising means for receiving inquiries from users regarding their health, lifestyle, and finances, and for generating and responding with appropriate advice.

[0920] "Example 1"

[0921] (Claim 1)

[0922] A means for receiving audio data from an electronic device available to the user and converting it into digital information,

[0923] A means for analyzing the digital information and converting it into text information,

[0924] A means for analyzing the text information using language analysis technology to identify the user's intent,

[0925] A means of authenticating users using voice recognition technology and a password,

[0926] A means to prevent duplicate actions by referring to the user's past behavior history,

[0927] A means of detecting fraudulent activity and issuing warnings to users and their associates,

[0928] A method for using an AI model to dynamically generate query statements based on user input,

[0929] A system that includes this.

[0930] (Claim 2)

[0931] The system according to claim 1, further comprising means for managing orders for products and services, and for checking and notifying users of the status of those orders.

[0932] (Claim 3)

[0933] The system according to claim 1, further comprising means for receiving inquiries from users regarding their health, lifestyle, and finances, and for generating and responding with appropriate guidance.

[0934] "Application Example 1"

[0935] (Claim 1)

[0936] A means for receiving voice input from an information processing device available to the user and converting it into digital information,

[0937] A means for analyzing the digital information and converting it into encoded information,

[0938] A means for analyzing the encoded information using natural language processing to identify the user's purpose,

[0939] A means of verifying and authenticating a user using voice characteristic recognition and a password,

[0940] A means to prevent duplicate activities by referring to the user's past activity history,

[0941] A means of detecting fraud risks and issuing warnings to users and their associates,

[0942] A method for selecting products based on voice commands and confirming order details by voice,

[0943] A system that includes this.

[0944] (Claim 2)

[0945] The system according to claim 1, further comprising means for processing online orders for goods and services for a user, and for confirming and notifying the user of the order history by voice.

[0946] (Claim 3)

[0947] The system according to claim 1, further comprising means for providing advice on all aspects of the user's life using the generated voice output, and supporting the user in being able to operate online with peace of mind.

[0948] "Example 2 of combining an emotion engine"

[0949] (Claim 1)

[0950] A means for receiving voice input from a communication device available to the user and converting it into numerical data,

[0951] A means for analyzing the numerical data and converting it into character data,

[0952] A means for analyzing the character data using language processing to identify the user's intent,

[0953] A method of verifying the user's identity using voice patterns and passwords,

[0954] A means to prevent duplicate operations by referring to the user's past operation history,

[0955] A means of detecting fraudulent activity risks and issuing warnings to users and their associates,

[0956] A means of identifying the user's emotions based on the characteristics of their voice and dynamically adjusting the dialogue using that information,

[0957] A system that includes this.

[0958] (Claim 2)

[0959] The system according to claim 1, further comprising means for managing orders for products and offerings, and for checking and notifying users of the status of those orders.

[0960] (Claim 3)

[0961] The system according to claim 1, further comprising means for receiving inquiries from users regarding their health, lifestyle, and finances, and for generating and responding with appropriate advice.

[0962] "Application example 2 when combining with an emotional engine"

[0963] (Claim 1)

[0964] A means of receiving voice input from an information terminal available to the user and converting it into digital data,

[0965] A means for analyzing the digital data and converting it into text data,

[0966] A means for analyzing the character data using natural language processing to identify the user's intent,

[0967] A means of authenticating a user using voice pattern recognition and a password,

[0968] A means to prevent duplicate actions by referring to the user's past behavior history,

[0969] A means to detect potential fraudulent activity and warn users and their associates,

[0970] A means to analyze emotions in voice and provide optimal information tailored to the customer's emotions,

[0971] A system that includes this.

[0972] (Claim 2)

[0973] The system according to claim 1, further comprising means for managing orders for goods and services, and for checking and notifying users of the status of those orders.

[0974] (Claim 3)

[0975] The system according to claim 1, further comprising means for receiving inquiries from users regarding their health, lifestyle, and finances, and for generating and responding with appropriate advice. [Explanation of symbols]

[0976] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of receiving voice input from a communication terminal available to the user and converting it into digital data, A means for analyzing the digital data and converting it into text data, A means for analyzing the text data using natural language processing to identify the user's intent, A means of authenticating a user using voice pattern recognition and a passphrase, A means to prevent duplicate actions by referring to the user's past action history, A means of detecting fraud risks and issuing warnings to users and their associates, A system that includes this.

2. The system according to claim 1, further comprising means for managing orders for goods and services for users, and for checking and notifying them of the order status.

3. The system according to claim 1, further comprising means for receiving inquiries from users regarding their health, lifestyle, and finances, and for generating and responding with appropriate advice.

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