system

Abstract

We provide the system. [Solution] A means for acquiring the conversation between the user and the processor as audio data, A conversion means for converting the aforementioned audio data into text data, An extraction means for extracting information necessary for registration from the converted character data, A generation means for automatically generating a registration form based on extracted information, A presentation means that presents the generated registration form to the user and allows them to confirm its contents, A means of completing the registration process after confirming the contents, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is 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 an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the registration process of mobile phones and other communication devices, it is required to efficiently reflect the conversation content between the user and the processor and shorten the time required for registration. However, currently, text conversion of voice and extraction of necessary information are often performed manually, resulting in waste of time and insufficient or redundant information. Furthermore, since customer service and registration are separated, opportunities for service improvement are missed. There is a need for an efficient system to improve such a situation and enhance the user experience.

Means for Solving the Problems

[0005] This invention efficiently captures conversation content by using an acquisition means to obtain conversations between a user and a processor as audio data. Next, it employs a conversion means to convert this audio data into text data, and further employs an extraction means to quickly extract the information necessary for registration from the converted text data. This makes it possible to automatically generate a registration form and present a confirmation screen to the user. It also provides an interface for the user to input or correct the presented content, allowing for timely confirmation of the content. Finally, after registration is complete, a list of necessary documents and notes are presented, creating a system that completes the registration process efficiently and transparently. This aims to improve the overall efficiency of the registration process and enhance user satisfaction.

[0006] "Acquisition means" refers to a device or technology for acquiring conversations between a user and a processor as audio data.

[0007] "Conversion means" refers to a device or technology for converting acquired audio data into text data.

[0008] "Extraction means" refers to a device or technology for identifying and extracting information necessary for registration from character data.

[0009] "Generation means" refers to a device or technology for automatically generating a registration form based on extracted information.

[0010] "Presentation means" refers to a device or technology that displays the generated registration form to the user and allows them to confirm its contents.

[0011] "Completion means" refers to a device or technology used to complete the registration process after user verification.

[0012] "Providing an interface" means preparing screens and operating methods for users to input or modify information.

[0013] The "list of required documents" is a list of documents that users are required to submit when registering.

[0014] "Notes" are sections that explain important information and points to keep in mind when using the service to the user. [Brief explanation of the drawing]

[0015] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), etc.

[0019] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disk (e.g., hard disk), or magnetic tape, etc.

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0028] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0035] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0036] The present invention is a system that utilizes real-time conversations between users and processors in the registration process, and its embodiments are described below.

[0037] First, the user converses with a processor, either face-to-face or remotely, through a device equipped with a microphone. The device captures this conversation as audio data and sends it to a server. This function ensures that the user's requests and information are accurately digitized.

[0038] Next, the server uses speech recognition technology to convert the received audio data into text data. At this stage, noise reduction and speech clarity are performed to generate highly accurate text data. The converted text is then analyzed using natural language processing technology to extract the information necessary for registration (e.g., contract details and plan selection).

[0039] The server automatically creates a registration form based on the extracted information. This form is properly filled with the necessary fields for the contract and is designed for the user to review later. The terminal presents this registration form to the user, allowing them to review and modify the contract details.

[0040] Users use the terminal interface to review and modify the presented registration form, ultimately completing the registration process. This system allows users to quickly provide the necessary information, and enables processors to perform registration work efficiently.

[0041] As a concrete example, consider a scenario where a user wants to purchase a new smartphone. In this case, the user communicates with a staff member through the device and communicates their desired plan. The server processes this information in real time and automatically generates a registration form that includes the user's selected plan and options. The device then presents the generated form to the user, who confirms it and then confirms the registration.

[0042] This system significantly reduces errors and time losses associated with traditional manual processes, improving the accuracy and speed of customer service.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The terminal captures the conversation between the user and the processor as audio data in real time. The terminal's microphone captures the audio and prepares to send the recorded audio data to the server.

[0046] Step 2:

[0047] The server receives the audio data sent from the terminal. It uses a speech recognition engine to convert this audio data into text. During this process, noise is removed and the clarity of the audio is maintained.

[0048] Step 3:

[0049] The server analyzes the converted text data using natural language processing technology and extracts the information necessary for registration. For example, it identifies information such as the subscriber's name, selected plan, and options.

[0050] Step 4:

[0051] The server automatically generates a registration form based on the extracted information. This form includes the necessary registration fields and is designed for user confirmation.

[0052] Step 5:

[0053] The terminal displays a registration form sent from the server to the user. The user can view, enter, or modify the registration details through the terminal's display.

[0054] Step 6:

[0055] The user reviews the information on the provided registration form and makes any necessary corrections. Once corrections are complete, they perform an action on their device to confirm the registration.

[0056] Step 7:

[0057] The terminal receives the user's registration confirmation and sends the final registration information to the server. The server saves the information to the database and completes the registration process.

