System

Abstract

A system is provided.SOLUTION: A system including means for acquiring a voice instruction of a user, means for transmitting acquired voice data to a server, the server analyzing the voice data and determining an intention of the user, means for generating payment details based on the intention of the user and confirming the payment details with the user as a voice message, means for acquiring an approval voice from the user, means for transmitting the acquired approval voice to the server, the server analyzing the approval voice and executing payment, and means for notifying the user of payment completion.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional QR code payment systems have the drawback of requiring users to take the time and effort to scan the QR code and enter the amount, placing a significant burden on users. Furthermore, stores are required to perform preparations and confirmation work before the QR code can be presented, resulting in reduced productivity. Furthermore, some users, such as the elderly and visually impaired, often find it difficult to operate QR codes. To address these issues, a new payment system was needed. [Means for solving the problem]

[0005] The present invention solves the above problems by providing a voice payment system that uses voice recognition and natural language processing technologies. Specifically, the system includes a means for acquiring user voice instructions and a means for transmitting the acquired voice data to a server. The server analyzes the voice data and determines the user's intention. It then generates payment details based on the determination result and asks the user for confirmation as a voice message. The system also includes a means for acquiring voice approval from the user and a means for transmitting the acquired voice approval to the server. The server analyzes the voice approval, executes payment based on the results, and notifies the user that payment has been completed. This configuration allows users to make smooth payments using only their voice, eliminating the need to scan a QR code or enter the amount.

[0006] "User" refers to an individual who uses the system to give voice instructions for payment.

[0007] "Voice instruction" refers to a voice instruction given by a user to the system for payment.

[0008] "Terminal" refers to a device that captures the user's voice and transmits it to a server.

[0009] "Voice data" refers to data obtained by converting a user's voice instructions into digital form.

[0010] "Server" refers to a central processing unit that analyzes voice data and executes payments.

[0011] A "voice recognition engine" refers to the technology that converts voice data into text.

[0012] A "natural language processing engine" refers to a technology that analyzes text data and determines the user's intent.

[0013] "Voice message" refers to a message in voice format that is generated by the server and returned to the user.

[0014] "Approval voice" refers to the voice uttered by the user to approve the payment.

[0015] "Payment system" refers to a system for executing payment processing.

[0016] "Notification means" refers to a means for notifying the user that payment has been completed. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0018] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0020] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0021] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0022] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0023] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0025] [First embodiment]

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

[0027] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0034] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] The present invention relates to a voice payment system that utilizes voice recognition technology and natural language processing technology. By allowing users to issue payment instructions by voice, the process of scanning a QR code and entering the amount is eliminated, providing a fast and smooth payment experience.

[0039] System configuration

[0040] This system consists of the following various devices and technologies:

[0041] 1. User: The individual making the payment and issuing the voice command.

[0042] 2. Terminal: The device through which the user issues voice commands, including a smartphone, tablet, or dedicated terminal. The terminal is responsible for capturing the user's voice and sending it to the server.

[0043] 3. Server: Receives the voice data, analyzes it using a voice recognition engine and natural language processing engine, and executes the payment.

[0044] 4. Payment system: This is the system that actually processes payments based on the payment instructions sent from the server.

[0045] Program processing

[0046] 1. Acquiring voice instructions

[0047] The user issues a voice command saying, "Please make payment."

[0048] The terminal captures the user's voice through a microphone and transmits the voice data to a server.

[0049] 2. Analysis of audio data

[0050] The server receives the voice data and converts it into text using a voice recognition engine.

[0051] The server analyzes the converted text using a natural language processing engine to determine the user's intent.

[0052] 3. Confirm payment details

[0053] The server generates a voice message saying, "The payment will be for XX yen. If you agree, please say OK," and sends it to the terminal.

[0054] The terminal plays this voice message and asks the user for confirmation.

[0055] 4. User Acknowledgment

[0056] The user confirms by saying "OK."

[0057] The terminal again captures the user's voice and sends it to the server.

[0058] 5. Execution of payment

[0059] The server receives the voice confirmation and uses the voice recognition engine to convert the voice "OK" into text and confirm it.

[0060] The server instructs the payment system to pay the amount and executes the payment.

[0061] 6. Payment completion notification

[0062] The server confirms the completion of the payment and sends a notification to the terminal that "payment has been completed."

[0063] The terminal plays this voice message to the user to notify them that the payment has been successfully completed.

[0064] Specific examples

[0065] For example, consider the case where a user is shopping at a supermarket and wants to make a payment at the register. The user says, "Please make the payment." The device captures this voice and sends it to the server. The server analyzes the voice data using a voice recognition engine and obtains the text "Please make the payment." It then analyzes the text using a natural language processing engine to confirm the user's intention. It then generates a voice message saying, "I will pay for 3,500 yen. Please say OK if you are happy with this," and sends it to the device. The device plays the message and asks the user for confirmation. When the user says "OK," the device captures the voice again and sends it to the server. After the server confirms the "OK" approval, it carries out the payment and notifies the device that "payment has been completed." The device then plays the message and notifies the user that the payment has been completed.

[0066] This series of processes allows users to complete payments quickly and smoothly using only their voice, eliminating the need to scan a QR code or enter the amount.

[0067] The processing flow will be explained below.

[0068] Program processing details

[0069] Step 1:

[0070] The user issues a voice command saying, "Please make payment."

[0071] Step 2:

[0072] The terminal acquires the user's voice instructions through a microphone.

[0073] Step 3:

[0074] The terminal transmits the acquired voice data to the server.

[0075] Step 4:

[0076] The server converts the received voice data into text using a voice recognition engine.

[0077] Step 5:

[0078] The server analyzes the converted text using a natural language processing engine and determines the user's intent as a "payment instruction."

[0079] Step 6:

[0080] Based on the user's instructions, the server generates a payment confirmation voice message saying, "I will pay for XX yen. If you agree, please say OK."

[0081] Step 7:

[0082] The server sends the generated voice message to the terminal.

[0083] Step 8:

[0084] The terminal plays the voice message received from the server and asks the user for confirmation.

[0085] Step 9:

[0086] The user confirms by saying "OK."

[0087] Step 10:

[0088] The terminal again obtains the user's approval voice.

[0089] Step 11:

[0090] The terminal transmits the acquired approval voice data to the server.

[0091] Step 12:

[0092] The server receives the approval voice data and converts it into text using a voice recognition engine.

[0093] Step 13:

[0094] The server checks the textual approval and determines that it contains "OK."

[0095] Step 14:

[0096] After the server confirms the authorization, it sends an instruction to pay the amount to the payment system.

[0097] Step 15:

[0098] The payment system executes the payment and sends the result back to the server.

[0099] Step 16:

[0100] The server confirms the completion of the payment and generates a voice message saying "Payment completed."

[0101] Step 17:

[0102] The server sends the generated payment completion message to the terminal.

[0103] Step 18:

[0104] The terminal reproduces the payment completion message received from the server and notifies the user.

[0105] Example 1

[0106] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0107] Conventional payment systems require users to scan QR codes or manually enter amounts, making the payment process cumbersome and making it difficult to provide a fast and smooth payment experience. Furthermore, conventional systems have low accuracy in speech recognition and natural language processing, which can easily lead to misrecognition of user intent.

[0108] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0109] In this invention, the server includes means for analyzing voice data and determining the user's intention, means for generating payment details based on the user's intention and confirming them with the user as a voice message, and means for analyzing the approval voice and executing the payment. This allows the user to complete the payment using only voice, eliminating the need to scan a QR code or manually enter the amount, enabling quick and smooth payment. Furthermore, by integrating a voice recognition engine and a natural language processing engine, voice data can be accurately converted and analyzed into text, enabling highly accurate determination of the user's intention.

[0110] A "user" is an individual who operates the system and issues voice commands.

[0111] A "terminal" is a device that acquires the user's voice and transmits the acquired voice data to a server.

[0112] The "server" is a central processing unit that analyzes voice data to determine the user's intentions and executes the payment.

[0113] A "speech recognition engine" is a software or hardware component for converting voice data into text.

[0114] A "natural language processing engine" is a software or hardware component for analyzing text and interpreting user intent.

[0115] A "speech synthesis engine" is a software or hardware component for converting text data into a voice message.

[0116] The "approval voice" is a voice uttered by the user to approve the payment details.

[0117] A "payment system" is a system for executing payments and returning the processing results to the server.

[0118] "Communication means" refers to the technical elements for sending and receiving data between a terminal and a server in real time.

[0119] This invention relates to a voice payment system that utilizes voice recognition and natural language processing technologies. By allowing users to issue payment instructions via voice, it eliminates the need to scan a QR code or input the amount, providing a fast and smooth payment experience. This system is composed of the following various devices and technologies:

[0120] 1. Users

[0121] The user is the individual making the payment and issues instructions to the system by speaking.

[0122] 2. Terminal

[0123] The terminal is the device through which the user issues voice commands, and can be a smartphone, tablet, or dedicated terminal. The terminal has the function of capturing the user's voice through a microphone and sending the voice data to a server. Communication technologies such as WebSocket are used to send and receive voice data in real time.

[0124] 3. Server

[0125] The server analyzes the voice data and determines the user's intent. Specifically, it converts the voice data into text using a speech recognition engine (e.g., Google Cloud Speech-to-Text), analyzes the text using a natural language processing engine (e.g., Google Cloud Natural Language), and interprets the user's intent. The server also generates confirmation and notification messages using a speech synthesis engine (e.g., Google Cloud Text-to-Speech), and sends them to the device.

[0126] 4. Payment System

[0127] A payment system is a system that processes actual payments based on payment instructions sent from a server. Specific examples include online payment platforms such as Stripe and PayPal.

[0128] Specific examples

[0129] For example, consider a case where a user is shopping at a supermarket and wants to pay at the register. The user says, "Please pay." The device captures this speech and sends it to the server. The server analyzes the speech data using Google Cloud Speech-to-Text and obtains the text "Please pay." The text is analyzed using Google Cloud Natural Language to confirm the user's intent. Google Cloud Text-to-Speech then generates a voice message saying, "I'll pay 3,500 yen. If you're happy with this, please say OK," and sends it to the device. The device plays the message and asks the user for confirmation. When the user says "OK," the device captures the speech again and sends it to the server. The server again recognizes it as "OK" using Google Cloud Speech-to-Text and calls the Stripe API to complete the payment. Finally, the server sends a notification to the device stating, "Payment completed," and the device plays the message to the user, completing the payment.

[0130] Example prompt sentence:

[0131] I want to pay by voice at the supermarket checkout. Please follow the instructions below to make a voice payment.

[0132] 1. Say "Please make payment."

[0133] 2. When the payment amount is presented, say "OK."

[0134] In this way, the voice payment system of the present invention allows users to complete payments simply and quickly using only their voice, without the need for complicated operations, thereby simultaneously improving the user experience and streamlining the payment process at stores.

[0135] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0136] Step 1:

[0137] The user gives the command "Please make payment" by voice. The device's built-in microphone picks up the user's voice. This voice data is temporarily stored in the device's local storage. The input is voice data, and the output is an audio file stored on the device. The specific operation uses the smartphone's microphone function.

[0138] Step 2:

[0139] The device compresses the audio data it acquires and sends it to the server. The input is the compressed audio data, and the output is the audio data sent to the server. Specifically, the device sends the data to the server in real time via WebSocket.

[0140] Step 3:

[0141] The server receives the voice data and calls the speech recognition engine (Google Cloud Speech-to-Text). The input is voice data and the output is text data. Specifically, the server sends the voice data to the API and receives a response in text format.

[0142] Step 4:

[0143] The server analyzes the text data using a natural language processing engine (Google Cloud Natural Language) to determine the user's intent. The input is text data converted from speech, and the output is data indicating the user's intent. Specific operations include entity extraction and sentiment analysis, and the system recognizes that the user's instruction is a payment.

[0144] Step 5:

[0145] The server uses a speech synthesis engine (Google Cloud Text-to-Speech) to generate a voice message saying, "I'll pay for XX yen. If you're happy with that, please say OK." The input is the user's intention and amount information, and the output is synthesized voice data. The specific operation is to convert the required text message into an audio file.

[0146] Step 6:

[0147] The server generates a voice message and sends it to the device. The input is synthesized voice data, and the output is the voice data sent to the device. The server then sends the data back to the device using WebSocket.

[0148] Step 7:

[0149] The device plays the received voice message and asks the user for confirmation. The input is the voice data sent from the server, and the output is the voice message being played. Specifically, the message is played using the smartphone's audio player function.

[0150] Step 8:

[0151] The user approves by saying "OK." The device again captures the user's voice and sends it to the server. The input is the approval voice data, and the output is the voice data sent to the server. In concrete terms, the voice data is captured in the same way as in the previous step and sent to the server.

[0152] Step 9:

[0153] The server receives the approval voice and again uses the speech recognition engine to convert the "OK" voice into text and confirm it. The input is the approval voice data and the output is text data. Specifically, the approval voice is sent to the API and a response in text format is received.

[0154] Step 10:

[0155] The server instructs the payment system (such as Stripe or PayPal) to make the payment and executes the payment. The input is the amount and the user's confirmation information, and the output is the payment result data. Specifically, the transaction is processed by calling the payment system's API.

[0156] Step 11:

[0157] The server confirms the completion of the payment, generates a notification "Payment completed" using a speech synthesis engine, and sends it to the terminal. The input is the payment result data, and the output is a synthesized speech notification. Specifically, the speech notification is generated using Google Cloud Text-to-Speech.

[0158] Step 12:

[0159] The terminal plays the received voice message to the user to notify them that the payment has been successfully completed. The input is the voice data sent from the server, and the output is the voice message that is played. Specifically, the notification is made using the smartphone's audio player function.

[0160] (Application example 1)

[0161] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0162] Conventional payment systems require the user to scan a QR code and enter the amount, which can be time-consuming and disruptive to the user's payment experience. Furthermore, manual approval procedures can degrade the user experience. There is a need for technology that can resolve these issues and enable more efficient and faster payments.

[0163] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0164] In this invention, the server includes means for acquiring a user's voice instruction, means for transmitting the acquired voice data to the server, means for analyzing the voice data and determining the user's intention, means for generating payment details based on the user's intention and confirming them as a voice message to the user, means for acquiring voice approval from the user, means for transmitting the acquired voice approval to the server, means for analyzing the voice approval and executing the payment, means for notifying the user that the payment has been completed, means for performing voice recognition and natural language processing via the smart device, and means for generating a voice message using prompt sentences and a generative AI model, thereby enabling the user to complete payment quickly and smoothly using only their voice.

[0165] "User" refers to the person or organization issuing the voice command.

[0166] "Voice instruction" refers to an instruction given by voice to a device by a user.

[0167] A "terminal" is a device that receives a user's voice instructions and transmits them to the server, and includes smartphones, smart glasses, and the like.

[0168] "Server" refers to a computer system that has the function of analyzing acquired voice data, determining the user's intentions, and carrying out payment processing.

[0169] "Audio data" refers to a digital data file that records a user's voice.

[0170] A "voice recognition engine" refers to software or algorithms that analyze voice data and convert it into text.

[0171] A "natural language processing engine" refers to software or algorithms that analyze text data and understand the user's intent and meaning.

[0172] "Payment system" refers to a system that actually processes payments based on user payment instructions.

[0173] "Prompt sentence" refers to the text used to generate a voice message using a generative AI model.

[0174] "Generative AI models" refer to machine learning models or artificial intelligence models used to perform natural language processing.

[0175] A "smart device" is a device for performing voice recognition and natural language processing, including smartphones and smart glasses.

[0176] "Approval voice" refers to voice data uttered by a user when approving payment by voice.

[0177] "Payment completion notification" refers to a notification to inform the user that the payment process has been successfully completed.

[0178] This invention provides a voice payment system that utilizes voice recognition and natural language processing technologies to enable users to make payments quickly and smoothly by voice instructions. This system works in conjunction with a server via a smart device, automating the entire process from voice instructions to payment completion.

[0179] This system consists of the following various devices and technologies:

[0180] 1. User: A person or organization that issues voice commands.

[0181] 2. Terminal: A device that receives the user's voice instructions and sends them to the server, including smartphones, smart glasses, etc.

[0182] 3. Server: A computer system that analyzes voice data, determines the user's intentions, and processes payments.

[0183] 4. Speech recognition engine: Software and algorithms that convert voice data into text.

[0184] 5. Natural language processing engine: Software and algorithms that analyze text data and understand user intent.

[0185] 6. Generative AI models: These are machine learning models used to perform natural language processing.

[0186] 7. Prompt: This is the text used to generate a voice message using the generative AI model.

[0187] System configuration

[0188] 1. Obtaining user voice commands

[0189] The user issues a voice command saying, "Please make payment."

[0190] The terminal receives this audio and transmits the audio data to the server.

[0191] 2. Analysis of audio data

[0192] The server converts the voice data into text using a voice recognition engine.

[0193] The server analyzes the converted text using a natural language processing engine to determine the user's intent.

[0194] 3. Confirm payment details

[0195] The server uses a generative AI model with the prompt sentence to generate a voice message such as, "I'll pay for XX yen. If you agree, please say OK."

[0196] The generated voice message is sent to the terminal.

[0197] The terminal plays this voice message and asks the user for confirmation.

[0198] 4. User Acknowledgment

[0199] The user confirms by saying "OK."

[0200] The terminal again captures the user's voice and transmits it to the server.

[0201] The server analyzes the voice confirmation and again uses a speech recognition engine to convert the voice "OK" into text.

[0202] The server instructs the payment system to pay the amount and executes the payment.

[0203] 5. Payment completion notification

[0204] The server confirms the completion of the payment and sends a notification to the terminal that "payment has been completed."

[0205] The terminal plays this voice message to the user to notify them that the payment has been successfully completed.

[0206] Specific examples

[0207] For example, a user is shopping at a supermarket and says "Please make the payment" at the cash register. The device captures this voice and sends it to the server. The server analyzes the voice data using a voice recognition engine and obtains the text "Please make the payment." It then analyzes the text using a natural language processing engine to confirm the user's intention. It then uses a generative AI model to generate a voice message saying "I will pay 3,500 yen. Please say OK if you are happy with this," and sends it to the device. The device plays the message and asks the user for confirmation. When the user says "OK," the device captures the voice again and sends it to the server. The server again confirms "OK" using its voice recognition engine, then carries out the payment and notifies the device that "payment has been completed." The device then plays back the message, informing the user that the payment has been completed.

[0208] Prompt Sentence Examples

[0209] Say "please pay."

[0210] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0211] Step 1:

[0212] The user issues a voice command saying, "Please make the payment." The terminal captures this voice using the built-in microphone. The captured voice data is saved as digital data within the terminal. The saved data is then sent to the server in the next step.

[0213] Step 2:

[0214] The device sends the acquired voice data to the server. This procedure uses a communication protocol (e.g., HTTP, WebSocket, etc.) to transfer the voice data to the server. The sent data is then passed to the voice recognition engine on the server side.

[0215] Step 3:

[0216] The server converts the voice data into text using a speech recognition engine. The input is voice data and the output is text data. The speech recognition engine analyzes the voice waveform and generates a corresponding string of characters.

[0217] Step 4:

[0218] The server passes the generated text data to a natural language processing engine for analysis. Here, the context and keywords of the text data are analyzed to identify the user's intent. This process recognizes the user's request, "Please make payment." The input is text data, and the output is data that represents the user's intent.

[0219] Step 5:

[0220] The server generates payment details based on the user's intent. It uses a prompt (e.g., "I'll pay 3,500 yen. Please say OK if you agree.") and generates a voice message using a generative AI model. The input is the payment details and the prompt, and the output is a voice message.

[0221] Step 6:

[0222] The server sends the generated voice message to the terminal, and the terminal plays the received voice message to the user. The hardware used here is a speaker, and this prompts the user for confirmation.

[0223] Step 7:

[0224] The user approves by saying "OK." The device again uses the built-in microphone to capture the user's voice and sends the data to the server.

[0225] Step 8:

[0226] The server analyzes the acquired approval voice again using a speech recognition engine and converts the voice "OK" into text. Next, it uses a natural language processing engine to check whether the approval voice contains specific approval keywords. The input is the voice data, and the output is the confirmation result of the approval keyword.

[0227] Step 9:

[0228] When the server confirms the authorization keyword, it instructs the payment system to pay the amount and executes the payment. The payment system then performs the actual payment processing based on this instruction. The input is the result of the authorization keyword confirmation, and the output is the result of the payment completion.

[0229] Step 10:

[0230] When the payment is complete, the server generates a notification saying "Payment completed" and sends it to the terminal. The terminal then plays this notification as a voice message to the user, informing them that the payment has been successfully completed.

[0231] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0232] This invention relates to a voice payment system that utilizes speech recognition, natural language processing, and emotion recognition technologies. By allowing users to issue payment instructions via voice, the system eliminates the need to scan a QR code or enter the amount, providing a fast and smooth payment experience. Furthermore, by recognizing the user's emotions, it is possible to improve the reliability of the payment process and the user experience.

[0233] System configuration

[0234] This system consists of the following various devices and technologies:

[0235] 1. User: The individual making the payment and issuing the voice command.

[0236] 2. Terminal: The device through which the user issues voice commands, including a smartphone, tablet, or dedicated terminal. The terminal is responsible for capturing the user's voice and sending it to the server.

[0237] 3. Server: Receives the voice data, analyzes it using a speech recognition engine, natural language processing engine, and emotion recognition engine, and executes the payment.

[0238] 4. Payment system: This is the system that actually processes payments based on the payment instructions sent from the server.