[0058] Step 8:

[0059] The terminal will present the user with necessary documents and instructions after registration is complete. The user will review these and make the necessary preparations.

[0060] (Example 1)

[0061] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0062] Traditional conversation-based registration procedures are often performed manually, making them prone to errors in information entry and omissions. Furthermore, manual processing is time-consuming, leading to decreased efficiency. Additionally, accurately registering information provided by users through dialogue is difficult, resulting in a lack of process reliability.

[0063] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0064] In this invention, the server includes means for collecting acoustic information, means for converting the acoustic information into document information, and means for extracting necessary information from the document information. This makes it possible to accurately digitize the interaction between the user and the processor in real time and to perform the registration procedure quickly and accurately.

[0065] "Acoustic information" refers to all audio data, including conversations between the user and the processor.

[0066] "Document information" refers to character data converted from acoustic information.

[0067] "Means of collection" refers to the devices and technologies used to capture acoustic information in real time.

[0068] "Means of conversion" refers to speech recognition technology used to convert acoustic information into document information.

[0069] "Means of extraction" refers to a technology or device for identifying and extracting information necessary for registration procedures from document information.

[0070] "Fill-in document" refers to a registration form that is automatically generated based on the extracted information.

[0071] "Interface" refers to a user interface that allows users to review and modify documents they have filled out.

[0072] "Noise reduction" is the process of removing unwanted background noise from acoustic information.

[0073] "Speech clarification" refers to processing that improves the clarity of speech within acoustic information.

[0074] This invention relates to a virtual registration system that efficiently facilitates registration procedures based on dialogue between a user and a processor. Specific embodiments are described below.

[0075] First, the user converses with the processor using a device equipped with a microphone. The device collects this conversation as acoustic information and transmits it to the server in real time. This collection utilizes a voice recognition microphone and dedicated software built into the device. The acoustic information is digitized and transmitted via a secure communication protocol, thus guaranteeing data security.

[0076] The server uses speech recognition technology to convert the received acoustic information into document information. Specifically, the speech recognition engine performs noise reduction and speech clarity to convert the acoustic data into highly accurate text data. This technology can also utilize cloud-based speech recognition services.

[0077] The converted document information is analyzed by a natural language processing engine, and the information necessary for registration is extracted. Based on pre-configured keywords and phrases, the system accurately identifies contract-related items (e.g., contract details and plan selection) and stores them in the database.

[0078] Subsequently, the server automatically generates a form using the extracted information. This form is presented on a terminal equipped with a user interface for the user to review or modify their registration. This interface is designed to be intuitive and easy to use, allowing users to easily make any necessary corrections.

[0079] As a concrete example, consider a case where a user signs up for a new communication service. In this scenario, the user communicates with a service representative via their device and communicates their desired plan. The AI ​​model generates a form containing this information in real time and automatically presents the details of the plan the user has selected. The user then reviews the document and officially completes the registration process.

[0080] An example of a prompt message would be, "I'd like to discuss my preferred communication plan; I'd like a 20GB monthly data plan with an international calling option." This system allows users to proceed with the process quickly and accurately, while also improving the efficiency of the processing staff.

[0081] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0082] Step 1:

[0083] The terminal acquires acoustic information via a microphone through conversation between the user and the processor. The input is the user's voice, which is converted into a digital signal in real time. As output, digitized acoustic data is generated. This data is prepared to be sent to the server in a later processing step.

[0084] Step 2:

[0085] The terminal transmits the acquired acoustic data to the server using a secure communication protocol. The input is digital acoustic data, which is transmitted in an encrypted format. As output, the server receives acoustic information that can be decrypted in real time.

[0086] Step 3:

[0087] The server converts received acoustic information into document information using speech recognition technology. The input is digital acoustic data, which undergoes noise reduction and speech clarification. The output is effectively converted, high-precision text data.

[0088] Step 4:

[0089] The server analyzes document information based on natural language processing and extracts the information necessary for registration. The input is text data, and important information is identified based on specific keywords and phrases. The output is a dataset containing the information necessary for the registration process.

[0090] Step 5:

[0091] The server automatically generates a form using the extracted information. The input is an organized dataset, and a form is created based on this data with the necessary fields for the contract appropriately filled in. The output is a completed form that should be presented to the user.

[0092] Step 6:

[0093] The terminal presents the generated form to the user and provides an interface for the user to review and modify it. The input is form data from the server. This interface allows the user to intuitively manipulate the form and modify information as needed. The output is the final version of the form, reviewed by the user.

[0094] Step 7:

[0095] The user reviews the final version of the document through the terminal interface and completes the registration process. The input is a user-confirmed process, and the user confirms their intention to complete registration by pressing the "Register" button after final confirmation. As output, the server stores the final registration data, including all necessary information.