[0239] Program processing

[0240] 1. Acquiring voice instructions

[0241] The user issues a voice command saying, "Please make payment."

[0242] The terminal captures the user's voice through a microphone and transmits the voice data to a server.

[0243] 2. Analysis of audio data

[0244] The server receives the voice data and converts it into text using a voice recognition engine.

[0245] The server analyzes the converted text using a natural language processing engine and determines the user's intent as a "payment instruction."

[0246] 3. Emotional Recognition

[0247] The server analyzes the voice data using an emotion recognition engine to determine the user's emotions.

[0248] 4. Confirm payment details

[0249] The server takes the user's emotions into consideration and generates an adjusted voice message such as, "I will pay for XX yen. If you agree, please say OK."

[0250] The server sends this voice message to the terminal, which plays the message and asks the user for confirmation.

[0251] 5. User Acknowledgment

[0252] The user confirms by saying "OK."

[0253] The terminal again acquires the user's approval voice and transmits it to the server.

[0254] 6. Acknowledgment Analysis

[0255] The server receives the approval voice and converts it into text using a speech recognition engine.

[0256] The server checks the textual approval and determines that it contains "OK."

[0257] The server also reconfirms the sentiment of the approval voice to determine the certainty of approval.

[0258] 7. Payment Execution

[0259] The server sends a payment instruction to the payment system to execute the payment.

[0260] 8. Payment completion notification

[0261] The server confirms the completion of the payment and generates a voice message saying "Payment completed."

[0262] The server transmits the generated payment completion message to the terminal, and the terminal reproduces the message to notify the user.

[0263] Specific examples

[0264] For example, consider a case where a user places an order at a cafe and wants to pay at the register. The user says, "Please pay." The device captures this voice and sends it to the server. The server analyzes the voice data using a voice recognition engine and obtains the text "Please pay." The natural language processing engine analyzes the text and confirms the user's intention. The server then analyzes the user's emotions using an emotion recognition engine and generates a voice message appropriately adjusted to match the user's emotions: "I will pay 500 yen. Please say OK if you are happy with this," which is sent to the device. The device plays the message and asks the user for confirmation. When the user says "OK," the device captures the voice again and sends it to the server. The server confirms and analyzes the "OK" voice confirmation, then performs the payment and sends a notification to the device stating, "Payment has been completed." The device then plays the message and notifies the user that the payment has been completed.

[0265] This series of processes allows users to complete payments quickly and smoothly, eliminating the need to scan QR codes or enter amounts, and utilizing voice and emotion recognition technology.

[0266] The processing flow will be explained below.

[0267] Program processing details

[0268] Step 1:

[0269] The user issues a voice command saying, "Please make payment."

[0270] Step 2:

[0271] The terminal acquires the user's voice instructions through a microphone.

[0272] Step 3:

[0273] The terminal transmits the acquired voice data to the server.

[0274] Step 4:

[0275] The server converts the received voice data into text using a voice recognition engine.

[0276] Step 5:

[0277] The server runs the converted voice data through a natural language processing engine and determines the user's intent as a "payment instruction."

[0278] Step 6:

[0279] The server runs the voice data through an emotion recognition engine to analyze the user's emotional state.

[0280] Step 7:

[0281] The server generates a voice message based on the user's intention and emotional state, such as "I'll pay for XX yen. Please say OK if you're happy with that." For example, if the user is anxious, the server generates a message in a polite and steady tone.

[0282] Step 8:

[0283] The server sends the generated voice message to the terminal.

[0284] Step 9:

[0285] The terminal plays the voice message received from the server and asks the user for confirmation.

[0286] Step 10:

[0287] The user confirms by saying "OK."

[0288] Step 11:

[0289] The terminal again obtains the user's approval voice.

[0290] Step 12:

[0291] The terminal transmits the acquired approval voice data to the server.

[0292] Step 13:

[0293] The server receives the approval voice data and converts it into text through a voice recognition engine.

[0294] Step 14:

[0295] The server checks the textual approval and determines that it contains "OK."

[0296] Step 15:

[0297] The server runs the approval voice through an emotion recognition engine to check the user's emotional state at the time of approval, for example, checking whether the user is feeling hesitant or anxious.

[0298] Step 16:

[0299] The server determines the authenticity of the authorization and then sends a payment instruction to the payment system.

[0300] Step 17:

[0301] The payment system executes the payment and sends the result back to the server.

[0302] Step 18:

[0303] The server confirms the completion of the payment and generates a "payment completed" notification.

[0304] Step 19:

[0305] The server sends the generated payment completion message to the terminal.

[0306] Step 20:

[0307] The terminal reproduces the payment completion message received from the server and notifies the user.

[0308] Example 2

[0309] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0310] Conventional payment systems require users to perform time-consuming tasks such as scanning QR codes or manually entering the amount. This can make the payment process particularly cumbersome and detract from the user experience. Furthermore, conventional systems have difficulty properly understanding the user's emotions and intentions, making them prone to misrecognition and incorrect operation, especially for inexperienced users. Therefore, there is a need for a user-friendly and reliable payment method that combines voice recognition and emotion recognition.

[0311] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0312] In this invention, the server includes means for analyzing voice data to determine the user's intention, means for analyzing the user's emotions, and means for notifying the user of payment completion. This not only recognizes the user's voice but also analyzes their emotions to generate an appropriate response, enabling a fast and smooth payment.

[0313] A "user" is an individual making a payment and issuing a voice instruction.

[0314] The term "means for acquiring voice instructions" refers to a device and its function for acquiring voices uttered by a user through a microphone.

[0315] "Central Processing Unit" refers to a server or high performance computing device for processing and managing voice data and analysis results.

[0316] "Means for analyzing voice data" refers to a voice recognition module or engine that analyzes the acquired voice data and extracts the necessary information.

[0317] "Means for determining the user's intent" refers to a natural language processing module or software that interprets the user's instructions based on the voice recognition results and determines their intent.

[0318] "Means for confirming to the user as a voice message" refers to a device and software that generates and plays a voice message to ask the user for confirmation.

[0319] "Means for analyzing user emotions" refers to emotion recognition modules or algorithms that identify user emotions from acquired voice data.

[0320] The "means for acquiring voice approval" refers to a device and its function for re-acquiring the voice approval uttered by the user.

[0321] "Means for effecting payments" means a payment system or API that effectuates the payment of amounts based on payment instructions.

[0322] "Means for notifying the user that payment has been completed" refers to a device or system that generates and plays a voice message to inform the user that payment has been completed.

[0323] "Speech Recognition Module" refers to software and hardware capable of converting speech into text.

[0324] A "natural language processing module" refers to software and hardware that has the ability to analyze text data and interpret the user's intentions and requests.

[0325] "Specific approval keywords" refer to predetermined spoken words or phrases that a user utters to indicate approval.

[0326] The "means for transmitting the acquired voice data to the central processing unit" refers to the communication protocol and network infrastructure for transmitting the voice data from the terminal to the central processing unit.

[0327] This invention relates to a voice payment system that utilizes speech recognition, natural language processing, and emotion recognition technologies. By allowing users to issue payment instructions via voice, the system eliminates the need to scan a QR code or enter the amount, providing a fast and smooth payment experience. Furthermore, by recognizing the user's emotions, it is possible to improve the reliability of the payment process and the user experience.

[0328] This system consists of various devices and technologies, such as a user, a device, a server, and a payment system. The device receives voice instructions from the user and sends them to the server. The server converts the voice data into text using a speech recognition engine (e.g., Google Cloud Speech-to-Text). The converted text is analyzed by a natural language processing engine (e.g., OpenAI GPT-4) to determine the user's intention. Furthermore, the user's emotions are analyzed by an emotion recognition engine (e.g., Microsoft Azure Emotion API).

[0329] Specifically, the system operates according to the following procedure.

[0330] When a user issues a voice command such as "please make a payment," the device captures the voice through the microphone and transmits it to the server in real time. The server receives the voice data and converts it into text using Google Cloud Speech-to-Text. The server then analyzes the text using OpenAI GPT-4 and determines that the user's intent is "to make a payment."

[0331] The server then uses the Microsoft Azure Emotion API to perform emotion recognition and determine the user's emotional state. Based on this information, the server generates a tailored voice message, such as "I'll pay you 500 yen. Please say OK if you're happy with this." This message is then sent to the device, which plays it back and asks for the user's confirmation.

[0332] If the user approves by saying "OK," the device captures the speech again and sends it to the server, which again uses Google Cloud Speech-to-Text to convert the speech to text, confirming that "OK" is included, and again uses the emotion recognition engine to determine the certainty of the approval.

[0333] Finally, the server sends a payment instruction to the payment system (e.g., Stripe) to execute the payment. When the payment is complete, the server generates a voice message saying "Payment completed" and sends it to the terminal. The terminal plays the message to notify the user that the payment has been completed.

[0334] As a concrete example, consider a situation where a user places an order at a cafe and pays at the cash register. The user says "Please pay" at the register, and the device captures this voice and sends it to the server. The server analyzes the voice data and generates the text "Please pay." The text is analyzed using a natural language processing engine to confirm the user's intention. An emotion recognition engine then analyzes the user's emotions and generates an appropriate voice message. If the user approves with "OK," the voice data is sent again to the server, and finally the payment is made and a completion notification is sent.

[0335] An example of a prompt sentence to input to the generative AI model is as follows:

[0336] prompt:

[0337] Please explain in detail what happens in a voice payment system when a user says "please pay" at the cash register. Please provide a detailed description of the entire process from when the terminal receives the voice message and sends it to the server, to when the server analyzes and recognizes it and executes the payment.

[0338] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0339] Step 1:

[0340] Acquiring voice commands

[0341] The user issues a voice command saying, "Please make payment."

[0342] Input: User's voice commands

[0343] The device captures the user's voice through a microphone, splits it into fragments in real time, and sends them as data packets to the server via the HTTPS protocol.

[0344] Output: Captured audio data (data packets)

[0345] Step 2:

[0346] Analysis of audio data

[0347] The server receives the audio data and converts it into text using Google Cloud Speech-to-Text.

[0348] Input: Captured audio data (data packets)

[0349] The server runs a voice recognition engine, analyzes the voice data, and generates the text "Please make payment."

[0350] Output: Text data (e.g. "Please make payment")

[0351] Step 3:

[0352] Determining intent

[0353] The text generated by the server is analyzed using OpenAI GPT-4, and the user's intention is determined to be a "payment instruction."

[0354] Input: Text data (e.g. "Please make payment")

[0355] The server uses a natural language processing engine to analyze the context of the text and interpret the intent as "payment instructions."

[0356] Output: User's instructions (e.g. "Payment instructions")

[0357] Step 4:

[0358] Emotion recognition

[0359] The server uses the Microsoft Azure Emotion API to analyze the user's emotions from the voice data.

[0360] Input: Captured audio data (data packets)

[0361] The server extracts features from the voice data and inputs them into an emotion recognition engine to identify emotions such as "joy" or "relief."

[0362] Output: User's emotional data (e.g., "Relief")

[0363] Step 5:

[0364] Confirm payment details

[0365] The server takes the user's emotions into consideration and generates an adjusted voice message such as, "I will pay for XX yen. If you agree, please say OK."

[0366] Input: User instructions, user emotion data (e.g., "Payment instructions," "Relief")

[0367] The server generates a voice message saying, "The payment will be 500 yen. If you agree, please say OK." This message is sent to the terminal, which plays it back.

[0368] Output: The generated voice message

[0369] Step 6:

[0370] User Authorization

[0371] The user confirms by saying "OK."

[0372] Input: A confirmation message from the server

[0373] The terminal captures the user's approval voice through the microphone and transmits it again to the server as a data packet.

[0374] Output: Acquired acknowledgement voice data (data packets)

[0375] Step 7:

[0376] Parsing Authorizations

[0377] The server again converts the approval speech into text using Google Cloud Speech-to-Text.

[0378] Input: Acquired acknowledgement voice data (data packets)

[0379] The server runs a speech recognition engine to analyze the audio data and generate the text "OK," and an emotion recognition engine to ensure that it contains a positive emotion, such as "relief."

[0380] Output: Text data (e.g., "OK"), emotion data (e.g., "Relieved")

[0381] Step 8:

[0382] Executing payments

[0383] The server sends a payment instruction to a payment system such as Stripe or PayPal to execute the payment.

[0384] Input: Text data (e.g., "OK"), user instructions (e.g., "Payment instructions")

[0385] The server sends a request for 500 yen to the payment system via the REST API and receives a success response.

[0386] Output: Payment completion data

[0387] Step 9:

[0388] Payment completion notification

[0389] The server confirms the completion of the payment and generates a voice message saying "Payment completed."

[0390] Input: Payment completion data

[0391] The server generates a voice message saying "Payment completed. Thank you very much" and sends it to the terminal. While the message is played on the terminal, the screen displays "Payment completed."

[0392] Output: The generated voice message

[0393] (Application example 2)

[0394] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0395] Conventional payment systems require users to scan a QR code and input the amount, which is a cumbersome process. Furthermore, even payment systems that use voice instructions have the problem of not being able to fully reflect the user's intentions and emotions, making it difficult to improve reliability and user experience. The present invention aims to solve these problems and provide a new voice payment system that improves user convenience and reliability.

[0396] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring a user's voice instruction, means for transmitting the acquired voice data to the server, means for analyzing the voice data and determining the user's intention, means for generating payment details based on the user's intention and confirming them as a voice message to the user, means for acquiring an approval voice from the user, means for transmitting the acquired approval voice to the server, means for analyzing the approval voice and executing the payment, means for notifying the user of payment completion, means for determining the user's emotion from the voice data, and means for adjusting the confirmation message based on the emotion determination result. This allows the user to avoid scanning a QR code or entering an amount, and enables highly reliable, quick and comfortable payment to be executed through emotion recognition.

[0397] A "means for obtaining voice instructions" is a device or system for collecting voice commands uttered by a user.

[0398] The "means for transmitting voice data to a server" refers to a device or system that has the function of transferring acquired voice information to a server via a network.

[0399] "Means for analyzing voice data and determining user intent" refers to an algorithm or engine that extracts text from voice data and interprets the user's requests and intent based on that text.

[0400] The "means for generating payment details and confirming them to the user as a voice message" is a system for creating payment details based on text data and playing them back as voice.

[0401] The "means for acquiring approval voice" is a device or system for collecting approval voice uttered by a user.

[0402] The "means for transmitting the acquired approval voice to the server" refers to a device or system that has the function of transferring the user's approval voice to the server via a network.

[0403] The "means for analyzing the approval voice and executing the payment" refers to an algorithm and system for converting the user's approval voice into text and completing the payment process based on that text.

[0404] The "means for notifying the user of the completion of the payment" is a system that generates and plays a voice message to notify the user that the payment has been successfully completed.

[0405] The "means for determining the user's emotion from the voice data" refers to an algorithm or engine for analyzing the emotional information contained in the voice data and identifying the user's emotional state.

[0406] The "means for adjusting the confirmation message based on the emotion determination result" is a system for appropriately changing the content and tone of the confirmation message depending on the user's emotional state.

[0407] This invention relates to a voice payment system that utilizes speech recognition, natural language processing, and emotion recognition technologies. This system allows users to issue payment instructions via voice, eliminating the need to scan a QR code or enter the amount, and providing a fast and smooth payment experience. Furthermore, by recognizing the user's emotions, it is possible to improve the reliability of the payment process and the user experience.

[0408] The system includes the following components:

[0409] 1. User: The individual making the payment and issuing the voice command.

[0410] 2. Terminal: The device through which the user issues voice commands, including a smartphone, tablet, or dedicated terminal. The terminal is responsible for capturing the user's voice and sending it to the server.

[0411] 3. Server: Receives the voice data, analyzes it using a speech recognition engine, natural language processing engine, and emotion recognition engine, and executes the payment.

[0412] 4. Payment system: This is the system that actually processes payments based on the payment instructions sent from the server.

[0413] Program processing

[0414] 1. Acquiring voice instructions

[0415] The user issues a voice command such as "Please make the payment." The device picks up this voice using the built-in microphone and sends the voice data to the cloud server.

[0416] 2. Analysis of audio data

[0417] The server analyzes the acquired voice data using a speech recognition engine (e.g., Google Cloud Speech-to-Text API) and converts it into text data. It then analyzes the text using a natural language processing engine (e.g., Google Cloud Natural Language API) to determine the user's intent.

[0418] 3. Emotional Recognition

[0419] The server analyzes the voice data using an emotion recognition engine (e.g., IBM Watson Tone Analyzer) to determine the user's emotions.

[0420] 4. Confirm payment details

[0421] The server generates an adjusted confirmation message, "I will pay for XX yen. Please say OK if you agree," taking into account the user's feelings, and sends it to the terminal. The terminal plays this message and asks the user for confirmation.

[0422] 5. User Acknowledgment

[0423] The user approves by saying "OK." The device reacquires the approval voice and sends it to the server.

[0424] 6. Acknowledgment Analysis

[0425] The server converts the received approval voice into text using a speech recognition engine, checks whether it contains "OK," and then checks the emotion of the approval voice again.

[0426] 7. Payment Execution

[0427] The server sends a payment instruction to the payment system (e.g. Stripe API) to execute the payment.

[0428] 8. Payment completion notification

[0429] The server confirms the completion of the payment and generates a voice message saying "Payment completed." The terminal plays this message to notify the user.

[0430] Specific examples

[0431] For example, after a user finishes shopping at a supermarket, they open a smartphone app and say, "Please make the payment." The device receives this instruction and sends the voice data to the server. The server then analyzes the voice data using a speech recognition engine and converts it into text. It then uses a natural language processing engine to determine the user's intent when they say, "Please make the payment." It then uses an emotion recognition engine to analyze the user's emotion from the voice data. Based on these analysis results, the device generates a tailored confirmation message, such as, "I'll pay 500 yen. Please say OK if you're happy with this," and sends it to the device. The device then plays this message to ask the user for confirmation. When the user replies, "OK," the voice is sent again to the server, where the approval voice is analyzed, confirming that it contains "OK," and the emotion is also reconfirmed. A payment instruction is then sent to the payment system, and the payment is executed. Finally, the user is notified that the payment has been completed.

[0432] Example prompts to input to the generative AI model

[0433] When you say "please pay," it uses speech recognition, natural language processing, and emotion recognition technologies to analyze your spoken payment instructions and complete the payment on your smartphone. Based on emotion recognition, it provides feedback to improve the user experience.

[0434] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0435] Step 1:

[0436] Acquiring voice commands

[0437] Input: A user speaks the command "please pay."

[0438] Specific operation: The user speaks into the microphone on the device (smartphone, tablet, etc.) saying "Please make payment."

[0439] Output: The device uses a built-in microphone to capture audio data, which is then converted into a digital format and sent directly to the server.

[0440] Step 2:

[0441] Sending audio data to the server

[0442] Input: Audio data captured by the device.

[0443] Specific operation: The device sends the acquired voice data to a cloud server via the network (Wi-Fi or 4G / 5G communication).

[0444] Output: The server receives the audio data sent from the terminal.

[0445] Step 3:

[0446] Analysis of audio data

[0447] Input: The audio data received by the server.

[0448] How it works: The server uses a speech recognition engine (e.g., Google Cloud Speech-to-Text API) to convert the voice data into text, which is then analyzed by a natural language processing engine (e.g., Google Cloud Natural Language API) to determine the user's intent (e.g., "please make payment").

[0449] Output: Text data as the analysis result and the user's intent.

[0450] Step 4:

[0451] Emotion recognition

[0452] Input: The audio data received by the server.

[0453] Specific operation: The server uses an emotion recognition engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotions from the voice data. This analysis evaluates whether the user is relaxed or stressed.

[0454] Output: Emotion data as the analysis result (e.g., relaxed, stressed, etc.).

[0455] Step 5:

[0456] Confirm payment details

[0457] Input: Text data and emotion data as analysis results.

[0458] Specific operation: The server generates a tailored confirmation message (e.g., "I will pay 500 yen. Please say OK if you agree") taking into account the user's feelings. It then sends this message to the terminal.

[0459] Output: The generated confirmation message and its transmission from the server.

[0460] Step 6:

[0461] Play confirmation message

[0462] Input: The confirmation message sent by the server.

[0463] Specific operation: The terminal plays a voice message and asks the user for confirmation (e.g., "The payment amount is 500 yen. Please say OK if you agree").

[0464] Output: An audio message is played to the user.

[0465] Step 7:

[0466] User Authorization

[0467] Input: The user's voice command after hearing the confirmation message (e.g., "OK").

[0468] Specific operation: The user approves by saying "OK" into the device's microphone. The device captures this voice and sends it back to the server.

[0469] Output: The acknowledgement voice acquired by the device is sent to the server.

[0470] Step 8:

[0471] Analysis of approval voice

[0472] Input: The acknowledgment audio sent to the server.

[0473] Specific operation: The server again uses the speech recognition engine to convert the approval voice into text and checks whether it contains "OK." It then uses the emotion recognition engine to check the emotion of the approval voice again.

[0474] Output: Text data and emotion data as analysis results.

[0475] Step 9:

[0476] Executing payments

[0477] Input: Approval data and emotion data as analysis results.

[0478] Specific operation: The server sends a payment instruction to the payment system (e.g. Stripe API) to execute the payment.

[0479] Output: The result of the payment execution (success or failure).

[0480] Step 10:

[0481] Payment completion notification

[0482] Input: Payment execution result.

[0483] Specific operation: The server confirms the completion of the payment, generates a voice message saying "Payment completed" and sends it to the terminal. The terminal plays this message to notify the user.