[0096] (Application Example 1)

[0097] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0098] In traditional commercial transactions, the reliance on paper documents and manual data entry for customer-employee conversations in stores led to problems such as information discrepancies and delays in procedures. Furthermore, the time-consuming process of creating and verifying registration forms often resulted in concerns about decreased customer satisfaction. Therefore, there is a need to establish technology that automatically and in real-time analyzes conversation content and generates order forms.

[0099] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0100] In this invention, the server includes acquisition means for acquiring the conversation between the user and the processor as audio data, conversion means for converting the audio data into text data, and extraction means for extracting information necessary for registration from the converted text data. This enables rapid digital processing of voice-based user requests and the generation of accurate order forms.

[0101] "Acquisition means" refers to a mechanism for acquiring conversations between the user and the processor as audio data.

[0102] "Conversion means" refers to technology for converting acquired audio data into text data.

[0103] "Extraction means" refers to a method for identifying and extracting information necessary for registration from converted character data.

[0104] "Generation method" refers to the process of automatically creating registration forms and order forms based on extracted information.

[0105] A "presentation means" is a means of showing the generated form to the user and providing an interface for them to confirm its contents.

[0106] A "completion mechanism" is a function that allows users to complete the registration process after reviewing the contents of a form.

[0107] "Commercial transactions" refer to all business processes related to the purchase and sale of goods and services.

[0108] An "order form" is an electronic form used by customers for final confirmation, reflecting their product selections and specified conditions in commercial transactions.

[0109] The embodiment for carrying out this invention is a system mainly consisting of a user-operated terminal and a server.

[0110] First, the terminal is equipped with a microphone and captures the conversation between the user and the processor as audio data. This audio data is sent from the terminal to the server. The server uses speech recognition technology such as Google Cloud Speech-to-Text to convert the audio data into text data. The converted text data is then processed using natural language processing with Python's NLTK or spaCy to extract the information necessary for registration.

[0111] Next, the server automatically generates a registration form using a web framework such as Flask or Django based on the extracted information. The generated form is then presented to the user's device. The user can use the device's interface to review and modify the form's contents before completing the registration process.

[0112] As a concrete example, consider a scenario where a user wants to order a red sweater at a clothing store. In this case, the terminal converts the user's voice, "I'm looking for a red sweater in size M," into text data, extracting the information "red sweater" and "size M." Based on this, an order form is generated and presented to the user.

[0113] An example of a prompt for a generative AI model would be: "Analyze the following conversation and extract the product category and size: 'I'm looking for a red sweater in size M.'"

[0114] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0115] Step 1:

[0116] The terminal captures the conversation between the user and the processor as audio data via the microphone. The input is real-time audio. After acquiring this audio data, the terminal prepares to send it to the server. The output is audio data in a transmittable format.

[0117] Step 2:

[0118] The server converts the audio data received from the terminal into text data using the Google Cloud Speech-to-Text API. The input is audio data, a speech recognition algorithm is applied to it, and the output is a corresponding string. Noise reduction is also performed in this step to improve the conversion accuracy.

[0119] Step 3:

[0120] The server performs natural language processing on the converted character data using Python's NLTK and spaCy. The input is character data, and the server extracts the information necessary for registration (e.g., product name and specifications) through text analysis. The output is a set of the extracted information. In this specific operation, keywords are extracted from the text and organized into structured data.

[0121] Step 4:

[0122] The server dynamically generates a registration form using Flask or Django based on the extracted information. The input is the extracted information, which is used to create a form that includes the order conditions required by the user. The output is the HTML of the generated registration form.

[0123] Step 5:

[0124] The terminal presents the generated registration form to the user. The input is an HTML form received from the server, and the output is a visual interface displayed on the user's screen. Specifically, the user can review the form contents and modify them if necessary.

[0125] Step 6:

[0126] The user reviews and modifies the form and confirms its contents. The input is the registration form reviewed by the user, and the output is the confirmed registration information. The user's specific action is to press the confirmation button, which completes the registration process.

[0127] Step 7:

[0128] The server stores the confirmed registration information and, if necessary, presents the user with relevant documents and notes. Input is the confirmed data after registration, and output is the stored data and notifications to the user regarding points to confirm. In this step, information is stored in the database, and the user is shown the next action.

[0129] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0130] This invention is a system that acquires conversations between users and processors as audio data, converts it to text, extracts necessary information, and reflects it in the registration process. In addition, it incorporates an emotion engine that analyzes the user's emotions. The aim of this system is to further improve user support and to more accurately understand user needs.

[0131] First, the user uses a device to have a voice conversation with the processor. The device acquires this voice data and sends it to the server. The server uses a speech recognition engine to convert the voice data into text and extracts the information necessary for registration from the converted text. In this process, an emotion engine analyzes the tone and speaking speed of the voice data and evaluates the user's emotional state.

[0132] The emotion engine identifies the user's emotional state, such as "anxiety" or "reassurance," and transmits this information to the server. Based on this emotion information, the server sends instructions to the terminal to customize the displayed content. For example, if the system detects that the user is feeling anxious, it can present additional explanations or guides during the registration form process.