[0484] Output: A payment completion message is played to the user.

[0485] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0486] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0487] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0488] [Second embodiment]

[0489] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0490] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0491] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0492] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0493] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0494] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0495] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0496] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0497] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0498] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0499] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0500] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0501] The present invention relates to a voice payment system that utilizes voice recognition technology and natural language processing technology. By allowing users to issue payment instructions by voice, the process of scanning a QR code and entering the amount is eliminated, providing a fast and smooth payment experience.

[0502] System configuration

[0503] This system consists of the following various devices and technologies:

[0504] 1. User: The individual making the payment and issuing the voice command.

[0505] 2. Terminal: The device through which the user issues voice commands, including a smartphone, tablet, or dedicated terminal. The terminal is responsible for capturing the user's voice and sending it to the server.

[0506] 3. Server: Receives the voice data, analyzes it using a voice recognition engine and natural language processing engine, and executes the payment.

[0507] 4. Payment system: This is the system that actually processes payments based on the payment instructions sent from the server.

[0508] Program processing

[0509] 1. Acquiring voice instructions

[0510] The user issues a voice command saying, "Please make payment."

[0511] The terminal captures the user's voice through a microphone and transmits the voice data to a server.

[0512] 2. Analysis of audio data

[0513] The server receives the voice data and converts it into text using a voice recognition engine.

[0514] The server analyzes the converted text using a natural language processing engine to determine the user's intent.

[0515] 3. Confirm payment details

[0516] The server generates a voice message saying, "The payment will be for XX yen. If you agree, please say OK," and sends it to the terminal.

[0517] The terminal plays this voice message and asks the user for confirmation.

[0518] 4. User Acknowledgment

[0519] The user confirms by saying "OK."

[0520] The terminal again captures the user's voice and sends it to the server.

[0521] 5. Execution of payment

[0522] The server receives the voice confirmation and uses the voice recognition engine to convert the voice "OK" into text and confirm it.

[0523] The server instructs the payment system to pay the amount and executes the payment.

[0524] 6. Payment completion notification

[0525] The server confirms the completion of the payment and sends a notification to the terminal that "payment has been completed."

[0526] The terminal plays this voice message to the user to notify them that the payment has been successfully completed.

[0527] Specific examples

[0528] For example, consider the case where a user is shopping at a supermarket and wants to make a payment at the register. The user says, "Please make the payment." The device captures this voice and sends it to the server. The server analyzes the voice data using a voice recognition engine and obtains the text "Please make the payment." It then analyzes the text using a natural language processing engine to confirm the user's intention. It then generates a voice message saying, "I will pay for 3,500 yen. Please say OK if you are happy with this," and sends it to the device. The device plays the message and asks the user for confirmation. When the user says "OK," the device captures the voice again and sends it to the server. After the server confirms the "OK" approval, it carries out the payment and notifies the device that "payment has been completed." The device then plays the message and notifies the user that the payment has been completed.

[0529] This series of processes allows users to complete payments quickly and smoothly using only their voice, eliminating the need to scan a QR code or enter the amount.

[0530] The processing flow will be explained below.

[0531] Program processing details

[0532] Step 1:

[0533] The user issues a voice command saying, "Please make payment."

[0534] Step 2:

[0535] The terminal acquires the user's voice instructions through a microphone.

[0536] Step 3:

[0537] The terminal transmits the acquired voice data to the server.

[0538] Step 4:

[0539] The server converts the received voice data into text using a voice recognition engine.

[0540] Step 5:

[0541] The server analyzes the converted text using a natural language processing engine and determines the user's intent as a "payment instruction."

[0542] Step 6:

[0543] Based on the user's instructions, the server generates a payment confirmation voice message saying, "I will pay for XX yen. If you agree, please say OK."

[0544] Step 7:

[0545] The server sends the generated voice message to the terminal.

[0546] Step 8:

[0547] The terminal plays the voice message received from the server and asks the user for confirmation.

[0548] Step 9:

[0549] The user confirms by saying "OK."

[0550] Step 10:

[0551] The terminal again obtains the user's approval voice.

[0552] Step 11:

[0553] The terminal transmits the acquired approval voice data to the server.

[0554] Step 12:

[0555] The server receives the approval voice data and converts it into text using a voice recognition engine.

[0556] Step 13:

[0557] The server checks the textual approval and determines that it contains "OK."

[0558] Step 14:

[0559] After the server confirms the authorization, it sends an instruction to pay the amount to the payment system.

[0560] Step 15:

[0561] The payment system executes the payment and sends the result back to the server.

[0562] Step 16:

[0563] The server confirms the completion of the payment and generates a voice message saying "Payment completed."

[0564] Step 17:

[0565] The server sends the generated payment completion message to the terminal.

[0566] Step 18:

[0567] The terminal reproduces the payment completion message received from the server and notifies the user.

[0568] Example 1

[0569] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0570] Conventional payment systems require users to scan QR codes or manually enter amounts, making the payment process cumbersome and making it difficult to provide a fast and smooth payment experience. Furthermore, conventional systems have low accuracy in speech recognition and natural language processing, which can easily lead to misrecognition of user intent.

[0571] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0572] In this invention, the server includes means for analyzing voice data and determining the user's intention, means for generating payment details based on the user's intention and confirming them with the user as a voice message, and means for analyzing the approval voice and executing the payment. This allows the user to complete the payment using only voice, eliminating the need to scan a QR code or manually enter the amount, enabling quick and smooth payment. Furthermore, by integrating a voice recognition engine and a natural language processing engine, voice data can be accurately converted and analyzed into text, enabling highly accurate determination of the user's intention.

[0573] A "user" is an individual who operates the system and issues voice commands.

[0574] A "terminal" is a device that acquires the user's voice and transmits the acquired voice data to a server.

[0575] The "server" is a central processing unit that analyzes voice data to determine the user's intentions and executes the payment.

[0576] A "speech recognition engine" is a software or hardware component for converting voice data into text.

[0577] A "natural language processing engine" is a software or hardware component for analyzing text and interpreting user intent.

[0578] A "speech synthesis engine" is a software or hardware component for converting text data into a voice message.

[0579] The "approval voice" is a voice uttered by the user to approve the payment details.

[0580] A "payment system" is a system for executing payments and returning the processing results to the server.

[0581] "Communication means" refers to the technical elements for sending and receiving data between a terminal and a server in real time.

[0582] This invention relates to a voice payment system that utilizes voice recognition and natural language processing technologies. By allowing users to issue payment instructions via voice, it eliminates the need to scan a QR code or input the amount, providing a fast and smooth payment experience. This system is composed of the following various devices and technologies:

[0583] 1. Users

[0584] The user is the individual making the payment and issues instructions to the system by speaking.

[0585] 2. Terminal

[0586] The terminal is the device through which the user issues voice commands, and can be a smartphone, tablet, or dedicated terminal. The terminal has the function of capturing the user's voice through a microphone and sending the voice data to a server. Communication technologies such as WebSocket are used to send and receive voice data in real time.

[0587] 3. Server

[0588] The server analyzes the voice data and determines the user's intent. Specifically, it converts the voice data into text using a speech recognition engine (e.g., Google Cloud Speech-to-Text), analyzes the text using a natural language processing engine (e.g., Google Cloud Natural Language), and interprets the user's intent. The server also generates confirmation and notification messages using a speech synthesis engine (e.g., Google Cloud Text-to-Speech), and sends them to the device.

[0589] 4. Payment System

[0590] A payment system is a system that processes actual payments based on payment instructions sent from a server. Specific examples include online payment platforms such as Stripe and PayPal.

[0591] Specific examples

[0592] For example, consider a case where a user is shopping at a supermarket and wants to pay at the register. The user says, "Please pay." The device captures this speech and sends it to the server. The server analyzes the speech data using Google Cloud Speech-to-Text and obtains the text "Please pay." The text is analyzed using Google Cloud Natural Language to confirm the user's intent. Google Cloud Text-to-Speech then generates a voice message saying, "I'll pay 3,500 yen. If you're happy with this, please say OK," and sends it to the device. The device plays the message and asks the user for confirmation. When the user says "OK," the device captures the speech again and sends it to the server. The server again recognizes it as "OK" using Google Cloud Speech-to-Text and calls the Stripe API to complete the payment. Finally, the server sends a notification to the device stating, "Payment completed," and the device plays the message to the user, completing the payment.

[0593] Example prompt sentence:

[0594] I want to pay by voice at the supermarket checkout. Please follow the instructions below to make a voice payment.

[0595] 1. Say "Please make payment."

[0596] 2. When the payment amount is presented, say "OK."

[0597] In this way, the voice payment system of the present invention allows users to complete payments simply and quickly using only their voice, without the need for complicated operations, thereby simultaneously improving the user experience and streamlining the payment process at stores.

[0598] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0599] Step 1:

[0600] The user gives the command "Please make payment" by voice. The device's built-in microphone picks up the user's voice. This voice data is temporarily stored in the device's local storage. The input is voice data, and the output is an audio file stored on the device. The specific operation uses the smartphone's microphone function.

[0601] Step 2:

[0602] The device compresses the audio data it acquires and sends it to the server. The input is the compressed audio data, and the output is the audio data sent to the server. Specifically, the device sends the data to the server in real time via WebSocket.

[0603] Step 3:

[0604] The server receives the voice data and calls the speech recognition engine (Google Cloud Speech-to-Text). The input is voice data and the output is text data. Specifically, the server sends the voice data to the API and receives a response in text format.

[0605] Step 4:

[0606] The server analyzes the text data using a natural language processing engine (Google Cloud Natural Language) to determine the user's intent. The input is text data converted from speech, and the output is data indicating the user's intent. Specific operations include entity extraction and sentiment analysis, and the system recognizes that the user's instruction is a payment.

[0607] Step 5:

[0608] The server uses a speech synthesis engine (Google Cloud Text-to-Speech) to generate a voice message saying, "I'll pay for XX yen. If you're happy with that, please say OK." The input is the user's intention and amount information, and the output is synthesized voice data. The specific operation is to convert the required text message into an audio file.

[0609] Step 6:

[0610] The server generates a voice message and sends it to the device. The input is synthesized voice data, and the output is the voice data sent to the device. The server then sends the data back to the device using WebSocket.

[0611] Step 7:

[0612] The device plays the received voice message and asks the user for confirmation. The input is the voice data sent from the server, and the output is the voice message being played. Specifically, the message is played using the smartphone's audio player function.

[0613] Step 8:

[0614] The user approves by saying "OK." The device again captures the user's voice and sends it to the server. The input is the approval voice data, and the output is the voice data sent to the server. In concrete terms, the voice data is captured in the same way as in the previous step and sent to the server.

[0615] Step 9:

[0616] The server receives the approval voice and again uses the speech recognition engine to convert the "OK" voice into text and confirm it. The input is the approval voice data and the output is text data. Specifically, the approval voice is sent to the API and a response in text format is received.

[0617] Step 10:

[0618] The server instructs the payment system (such as Stripe or PayPal) to make the payment and executes the payment. The input is the amount and the user's confirmation information, and the output is the payment result data. Specifically, the transaction is processed by calling the payment system's API.

[0619] Step 11:

[0620] The server confirms the completion of the payment, generates a notification "Payment completed" using a speech synthesis engine, and sends it to the terminal. The input is the payment result data, and the output is a synthesized speech notification. Specifically, the speech notification is generated using Google Cloud Text-to-Speech.

[0621] Step 12:

[0622] The terminal plays the received voice message to the user to notify them that the payment has been successfully completed. The input is the voice data sent from the server, and the output is the voice message that is played. Specifically, the notification is made using the smartphone's audio player function.

[0623] (Application example 1)

[0624] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0625] Conventional payment systems require the user to scan a QR code and enter the amount, which can be time-consuming and disruptive to the user's payment experience. Furthermore, manual approval procedures can degrade the user experience. There is a need for technology that can resolve these issues and enable more efficient and faster payments.

[0626] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0627] In this invention, the server includes means for acquiring a user's voice instruction, means for transmitting the acquired voice data to the server, means for analyzing the voice data and determining the user's intention, means for generating payment details based on the user's intention and confirming them as a voice message to the user, means for acquiring voice approval from the user, means for transmitting the acquired voice approval to the server, means for analyzing the voice approval and executing the payment, means for notifying the user that the payment has been completed, means for performing voice recognition and natural language processing via the smart device, and means for generating a voice message using prompt sentences and a generative AI model, thereby enabling the user to complete payment quickly and smoothly using only their voice.

[0628] "User" refers to the person or organization issuing the voice command.

[0629] "Voice instruction" refers to an instruction given by voice to a device by a user.

[0630] A "terminal" is a device that receives a user's voice instructions and transmits them to the server, and includes smartphones, smart glasses, and the like.

[0631] "Server" refers to a computer system that has the function of analyzing acquired voice data, determining the user's intentions, and carrying out payment processing.

[0632] "Audio data" refers to a digital data file that records a user's voice.

[0633] A "voice recognition engine" refers to software or algorithms that analyze voice data and convert it into text.

[0634] A "natural language processing engine" refers to software or algorithms that analyze text data and understand the user's intent and meaning.

[0635] "Payment system" refers to a system that actually processes payments based on user payment instructions.

[0636] "Prompt sentence" refers to the text used to generate a voice message using a generative AI model.

[0637] "Generative AI models" refer to machine learning models or artificial intelligence models used to perform natural language processing.

[0638] A "smart device" is a device for performing voice recognition and natural language processing, including smartphones and smart glasses.

[0639] "Approval voice" refers to voice data uttered by a user when approving payment by voice.

[0640] "Payment completion notification" refers to a notification to inform the user that the payment process has been successfully completed.

[0641] This invention provides a voice payment system that utilizes voice recognition and natural language processing technologies to enable users to make payments quickly and smoothly by voice instructions. This system works in conjunction with a server via a smart device, automating the entire process from voice instructions to payment completion.

[0642] This system consists of the following various devices and technologies:

[0643] 1. User: A person or organization that issues voice commands.

[0644] 2. Terminal: A device that receives the user's voice instructions and sends them to the server, including smartphones, smart glasses, etc.

[0645] 3. Server: A computer system that analyzes voice data, determines the user's intentions, and processes payments.

[0646] 4. Speech recognition engine: Software and algorithms that convert voice data into text.

[0647] 5. Natural language processing engine: Software and algorithms that analyze text data and understand user intent.

[0648] 6. Generative AI models: These are machine learning models used to perform natural language processing.

[0649] 7. Prompt: This is the text used to generate a voice message using the generative AI model.

[0650] System configuration

[0651] 1. Obtaining user voice commands

[0652] The user issues a voice command saying, "Please make payment."

[0653] The terminal receives this audio and transmits the audio data to the server.

[0654] 2. Analysis of audio data

[0655] The server converts the voice data into text using a voice recognition engine.

[0656] The server analyzes the converted text using a natural language processing engine to determine the user's intent.

[0657] 3. Confirm payment details

[0658] The server uses a generative AI model with the prompt sentence to generate a voice message such as, "I'll pay for XX yen. If you agree, please say OK."

[0659] The generated voice message is sent to the terminal.

[0660] The terminal plays this voice message and asks the user for confirmation.

[0661] 4. User Acknowledgment

[0662] The user confirms by saying "OK."

[0663] The terminal again captures the user's voice and transmits it to the server.

[0664] The server analyzes the voice confirmation and again uses a speech recognition engine to convert the voice "OK" into text.

[0665] The server instructs the payment system to pay the amount and executes the payment.

[0666] 5. Payment completion notification

[0667] The server confirms the completion of the payment and sends a notification to the terminal that "payment has been completed."

[0668] The terminal plays this voice message to the user to notify them that the payment has been successfully completed.

[0669] Specific examples

[0670] For example, a user is shopping at a supermarket and says "Please make the payment" at the cash register. The device captures this voice and sends it to the server. The server analyzes the voice data using a voice recognition engine and obtains the text "Please make the payment." It then analyzes the text using a natural language processing engine to confirm the user's intention. It then uses a generative AI model to generate a voice message saying "I will pay 3,500 yen. Please say OK if you are happy with this," and sends it to the device. The device plays the message and asks the user for confirmation. When the user says "OK," the device captures the voice again and sends it to the server. The server again confirms "OK" using its voice recognition engine, then carries out the payment and notifies the device that "payment has been completed." The device then plays back the message, informing the user that the payment has been completed.

[0671] Prompt Sentence Examples

[0672] Say "please pay."

[0673] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0674] Step 1:

[0675] The user issues a voice command saying, "Please make the payment." The terminal captures this voice using the built-in microphone. The captured voice data is saved as digital data within the terminal. The saved data is then sent to the server in the next step.

[0676] Step 2:

[0677] The device sends the acquired voice data to the server. This procedure uses a communication protocol (e.g., HTTP, WebSocket, etc.) to transfer the voice data to the server. The sent data is then passed to the voice recognition engine on the server side.

[0678] Step 3:

[0679] The server converts the voice data into text using a speech recognition engine. The input is voice data and the output is text data. The speech recognition engine analyzes the voice waveform and generates a corresponding string of characters.

[0680] Step 4:

[0681] The server passes the generated text data to a natural language processing engine for analysis. Here, the context and keywords of the text data are analyzed to identify the user's intent. This process recognizes the user's request, "Please make payment." The input is text data, and the output is data that represents the user's intent.

[0682] Step 5:

[0683] The server generates payment details based on the user's intent. It uses a prompt (e.g., "I'll pay 3,500 yen. Please say OK if you agree.") and generates a voice message using a generative AI model. The input is the payment details and the prompt, and the output is a voice message.

[0684] Step 6:

[0685] The server sends the generated voice message to the terminal, and the terminal plays the received voice message to the user. The hardware used here is a speaker, and this prompts the user for confirmation.

[0686] Step 7:

[0687] The user approves by saying "OK." The device again uses the built-in microphone to capture the user's voice and sends the data to the server.

[0688] Step 8:

[0689] The server analyzes the acquired approval voice again using a speech recognition engine and converts the voice "OK" into text. Next, it uses a natural language processing engine to check whether the approval voice contains specific approval keywords. The input is the voice data, and the output is the confirmation result of the approval keyword.

[0690] Step 9:

[0691] When the server confirms the authorization keyword, it instructs the payment system to pay the amount and executes the payment. The payment system then performs the actual payment processing based on this instruction. The input is the result of the authorization keyword confirmation, and the output is the result of the payment completion.

[0692] Step 10:

[0693] When the payment is complete, the server generates a notification saying "Payment completed" and sends it to the terminal. The terminal then plays this notification as a voice message to the user, informing them that the payment has been successfully completed.

[0694] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0695] This invention relates to a voice payment system that utilizes speech recognition, natural language processing, and emotion recognition technologies. By allowing users to issue payment instructions via voice, the system eliminates the need to scan a QR code or enter the amount, providing a fast and smooth payment experience. Furthermore, by recognizing the user's emotions, it is possible to improve the reliability of the payment process and the user experience.

[0696] System configuration

[0697] This system consists of the following various devices and technologies:

[0698] 1. User: The individual making the payment and issuing the voice command.

[0699] 2. Terminal: The device through which the user issues voice commands, including a smartphone, tablet, or dedicated terminal. The terminal is responsible for capturing the user's voice and sending it to the server.

[0700] 3. Server: Receives the voice data, analyzes it using a speech recognition engine, natural language processing engine, and emotion recognition engine, and executes the payment.

[0701] 4. Payment system: This is the system that actually processes payments based on the payment instructions sent from the server.

[0702] Program processing

[0703] 1. Acquiring voice instructions

[0704] The user issues a voice command saying, "Please make payment."

[0705] The terminal captures the user's voice through a microphone and transmits the voice data to a server.

[0706] 2. Analysis of audio data

[0707] The server receives the voice data and converts it into text using a voice recognition engine.

[0708] The server analyzes the converted text using a natural language processing engine and determines the user's intent as a "payment instruction."

[0709] 3. Emotional Recognition

[0710] The server analyzes the voice data using an emotion recognition engine to determine the user's emotions.

[0711] 4. Confirm payment details

[0712] The server takes the user's emotions into consideration and generates an adjusted voice message such as, "I will pay for XX yen. If you agree, please say OK."

[0713] The server sends this voice message to the terminal, which plays the message and asks the user for confirmation.

[0714] 5. User Acknowledgment

[0715] The user confirms by saying "OK."

[0716] The terminal again acquires the user's approval voice and transmits it to the server.

[0717] 6. Acknowledgment Analysis

[0718] The server receives the approval voice and converts it into text using a speech recognition engine.

[0719] The server checks the textual approval and determines that it contains "OK."

[0720] The server also reconfirms the sentiment of the approval voice to determine the certainty of approval.

[0721] 7. Payment Execution

[0722] The server sends a payment instruction to the payment system to execute the payment.

[0723] 8. Payment completion notification

[0724] The server confirms the completion of the payment and generates a voice message saying "Payment completed."

[0725] The server transmits the generated payment completion message to the terminal, and the terminal reproduces the message to notify the user.

[0726] Specific examples

[0727] For example, consider a case where a user places an order at a cafe and wants to pay at the register. The user says, "Please pay." The device captures this voice and sends it to the server. The server analyzes the voice data using a voice recognition engine and obtains the text "Please pay." The natural language processing engine analyzes the text and confirms the user's intention. The server then analyzes the user's emotions using an emotion recognition engine and generates a voice message appropriately adjusted to match the user's emotions: "I will pay 500 yen. Please say OK if you are happy with this," which is sent to the device. The device plays the message and asks the user for confirmation. When the user says "OK," the device captures the voice again and sends it to the server. The server confirms and analyzes the "OK" voice confirmation, then performs the payment and sends a notification to the device stating, "Payment has been completed." The device then plays the message and notifies the user that the payment has been completed.