[0133] For example, suppose a user is applying for a new communication plan and the system detects that they have concerns about data capacity or fees. In this case, the device, based on instructions from the server, displays a screen providing additional explanations to the user, guiding them to proceed with the process with confidence. If positive emotions are detected, the system can simply provide standard information to ensure a smooth process.

[0134] This system allows processors to take the user's emotional state into account when responding, improving the user experience and streamlining the registration process. With its immediate feedback based on emotion analysis and flexible response capabilities, this system can be a crucial tool for increasing user satisfaction.

[0135] The following describes the processing flow.

[0136] Step 1:

[0137] The terminal captures the conversation between the user and the processor as audio data via the microphone. This audio data is also used as information for sentiment analysis and is sent to the server.

[0138] Step 2:

[0139] The server receives audio data transmitted from the terminal and converts it into text data using a speech recognition engine. Simultaneously, it uses an emotion engine to analyze the tone and speaking speed of the audio data and evaluate the user's emotional state.

[0140] Step 3:

[0141] The server extracts the information necessary for registration from the converted text data using natural language processing technology. For example, it identifies the user's desired plan and contract terms.

[0142] Step 4:

[0143] The server automatically generates a registration form based on the extracted information and the sentiment evaluation results from the sentiment engine. Emotional states are taken into consideration, and the form content and presentation method are adjusted as needed.

[0144] Step 5:

[0145] The terminal displays the registration form sent from the server to the user and provides an interface that allows the user to review and modify the content. Additional explanations and guides may be provided based on sentiment ratings.

[0146] Step 6:

[0147] The user reviews the provided registration form and makes any necessary corrections. Once the user determines that the operation is complete, they provide instructions on the terminal to confirm the registration.

[0148] Step 7:

[0149] The terminal sends the user's registration confirmation operation to the server. The server saves the final data to the database and completes the registration process. At this time, the information obtained through sentiment evaluation may be used to improve future customer service.

[0150] Step 8:

[0151] The device displays necessary documents and instructions to the user after registration is complete. The user then makes the necessary preparations according to the information provided. Emotional feedback may also be provided at this stage.

[0152] (Example 2)

[0153] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0154] In user-service provider interactions, there is a need for a system that can appropriately consider the user's emotional state and present them with the most relevant information. This challenge is crucial for improving the user experience and streamlining the registration process. In particular, achieving flexible and effective information presentation tailored to the user's emotions is difficult.

[0155] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0156] In this invention, the server includes means for converting acoustic information into text information, means for extracting information necessary for registration from the converted text information, and means for analyzing the user's emotional state from the acoustic information. This enables the presentation of appropriate information based on the user's emotions and a smooth registration process.

[0157] "Acquisition method" refers to a function for collecting the dialogue between the user and the service provider as acoustic information.

[0158] "Conversion means" refers to a function for converting collected acoustic information into textual information.

[0159] "Extraction means" refers to a function for identifying and extracting information necessary for registration from the converted character information.

[0160] "Generation means" refers to a function that automatically creates a registration screen based on specified information.

[0161] "Presentation method" refers to a function that displays a generated registration screen to the user and prompts them to confirm the contents.

[0162] "Analysis means" refers to a function that evaluates and identifies the user's emotional state based on acoustic information.

[0163] "Adjustment mechanism" refers to a function that appropriately modifies the information displayed based on the analyzed emotional information.

[0164] "Completion mechanism" refers to a function that allows the user to finish the registration process after confirming the content.

[0165] This system effectively manages user-service provider interactions and provides information optimized based on the user's emotions. Its main components are programs that implement means for acquiring acoustic information, converting it to text, extracting necessary information, analyzing emotional states, and adjusting displayed content.

[0166] First, the user initiates a conversation with the service provider using their device. The device incorporates a mechanism for acquiring acoustic information, which collects the conversation in real time and sends it to the server. The server then converts the received acoustic information into text using a "speech recognition engine." Specifically, "Google Speech-to-Text" is one such speech recognition engine that can be used.

[0167] Next, the server uses a "natural language processing tool" to extract the information necessary for registration from the converted text information. Examples of such tools include "NLTK". The server is also equipped with an "emotion analysis engine" for sentiment analysis, which analyzes the user's emotional state using software such as "IBM Watson® Tone Analyzer". Sentiment analysis is performed based on parameters such as voice tone and speaking speed.

[0168] The analyzed emotional information is then processed on a server, and instructions for displaying information tailored to the user's emotions are sent to the device. For example, if it is detected that the user is feeling "anxious" when applying for a new communication plan, the device will receive instructions from the server and display a screen offering additional explanations. In this way, the user experience is improved by providing appropriate feedback according to the user's emotions.

[0169] As a concrete example, when the prompt "Explain how to display additional information if the emotion extracted from the voice is determined to be anxiety" is input to the generating AI model, the system executes a process to provide the user, who is feeling anxious, with additional explanations about the procedure. This allows the user to proceed with the procedure with peace of mind.

[0170] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0171] Step 1:

[0172] The device records the conversation between the user and the service provider in real time and collects it as acoustic information. The input is the conversational audio, and the output is digital acoustic data. Specifically, it captures the audio signal through the device's microphone and saves it as digital data.

[0173] Step 2:

[0174] The terminal transmits the collected acoustic data to the server. Data transmission takes place via network communication, with acoustic data as the input and data transfer to the server as the output. Specifically, the terminal uses a communication protocol to send data to the server.

[0175] Step 3:

[0176] The server converts received audio data into text information using a speech recognition engine. The input to this process is audio data, and the output is text data. Specifically, the server analyzes the audio signal and maps it to text through phoneme recognition.

[0177] Step 4:

[0178] The server analyzes the converted text information using natural language processing tools and extracts the information necessary for registration. The input is text data, and the output is the extracted information. Specifically, the server detects keywords and phrases within the text and organizes them as structured data.

[0179] Step 5:

[0180] The server processes acoustic information using an emotion analysis engine to evaluate the user's emotional state. The input is the original acoustic data, and the output is the analyzed emotion information. Specifically, the server analyzes voice tone, speech rate, and emphasis to classify the emotional state.

[0181] Step 6:

[0182] The server sends instructions to the terminal to customize the displayed content based on the analyzed sentiment information. The input is sentiment information, and the output is customization instructions. Specifically, the server instructs the terminal to make appropriate content corrections and transfers the necessary data to the terminal.

[0183] Step 7:

[0184] The terminal receives instructions from the server and displays customized information to the user. Input is the customization instructions, and output is the presentation of information to the user. Specifically, the terminal updates the screen display, allowing the user to view additional information and guides.

[0185] (Application Example 2)

[0186] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0187] In the user-processor-based registration process, there is a challenge in providing appropriate information based on the user's emotional state, resulting in insufficient improvement of the user experience. Furthermore, there is difficulty in responding flexibly to users who experience anxiety or stress, taking their emotions into consideration.

[0188] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0189] In this invention, the server includes emotion analysis means for analyzing the tone and speaking speed of voice information to evaluate the user's emotional state, adjustment means for adjusting the presented content based on the user's emotional information, and means for presenting additional explanations or guides when the user is evaluated as being in an anxious state. This enables the presentation of information in accordance with the user's emotions, improving the user experience and streamlining the registration process.

[0190] "Acquisition means" refers to the means of acquiring the conversation between the user and the processor as audio information.

[0191] "Conversion means" refers to means for converting the acquired audio information into text information.

[0192] "Extraction means" refers to means for extracting information necessary for registration from the converted character information.

[0193] "Generation means" refers to means for automatically generating registration forms based on extracted information.

[0194] "Presentation means" refers to a means of presenting the generated registration form to the user and allowing them to confirm its contents.

[0195] "Completion method" refers to the means used to complete the registration process after the content has been verified.

[0196] "Emotional analysis means" refers to a method for evaluating a user's emotional state by analyzing the tone and speaking speed of voice information.

[0197] "Adjustment means" are means for adjusting the presented content based on the user's emotional information.

[0198] This invention is a system that acquires conversations between a user and a processor as audio information, converts it into text information, and extracts necessary registration data. This system incorporates speech recognition and sentiment analysis technologies and was developed to improve the user experience.

[0199] First, the user engages in conversation using a device such as a smartphone or a home robot. This device is equipped with a microphone and internet connectivity to capture the audio information of the conversation. The server receives this audio information and uses the Google Speech-to-Text API as software for speech recognition. Here, the audio information is converted into text information.

[0200] From the converted text information, the system extracts the information necessary for registration. Furthermore, the server uses an emotion analysis engine to analyze the tone and speaking speed of the voice information and evaluate the user's emotional state. Based on this analysis, instructions are sent to the terminal to adjust the displayed content based on the user's emotional information.

[0201] As a concrete example, imagine a user asking a consumer robot, "What should we do today?" The robot analyzes the tone of the conversation and detects a feeling of boredom. In this case, the robot provides a user-friendly service by suggesting a new activity that will stimulate the user's interest. An example of a prompt in this scenario would be, "Analyze the emotion from the tone of voice and generate a response that suggests an action appropriate to the mood."

[0202] This system allows terminals and servers to recognize specific emotional states of individual users and provide more personalized information. In this way, the user experience is improved, and the registration process and daily operations become more efficient.

[0203] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0204] Step 1:

[0205] The device acquires the user's voice via a microphone. The input is audio data, which is then converted to a digital format and prepared for transmission to the server. The output is digital audio data.