[0728] This series of processes allows users to complete payments quickly and smoothly, eliminating the need to scan QR codes or enter amounts, and utilizing voice and emotion recognition technology.

[0729] The processing flow will be explained below.

[0730] Program processing details

[0731] Step 1:

[0732] The user issues a voice command saying, "Please make payment."

[0733] Step 2:

[0734] The terminal acquires the user's voice instructions through a microphone.

[0735] Step 3:

[0736] The terminal transmits the acquired voice data to the server.

[0737] Step 4:

[0738] The server converts the received voice data into text using a voice recognition engine.

[0739] Step 5:

[0740] The server runs the converted voice data through a natural language processing engine and determines the user's intent as a "payment instruction."

[0741] Step 6:

[0742] The server runs the voice data through an emotion recognition engine to analyze the user's emotional state.

[0743] Step 7:

[0744] The server generates a voice message based on the user's intention and emotional state, such as "I'll pay for XX yen. Please say OK if you're happy with that." For example, if the user is anxious, the server generates a message in a polite and steady tone.

[0745] Step 8:

[0746] The server sends the generated voice message to the terminal.

[0747] Step 9:

[0748] The terminal plays the voice message received from the server and asks the user for confirmation.

[0749] Step 10:

[0750] The user confirms by saying "OK."

[0751] Step 11:

[0752] The terminal again obtains the user's approval voice.

[0753] Step 12:

[0754] The terminal transmits the acquired approval voice data to the server.

[0755] Step 13:

[0756] The server receives the approval voice data and converts it into text through a voice recognition engine.

[0757] Step 14:

[0758] The server checks the textual approval and determines that it contains "OK."

[0759] Step 15:

[0760] The server runs the approval voice through an emotion recognition engine to check the user's emotional state at the time of approval, for example, checking whether the user is feeling hesitant or anxious.

[0761] Step 16:

[0762] The server determines the certainty of the authorization and then sends a payment instruction to the payment system.

[0763] Step 17:

[0764] The payment system executes the payment and sends the result back to the server.

[0765] Step 18:

[0766] The server confirms the completion of the payment and generates a "payment completed" notification.

[0767] Step 19:

[0768] The server sends the generated payment completion message to the terminal.

[0769] Step 20:

[0770] The terminal reproduces the payment completion message received from the server and notifies the user.

[0771] Example 2

[0772] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0773] Conventional payment systems require users to perform time-consuming tasks such as scanning QR codes or manually entering the amount. This can make the payment process particularly cumbersome and detract from the user experience. Furthermore, conventional systems have difficulty properly understanding the user's emotions and intentions, making them prone to misrecognition and incorrect operation, especially for inexperienced users. Therefore, there is a need for a user-friendly and reliable payment method that combines voice recognition and emotion recognition.

[0774] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0775] In this invention, the server includes means for analyzing voice data to determine the user's intention, means for analyzing the user's emotions, and means for notifying the user of payment completion. This not only recognizes the user's voice but also analyzes their emotions to generate an appropriate response, enabling a fast and smooth payment.

[0776] A "user" is an individual making a payment and issuing a voice instruction.

[0777] The term "means for acquiring voice instructions" refers to a device and its function for acquiring voices uttered by a user through a microphone.

[0778] "Central Processing Unit" refers to a server or high performance computing device for processing and managing voice data and analysis results.

[0779] "Means for analyzing voice data" refers to a voice recognition module or engine that analyzes the acquired voice data and extracts the necessary information.

[0780] "Means for determining the user's intent" refers to a natural language processing module or software that interprets the user's instructions based on the voice recognition results and determines their intent.

[0781] "Means for confirming to the user as a voice message" refers to a device and software that generates and plays a voice message to ask the user for confirmation.

[0782] "Means for analyzing user emotions" refers to emotion recognition modules or algorithms that identify user emotions from acquired voice data.

[0783] The "means for acquiring voice approval" refers to a device and its function for re-acquiring the voice approval uttered by the user.

[0784] "Means for effecting payments" means a payment system or API that effectuates the payment of amounts based on payment instructions.

[0785] "Means for notifying the user that payment has been completed" refers to a device or system that generates and plays a voice message to inform the user that payment has been completed.

[0786] "Speech Recognition Module" refers to software and hardware capable of converting speech into text.

[0787] A "natural language processing module" refers to software and hardware that has the ability to analyze text data and interpret the user's intentions and requests.

[0788] "Specific approval keywords" refer to predetermined spoken words or phrases that a user utters to indicate approval.

[0789] The "means for transmitting the acquired voice data to the central processing unit" refers to the communication protocol and network infrastructure for transmitting the voice data from the terminal to the central processing unit.

[0790] This invention relates to a voice payment system that utilizes speech recognition, natural language processing, and emotion recognition technologies. By allowing users to issue payment instructions via voice, the system eliminates the need to scan a QR code or enter the amount, providing a fast and smooth payment experience. Furthermore, by recognizing the user's emotions, it is possible to improve the reliability of the payment process and the user experience.

[0791] This system consists of various devices and technologies, such as a user, a device, a server, and a payment system. The device receives voice instructions from the user and sends them to the server. The server converts the voice data into text using a speech recognition engine (e.g., Google Cloud Speech-to-Text). The converted text is analyzed by a natural language processing engine (e.g., OpenAI GPT-4) to determine the user's intention. Furthermore, the user's emotions are analyzed by an emotion recognition engine (e.g., Microsoft Azure Emotion API).

[0792] Specifically, the system operates according to the following procedure.

[0793] When a user issues a voice command such as "please make a payment," the device captures the voice through the microphone and transmits it to the server in real time. The server receives the voice data and converts it into text using Google Cloud Speech-to-Text. The server then analyzes the text using OpenAI GPT-4 and determines that the user's intent is "to make a payment."

[0794] The server then uses the Microsoft Azure Emotion API to perform emotion recognition and determine the user's emotional state. Based on this information, the server generates a tailored voice message, such as "I'll pay you 500 yen. Please say OK if you're happy with this." This message is then sent to the device, which plays it back and asks for the user's confirmation.

[0795] If the user approves by saying "OK," the device captures the speech again and sends it to the server, which again uses Google Cloud Speech-to-Text to convert the speech to text, confirming that "OK" is included, and again uses the emotion recognition engine to determine the certainty of the approval.

[0796] Finally, the server sends a payment instruction to the payment system (e.g., Stripe) to execute the payment. When the payment is complete, the server generates a voice message saying "Payment completed" and sends it to the terminal. The terminal plays the message to notify the user that the payment has been completed.

[0797] As a concrete example, consider a situation where a user places an order at a cafe and pays at the cash register. The user says "Please pay" at the register, and the device captures this voice and sends it to the server. The server analyzes the voice data and generates the text "Please pay." The text is analyzed using a natural language processing engine to confirm the user's intention. An emotion recognition engine then analyzes the user's emotions and generates an appropriate voice message. If the user approves with "OK," the voice data is sent again to the server, and finally the payment is made and a completion notification is sent.

[0798] An example of a prompt sentence to input to the generative AI model is as follows:

[0799] prompt:

[0800] Please explain in detail what happens in a voice payment system when a user says "please pay" at the cash register. Please provide a detailed description of the entire process from when the terminal receives the voice message and sends it to the server, to when the server analyzes and recognizes it and executes the payment.

[0801] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0802] Step 1:

[0803] Acquiring voice commands

[0804] The user issues a voice command saying, "Please make payment."

[0805] Input: User's voice commands

[0806] The device captures the user's voice through a microphone, splits it into fragments in real time, and sends them as data packets to the server via the HTTPS protocol.

[0807] Output: Captured audio data (data packets)

[0808] Step 2:

[0809] Analysis of audio data

[0810] The server receives the audio data and converts it into text using Google Cloud Speech-to-Text.

[0811] Input: Captured audio data (data packets)

[0812] The server runs a voice recognition engine, analyzes the voice data, and generates the text "Please make payment."

[0813] Output: Text data (e.g. "Please make payment")

[0814] Step 3:

[0815] Determining intent

[0816] The text generated by the server is analyzed using OpenAI GPT-4, and the user's intention is determined to be a "payment instruction."

[0817] Input: Text data (e.g. "Please make payment")

[0818] The server uses a natural language processing engine to analyze the context of the text and interpret the intent as "payment instructions."

[0819] Output: User's instructions (e.g. "Payment instructions")

[0820] Step 4:

[0821] Emotion recognition

[0822] The server uses the Microsoft Azure Emotion API to analyze the user's emotions from the voice data.

[0823] Input: Captured audio data (data packets)

[0824] The server extracts features from the voice data and inputs them into an emotion recognition engine to identify emotions such as "joy" or "relief."

[0825] Output: User's emotional data (e.g., "Relief")

[0826] Step 5:

[0827] Confirm payment details

[0828] The server takes the user's emotions into consideration and generates an adjusted voice message such as, "I will pay for XX yen. If you agree, please say OK."

[0829] Input: User instructions, user emotion data (e.g., "Payment instructions," "Relief")

[0830] The server generates a voice message saying, "The payment will be 500 yen. If you agree, please say OK." This message is sent to the terminal, which plays it back.

[0831] Output: The generated voice message

[0832] Step 6:

[0833] User Authorization

[0834] The user confirms by saying "OK."

[0835] Input: A confirmation message from the server

[0836] The terminal captures the user's approval voice through the microphone and transmits it again to the server as a data packet.

[0837] Output: Acquired acknowledgement voice data (data packets)

[0838] Step 7:

[0839] Parsing Authorizations

[0840] The server again converts the approval speech into text using Google Cloud Speech-to-Text.

[0841] Input: Acquired acknowledgement voice data (data packets)

[0842] The server runs a speech recognition engine to analyze the audio data and generate the text "OK," and an emotion recognition engine to ensure that it contains a positive emotion, such as "relief."

[0843] Output: Text data (e.g., "OK"), emotion data (e.g., "Relieved")

[0844] Step 8:

[0845] Executing payments

[0846] The server sends a payment instruction to a payment system such as Stripe or PayPal to execute the payment.

[0847] Input: Text data (e.g., "OK"), user instructions (e.g., "Payment instructions")

[0848] The server sends a request for 500 yen to the payment system via the REST API and receives a success response.

[0849] Output: Payment completion data

[0850] Step 9:

[0851] Payment completion notification

[0852] The server confirms the completion of the payment and generates a voice message saying "Payment completed."

[0853] Input: Payment completion data

[0854] The server generates a voice message saying "Payment completed. Thank you very much" and sends it to the terminal. While the message is played, the terminal displays "Payment completed" on the screen.

[0855] Output: The generated voice message

[0856] (Application example 2)

[0857] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0858] Conventional payment systems require users to scan a QR code and input the amount, which is a cumbersome process. Furthermore, even payment systems that use voice instructions have the problem of not being able to fully reflect the user's intentions and emotions, making it difficult to improve reliability and user experience. The present invention aims to solve these problems and provide a new voice payment system that improves user convenience and reliability.

[0859] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring a user's voice instruction, means for transmitting the acquired voice data to the server, means for analyzing the voice data and determining the user's intention, means for generating payment details based on the user's intention and confirming them as a voice message to the user, means for acquiring an approval voice from the user, means for transmitting the acquired approval voice to the server, means for analyzing the approval voice and executing the payment, means for notifying the user of payment completion, means for determining the user's emotion from the voice data, and means for adjusting the confirmation message based on the emotion determination result. This allows the user to avoid scanning a QR code or entering an amount, and enables highly reliable, quick and comfortable payment to be executed through emotion recognition.

[0860] A "means for obtaining voice instructions" is a device or system for collecting voice commands uttered by a user.

[0861] The "means for transmitting voice data to a server" refers to a device or system that has the function of transferring acquired voice information to a server via a network.

[0862] "Means for analyzing voice data and determining user intent" refers to an algorithm or engine that extracts text from voice data and interprets the user's requests and intent based on that text.

[0863] The "means for generating payment details and confirming them to the user as a voice message" is a system for creating payment details based on text data and playing them back as voice.

[0864] The "means for acquiring approval voice" is a device or system for collecting approval voice uttered by a user.

[0865] The "means for transmitting the acquired approval voice to the server" refers to a device or system that has the function of transferring the user's approval voice to the server via a network.

[0866] The "means for analyzing the approval voice and executing the payment" refers to an algorithm and system for converting the user's approval voice into text and completing the payment process based on that text.

[0867] The "means for notifying the user of the completion of the payment" is a system that generates and plays a voice message to notify the user that the payment has been successfully completed.

[0868] The "means for determining the user's emotion from the voice data" refers to an algorithm or engine for analyzing the emotional information contained in the voice data and identifying the user's emotional state.

[0869] The "means for adjusting the confirmation message based on the emotion determination result" is a system for appropriately changing the content and tone of the confirmation message depending on the user's emotional state.

[0870] This invention relates to a voice payment system that utilizes speech recognition, natural language processing, and emotion recognition technologies. This system allows users to issue payment instructions via voice, eliminating the need to scan a QR code or enter the amount, and providing a fast and smooth payment experience. Furthermore, by recognizing the user's emotions, it is possible to improve the reliability of the payment process and the user experience.

[0871] The system includes the following components:

[0872] 1. User: The individual making the payment and issuing the voice command.

[0873] 2. Terminal: The device through which the user issues voice commands, including a smartphone, tablet, or dedicated terminal. The terminal is responsible for capturing the user's voice and sending it to the server.

[0874] 3. Server: Receives the voice data, analyzes it using a speech recognition engine, natural language processing engine, and emotion recognition engine, and executes the payment.

[0875] 4. Payment system: This is the system that actually processes payments based on the payment instructions sent from the server.

[0876] Program processing

[0877] 1. Acquiring voice instructions

[0878] The user issues a voice command such as "Please make the payment." The device picks up this voice using the built-in microphone and sends the voice data to the cloud server.

[0879] 2. Analysis of audio data

[0880] The server analyzes the acquired voice data using a speech recognition engine (e.g., Google Cloud Speech-to-Text API) and converts it into text data. It then analyzes the text using a natural language processing engine (e.g., Google Cloud Natural Language API) to determine the user's intent.

[0881] 3. Emotional Recognition

[0882] The server analyzes the voice data using an emotion recognition engine (e.g., IBM Watson Tone Analyzer) to determine the user's emotions.

[0883] 4. Confirm payment details

[0884] The server generates an adjusted confirmation message, "I will pay for XX yen. Please say OK if you agree," taking into account the user's feelings, and sends it to the terminal. The terminal plays this message and asks the user for confirmation.

[0885] 5. User Acknowledgment

[0886] The user approves by saying "OK." The device reacquires the approval voice and sends it to the server.

[0887] 6. Acknowledgment Analysis

[0888] The server converts the received approval voice into text using a speech recognition engine, checks whether it contains "OK," and then checks the emotion of the approval voice again.

[0889] 7. Payment Execution

[0890] The server sends a payment instruction to the payment system (e.g. Stripe API) to execute the payment.

[0891] 8. Payment completion notification

[0892] The server confirms the completion of the payment and generates a voice message saying "Payment completed." The terminal plays this message to notify the user.

[0893] Specific examples

[0894] For example, after a user finishes shopping at a supermarket, they open a smartphone app and say, "Please make the payment." The device receives this instruction and sends the voice data to the server. The server then analyzes the voice data using a speech recognition engine and converts it into text. It then uses a natural language processing engine to determine the user's intent when they say, "Please make the payment." It then uses an emotion recognition engine to analyze the user's emotion from the voice data. Based on these analysis results, the device generates a tailored confirmation message, such as, "I'll pay 500 yen. Please say OK if you're happy with this," and sends it to the device. The device then plays this message to ask the user for confirmation. When the user replies, "OK," the voice is sent again to the server, where the approval voice is analyzed, confirming that it contains "OK," and the emotion is also reconfirmed. A payment instruction is then sent to the payment system, and the payment is executed. Finally, the user is notified that the payment has been completed.

[0895] Example prompts to input to the generative AI model

[0896] When you say "please pay," it uses speech recognition, natural language processing, and emotion recognition technologies to analyze your spoken payment instructions and complete the payment on your smartphone. Based on emotion recognition, it provides feedback to improve the user experience.

[0897] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0898] Step 1:

[0899] Acquiring voice commands

[0900] Input: A user speaks the command "please pay."

[0901] Specific operation: The user speaks into the microphone on the device (smartphone, tablet, etc.) saying "Please make payment."

[0902] Output: The device uses a built-in microphone to capture audio data, which is then converted into a digital format and sent directly to the server.

[0903] Step 2:

[0904] Sending audio data to the server

[0905] Input: Audio data captured by the device.

[0906] Specific operation: The device sends the acquired voice data to a cloud server via the network (Wi-Fi or 4G / 5G communication).

[0907] Output: The server receives the audio data sent from the terminal.

[0908] Step 3:

[0909] Analysis of audio data

[0910] Input: The audio data received by the server.

[0911] How it works: The server uses a speech recognition engine (e.g., Google Cloud Speech-to-Text API) to convert the voice data into text, which is then analyzed by a natural language processing engine (e.g., Google Cloud Natural Language API) to determine the user's intent (e.g., "please make payment").

[0912] Output: Text data as the analysis result and the user's intent.

[0913] Step 4:

[0914] Emotion recognition

[0915] Input: The audio data received by the server.

[0916] Specific operation: The server uses an emotion recognition engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotions from the voice data. This analysis evaluates whether the user is relaxed or stressed.

[0917] Output: Emotion data as the analysis result (e.g., relaxed, stressed, etc.).

[0918] Step 5:

[0919] Confirm payment details

[0920] Input: Text data and emotion data as analysis results.

[0921] Specific operation: The server generates a tailored confirmation message (e.g., "I will pay 500 yen. Please say OK if you agree") taking into account the user's feelings. It then sends this message to the terminal.

[0922] Output: The generated confirmation message and its transmission from the server.

[0923] Step 6:

[0924] Play confirmation message

[0925] Input: The confirmation message sent by the server.

[0926] Specific operation: The terminal plays a voice message and asks the user for confirmation (e.g., "The payment amount is 500 yen. Please say OK if you agree").

[0927] Output: An audio message is played to the user.

[0928] Step 7:

[0929] User Authorization

[0930] Input: The user's voice command after hearing the confirmation message (e.g., "OK").

[0931] Specific operation: The user approves by saying "OK" into the device's microphone. The device captures this voice and sends it back to the server.

[0932] Output: The acknowledgement voice acquired by the device is sent to the server.

[0933] Step 8:

[0934] Analysis of approval voice

[0935] Input: The acknowledgment audio sent to the server.

[0936] Specific operation: The server again uses the speech recognition engine to convert the approval voice into text and checks whether it contains "OK." It then uses the emotion recognition engine to check the emotion of the approval voice again.

[0937] Output: Text data and emotion data as analysis results.

[0938] Step 9:

[0939] Executing payments

[0940] Input: Approval data and emotion data as analysis results.

[0941] Specific operation: The server sends a payment instruction to the payment system (e.g. Stripe API) to execute the payment.

[0942] Output: The result of the payment execution (success or failure).

[0943] Step 10:

[0944] Payment completion notification

[0945] Input: Payment execution result.

[0946] Specific operation: The server confirms the completion of the payment, generates a voice message saying "Payment completed" and sends it to the terminal. The terminal plays this message to notify the user.

[0947] Output: A payment completion message is played to the user.

[0948] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0949] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0950] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0951] [Third embodiment]

[0952] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0953] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0954] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0955] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0956] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0957] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0958] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0959] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0960] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0961] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0962] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0963] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0964] The present invention relates to a voice payment system that utilizes voice recognition technology and natural language processing technology. By allowing users to issue payment instructions by voice, the process of scanning a QR code and entering the amount is eliminated, providing a fast and smooth payment experience.

[0965] System configuration

[0966] This system consists of the following various devices and technologies:

[0967] 1. User: The individual making the payment and issuing the voice command.

[0968] 2. Terminal: The device through which the user issues voice commands, including a smartphone, tablet, or dedicated terminal. The terminal is responsible for capturing the user's voice and sending it to the server.

[0969] 3. Server: Receives the voice data, analyzes it using a voice recognition engine and natural language processing engine, and executes the payment.

[0970] 4. Payment system: This is the system that actually processes payments based on the payment instructions sent from the server.

[0971] Program processing

[0972] 1. Acquiring voice instructions

[0973] The user issues a voice command saying, "Please make payment."

[0974] The terminal captures the user's voice through a microphone and transmits the voice data to a server.

[0975] 2. Analysis of audio data

[0976] The server receives the voice data and converts it into text using a voice recognition engine.

[0977] The server analyzes the converted text using a natural language processing engine to determine the user's intent.

[0978] 3. Confirm payment details

[0979] The server generates a voice message saying, "The payment will be for XX yen. If you agree, please say OK," and sends it to the terminal.

[0980] The terminal plays this voice message and asks the user for confirmation.

[0981] 4. User Acknowledgment

[0982] The user confirms by saying "OK."

[0983] The terminal again captures the user's voice and transmits it to the server.

[0984] 5. Execution of payment

[0985] The server receives the voice confirmation and uses the voice recognition engine to convert the voice "OK" into text and confirm it.

[0986] The server instructs the payment system to pay the amount and executes the payment.

[0987] 6. Payment completion notification

[0988] The server confirms the completion of the payment and sends a notification to the terminal that "payment has been completed."