[0206] Step 2:

[0207] The server receives digital audio data and performs speech recognition using the Google Speech-to-Text API. The input is digital audio data, and speech recognition generates text data. The output is the converted text data.

[0208] Step 3:

[0209] This process extracts the necessary registration information from text data generated by the server. The input is text data, and information analysis is performed to identify and extract the required data fields. The output is the extracted registration information.

[0210] Step 4:

[0211] The server uses an emotion analysis engine to evaluate the user's emotional state based on the tone and speaking speed of the voice data. The input is digital voice data, and the voice features are analyzed to generate emotion data. The output is the user's emotional state data.

[0212] Step 5:

[0213] The server generates instructions to adjust the presented content based on the user's emotional state data. The input consists of emotional state data and extracted registration information, and the server performs data processing to optimize information presentation. The output is adjustment instruction data.

[0214] Step 6:

[0215] The terminal receives adjustment instruction data sent from the server and displays information optimized for the user based on that data. The input is the adjustment instruction data, which provides appropriate information on the user interface. The output is the customized information displayed on the user interface.

[0216] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0217] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0218] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0219] [Second Embodiment]

[0220] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0221] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0222] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0223] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0224] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0225] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0226] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0227] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0228] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0229] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0230] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0231] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0232] The present invention is a system that utilizes real-time conversations between users and processors in the registration process, and its embodiments are described below.

[0233] First, the user converses with a processor, either face-to-face or remotely, through a device equipped with a microphone. The device captures this conversation as audio data and sends it to a server. This function ensures that the user's requests and information are accurately digitized.

[0234] Next, the server uses speech recognition technology to convert the received audio data into text data. At this stage, noise reduction and speech clarity are performed to generate highly accurate text data. The converted text is then analyzed using natural language processing technology to extract the information necessary for registration (e.g., contract details and plan selection).

[0235] The server automatically creates a registration form based on the extracted information. This form is properly filled with the necessary fields for the contract and is designed for the user to review later. The terminal presents this registration form to the user, allowing them to review and modify the contract details.

[0236] Users use the terminal interface to review and modify the presented registration form, ultimately completing the registration process. This system allows users to quickly provide the necessary information, and enables processors to perform registration work efficiently.

[0237] As a concrete example, consider a scenario where a user wants to purchase a new smartphone. In this case, the user communicates with a staff member through the device and communicates their desired plan. The server processes this information in real time and automatically generates a registration form that includes the user's selected plan and options. The device then presents the generated form to the user, who confirms it and then confirms the registration.

[0238] This system significantly reduces errors and time losses associated with traditional manual processes, improving the accuracy and speed of customer service.

[0239] The following describes the processing flow.

[0240] Step 1:

[0241] The terminal captures the conversation between the user and the processor as audio data in real time. The terminal's microphone captures the audio and prepares to send the recorded audio data to the server.

[0242] Step 2:

[0243] The server receives the audio data sent from the terminal. It uses a speech recognition engine to convert this audio data into text. During this process, noise is removed and the clarity of the audio is maintained.

[0244] Step 3:

[0245] The server analyzes the converted text data using natural language processing technology and extracts the information necessary for registration. For example, it identifies information such as the subscriber's name, selected plan, and options.

[0246] Step 4:

[0247] The server automatically generates a registration form based on the extracted information. This form includes the necessary registration fields and is designed for user confirmation.

[0248] Step 5:

[0249] The terminal displays a registration form sent from the server to the user. The user can view, enter, or modify the registration details through the terminal's display.

[0250] Step 6:

[0251] The user reviews the information on the provided registration form and makes any necessary corrections. Once corrections are complete, they perform an action on their device to confirm the registration.

[0252] Step 7:

[0253] The terminal receives the user's registration confirmation and sends the final registration information to the server. The server saves the information to the database and completes the registration process.

[0254] Step 8:

[0255] The terminal will present the user with necessary documents and instructions after registration is complete. The user will review these and make the necessary preparations.

[0256] (Example 1)

[0257] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0258] Traditional conversation-based registration procedures are often performed manually, making them prone to errors in information entry and omissions. Furthermore, manual processing is time-consuming, leading to decreased efficiency. Additionally, accurately registering information provided by users through dialogue is difficult, resulting in a lack of process reliability.

[0259] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0260] In this invention, the server includes means for collecting acoustic information, means for converting the acoustic information into document information, and means for extracting necessary information from the document information. This makes it possible to accurately digitize the interaction between the user and the processor in real time and to perform the registration procedure quickly and accurately.

[0261] "Acoustic information" refers to all audio data, including conversations between the user and the processor.

[0262] "Document information" refers to character data converted from acoustic information.

[0263] "Means of collection" refers to the devices and technologies used to capture acoustic information in real time.

[0264] "Means of conversion" refers to speech recognition technology used to convert acoustic information into document information.

[0265] "Means of extraction" refers to a technology or device for identifying and extracting information necessary for registration procedures from document information.

[0266] "Fill-in document" refers to a registration form that is automatically generated based on the extracted information.

[0267] "Interface" refers to a user interface that allows users to review and modify documents they have filled out.

[0268] "Noise reduction" is the process of removing unwanted background noise from acoustic information.

[0269] "Speech clarification" refers to processing that improves the clarity of speech within acoustic information.

[0270] This invention relates to a virtual registration system that efficiently facilitates registration procedures based on dialogue between a user and a processor. Specific embodiments are described below.

[0271] First, the user converses with the processor using a device equipped with a microphone. The device collects this conversation as acoustic information and transmits it to the server in real time. This collection utilizes a voice recognition microphone and dedicated software built into the device. The acoustic information is digitized and transmitted via a secure communication protocol, thus guaranteeing data security.

[0272] The server uses speech recognition technology to convert the received acoustic information into document information. Specifically, the speech recognition engine performs noise reduction and speech clarity to convert the acoustic data into highly accurate text data. This technology can also utilize cloud-based speech recognition services.

[0273] The converted document information is analyzed by a natural language processing engine, and the information necessary for registration is extracted. Based on pre-configured keywords and phrases, the system accurately identifies contract-related items (e.g., contract details and plan selection) and stores them in the database.

[0274] Subsequently, the server automatically generates a form using the extracted information. This form is presented on a terminal equipped with a user interface for the user to review or modify their registration. This interface is designed to be intuitive and easy to use, allowing users to easily make any necessary corrections.

[0275] As a concrete example, consider a case where a user signs up for a new communication service. In this scenario, the user communicates with a service representative via their device and communicates their desired plan. The AI ​​model generates a form containing this information in real time and automatically presents the details of the plan the user has selected. The user then reviews the document and officially completes the registration process.

[0276] An example of a prompt message would be, "I'd like to discuss my preferred communication plan; I'd like a 20GB monthly data plan with an international calling option." This system allows users to proceed with the process quickly and accurately, while also improving the efficiency of the processing staff.

[0277] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0278] Step 1:

[0279] The terminal acquires acoustic information via a microphone through conversation between the user and the processor. The input is the user's voice, which is converted into a digital signal in real time. As output, digitized acoustic data is generated. This data is prepared to be sent to the server in a later processing step.

[0280] Step 2:

[0281] The terminal transmits the acquired acoustic data to the server using a secure communication protocol. The input is digital acoustic data, and this data is transmitted in an encrypted form. As output, the server receives acoustic information that can be decoded in real time.

[0282] Step 3:

[0283] The server converts the received acoustic information into document information using speech recognition technology. The input is digital acoustic data, and noise removal and speech clarification are performed on this data. As output, highly accurate text data that has been effectively converted is generated.

[0284] Step 4:

[0285] The server analyzes the document information based on natural language processing and extracts the information necessary for registration. The input is text data, and important information is identified based on specific keywords and phrases. As output, a dataset in which the information necessary for the registration procedure is organized is output.

[0286] Step 5:

[0287] The server automatically generates a filling document using the extracted information. The input is the organized dataset, and based on this data, a form in which the items necessary for the contract are appropriately filled in is created. As output, a completed filling document to be presented to the user is generated.

[0288] Step 6:

[0289] The terminal presents the generated filling document to the user and provides an interface for the user to confirm and modify it. The input is the filling document data from the server. Through this interface, the user can intuitively operate the form and modify the information if necessary. As output, the final version of the filling document confirmed by the user is generated.

[0290] Step 7:

[0291] The user reviews the final version of the document through the terminal interface and completes the registration process. The input is a user-confirmed process, and the user confirms their intention to complete registration by pressing the "Register" button after final confirmation. As output, the server stores the final registration data, including all necessary information.

[0292] (Application Example 1)

[0293] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0294] In traditional commercial transactions, the reliance on paper documents and manual data entry for customer-employee conversations in stores led to problems such as information discrepancies and delays in procedures. Furthermore, the time-consuming process of creating and verifying registration forms often resulted in concerns about decreased customer satisfaction. Therefore, there is a need to establish technology that automatically and in real-time analyzes conversation content and generates order forms.

[0295] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0296] In this invention, the server includes acquisition means for acquiring the conversation between the user and the processor as audio data, conversion means for converting the audio data into text data, and extraction means for extracting information necessary for registration from the converted text data. This enables rapid digital processing of voice-based user requests and the generation of accurate order forms.

[0297] "Acquisition means" refers to a mechanism for acquiring conversations between the user and the processor as audio data.

[0298] "Conversion means" refers to technology for converting acquired audio data into text data.

[0299] "Extraction means" refers to a method for identifying and extracting information necessary for registration from converted character data.

[0300] "Generation method" refers to the process of automatically creating registration forms and order forms based on extracted information.