[0989] The terminal plays this voice message to the user to notify them that the payment has been successfully completed.

[0990] Specific examples

[0991] For example, consider the case where a user is shopping at a supermarket and wants to make a payment at the register. The user says, "Please make the payment." The device captures this voice and sends it to the server. The server analyzes the voice data using a voice recognition engine and obtains the text "Please make the payment." It then analyzes the text using a natural language processing engine to confirm the user's intention. It then generates a voice message saying, "I will pay for 3,500 yen. Please say OK if you are happy with this," and sends it to the device. The device plays the message and asks the user for confirmation. When the user says "OK," the device captures the voice again and sends it to the server. After the server confirms the "OK" approval, it carries out the payment and notifies the device that "payment has been completed." The device then plays the message and notifies the user that the payment has been completed.

[0992] This series of processes allows users to complete payments quickly and smoothly using only their voice, eliminating the need to scan a QR code or enter the amount.

[0993] The processing flow will be explained below.

[0994] Program processing details

[0995] Step 1:

[0996] The user issues a voice command saying, "Please make payment."

[0997] Step 2:

[0998] The terminal acquires the user's voice instructions through a microphone.

[0999] Step 3:

[1000] The terminal transmits the acquired voice data to the server.

[1001] Step 4:

[1002] The server converts the received voice data into text using a voice recognition engine.

[1003] Step 5:

[1004] The server analyzes the converted text using a natural language processing engine and determines the user's intent as a "payment instruction."

[1005] Step 6:

[1006] Based on the user's instructions, the server generates a payment confirmation voice message saying, "I will pay for XX yen. If you agree, please say OK."

[1007] Step 7:

[1008] The server sends the generated voice message to the terminal.

[1009] Step 8:

[1010] The terminal plays the voice message received from the server and asks the user for confirmation.

[1011] Step 9:

[1012] The user confirms by saying "OK."

[1013] Step 10:

[1014] The terminal again obtains the user's approval voice.

[1015] Step 11:

[1016] The terminal transmits the acquired approval voice data to the server.

[1017] Step 12:

[1018] The server receives the approval voice data and converts it into text using a voice recognition engine.

[1019] Step 13:

[1020] The server checks the textual approval and determines that it contains "OK."

[1021] Step 14:

[1022] After the server confirms the authorization, it sends an instruction to pay the amount to the payment system.

[1023] Step 15:

[1024] The payment system executes the payment and sends the result back to the server.

[1025] Step 16:

[1026] The server confirms the completion of the payment and generates a voice message saying "Payment completed."

[1027] Step 17:

[1028] The server sends the generated payment completion message to the terminal.

[1029] Step 18:

[1030] The terminal reproduces the payment completion message received from the server and notifies the user.

[1031] Example 1

[1032] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1033] Conventional payment systems require users to scan QR codes or manually enter amounts, making the payment process cumbersome and making it difficult to provide a fast and smooth payment experience. Furthermore, conventional systems have low accuracy in speech recognition and natural language processing, which can easily lead to misrecognition of user intent.

[1034] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1035] In this invention, the server includes means for analyzing voice data and determining the user's intention, means for generating payment details based on the user's intention and confirming them with the user as a voice message, and means for analyzing the approval voice and executing the payment. This allows the user to complete the payment using only voice, eliminating the need to scan a QR code or manually enter the amount, enabling quick and smooth payment. Furthermore, by integrating a voice recognition engine and a natural language processing engine, voice data can be accurately converted and analyzed into text, enabling highly accurate determination of the user's intention.

[1036] A "user" is an individual who operates the system and issues voice commands.

[1037] A "terminal" is a device that acquires the user's voice and transmits the acquired voice data to a server.

[1038] The "server" is a central processing unit that analyzes voice data to determine the user's intentions and executes the payment.

[1039] A "speech recognition engine" is a software or hardware component for converting voice data into text.

[1040] A "natural language processing engine" is a software or hardware component for analyzing text and interpreting user intent.

[1041] A "speech synthesis engine" is a software or hardware component for converting text data into a voice message.

[1042] The "approval voice" is a voice uttered by the user to approve the payment details.

[1043] A "payment system" is a system for executing payments and returning the processing results to the server.

[1044] "Communication means" refers to the technical elements for sending and receiving data between a terminal and a server in real time.

[1045] This invention relates to a voice payment system that utilizes voice recognition and natural language processing technologies. By allowing users to issue payment instructions via voice, it eliminates the need to scan a QR code or input the amount, providing a fast and smooth payment experience. This system is composed of the following various devices and technologies:

[1046] 1. Users

[1047] The user is the individual making the payment and issues instructions to the system by speaking.

[1048] 2. Terminal

[1049] The terminal is the device through which the user issues voice commands, and can be a smartphone, tablet, or dedicated terminal. The terminal has the function of capturing the user's voice through a microphone and sending the voice data to a server. Communication technologies such as WebSocket are used to send and receive voice data in real time.

[1050] 3. Server

[1051] The server analyzes the voice data and determines the user's intent. Specifically, it converts the voice data into text using a speech recognition engine (e.g., Google Cloud Speech-to-Text), analyzes the text using a natural language processing engine (e.g., Google Cloud Natural Language), and interprets the user's intent. The server also generates confirmation and notification messages using a speech synthesis engine (e.g., Google Cloud Text-to-Speech), and sends them to the device.

[1052] 4. Payment System

[1053] A payment system is a system that processes actual payments based on payment instructions sent from a server. Specific examples include online payment platforms such as Stripe and PayPal.

[1054] Specific examples

[1055] For example, consider a case where a user is shopping at a supermarket and wants to pay at the register. The user says, "Please pay." The device captures this speech and sends it to the server. The server analyzes the speech data using Google Cloud Speech-to-Text and obtains the text "Please pay." The text is analyzed using Google Cloud Natural Language to confirm the user's intent. Google Cloud Text-to-Speech then generates a voice message saying, "I'll pay 3,500 yen. If you're happy with this, please say OK," and sends it to the device. The device plays the message and asks the user for confirmation. When the user says "OK," the device captures the speech again and sends it to the server. The server again recognizes it as "OK" using Google Cloud Speech-to-Text and calls the Stripe API to complete the payment. Finally, the server sends a notification to the device stating, "Payment completed," and the device plays the message to the user, completing the payment.

[1056] Example prompt sentence:

[1057] I want to pay by voice at the supermarket checkout. Please follow the instructions below to make a voice payment.

[1058] 1. Say "Please make payment."

[1059] 2. When the payment amount is presented, say "OK."

[1060] In this way, the voice payment system of the present invention allows users to complete payments simply and quickly using only their voice, without the need for complicated operations, thereby simultaneously improving the user experience and streamlining the payment process at stores.

[1061] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1062] Step 1:

[1063] The user gives the command "Please make payment" by voice. The device's built-in microphone picks up the user's voice. This voice data is temporarily stored in the device's local storage. The input is voice data, and the output is an audio file stored on the device. The specific operation uses the smartphone's microphone function.

[1064] Step 2:

[1065] The device compresses the audio data it acquires and sends it to the server. The input is the compressed audio data, and the output is the audio data sent to the server. Specifically, the device sends the data to the server in real time via WebSocket.

[1066] Step 3:

[1067] The server receives the voice data and calls the speech recognition engine (Google Cloud Speech-to-Text). The input is voice data and the output is text data. Specifically, the server sends the voice data to the API and receives a response in text format.

[1068] Step 4:

[1069] The server analyzes the text data using a natural language processing engine (Google Cloud Natural Language) to determine the user's intent. The input is text data converted from speech, and the output is data indicating the user's intent. Specific operations include entity extraction and sentiment analysis, and the system recognizes that the user's instruction is a payment.

[1070] Step 5:

[1071] The server uses a speech synthesis engine (Google Cloud Text-to-Speech) to generate a voice message saying, "I'll pay for XX yen. If you're happy with that, please say OK." The input is the user's intention and amount information, and the output is synthesized voice data. The specific operation is to convert the required text message into an audio file.

[1072] Step 6:

[1073] The server generates a voice message and sends it to the device. The input is synthesized voice data, and the output is the voice data sent to the device. The server then sends the data back to the device using WebSocket.

[1074] Step 7:

[1075] The device plays the received voice message and asks the user for confirmation. The input is the voice data sent from the server, and the output is the voice message being played. Specifically, the message is played using the smartphone's audio player function.

[1076] Step 8:

[1077] The user approves by saying "OK." The device again captures the user's voice and sends it to the server. The input is the approval voice data, and the output is the voice data sent to the server. In concrete terms, the voice data is captured in the same way as in the previous step and sent to the server.

[1078] Step 9:

[1079] The server receives the approval voice and again uses the speech recognition engine to convert the "OK" voice into text and confirm it. The input is the approval voice data and the output is text data. Specifically, the approval voice is sent to the API and a response in text format is received.

[1080] Step 10:

[1081] The server instructs the payment system (such as Stripe or PayPal) to make the payment and executes the payment. The input is the amount and the user's confirmation information, and the output is the payment result data. Specifically, the transaction is processed by calling the payment system's API.

[1082] Step 11:

[1083] The server confirms the completion of the payment, generates a notification "Payment completed" using a speech synthesis engine, and sends it to the terminal. The input is the payment result data, and the output is a synthesized speech notification. Specifically, the speech notification is generated using Google Cloud Text-to-Speech.

[1084] Step 12:

[1085] The terminal plays the received voice message to the user to notify them that the payment has been successfully completed. The input is the voice data sent from the server, and the output is the voice message that is played. Specifically, the notification is made using the smartphone's audio player function.

[1086] (Application example 1)

[1087] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1088] Conventional payment systems require the user to scan a QR code and enter the amount, which can be time-consuming and disruptive to the user's payment experience. Furthermore, manual approval procedures can degrade the user experience. There is a need for technology that can resolve these issues and enable more efficient and faster payments.

[1089] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1090] In this invention, the server includes means for acquiring a user's voice instruction, means for transmitting the acquired voice data to the server, means for analyzing the voice data and determining the user's intention, means for generating payment details based on the user's intention and confirming them as a voice message to the user, means for acquiring voice approval from the user, means for transmitting the acquired voice approval to the server, means for analyzing the voice approval and executing the payment, means for notifying the user that the payment has been completed, means for performing voice recognition and natural language processing via the smart device, and means for generating a voice message using prompt sentences and a generative AI model, thereby enabling the user to complete payment quickly and smoothly using only their voice.

[1091] "User" refers to the person or organization issuing the voice command.

[1092] "Voice instruction" refers to an instruction given by voice to a device by a user.

[1093] A "terminal" is a device that receives a user's voice instructions and transmits them to the server, and includes smartphones, smart glasses, and the like.

[1094] "Server" refers to a computer system that has the function of analyzing acquired voice data, determining the user's intentions, and carrying out payment processing.

[1095] "Audio data" refers to a digital data file that records a user's voice.

[1096] A "voice recognition engine" refers to software or algorithms that analyze voice data and convert it into text.

[1097] A "natural language processing engine" refers to software or algorithms that analyze text data and understand the user's intent and meaning.

[1098] "Payment system" refers to a system that actually processes payments based on user payment instructions.

[1099] "Prompt sentence" refers to the text used to generate a voice message using a generative AI model.

[1100] "Generative AI models" refer to machine learning models or artificial intelligence models used to perform natural language processing.

[1101] A "smart device" is a device for performing voice recognition and natural language processing, including smartphones and smart glasses.

[1102] "Approval voice" refers to voice data uttered by a user when approving payment by voice.

[1103] "Payment completion notification" refers to a notification to inform the user that the payment process has been successfully completed.

[1104] This invention provides a voice payment system that utilizes voice recognition and natural language processing technologies to enable users to make payments quickly and smoothly by voice instructions. This system works in conjunction with a server via a smart device, automating the entire process from voice instructions to payment completion.

[1105] This system consists of the following various devices and technologies:

[1106] 1. User: A person or organization that issues voice commands.

[1107] 2. Terminal: A device that receives the user's voice instructions and sends them to the server, including smartphones, smart glasses, etc.

[1108] 3. Server: A computer system that analyzes voice data, determines the user's intentions, and processes payments.

[1109] 4. Speech recognition engine: Software and algorithms that convert voice data into text.

[1110] 5. Natural language processing engine: Software and algorithms that analyze text data and understand user intent.

[1111] 6. Generative AI models: These are machine learning models used to perform natural language processing.

[1112] 7. Prompt: This is the text used to generate a voice message using the generative AI model.

[1113] System configuration

[1114] 1. Obtaining user voice commands

[1115] The user issues a voice command saying, "Please make payment."

[1116] The terminal receives this audio and transmits the audio data to the server.

[1117] 2. Analysis of audio data

[1118] The server converts the voice data into text using a voice recognition engine.

[1119] The server analyzes the converted text using a natural language processing engine to determine the user's intent.

[1120] 3. Confirm payment details

[1121] The server uses a generative AI model with the prompt sentence to generate a voice message such as, "I'll pay for XX yen. If you agree, please say OK."

[1122] The generated voice message is sent to the terminal.

[1123] The terminal plays this voice message and asks the user for confirmation.

[1124] 4. User Acknowledgment

[1125] The user confirms by saying "OK."

[1126] The terminal again captures the user's voice and sends it to the server.

[1127] The server analyzes the voice confirmation and again uses a speech recognition engine to convert the voice "OK" into text.

[1128] The server instructs the payment system to pay the amount and executes the payment.

[1129] 5. Payment completion notification

[1130] The server confirms the completion of the payment and sends a notification to the terminal that "payment has been completed."

[1131] The terminal plays this voice message to the user to notify them that the payment has been successfully completed.

[1132] Specific examples

[1133] For example, a user is shopping at a supermarket and says "Please make the payment" at the cash register. The device captures this voice and sends it to the server. The server analyzes the voice data using a voice recognition engine and obtains the text "Please make the payment." It then analyzes the text using a natural language processing engine to confirm the user's intention. It then uses a generative AI model to generate a voice message saying "I will pay 3,500 yen. Please say OK if you are happy with this," and sends it to the device. The device plays the message and asks the user for confirmation. When the user says "OK," the device captures the voice again and sends it to the server. The server again confirms "OK" using its voice recognition engine, then carries out the payment and notifies the device that "payment has been completed." The device then plays back the message, informing the user that the payment has been completed.

[1134] Prompt Sentence Examples

[1135] Say "please pay."

[1136] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1137] Step 1:

[1138] The user issues a voice command saying, "Please make the payment." The terminal captures this voice using the built-in microphone. The captured voice data is saved as digital data within the terminal. The saved data is then sent to the server in the next step.

[1139] Step 2:

[1140] The device sends the acquired voice data to the server. This procedure uses a communication protocol (e.g., HTTP, WebSocket, etc.) to transfer the voice data to the server. The sent data is then passed to the voice recognition engine on the server side.

[1141] Step 3:

[1142] The server converts the voice data into text using a speech recognition engine. The input is voice data and the output is text data. The speech recognition engine analyzes the voice waveform and generates a corresponding string of characters.

[1143] Step 4:

[1144] The server passes the generated text data to a natural language processing engine for analysis. Here, the context and keywords of the text data are analyzed to identify the user's intent. This process recognizes the user's request, "Please make payment." The input is text data, and the output is data that represents the user's intent.

[1145] Step 5:

[1146] The server generates payment details based on the user's intent. It uses a prompt (e.g., "I'll pay 3,500 yen. Please say OK if you agree.") and generates a voice message using a generative AI model. The input is the payment details and the prompt, and the output is a voice message.

[1147] Step 6:

[1148] The server sends the generated voice message to the terminal, and the terminal plays the received voice message to the user. The hardware used here is a speaker, and this prompts the user for confirmation.

[1149] Step 7:

[1150] The user approves by saying "OK." The device again uses the built-in microphone to capture the user's voice and sends the data to the server.

[1151] Step 8:

[1152] The server analyzes the acquired approval voice again using a speech recognition engine and converts the voice "OK" into text. Next, it uses a natural language processing engine to check whether the approval voice contains specific approval keywords. The input is the voice data, and the output is the confirmation result of the approval keyword.

[1153] Step 9:

[1154] When the server confirms the authorization keyword, it instructs the payment system to pay the amount and executes the payment. The payment system then performs the actual payment processing based on this instruction. The input is the result of the authorization keyword confirmation, and the output is the result of the payment completion.

[1155] Step 10:

[1156] When the payment is complete, the server generates a notification saying "Payment completed" and sends it to the terminal. The terminal then plays this notification as a voice message to the user, informing them that the payment has been successfully completed.

[1157] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1158] This invention relates to a voice payment system that utilizes speech recognition, natural language processing, and emotion recognition technologies. By allowing users to issue payment instructions via voice, the system eliminates the need to scan a QR code or enter the amount, providing a fast and smooth payment experience. Furthermore, by recognizing the user's emotions, it is possible to improve the reliability of the payment process and the user experience.

[1159] System configuration

[1160] This system consists of the following various devices and technologies:

[1161] 1. User: The individual making the payment and issuing the voice command.

[1162] 2. Terminal: The device through which the user issues voice commands, including a smartphone, tablet, or dedicated terminal. The terminal is responsible for capturing the user's voice and sending it to the server.

[1163] 3. Server: Receives the voice data, analyzes it using a speech recognition engine, natural language processing engine, and emotion recognition engine, and executes the payment.

[1164] 4. Payment system: This is the system that actually processes payments based on the payment instructions sent from the server.

[1165] Program processing

[1166] 1. Acquiring voice instructions

[1167] The user issues a voice command saying, "Please make payment."

[1168] The terminal captures the user's voice through a microphone and transmits the voice data to a server.

[1169] 2. Analysis of audio data

[1170] The server receives the voice data and converts it into text using a voice recognition engine.

[1171] The server analyzes the converted text using a natural language processing engine and determines the user's intent as a "payment instruction."

[1172] 3. Emotional Recognition

[1173] The server analyzes the voice data using an emotion recognition engine to determine the user's emotions.

[1174] 4. Confirm payment details

[1175] The server takes the user's emotions into consideration and generates an adjusted voice message such as, "I will pay for XX yen. If you agree, please say OK."

[1176] The server sends this voice message to the terminal, which plays the message and asks the user for confirmation.

[1177] 5. User Acknowledgment

[1178] The user confirms by saying "OK."

[1179] The terminal again acquires the user's approval voice and transmits it to the server.

[1180] 6. Acknowledgment Analysis

[1181] The server receives the approval voice and converts it into text using a speech recognition engine.

[1182] The server checks the textual approval and determines that it contains "OK."

[1183] The server also reconfirms the sentiment of the approval voice to determine the certainty of approval.

[1184] 7. Payment Execution

[1185] The server sends a payment instruction to the payment system to execute the payment.

[1186] 8. Payment completion notification

[1187] The server confirms the completion of the payment and generates a voice message saying "Payment completed."

[1188] The server transmits the generated payment completion message to the terminal, and the terminal reproduces the message to notify the user.

[1189] Specific examples

[1190] For example, consider a case where a user places an order at a cafe and wants to pay at the register. The user says, "Please pay." The device captures this voice and sends it to the server. The server analyzes the voice data using a voice recognition engine and obtains the text "Please pay." The natural language processing engine analyzes the text and confirms the user's intention. The server then analyzes the user's emotions using an emotion recognition engine and generates a voice message appropriately adjusted to match the user's emotions: "I will pay 500 yen. Please say OK if you are happy with this," which is sent to the device. The device plays the message and asks the user for confirmation. When the user says "OK," the device captures the voice again and sends it to the server. The server confirms and analyzes the "OK" voice confirmation, then performs the payment and sends a notification to the device stating, "Payment has been completed." The device then plays the message and notifies the user that the payment has been completed.

[1191] This series of processes allows users to complete payments quickly and smoothly, eliminating the need to scan QR codes or enter amounts, and utilizing voice and emotion recognition technology.

[1192] The processing flow will be explained below.

[1193] Program processing details

[1194] Step 1:

[1195] The user issues a voice command saying, "Please make payment."

[1196] Step 2:

[1197] The terminal acquires the user's voice instructions through a microphone.

[1198] Step 3:

[1199] The terminal transmits the acquired voice data to the server.

[1200] Step 4:

[1201] The server converts the received voice data into text using a voice recognition engine.

[1202] Step 5:

[1203] The server runs the converted voice data through a natural language processing engine and determines the user's intent as a "payment instruction."

[1204] Step 6:

[1205] The server runs the voice data through an emotion recognition engine to analyze the user's emotional state.

[1206] Step 7:

[1207] The server generates a voice message based on the user's intention and emotional state, such as "I'll pay for XX yen. Please say OK if you're happy with that." For example, if the user is anxious, the server generates a message in a polite and steady tone.

[1208] Step 8:

[1209] The server sends the generated voice message to the terminal.

[1210] Step 9:

[1211] The terminal plays the voice message received from the server and asks the user for confirmation.

[1212] Step 10:

[1213] The user confirms by saying "OK."

[1214] Step 11:

[1215] The terminal again obtains the user's approval voice.

[1216] Step 12:

[1217] The terminal transmits the acquired approval voice data to the server.

[1218] Step 13:

[1219] The server receives the approval voice data and converts it into text through a voice recognition engine.

[1220] Step 14:

[1221] The server checks the textual approval and determines that it contains "OK."

[1222] Step 15:

[1223] The server runs the approval voice through an emotion recognition engine to check the user's emotional state at the time of approval, for example, checking whether the user is feeling hesitant or anxious.

[1224] Step 16:

[1225] The server determines the certainty of the authorization and then sends a payment instruction to the payment system.

[1226] Step 17:

[1227] The payment system executes the payment and sends the result back to the server.

[1228] Step 18:

[1229] The server confirms the completion of the payment and generates a "payment completed" notification.

[1230] Step 19:

[1231] The server sends the generated payment completion message to the terminal.

[1232] Step 20:

[1233] The terminal reproduces the payment completion message received from the server and notifies the user.

[1234] Example 2

[1235] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1236] Conventional payment systems require users to perform time-consuming tasks such as scanning QR codes or manually entering the amount. This can make the payment process particularly cumbersome and detract from the user experience. Furthermore, conventional systems have difficulty properly understanding the user's emotions and intentions, making them prone to misrecognition and incorrect operation, especially for inexperienced users. Therefore, there is a need for a user-friendly and reliable payment method that combines voice recognition and emotion recognition.

[1237] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1238] In this invention, the server includes means for analyzing voice data to determine the user's intention, means for analyzing the user's emotions, and means for notifying the user of payment completion. This not only recognizes the user's voice but also analyzes their emotions to generate an appropriate response, enabling a fast and smooth payment.

[1239] A "user" is an individual making a payment and issuing a voice instruction.

[1240] The term "means for acquiring voice instructions" refers to a device and its function for acquiring voices uttered by a user through a microphone.

[1241] "Central Processing Unit" refers to a server or high performance computing device for processing and managing voice data and analysis results.

[1242] "Means for analyzing voice data" refers to a voice recognition module or engine that analyzes the acquired voice data and extracts the necessary information.

[1243] "Means for determining the user's intent" refers to a natural language processing module or software that interprets the user's instructions based on the voice recognition results and determines their intent.

[1244] "Means for confirming to the user as a voice message" refers to a device and software that generates and plays a voice message to ask the user for confirmation.

[1245] "Means for analyzing user emotions" refers to emotion recognition modules or algorithms that identify user emotions from acquired voice data.

[1246] The "means for acquiring voice approval" refers to a device and its function for re-acquiring the voice approval uttered by the user.

[1247] "Means for effecting payments" means a payment system or API that effectuates the payment of amounts based on payment instructions.

[1248] "Means for notifying the user that payment has been completed" refers to a device or system that generates and plays a voice message to inform the user that payment has been completed.

[1249] "Speech Recognition Module" refers to software and hardware capable of converting speech into text.

[1250] A "natural language processing module" refers to software and hardware that has the ability to analyze text data and interpret the user's intentions and requests.

[1251] "Specific approval keywords" refer to predetermined spoken words or phrases that a user utters to indicate approval.

[1252] The "means for transmitting the acquired voice data to the central processing unit" refers to the communication protocol and network infrastructure for transmitting the voice data from the terminal to the central processing unit.

[1253] This invention relates to a voice payment system that utilizes speech recognition, natural language processing, and emotion recognition technologies. By allowing users to issue payment instructions via voice, the system eliminates the need to scan a QR code or enter the amount, providing a fast and smooth payment experience. Furthermore, by recognizing the user's emotions, it is possible to improve the reliability of the payment process and the user experience.

[1254] This system consists of various devices and technologies, such as a user, a device, a server, and a payment system. The device receives voice instructions from the user and sends them to the server. The server converts the voice data into text using a speech recognition engine (e.g., Google Cloud Speech-to-Text). The converted text is analyzed by a natural language processing engine (e.g., OpenAI GPT-4) to determine the user's intention. Furthermore, the user's emotions are analyzed by an emotion recognition engine (e.g., Microsoft Azure Emotion API).

[1255] Specifically, the system operates according to the following procedure.

[1256] When a user issues a voice command such as "please make a payment," the device captures the voice through the microphone and transmits it to the server in real time. The server receives the voice data and converts it into text using Google Cloud Speech-to-Text. The server then analyzes the text using OpenAI GPT-4 and determines that the user's intent is "to make a payment."

[1257] The server then uses the Microsoft Azure Emotion API to perform emotion recognition and determine the user's emotional state. Based on this information, the server generates a tailored voice message, such as "I'll pay you 500 yen. Please say OK if you're happy with this." This message is then sent to the device, which plays it back and asks for the user's confirmation.

[1258] If the user approves by saying "OK," the device captures the speech again and sends it to the server, which again uses Google Cloud Speech-to-Text to convert the speech to text, confirming that "OK" is included, and again uses the emotion recognition engine to determine the certainty of the approval.

[1259] Finally, the server sends a payment instruction to the payment system (e.g., Stripe) to execute the payment. When the payment is complete, the server generates a voice message saying "Payment completed" and sends it to the terminal. The terminal plays the message to notify the user that the payment has been completed.

[1260] As a concrete example, consider a situation where a user places an order at a cafe and pays at the cash register. The user says "Please pay" at the register, and the device captures this voice and sends it to the server. The server analyzes the voice data and generates the text "Please pay." The text is analyzed using a natural language processing engine to confirm the user's intention. An emotion recognition engine then analyzes the user's emotions and generates an appropriate voice message. If the user approves with "OK," the voice data is sent again to the server, and finally the payment is made and a completion notification is sent.

[1261] An example of a prompt sentence to input to the generative AI model is as follows:

[1262] prompt:

[1263] Please explain in detail what happens in a voice payment system when a user says "please pay" at the cash register. Please provide a detailed description of the entire process from when the terminal receives the voice message and sends it to the server, to when the server analyzes and recognizes it and executes the payment.

[1264] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1265] Step 1:

[1266] Acquiring voice commands

[1267] The user issues a voice command saying, "Please make payment."

[1268] Input: User's voice commands

[1269] The device captures the user's voice through a microphone, splits it into fragments in real time, and sends them as data packets to the server via the HTTPS protocol.

[1270] Output: Captured audio data (data packets)

[1271] Step 2:

[1272] Analysis of audio data

[1273] The server receives the audio data and converts it into text using Google Cloud Speech-to-Text.

[1274] Input: Captured audio data (data packets)

[1275] The server runs a voice recognition engine, analyzes the voice data, and generates the text "Please make payment."

[1276] Output: Text data (e.g. "Please make payment")

[1277] Step 3:

[1278] Determining intent

[1279] The text generated by the server is analyzed using OpenAI GPT-4, and the user's intention is determined to be a "payment instruction."

[1280] Input: Text data (e.g. "Please make payment")

[1281] The server uses a natural language processing engine to analyze the context of the text and interpret the intent as "payment instructions."

[1282] Output: User's instructions (e.g. "Payment instructions")

[1283] Step 4:

[1284] Emotion recognition

[1285] The server uses the Microsoft Azure Emotion API to analyze the user's emotions from the voice data.

[1286] Input: Captured audio data (data packets)

[1287] The server extracts features from the voice data and inputs them into an emotion recognition engine to identify emotions such as "joy" or "relief."

[1288] Output: User's emotional data (e.g., "Relief")

[1289] Step 5:

[1290] Confirm payment details

[1291] The server takes the user's emotions into consideration and generates an adjusted voice message such as, "I will pay for XX yen. If you agree, please say OK."

[1292] Input: User instructions, user emotion data (e.g., "Payment instructions," "Relief")

[1293] The server generates a voice message saying, "The payment will be 500 yen. If you agree, please say OK." This message is sent to the terminal, which plays it back.

[1294] Output: The generated voice message

[1295] Step 6:

[1296] User Authorization

[1297] The user confirms by saying "OK."

[1298] Input: A confirmation message from the server

[1299] The terminal captures the user's approval voice through the microphone and transmits it again to the server as a data packet.

[1300] Output: Acquired acknowledgement voice data (data packets)

[1301] Step 7:

[1302] Parsing Authorizations

[1303] The server again converts the approval speech into text using Google Cloud Speech-to-Text.

[1304] Input: Acquired acknowledgement voice data (data packets)

[1305] The server runs a speech recognition engine to analyze the audio data and generate the text "OK," and an emotion recognition engine to ensure that it contains a positive emotion, such as "relief."

[1306] Output: Text data (e.g., "OK"), emotion data (e.g., "Relieved")

[1307] Step 8:

[1308] Executing payments

[1309] The server sends a payment instruction to a payment system such as Stripe or PayPal to execute the payment.

[1310] Input: Text data (e.g., "OK"), user instructions (e.g., "Payment instructions")

[1311] The server sends a request for 500 yen to the payment system via the REST API and receives a success response.

[1312] Output: Payment completion data

[1313] Step 9:

[1314] Payment completion notification

[1315] The server confirms the completion of the payment and generates a voice message saying "Payment completed."

[1316] Input: Payment completion data

[1317] The server generates a voice message saying "Payment completed. Thank you very much" and sends it to the terminal. While the message is played, the terminal displays "Payment completed" on the screen.

[1318] Output: The generated voice message

[1319] (Application example 2)

[1320] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1321] Conventional payment systems require users to scan a QR code and input the amount, which is a cumbersome process. Furthermore, even payment systems that use voice instructions have the problem of not being able to fully reflect the user's intentions and emotions, making it difficult to improve reliability and user experience. The present invention aims to solve these problems and provide a new voice payment system that improves user convenience and reliability.

[1322] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring a user's voice instruction, means for transmitting the acquired voice data to the server, means for analyzing the voice data and determining the user's intention, means for generating payment details based on the user's intention and confirming them as a voice message to the user, means for acquiring an approval voice from the user, means for transmitting the acquired approval voice to the server, means for analyzing the approval voice and executing the payment, means for notifying the user of payment completion, means for determining the user's emotion from the voice data, and means for adjusting the confirmation message based on the emotion determination result. This allows the user to avoid scanning a QR code or entering an amount, and enables highly reliable, quick and comfortable payment to be executed through emotion recognition.

[1323] A "means for obtaining voice instructions" is a device or system for collecting voice commands uttered by a user.

[1324] The "means for transmitting voice data to a server" refers to a device or system that has the function of transferring acquired voice information to a server via a network.

[1325] "Means for analyzing voice data and determining user intent" refers to an algorithm or engine that extracts text from voice data and interprets the user's requests and intent based on that text.

[1326] The "means for generating payment details and confirming them to the user as a voice message" is a system for creating payment details based on text data and playing them back as voice.

[1327] The "means for acquiring approval voice" is a device or system for collecting approval voice uttered by a user.

[1328] The "means for transmitting the acquired approval voice to the server" refers to a device or system that has the function of transferring the user's approval voice to the server via a network.

[1329] The "means for analyzing the approval voice and executing the payment" refers to an algorithm and system for converting the user's approval voice into text and completing the payment process based on that text.

[1330] The "means for notifying the user of the completion of the payment" is a system that generates and plays a voice message to notify the user that the payment has been successfully completed.

[1331] The "means for determining the user's emotion from the voice data" refers to an algorithm or engine for analyzing the emotional information contained in the voice data and identifying the user's emotional state.

[1332] The "means for adjusting the confirmation message based on the emotion determination result" is a system for appropriately changing the content and tone of the confirmation message depending on the user's emotional state.

[1333] This invention relates to a voice payment system that utilizes speech recognition, natural language processing, and emotion recognition technologies. This system allows users to issue payment instructions via voice, eliminating the need to scan a QR code or enter the amount, and providing a fast and smooth payment experience. Furthermore, by recognizing the user's emotions, it is possible to improve the reliability of the payment process and the user experience.

[1334] The system includes the following components:

[1335] 1. User: The individual making the payment and issuing the voice command.

[1336] 2. Terminal: The device through which the user issues voice commands, including a smartphone, tablet, or dedicated terminal. The terminal is responsible for capturing the user's voice and sending it to the server.

[1337] 3. Server: Receives the voice data, analyzes it using a speech recognition engine, natural language processing engine, and emotion recognition engine, and executes the payment.

[1338] 4. Payment system: This is the system that actually processes payments based on the payment instructions sent from the server.

[1339] Program processing

[1340] 1. Acquiring voice instructions

[1341] The user issues a voice command such as "Please make the payment." The device picks up this voice using the built-in microphone and sends the voice data to the cloud server.

[1342] 2. Analysis of audio data

[1343] The server analyzes the acquired voice data using a speech recognition engine (e.g., Google Cloud Speech-to-Text API) and converts it into text data. It then analyzes the text using a natural language processing engine (e.g., Google Cloud Natural Language API) to determine the user's intent.

[1344] 3. Emotional Recognition

[1345] The server analyzes the voice data using an emotion recognition engine (e.g., IBM Watson Tone Analyzer) to determine the user's emotions.

[1346] 4. Confirm payment details

[1347] The server generates an adjusted confirmation message, "I will pay for XX yen. Please say OK if you agree," taking into account the user's feelings, and sends it to the terminal. The terminal plays this message and asks the user for confirmation.

[1348] 5. User Acknowledgment

[1349] The user approves by saying "OK." The device reacquires the approval voice and sends it to the server.

[1350] 6. Acknowledgment Analysis

[1351] The server converts the received approval voice into text using a speech recognition engine, checks whether it contains "OK," and then checks the emotion of the approval voice again.

[1352] 7. Payment Execution

[1353] The server sends a payment instruction to the payment system (e.g. Stripe API) to execute the payment.

[1354] 8. Payment completion notification

[1355] The server confirms the completion of the payment and generates a voice message saying "Payment completed." The terminal plays this message to notify the user.

[1356] Specific examples

[1357] For example, after a user finishes shopping at a supermarket, they open a smartphone app and say, "Please make the payment." The device receives this instruction and sends the voice data to the server. The server then analyzes the voice data using a speech recognition engine and converts it into text. It then uses a natural language processing engine to determine the user's intent when they say, "Please make the payment." It then uses an emotion recognition engine to analyze the user's emotion from the voice data. Based on these analysis results, the device generates a tailored confirmation message, such as, "I'll pay 500 yen. Please say OK if you're happy with this," and sends it to the device. The device then plays this message to ask the user for confirmation. When the user replies, "OK," the voice is sent again to the server, where the approval voice is analyzed, confirming that it contains "OK," and the emotion is also reconfirmed. A payment instruction is then sent to the payment system, and the payment is executed. Finally, the user is notified that the payment has been completed.

[1358] Example prompts to input to the generative AI model

[1359] When you say "please pay," it uses speech recognition, natural language processing, and emotion recognition technologies to analyze your spoken payment instructions and complete the payment on your smartphone. Based on emotion recognition, it provides feedback to improve the user experience.

[1360] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1361] Step 1:

[1362] Acquiring voice commands

[1363] Input: A user speaks the command "please pay."

[1364] Specific operation: The user speaks into the microphone on the device (smartphone, tablet, etc.) saying "Please make payment."

[1365] Output: The device uses a built-in microphone to capture audio data, which is then converted into a digital format and sent directly to the server.

[1366] Step 2:

[1367] Sending audio data to the server

[1368] Input: Audio data captured by the device.

[1369] Specific operation: The device sends the acquired voice data to a cloud server via the network (Wi-Fi or 4G / 5G communication).

[1370] Output: The server receives the audio data sent from the terminal.

[1371] Step 3:

[1372] Analysis of audio data

[1373] Input: The audio data received by the server.

[1374] How it works: The server uses a speech recognition engine (e.g., Google Cloud Speech-to-Text API) to convert the voice data into text, which is then analyzed by a natural language processing engine (e.g., Google Cloud Natural Language API) to determine the user's intent (e.g., "please make payment").

[1375] Output: Text data as the analysis result and the user's intent.

[1376] Step 4:

[1377] Emotion recognition

[1378] Input: The audio data received by the server.

[1379] Specific operation: The server uses an emotion recognition engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotions from the voice data. This analysis evaluates whether the user is relaxed or stressed.

[1380] Output: Emotion data as the analysis result (e.g., relaxed, stressed, etc.).

[1381] Step 5:

[1382] Confirm payment details

[1383] Input: Text data and emotion data as analysis results.

[1384] Specific operation: The server generates a tailored confirmation message (e.g., "I will pay 500 yen. Please say OK if you agree") taking into account the user's feelings. It then sends this message to the terminal.

[1385] Output: The generated confirmation message and its transmission from the server.

[1386] Step 6:

[1387] Play confirmation message

[1388] Input: The confirmation message sent by the server.

[1389] Specific operation: The terminal plays a voice message and asks the user for confirmation (e.g., "The payment amount is 500 yen. Please say OK if you agree").

[1390] Output: An audio message is played to the user.

[1391] Step 7:

[1392] User Authorization

[1393] Input: The user's voice command after hearing the confirmation message (e.g., "OK").

[1394] Specific operation: The user approves by saying "OK" into the device's microphone. The device captures this voice and sends it back to the server.

[1395] Output: The acknowledgement voice acquired by the device is sent to the server.

[1396] Step 8:

[1397] Analysis of approval voice

[1398] Input: The acknowledgment audio sent to the server.

[1399] Specific operation: The server again uses the speech recognition engine to convert the approval voice into text and checks whether it contains "OK." It then uses the emotion recognition engine to check the emotion of the approval voice again.

[1400] Output: Text data and emotion data as analysis results.

[1401] Step 9:

[1402] Executing payments

[1403] Input: Approval data and emotion data as analysis results.

[1404] Specific operation: The server sends a payment instruction to the payment system (e.g. Stripe API) to execute the payment.

[1405] Output: The result of the payment execution (success or failure).

[1406] Step 10:

[1407] Payment completion notification

[1408] Input: Payment execution result.

[1409] Specific operation: The server confirms the completion of the payment, generates a voice message saying "Payment completed" and sends it to the terminal. The terminal plays this message to notify the user.

[1410] Output: A payment completion message is played to the user.

[1411] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1412] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1413] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1414] [Fourth embodiment]

[1415] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1416] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1417] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1418] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1419] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1420] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1421] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1422] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1423] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1424] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1425] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1426] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1427] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1428] The present invention relates to a voice payment system that utilizes voice recognition technology and natural language processing technology. By allowing users to issue payment instructions by voice, the process of scanning a QR code and entering the amount is eliminated, providing a fast and smooth payment experience.

[1429] System configuration

[1430] This system consists of the following various devices and technologies:

[1431] 1. User: The individual making the payment and issuing the voice command.

[1432] 2. Terminal: The device through which the user issues voice commands, including a smartphone, tablet, or dedicated terminal. The terminal is responsible for capturing the user's voice and sending it to the server.

[1433] 3. Server: Receives the voice data, analyzes it using a voice recognition engine and natural language processing engine, and executes the payment.

[1434] 4. Payment system: This is the system that actually processes payments based on the payment instructions sent from the server.

[1435] Program processing

[1436] 1. Acquiring voice instructions

[1437] The user issues a voice command saying, "Please make payment."

[1438] The terminal captures the user's voice through a microphone and transmits the voice data to a server.

[1439] 2. Analysis of audio data

[1440] The server receives the voice data and converts it into text using a voice recognition engine.

[1441] The server analyzes the converted text using a natural language processing engine to determine the user's intent.

[1442] 3. Confirm payment details

[1443] The server generates a voice message saying, "The payment will be for XX yen. If you agree, please say OK," and sends it to the terminal.

[1444] The terminal plays this voice message and asks the user for confirmation.

[1445] 4. User Acknowledgment

[1446] The user confirms by saying "OK."

[1447] The terminal again captures the user's voice and transmits it to the server.

[1448] 5. Execution of payment

[1449] The server receives the voice confirmation and uses the voice recognition engine to convert the voice "OK" into text and confirm it.

[1450] The server instructs the payment system to pay the amount and executes the payment.

[1451] 6. Payment completion notification

[1452] The server confirms the completion of the payment and sends a notification to the terminal that "payment has been completed."

[1453] The terminal plays this voice message to the user to notify them that the payment has been successfully completed.

[1454] Specific examples

[1455] For example, consider the case where a user is shopping at a supermarket and wants to make a payment at the register. The user says, "Please make the payment." The device captures this voice and sends it to the server. The server analyzes the voice data using a voice recognition engine and obtains the text "Please make the payment." It then analyzes the text using a natural language processing engine to confirm the user's intention. It then generates a voice message saying, "I will pay for 3,500 yen. Please say OK if you are happy with this," and sends it to the device. The device plays the message and asks the user for confirmation. When the user says "OK," the device captures the voice again and sends it to the server. After the server confirms the "OK" approval, it carries out the payment and notifies the device that "payment has been completed." The device then plays the message and notifies the user that the payment has been completed.

[1456] This series of processes allows users to complete payments quickly and smoothly using only their voice, eliminating the need to scan a QR code or enter the amount.

[1457] The processing flow will be explained below.

[1458] Program processing details

[1459] Step 1:

[1460] The user issues a voice command saying, "Please make payment."

[1461] Step 2:

[1462] The terminal acquires the user's voice instructions through a microphone.

[1463] Step 3:

[1464] The terminal transmits the acquired voice data to the server.

[1465] Step 4:

[1466] The server converts the received voice data into text using a voice recognition engine.

[1467] Step 5:

[1468] The server analyzes the converted text using a natural language processing engine and determines the user's intent as a "payment instruction."

[1469] Step 6:

[1470] Based on the user's instructions, the server generates a payment confirmation voice message saying, "I will pay for XX yen. If you agree, please say OK."

[1471] Step 7:

[1472] The server sends the generated voice message to the terminal.

[1473] Step 8:

[1474] The terminal plays the voice message received from the server and asks the user for confirmation.

[1475] Step 9:

[1476] The user confirms by saying "OK."

[1477] Step 10:

[1478] The terminal again obtains the user's approval voice.

[1479] Step 11:

[1480] The terminal transmits the acquired approval voice data to the server.

[1481] Step 12:

[1482] The server receives the approval voice data and converts it into text using a voice recognition engine.

[1483] Step 13:

[1484] The server checks the textual approval and determines that it contains "OK."

[1485] Step 14:

[1486] After the server confirms the authorization, it sends an instruction to pay the amount to the payment system.

[1487] Step 15:

[1488] The payment system executes the payment and sends the result back to the server.

[1489] Step 16:

[1490] The server confirms the completion of the payment and generates a voice message saying "Payment completed."

[1491] Step 17:

[1492] The server sends the generated payment completion message to the terminal.

[1493] Step 18:

[1494] The terminal reproduces the payment completion message received from the server and notifies the user.

[1495] Example 1

[1496] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1497] Conventional payment systems require users to scan QR codes or manually enter amounts, making the payment process cumbersome and making it difficult to provide a fast and smooth payment experience. Furthermore, conventional systems have low accuracy in speech recognition and natural language processing, which can easily lead to misrecognition of user intent.

[1498] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1499] In this invention, the server includes means for analyzing voice data and determining the user's intention, means for generating payment details based on the user's intention and confirming them with the user as a voice message, and means for analyzing the approval voice and executing the payment. This allows the user to complete the payment using only voice, eliminating the need to scan a QR code or manually enter the amount, enabling quick and smooth payment. Furthermore, by integrating a voice recognition engine and a natural language processing engine, voice data can be accurately converted and analyzed into text, enabling highly accurate determination of the user's intention.

[1500] A "user" is an individual who operates the system and issues voice commands.

[1501] A "terminal" is a device that acquires the user's voice and transmits the acquired voice data to a server.

[1502] The "server" is a central processing unit that analyzes voice data to determine the user's intentions and executes the payment.

[1503] A "speech recognition engine" is a software or hardware component for converting voice data into text.

[1504] A "natural language processing engine" is a software or hardware component for analyzing text and interpreting user intent.

[1505] A "speech synthesis engine" is a software or hardware component for converting text data into a voice message.

[1506] The "approval voice" is a voice uttered by the user to approve the payment details.

[1507] A "payment system" is a system for executing payments and returning the processing results to the server.

[1508] "Communication means" refers to the technical elements for sending and receiving data between a terminal and a server in real time.

[1509] This invention relates to a voice payment system that utilizes voice recognition and natural language processing technologies. By allowing users to issue payment instructions via voice, it eliminates the need to scan a QR code or input the amount, providing a fast and smooth payment experience. This system is composed of the following various devices and technologies:

[1510] 1. Users

[1511] The user is the individual making the payment and issues instructions to the system by speaking.

[1512] 2. Terminal

[1513] The terminal is the device through which the user issues voice commands, and can be a smartphone, tablet, or dedicated terminal. The terminal has the function of capturing the user's voice through a microphone and sending the voice data to a server. Communication technologies such as WebSocket are used to send and receive voice data in real time.

[1514] 3. Server

[1515] The server analyzes the voice data and determines the user's intent. Specifically, it converts the voice data into text using a speech recognition engine (e.g., Google Cloud Speech-to-Text), analyzes the text using a natural language processing engine (e.g., Google Cloud Natural Language), and interprets the user's intent. The server also generates confirmation and notification messages using a speech synthesis engine (e.g., Google Cloud Text-to-Speech), and sends them to the device.

[1516] 4. Payment System

[1517] A payment system is a system that processes actual payments based on payment instructions sent from a server. Specific examples include online payment platforms such as Stripe and PayPal.

[1518] Specific examples

[1519] For example, consider a case where a user is shopping at a supermarket and wants to pay at the register. The user says, "Please pay." The device captures this speech and sends it to the server. The server analyzes the speech data using Google Cloud Speech-to-Text and obtains the text "Please pay." The text is analyzed using Google Cloud Natural Language to confirm the user's intent. Google Cloud Text-to-Speech then generates a voice message saying, "I'll pay 3,500 yen. If you're happy with this, please say OK," and sends it to the device. The device plays the message and asks the user for confirmation. When the user says "OK," the device captures the speech again and sends it to the server. The server again recognizes it as "OK" using Google Cloud Speech-to-Text and calls the Stripe API to complete the payment. Finally, the server sends a notification to the device stating, "Payment completed," and the device plays the message to the user, completing the payment.

[1520] Example prompt sentence:

[1521] I want to pay by voice at the supermarket checkout. Please follow the instructions below to make a voice payment.

[1522] 1. Say "Please make payment."

[1523] 2. When the payment amount is presented, say "OK."

[1524] In this way, the voice payment system of the present invention allows users to complete payments simply and quickly using only their voice, without the need for complicated operations, thereby simultaneously improving the user experience and streamlining the payment process at stores.

[1525] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1526] Step 1:

[1527] The user gives the command "Please make payment" by voice. The device's built-in microphone picks up the user's voice. This voice data is temporarily stored in the device's local storage. The input is voice data, and the output is an audio file stored on the device. The specific operation uses the smartphone's microphone function.

[1528] Step 2:

[1529] The device compresses the audio data it acquires and sends it to the server. The input is the compressed audio data, and the output is the audio data sent to the server. Specifically, the device sends the data to the server in real time via WebSocket.

[1530] Step 3:

[1531] The server receives the voice data and calls the speech recognition engine (Google Cloud Speech-to-Text). The input is voice data and the output is text data. Specifically, the server sends the voice data to the API and receives a response in text format.

[1532] Step 4:

[1533] The server analyzes the text data using a natural language processing engine (Google Cloud Natural Language) to determine the user's intent. The input is text data converted from speech, and the output is data indicating the user's intent. Specific operations include entity extraction and sentiment analysis, and the system recognizes that the user's instruction is a payment.

[1534] Step 5:

[1535] The server uses a speech synthesis engine (Google Cloud Text-to-Speech) to generate a voice message saying, "I'll pay for XX yen. If you're happy with that, please say OK." The input is the user's intention and amount information, and the output is synthesized voice data. The specific operation is to convert the required text message into an audio file.

[1536] Step 6:

[1537] The server generates a voice message and sends it to the device. The input is synthesized voice data, and the output is the voice data sent to the device. The server then sends the data back to the device using WebSocket.

[1538] Step 7:

[1539] The device plays the received voice message and asks the user for confirmation. The input is the voice data sent from the server, and the output is the voice message being played. Specifically, the message is played using the smartphone's audio player function.

[1540] Step 8:

[1541] The user approves by saying "OK." The device again captures the user's voice and sends it to the server. The input is the approval voice data, and the output is the voice data sent to the server. In concrete terms, the voice data is captured in the same way as in the previous step and sent to the server.

[1542] Step 9:

[1543] The server receives the approval voice and again uses the speech recognition engine to convert the "OK" voice into text and confirm it. The input is the approval voice data and the output is text data. Specifically, the approval voice is sent to the API and a response in text format is received.

[1544] Step 10:

[1545] The server instructs the payment system (such as Stripe or PayPal) to make the payment and executes the payment. The input is the amount and the user's confirmation information, and the output is the payment result data. Specifically, the transaction is processed by calling the payment system's API.

[1546] Step 11:

[1547] The server confirms the completion of the payment, generates a notification "Payment completed" using a speech synthesis engine, and sends it to the terminal. The input is the payment result data, and the output is a synthesized speech notification. Specifically, the speech notification is generated using Google Cloud Text-to-Speech.

[1548] Step 12:

[1549] The terminal plays the received voice message to the user to notify them that the payment has been successfully completed. The input is the voice data sent from the server, and the output is the voice message that is played. Specifically, the notification is made using the smartphone's audio player function.

[1550] (Application example 1)

[1551] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1552] Conventional payment systems require the user to scan a QR code and enter the amount, which can be time-consuming and disruptive to the user's payment experience. Furthermore, manual approval procedures can degrade the user experience. There is a need for technology that can resolve these issues and enable more efficient and faster payments.

[1553] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1554] In this invention, the server includes means for acquiring a user's voice instruction, means for transmitting the acquired voice data to the server, means for analyzing the voice data and determining the user's intention, means for generating payment details based on the user's intention and confirming them as a voice message to the user, means for acquiring voice approval from the user, means for transmitting the acquired voice approval to the server, means for analyzing the voice approval and executing the payment, means for notifying the user that the payment has been completed, means for performing voice recognition and natural language processing via the smart device, and means for generating a voice message using prompt sentences and a generative AI model, thereby enabling the user to complete payment quickly and smoothly using only their voice.

[1555] "User" refers to the person or organization issuing the voice command.

[1556] "Voice instruction" refers to an instruction given by voice to a device by a user.

[1557] A "terminal" is a device that receives a user's voice instructions and transmits them to the server, and includes smartphones, smart glasses, and the like.

[1558] "Server" refers to a computer system that has the function of analyzing acquired voice data, determining the user's intentions, and carrying out payment processing.

[1559] "Audio data" refers to a digital data file that records a user's voice.

[1560] A "voice recognition engine" refers to software or algorithms that analyze voice data and convert it into text.

[1561] A "natural language processing engine" refers to software or algorithms that analyze text data and understand the user's intent and meaning.

[1562] "Payment system" refers to a system that actually processes payments based on user payment instructions.

[1563] "Prompt sentence" refers to the text used to generate a voice message using a generative AI model.

[1564] "Generative AI models" refer to machine learning models or artificial intelligence models used to perform natural language processing.

[1565] A "smart device" is a device for performing voice recognition and natural language processing, including smartphones and smart glasses.

[1566] "Approval voice" refers to voice data uttered by a user when approving payment by voice.

[1567] "Payment completion notification" refers to a notification to inform the user that the payment process has been successfully completed.

[1568] This invention provides a voice payment system that utilizes voice recognition and natural language processing technologies to enable users to make payments quickly and smoothly by voice instructions. This system works in conjunction with a server via a smart device, automating the entire process from voice instructions to payment completion.

[1569] This system consists of the following various devices and technologies:

[1570] 1. User: A person or organization that issues voice commands.

[1571] 2. Terminal: A device that receives the user's voice instructions and sends them to the server, including smartphones, smart glasses, etc.

[1572] 3. Server: A computer system that analyzes voice data, determines the user's intentions, and processes payments.

[1573] 4. Speech recognition engine: Software and algorithms that convert voice data into text.

[1574] 5. Natural language processing engine: Software and algorithms that analyze text data and understand user intent.

[1575] 6. Generative AI models: These are machine learning models used to perform natural language processing.

[1576] 7. Prompt: This is the text used to generate a voice message using the generative AI model.

[1577] System configuration

[1578] 1. Obtaining user voice commands

[1579] The user issues a voice command saying, "Please make payment."

[1580] The terminal receives this audio and transmits the audio data to the server.

[1581] 2. Analysis of audio data

[1582] The server converts the voice data into text using a voice recognition engine.

[1583] The server analyzes the converted text using a natural language processing engine to determine the user's intent.

[1584] 3. Confirm payment details

[1585] The server uses a generative AI model with the prompt sentence to generate a voice message such as, "I'll pay for XX yen. If you agree, please say OK."

[1586] The generated voice message is sent to the terminal.

[1587] The terminal plays this voice message and asks the user for confirmation.

[1588] 4. User Acknowledgment

[1589] The user confirms by saying "OK."

[1590] The terminal again captures the user's voice and sends it to the server.

[1591] The server analyzes the voice confirmation and again uses a speech recognition engine to convert the voice "OK" into text.

[1592] The server instructs the payment system to pay the amount and executes the payment.

[1593] 5. Payment completion notification

[1594] The server confirms the completion of the payment and sends a notification to the terminal that "payment has been completed."

[1595] The terminal plays this voice message to the user to notify them that the payment has been successfully completed.

[1596] Specific examples

[1597] For example, a user is shopping at a supermarket and says "Please make the payment" at the cash register. The device captures this voice and sends it to the server. The server analyzes the voice data using a voice recognition engine and obtains the text "Please make the payment." It then analyzes the text using a natural language processing engine to confirm the user's intention. It then uses a generative AI model to generate a voice message saying "I will pay 3,500 yen. Please say OK if you are happy with this," and sends it to the device. The device plays the message and asks the user for confirmation. When the user says "OK," the device captures the voice again and sends it to the server. The server again confirms "OK" using its voice recognition engine, then carries out the payment and notifies the device that "payment has been completed." The device then plays back the message, informing the user that the payment has been completed.

[1598] Prompt Sentence Examples

[1599] Say "please pay."

[1600] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1601] Step 1:

[1602] The user issues a voice command saying, "Please make the payment." The terminal captures this voice using the built-in microphone. The captured voice data is saved as digital data within the terminal. The saved data is then sent to the server in the next step.

[1603] Step 2:

[1604] The device sends the acquired voice data to the server. This procedure uses a communication protocol (e.g., HTTP, WebSocket, etc.) to transfer the voice data to the server. The sent data is then passed to the voice recognition engine on the server side.

[1605] Step 3:

[1606] The server converts the voice data into text using a speech recognition engine. The input is voice data and the output is text data. The speech recognition engine analyzes the voice waveform and generates a corresponding string of characters.

[1607] Step 4:

[1608] The server passes the generated text data to a natural language processing engine for analysis. Here, the context and keywords of the text data are analyzed to identify the user's intent. This process recognizes the user's request, "Please make payment." The input is text data, and the output is data that represents the user's intent.

[1609] Step 5:

[1610] The server generates payment details based on the user's intent. It uses a prompt (e.g., "I'll pay 3,500 yen. Please say OK if you agree.") and generates a voice message using a generative AI model. The input is the payment details and the prompt, and the output is a voice message.

[1611] Step 6:

[1612] The server sends the generated voice message to the terminal, and the terminal plays the received voice message to the user. The hardware used here is a speaker, and this prompts the user for confirmation.

[1613] Step 7:

[1614] The user approves by saying "OK." The device again uses the built-in microphone to capture the user's voice and sends the data to the server.

[1615] Step 8:

[1616] The server analyzes the acquired approval voice again using a speech recognition engine and converts the voice "OK" into text. Next, it uses a natural language processing engine to check whether the approval voice contains specific approval keywords. The input is the voice data, and the output is the confirmation result of the approval keyword.

[1617] Step 9:

[1618] When the server confirms the authorization keyword, it instructs the payment system to pay the amount and executes the payment. The payment system then performs the actual payment processing based on this instruction. The input is the result of the authorization keyword confirmation, and the output is the result of the payment completion.

[1619] Step 10:

[1620] When the payment is complete, the server generates a notification saying "Payment completed" and sends it to the terminal. The terminal then plays this notification as a voice message to the user, informing them that the payment has been successfully completed.

[1621] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1622] This invention relates to a voice payment system that utilizes speech recognition, natural language processing, and emotion recognition technologies. By allowing users to issue payment instructions via voice, the system eliminates the need to scan a QR code or enter the amount, providing a fast and smooth payment experience. Furthermore, by recognizing the user's emotions, it is possible to improve the reliability of the payment process and the user experience.

[1623] System configuration

[1624] This system consists of the following various devices and technologies:

[1625] 1. User: The individual making the payment and issuing the voice command.

[1626] 2. Terminal: The device through which the user issues voice commands, including a smartphone, tablet, or dedicated terminal. The terminal is responsible for capturing the user's voice and sending it to the server.

[1627] 3. Server: Receives the voice data, analyzes it using a speech recognition engine, natural language processing engine, and emotion recognition engine, and executes the payment.

[1628] 4. Payment system: This is the system that actually processes payments based on the payment instructions sent from the server.

[1629] Program processing

[1630] 1. Acquiring voice instructions

[1631] The user issues a voice command saying, "Please make payment."

[1632] The terminal captures the user's voice through a microphone and transmits the voice data to a server.

[1633] 2. Analysis of audio data

[1634] The server receives the voice data and converts it into text using a voice recognition engine.

[1635] The server analyzes the converted text using a natural language processing engine and determines the user's intent as a "payment instruction."

[1636] 3. Emotional Recognition

[1637] The server analyzes the voice data using an emotion recognition engine to determine the user's emotions.

[1638] 4. Confirm payment details

[1639] The server takes the user's emotions into consideration and generates an adjusted voice message such as, "I will pay for XX yen. If you agree, please say OK."

[1640] The server sends this voice message to the terminal, which plays the message and asks the user for confirmation.

[1641] 5. User Acknowledgment

[1642] The user confirms by saying "OK."

[1643] The terminal again acquires the user's approval voice and transmits it to the server.

[1644] 6. Acknowledgment Analysis

[1645] The server receives the approval voice and converts it into text using a speech recognition engine.

[1646] The server checks the textual approval and determines that it contains "OK."

[1647] The server also reconfirms the sentiment of the approval voice to determine the certainty of approval.

[1648] 7. Payment Execution

[1649] The server sends a payment instruction to the payment system to execute the payment.

[1650] 8. Payment completion notification

[1651] The server confirms the completion of the payment and generates a voice message saying "Payment completed."

[1652] The server transmits the generated payment completion message to the terminal, and the terminal reproduces the message to notify the user.

[1653] Specific examples

[1654] For example, consider a case where a user places an order at a cafe and wants to pay at the register. The user says, "Please pay." The device captures this voice and sends it to the server. The server analyzes the voice data using a voice recognition engine and obtains the text "Please pay." The natural language processing engine analyzes the text and confirms the user's intention. The server then analyzes the user's emotions using an emotion recognition engine and generates a voice message appropriately adjusted to match the user's emotions: "I will pay 500 yen. Please say OK if you are happy with this," which is sent to the device. The device plays the message and asks the user for confirmation. When the user says "OK," the device captures the voice again and sends it to the server. The server confirms and analyzes the "OK" voice confirmation, then performs the payment and sends a notification to the device stating, "Payment has been completed." The device then plays the message and notifies the user that the payment has been completed.

[1655] This series of processes eliminates the need for users to scan QR codes or enter amounts, and allows them to complete payments quickly and smoothly using voice and emotion recognition technology.

[1656] The processing flow will be explained below.

[1657] Program processing details

[1658] Step 1:

[1659] The user issues a voice command saying, "Please make payment."

[1660] Step 2:

[1661] The terminal acquires the user's voice instructions through a microphone.

[1662] Step 3:

[1663] The terminal transmits the acquired voice data to the server.

[1664] Step 4:

[1665] The server converts the received voice data into text using a voice recognition engine.

[1666] Step 5:

[1667] The server runs the converted voice data through a natural language processing engine and determines the user's intent as a "payment instruction."

[1668] Step 6:

[1669] The server runs the voice data through an emotion recognition engine to analyze the user's emotional state.

[1670] Step 7:

[1671] The server generates a voice message based on the user's intention and emotional state, such as "I'll pay for XX yen. Please say OK if you're happy with that." For example, if the user is anxious, the server generates a message in a polite and steady tone.

[1672] Step 8:

[1673] The server sends the generated voice message to the terminal.

[1674] Step 9:

[1675] The terminal plays the voice message received from the server and asks the user for confirmation.

[1676] Step 10:

[1677] The user confirms by saying "OK."

[1678] Step 11:

[1679] The terminal again obtains the user's approval voice.

[1680] Step 12:

[1681] The terminal transmits the acquired approval voice data to the server.

[1682] Step 13:

[1683] The server receives the approval voice data and converts it into text through a voice recognition engine.

[1684] Step 14:

[1685] The server checks the textual approval and determines that it contains "OK."

[1686] Step 15:

[1687] The server runs the approval voice through an emotion recognition engine to check the user's emotional state at the time of approval, for example, checking whether the user is feeling hesitant or anxious.

[1688] Step 16:

[1689] The server determines the certainty of the authorization and then sends a payment instruction to the payment system.

[1690] Step 17:

[1691] The payment system executes the payment and sends the result back to the server.

[1692] Step 18:

[1693] The server confirms the completion of the payment and generates a "payment completed" notification.

[1694] Step 19:

[1695] The server sends the generated payment completion message to the terminal.

[1696] Step 20:

[1697] The terminal reproduces the payment completion message received from the server and notifies the user.

[1698] Example 2

[1699] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1700] Conventional payment systems require users to perform time-consuming tasks such as scanning QR codes or manually entering the amount. This can make the payment process particularly cumbersome and detract from the user experience. Furthermore, conventional systems have difficulty properly understanding the user's emotions and intentions, making them prone to misrecognition and incorrect operation, especially for inexperienced users. Therefore, there is a need for a user-friendly and reliable payment method that combines voice recognition and emotion recognition.

[1701] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1702] In this invention, the server includes means for analyzing voice data to determine the user's intention, means for analyzing the user's emotions, and means for notifying the user of payment completion. This not only recognizes the user's voice but also analyzes their emotions to generate an appropriate response, enabling a fast and smooth payment.

[1703] A "user" is an individual making a payment and issuing a voice instruction.

[1704] The term "means for acquiring voice instructions" refers to a device and its function for acquiring voices uttered by a user through a microphone.

[1705] "Central Processing Unit" refers to a server or high performance computing device for processing and managing voice data and analysis results.

[1706] "Means for analyzing voice data" refers to a voice recognition module or engine that analyzes the acquired voice data and extracts the necessary information.

[1707] "Means for determining the user's intent" refers to a natural language processing module or software that interprets the user's instructions based on the voice recognition results and determines their intent.

[1708] "Means for confirming to the user as a voice message" refers to a device and software that generates and plays a voice message to ask the user for confirmation.

[1709] "Means for analyzing user emotions" refers to emotion recognition modules or algorithms that identify user emotions from acquired voice data.

[1710] The "means for acquiring voice approval" refers to a device and its function for re-acquiring the voice approval uttered by the user.

[1711] "Means for effecting payments" means a payment system or API that effectuates the payment of amounts based on payment instructions.

[1712] "Means for notifying the user that payment has been completed" refers to a device or system that generates and plays a voice message to inform the user that payment has been completed.

[1713] "Speech Recognition Module" refers to software and hardware capable of converting speech into text.

[1714] A "natural language processing module" refers to software and hardware that has the ability to analyze text data and interpret the user's intentions and requests.

[1715] "Specific approval keywords" refer to predetermined spoken words or phrases that a user utters to indicate approval.

[1716] The "means for transmitting the acquired voice data to the central processing unit" refers to the communication protocol and network infrastructure for transmitting the voice data from the terminal to the central processing unit.

[1717] This invention relates to a voice payment system that utilizes speech recognition, natural language processing, and emotion recognition technologies. By allowing users to issue payment instructions via voice, the system eliminates the need to scan a QR code or enter the amount, providing a fast and smooth payment experience. Furthermore, by recognizing the user's emotions, it is possible to improve the reliability of the payment process and the user experience.

[1718] This system consists of various devices and technologies, such as a user, a device, a server, and a payment system. The device receives voice instructions from the user and sends them to the server. The server converts the voice data into text using a speech recognition engine (e.g., Google Cloud Speech-to-Text). The converted text is analyzed by a natural language processing engine (e.g., OpenAI GPT-4) to determine the user's intention. Furthermore, the user's emotions are analyzed by an emotion recognition engine (e.g., Microsoft Azure Emotion API).

[1719] Specifically, the system operates according to the following procedure.

[1720] When a user issues a voice command such as "please make a payment," the device captures the voice through the microphone and transmits it to the server in real time. The server receives the voice data and converts it into text using Google Cloud Speech-to-Text. The server then analyzes the text using OpenAI GPT-4 and determines that the user's intent is "to make a payment."

[1721] The server then uses the Microsoft Azure Emotion API to perform emotion recognition and determine the user's emotional state. Based on this information, the server generates a tailored voice message, such as "I'll pay you 500 yen. Please say OK if you're happy with this." This message is then sent to the device, which plays it back and asks for the user's confirmation.

[1722] If the user approves by saying "OK," the device captures the speech again and sends it to the server, which again uses Google Cloud Speech-to-Text to convert the speech to text, confirming that "OK" is included, and again uses the emotion recognition engine to determine the certainty of the approval.

[1723] Finally, the server sends a payment instruction to the payment system (e.g., Stripe) to execute the payment. When the payment is complete, the server generates a voice message saying "Payment completed" and sends it to the terminal. The terminal plays the message to notify the user that the payment has been completed.

[1724] As a concrete example, consider a situation where a user places an order at a cafe and pays at the cash register. The user says "Please pay" at the register, and the device captures this voice and sends it to the server. The server analyzes the voice data and generates the text "Please pay." The text is analyzed using a natural language processing engine to confirm the user's intention. An emotion recognition engine then analyzes the user's emotions and generates an appropriate voice message. If the user approves with "OK," the voice data is sent again to the server, and finally the payment is made and a completion notification is sent.

[1725] An example of a prompt sentence to input to the generative AI model is as follows:

[1726] prompt:

[1727] Please explain in detail what happens in a voice payment system when a user says "please pay" at the cash register. Please provide a detailed description of the entire process from when the terminal receives the voice message and sends it to the server, to when the server analyzes and recognizes it and executes the payment.

[1728] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1729] Step 1:

[1730] Acquiring voice commands

[1731] The user issues a voice command saying, "Please make payment."

[1732] Input: User's voice commands

[1733] The device captures the user's voice through a microphone, splits it into fragments in real time, and sends them as data packets to the server via the HTTPS protocol.

[1734] Output: Captured audio data (data packets)

[1735] Step 2:

[1736] Analysis of audio data

[1737] The server receives the audio data and converts it into text using Google Cloud Speech-to-Text.

[1738] Input: Captured audio data (data packets)

[1739] The server runs a voice recognition engine, analyzes the voice data, and generates the text "Please make payment."

[1740] Output: Text data (e.g. "Please make payment")

[1741] Step 3:

[1742] Determining intent

[1743] The text generated by the server is analyzed using OpenAI GPT-4, and the user's intention is determined to be a "payment instruction."

[1744] Input: Text data (e.g. "Please make payment")

[1745] The server uses a natural language processing engine to analyze the context of the text and interpret the intent as "payment instructions."

[1746] Output: User's instructions (e.g. "Payment instructions")

[1747] Step 4:

[1748] Emotion recognition

[1749] The server uses the Microsoft Azure Emotion API to analyze the user's emotions from the voice data.

[1750] Input: Captured audio data (data packets)

[1751] The server extracts features from the voice data and inputs them into an emotion recognition engine to identify emotions such as "joy" or "relief."

[1752] Output: User's emotional data (e.g., "Relief")

[1753] Step 5:

[1754] Confirm payment details

[1755] The server takes the user's emotions into consideration and generates an adjusted voice message such as, "I will pay for XX yen. If you agree, please say OK."

[1756] Input: User instructions, user emotion data (e.g., "Payment instructions," "Relief")

[1757] The server generates a voice message saying, "The payment will be 500 yen. If you agree, please say OK." This message is sent to the terminal, which plays it back.

[1758] Output: The generated voice message

[1759] Step 6:

[1760] User Authorization

[1761] The user confirms by saying "OK."

[1762] Input: A confirmation message from the server

[1763] The terminal captures the user's approval voice through the microphone and transmits it again to the server as a data packet.

[1764] Output: Acquired acknowledgement voice data (data packets)

[1765] Step 7:

[1766] Parsing Authorizations

[1767] The server again converts the approval speech into text using Google Cloud Speech-to-Text.

[1768] Input: Acquired acknowledgement voice data (data packets)

[1769] The server runs a speech recognition engine to analyze the audio data and generate the text "OK," and an emotion recognition engine to ensure that it contains a positive emotion, such as "relief."

[1770] Output: Text data (e.g., "OK"), emotion data (e.g., "Relieved")

[1771] Step 8:

[1772] Executing payments

[1773] The server sends a payment instruction to a payment system such as Stripe or PayPal to execute the payment.

[1774] Input: Text data (e.g., "OK"), user instructions (e.g., "Payment instructions")

[1775] The server sends a request for 500 yen to the payment system via the REST API and receives a success response.

[1776] Output: Payment completion data

[1777] Step 9:

[1778] Payment completion notification

[1779] The server confirms the completion of the payment and generates a voice message saying "Payment completed."

[1780] Input: Payment completion data

[1781] The server generates a voice message saying "Payment completed. Thank you very much" and sends it to the terminal. While the message is played on the terminal, the screen displays "Payment completed."

[1782] Output: The generated voice message

[1783] (Application example 2)

[1784] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1785] Conventional payment systems require users to scan a QR code and input the amount, which is a cumbersome process. Furthermore, even payment systems that use voice instructions have the problem of not being able to fully reflect the user's intentions and emotions, making it difficult to improve reliability and user experience. The present invention aims to solve these problems and provide a new voice payment system that improves user convenience and reliability.

[1786] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring a user's voice instruction, means for transmitting the acquired voice data to the server, means for analyzing the voice data and determining the user's intention, means for generating payment details based on the user's intention and confirming them as a voice message to the user, means for acquiring an approval voice from the user, means for transmitting the acquired approval voice to the server, means for analyzing the approval voice and executing the payment, means for notifying the user of payment completion, means for determining the user's emotion from the voice data, and means for adjusting the confirmation message based on the emotion determination result. This allows the user to avoid scanning a QR code or entering an amount, and enables highly reliable, quick and comfortable payment to be executed through emotion recognition.

[1787] A "means for obtaining voice instructions" is a device or system for collecting voice commands uttered by a user.

[1788] The "means for transmitting voice data to a server" refers to a device or system that has the function of transferring acquired voice information to a server via a network.

[1789] "Means for analyzing voice data and determining user intent" refers to an algorithm or engine that extracts text from voice data and interprets the user's requests and intent based on that text.

[1790] The "means for generating payment details and confirming them to the user as a voice message" is a system for creating payment details based on text data and playing them back as voice.

[1791] The "means for acquiring approval voice" is a device or system for collecting approval voice uttered by a user.

[1792] The "means for transmitting the acquired approval voice to the server" refers to a device or system that has the function of transferring the user's approval voice to the server via a network.

[1793] The "means for analyzing the approval voice and executing the payment" refers to an algorithm and system for converting the user's approval voice into text and completing the payment process based on that text.

[1794] The "means for notifying the user of the completion of the payment" is a system that generates and plays a voice message to notify the user that the payment has been successfully completed.

[1795] The "means for determining the user's emotion from the voice data" refers to an algorithm or engine for analyzing the emotional information contained in the voice data and identifying the user's emotional state.

[1796] The "means for adjusting the confirmation message based on the emotion determination result" is a system for appropriately changing the content and tone of the confirmation message depending on the user's emotional state.

[1797] This invention relates to a voice payment system that utilizes speech recognition, natural language processing, and emotion recognition technologies. This system allows users to issue payment instructions via voice, eliminating the need to scan a QR code or enter the amount, and providing a fast and smooth payment experience. Furthermore, by recognizing the user's emotions, it is possible to improve the reliability of the payment process and the user experience.

[1798] The system includes the following components:

[1799] 1. User: The individual making the payment and issuing the voice command.

[1800] 2. Terminal: The device through which the user issues voice commands, including a smartphone, tablet, or dedicated terminal. The terminal is responsible for capturing the user's voice and sending it to the server.

[1801] 3. Server: Receives the voice data, analyzes it using a speech recognition engine, natural language processing engine, and emotion recognition engine, and executes the payment.

[1802] 4. Payment system: This is the system that actually processes payments based on the payment instructions sent from the server.

[1803] Program processing

[1804] 1. Acquiring voice instructions

[1805] The user issues a voice command such as "Please make the payment." The device picks up this voice using the built-in microphone and sends the voice data to the cloud server.

[1806] 2. Analysis of audio data

[1807] The server analyzes the acquired voice data using a speech recognition engine (e.g., Google Cloud Speech-to-Text API) and converts it into text data. It then analyzes the text using a natural language processing engine (e.g., Google Cloud Natural Language API) to determine the user's intent.

[1808] 3. Emotional Recognition

[1809] The server analyzes the voice data using an emotion recognition engine (e.g., IBM Watson Tone Analyzer) to determine the user's emotions.

[1810] 4. Confirm payment details

[1811] The server generates an adjusted confirmation message, "I will pay for XX yen. Please say OK if you agree," taking into account the user's feelings, and sends it to the terminal. The terminal plays this message and asks the user for confirmation.

[1812] 5. User Acknowledgment

[1813] The user approves by saying "OK." The device reacquires the approval voice and sends it to the server.

[1814] 6. Acknowledgment Analysis

[1815] The server converts the received approval voice into text using a speech recognition engine, checks whether it contains "OK," and then checks the emotion of the approval voice again.

[1816] 7. Payment Execution

[1817] The server sends a payment instruction to the payment system (e.g. Stripe API) to execute the payment.

[1818] 8. Payment completion notification

[1819] The server confirms the completion of the payment and generates a voice message saying "Payment completed." The terminal plays this message to notify the user.

[1820] Specific examples

[1821] For example, after a user finishes shopping at a supermarket, they open a smartphone app and say, "Please make the payment." The device receives this instruction and sends the voice data to the server. The server then analyzes the voice data using a speech recognition engine and converts it into text. It then uses a natural language processing engine to determine the user's intent when they say, "Please make the payment." It then uses an emotion recognition engine to analyze the user's emotion from the voice data. Based on these analysis results, the device generates a tailored confirmation message, such as, "I'll pay 500 yen. Please say OK if you're happy with this," and sends it to the device. The device then plays this message to ask the user for confirmation. When the user replies, "OK," the voice is sent again to the server, where the approval voice is analyzed, confirming that it contains "OK," and the emotion is also reconfirmed. A payment instruction is then sent to the payment system, and the payment is executed. Finally, the user is notified that the payment has been completed.

[1822] Example prompts to input to the generative AI model

[1823] When you say "please pay," it uses speech recognition, natural language processing, and emotion recognition technologies to analyze your spoken payment instructions and complete the payment on your smartphone. Based on emotion recognition, it provides feedback to improve the user experience.

[1824] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1825] Step 1:

[1826] Acquiring voice commands

[1827] Input: A user speaks the command "please pay."

[1828] Specific operation: The user speaks into the microphone on the device (smartphone, tablet, etc.) saying "Please make payment."

[1829] Output: The device uses a built-in microphone to capture audio data, which is then converted into a digital format and sent directly to the server.

[1830] Step 2:

[1831] Sending audio data to the server

[1832] Input: Audio data captured by the device.

[1833] Specific operation: The device sends the acquired voice data to a cloud server via the network (Wi-Fi or 4G / 5G communication).

[1834] Output: The server receives the audio data sent from the terminal.

[1835] Step 3:

[1836] Analysis of audio data

[1837] Input: The audio data received by the server.

[1838] How it works: The server uses a speech recognition engine (e.g., Google Cloud Speech-to-Text API) to convert the voice data into text, which is then analyzed by a natural language processing engine (e.g., Google Cloud Natural Language API) to determine the user's intent (e.g., "please make payment").

[1839] Output: Text data as the analysis result and the user's intent.

[1840] Step 4:

[1841] Emotion recognition

[1842] Input: The audio data received by the server.

[1843] Specific operation: The server uses an emotion recognition engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotions from the voice data. This analysis evaluates whether the user is relaxed or stressed.

[1844] Output: Emotion data as the analysis result (e.g., relaxed, stressed, etc.).

[1845] Step 5:

[1846] Confirm payment details

[1847] Input: Text data and emotion data as analysis results.

[1848] Specific operation: The server generates a tailored confirmation message (e.g., "I will pay 500 yen. Please say OK if you agree") taking into account the user's feelings. It then sends this message to the terminal.

[1849] Output: The generated confirmation message and its transmission from the server.

[1850] Step 6:

[1851] Play confirmation message

[1852] Input: The confirmation message sent by the server.

[1853] Specific operation: The terminal plays a voice message and asks the user for confirmation (e.g., "The payment amount is 500 yen. Please say OK if you agree").

[1854] Output: An audio message is played to the user.

[1855] Step 7:

[1856] User Authorization

[1857] Input: The user's voice command after hearing the confirmation message (e.g., "OK").

[1858] Specific operation: The user approves by saying "OK" into the device's microphone. The device captures this voice and sends it back to the server.

[1859] Output: The acknowledgement voice acquired by the device is sent to the server.

[1860] Step 8:

[1861] Analysis of approval voice

[1862] Input: The acknowledgment audio sent to the server.

[1863] Specific operation: The server again uses the speech recognition engine to convert the approval voice into text and checks whether it contains "OK." It then uses the emotion recognition engine to check the emotion of the approval voice again.

[1864] Output: Text data and emotion data as analysis results.

[1865] Step 9:

[1866] Executing payments

[1867] Input: Approval data and emotion data as analysis results.

[1868] Specific operation: The server sends a payment instruction to the payment system (e.g. Stripe API) to execute the payment.

[1869] Output: The result of the payment execution (success or failure).

[1870] Step 10:

[1871] Payment completion notification

[1872] Input: Payment execution result.

[1873] Specific operation: The server confirms the completion of the payment, generates a voice message saying "Payment completed" and sends it to the terminal. The terminal plays this message to notify the user.

[1874] Output: A payment completion message is played to the user.

[1875] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1876] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1877] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1878] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1879] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1880] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1881] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1882] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1883] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1884] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1885] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1886] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1887] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1888] 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.

[1889] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1890] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1891] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1892] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1893] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1894] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1895] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1896] The following is further disclosed regarding the above embodiment.

[1897] (Claim 1)

[1898] means for obtaining a user's voice instruction;

[1899] means for transmitting the acquired voice data to a server;

[1900] a server that analyzes the voice data and determines the user's intention;

[1901] means for generating payment details based on the user's intent and confirming them to the user as a voice message;

[1902] means for obtaining voice approval from the user;

[1903] means for transmitting the acquired approval voice to a server;

[1904] a server that analyzes the approval voice and executes the payment;

[1905] A means for notifying the user of the completion of payment;

[1906] A system including:

[1907] (Claim 2)

[1908] means for converting voice data into text using a voice recognition engine;

[1909] means for analyzing text and interpreting user intent using a natural language processing engine;

[1910] 10. The system of claim 1.

[1911] (Claim 3)

[1912] means for verifying that the user's approval voice includes a specific approval keyword;

[1913] including the means to effect payment after verification;

[1914] 10. The system of claim 1.

[1915] "Example 1"

[1916] (Claim 1)

[1917] means for obtaining a user's voice instruction;

[1918] means for transmitting the acquired voice data to a server;

[1919] a server that analyzes the voice data and determines the user's intention;

[1920] means for generating payment details based on the user's intent and confirming them to the user as a voice message;

[1921] means for obtaining voice approval from the user;

[1922] means for transmitting the acquired approval voice to a server;

[1923] a server that analyzes the approval voice and executes the payment;

[1924] A means for notifying the user of the completion of payment;

[1925] a means for integrating a speech recognition engine and a natural language processing engine to convert and analyze speech data into text;

[1926] A system that includes a communication means for real-time data communication throughout the system.

[1927] (Claim 2)

[1928] means for converting voice data into text using a voice recognition engine;

[1929] A means for analyzing text and interpreting user intent using a natural language processing engine;

[1930] means for generating confirmation and notification messages using a speech synthesis engine;

[1931] 10. The system of claim 1.

[1932] (Claim 3)

[1933] means for verifying that the user's approval voice includes a specific approval keyword;

[1934] including the means to effect payment after verification;

[1935] 10. The system of claim 1.

[1936] "Application Example 1"

[1937] (Claim 1)

[1938] means for obtaining a user's voice instruction;

[1939] means for transmitting the acquired voice data to a server;

[1940] a server that analyzes the voice data and determines the user's intention;

[1941] means for generating payment details based on the user's intent and confirming them to the user as a voice message;

[1942] means for obtaining voice approval from the user;

[1943] means for transmitting the acquired approval voice to a server;

[1944] a server that analyzes the approval voice and executes the payment;

[1945] A means for notifying the user of the completion of payment;

[1946] a means of speech recognition and natural language processing via a smart device;

[1947] A system including:

[1948] (Claim 2)

[1949] means for converting voice data into text using a voice recognition engine;

[1950] means for analyzing text and interpreting user intent using a natural language processing engine;

[1951] including the generation of voice messages using prompts and generative AI models;

[1952] 10. The system of claim 1.

[1953] (Claim 3)

[1954] means for verifying that the user's approval voice includes a specific approval keyword;

[1955] a means for confirming the authorization keyword and executing the payment after authorization via a smart device;

[1956] 10. The system of claim 1.

[1957] "Example 2: Combining Emotion Engines"

[1958] (Claim 1)

[1959] means for obtaining a user's voice instruction;

[1960] means for transmitting the acquired voice data to a central processing unit;

[1961] a central processing unit that analyzes the voice data and determines the user's intention;

[1962] means for generating payment details based on the user's intent and confirming them to the user as a voice message;

[1963] means for analyzing user emotions;

[1964] means for obtaining voice approval from the user;

[1965] means for transmitting the acquired approval voice to a central processing unit;

[1966] a central processing unit that analyzes the approval voice and executes the settlement;

[1967] A means for notifying the user of the completion of payment;

[1968] A system including:

[1969] (Claim 2)

[1970] means for converting voice data into text using a voice recognition module;

[1971] means for analyzing the text and interpreting the user's intent using a natural language processing module;

[1972] 10. The system of claim 1.

[1973] (Claim 3)

[1974] means for verifying that the user's approval voice includes a specific approval keyword;

[1975] including the means to effect payment after verification;

[1976] 10. The system of claim 1.

[1977] "Application example 2 when combining emotion engines"

[1978] (Claim 1)

[1979] means for obtaining a user's voice instruction;

[1980] means for transmitting the acquired voice data to a server;

[1981] a server that analyzes the voice data and determines the user's intention;

[1982] means for generating payment details based on the user's intent and confirming them to the user as a voice message;

[1983] means for obtaining voice approval from the user;

[1984] means for transmitting the acquired approval voice to a server;

[1985] a server that analyzes the approval voice and executes the payment;

[1986] A means for notifying the user of the completion of payment;

[1987] means for determining a user's emotion from the voice data;

[1988] means for adjusting the confirmation message based on the emotion determination result;

[1989] A system including:

[1990] (Claim 2)

[1991] means for converting voice data into text using a voice recognition engine;

[1992] means for analyzing text and interpreting user intent using a natural language processing engine;

[1993] 10. The system of claim 1.

[1994] (Claim 3)

[1995] means for verifying that the user's approval voice includes a specific approval keyword;

[1996] including the means to effect payment after verification;

[1997] 10. The system of claim 1. [Explanation of symbols]

[1998] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for obtaining a user's voice instruction; means for transmitting the acquired voice data to a server; a server that analyzes the voice data and determines the user's intention; means for generating payment details based on the user's intent and confirming them to the user as a voice message; means for obtaining voice approval from the user; means for transmitting the acquired approval voice to a server; a server that analyzes the approval voice and executes the payment; A means for notifying the user of the completion of payment; A system including:

2. means for converting voice data into text using a voice recognition engine; means for analyzing text and interpreting user intent using a natural language processing engine; The system of claim 1 .

3. means for verifying that the user's approval voice includes a specific approval keyword; including the means to effect payment after verification; The system of claim 1 .

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