[0301] A "presentation means" is a means of showing the generated form to the user and providing an interface for them to confirm its contents.

[0302] A "completion mechanism" is a function that allows users to complete the registration process after reviewing the contents of a form.

[0303] "Commercial transactions" refer to all business processes related to the purchase and sale of goods and services.

[0304] An "order form" is an electronic form used by customers for final confirmation, reflecting their product selections and specified conditions in commercial transactions.

[0305] The embodiment for carrying out this invention is a system mainly consisting of a user-operated terminal and a server.

[0306] First, the terminal is equipped with a microphone and captures the conversation between the user and the processor as audio data. This audio data is sent from the terminal to the server. The server uses speech recognition technology such as Google Cloud Speech-to-Text to convert the audio data into text data. The converted text data is then processed using natural language processing with Python's NLTK or spaCy to extract the information necessary for registration.

[0307] Next, based on the extracted information, the server automatically generates a registration form using a web framework such as Flask or Django. The generated form is presented to the user's terminal. The user can utilize the terminal interface to view and modify the form content, and then complete the registration process.

[0308] As a specific example, consider the case where a user wants to order a red sweater at a clothing store. At this time, the terminal converts the user's voice "Looking for a red sweater in size M" into character data and extracts information such as "red sweater" and "size M". Then, based on this, an order form is generated and presented to the user.

[0309] An example of the prompt text for the generation AI model would be in the form of "Please analyze the following conversation and extract the product category and size: 'Looking for a red sweater in size M'".

[0310] The flow of the specific process in Application Example 1 will be described using Figure 12.

[0311] Step 1:

[0312] The terminal obtains the conversation between the user and the processor as voice data through the microphone. The input is real-time voice. After obtaining this voice data, the terminal prepares to send it to the server. The output is voice data in a sendable format.

[0313] Step 2:

[0314] The server converts the voice data received from the terminal into character data using the Google Cloud Speech-to-Text API. The input is voice data, and an audio recognition algorithm is applied to it to obtain the corresponding character string as the output. In this step, noise removal is also performed to improve the conversion accuracy.

[0315] Step 3:

[0316] The server performs natural language processing on the converted character data using Python's NLTK and spaCy. The input is character data, and the server extracts the information necessary for registration (e.g., product name and specifications) through text analysis. The output is a set of the extracted information. In this specific operation, keywords are extracted from the text and organized into structured data.

[0317] Step 4:

[0318] The server dynamically generates a registration form using Flask or Django based on the extracted information. The input is the extracted information, which is used to create a form that includes the order conditions required by the user. The output is the HTML of the generated registration form.

[0319] Step 5:

[0320] The terminal presents the generated registration form to the user. The input is an HTML form received from the server, and the output is a visual interface displayed on the user's screen. Specifically, the user can review the form contents and modify them if necessary.

[0321] Step 6:

[0322] The user reviews and modifies the form and confirms its contents. The input is the registration form reviewed by the user, and the output is the confirmed registration information. The user's specific action is to press the confirmation button, which completes the registration process.

[0323] Step 7:

[0324] The server stores the confirmed registration information and, if necessary, presents the user with relevant documents and notes. Input is the confirmed data after registration, and output is the stored data and notifications to the user regarding points to confirm. In this step, information is stored in the database, and the user is shown the next action.

[0325] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0326] This invention is a system that acquires conversations between users and processors as audio data, converts it to text, extracts necessary information, and reflects it in the registration process. In addition, it incorporates an emotion engine that analyzes the user's emotions. The aim of this system is to further improve user support and to more accurately understand user needs.

[0327] First, the user uses a device to have a voice conversation with the processor. The device acquires this voice data and sends it to the server. The server uses a speech recognition engine to convert the voice data into text and extracts the information necessary for registration from the converted text. In this process, an emotion engine analyzes the tone and speaking speed of the voice data and evaluates the user's emotional state.

[0328] The emotion engine identifies the user's emotional state, such as "anxiety" or "reassurance," and transmits this information to the server. Based on this emotion information, the server sends instructions to the terminal to customize the displayed content. For example, if the system detects that the user is feeling anxious, it can present additional explanations or guides during the registration form process.

[0329] For example, suppose a user is applying for a new communication plan and the system detects that they have concerns about data capacity or fees. In this case, the device, based on instructions from the server, displays a screen providing additional explanations to the user, guiding them to proceed with the process with confidence. If positive emotions are detected, the system can simply provide standard information to ensure a smooth process.

[0330] This system allows processors to take the user's emotional state into account when responding, improving the user experience and streamlining the registration process. With its immediate feedback based on emotion analysis and flexible response capabilities, this system can be a crucial tool for increasing user satisfaction.

[0331] The following describes the processing flow.

[0332] Step 1:

[0333] The terminal captures the conversation between the user and the processor as audio data via the microphone. This audio data is also used as information for sentiment analysis and is sent to the server.

[0334] Step 2:

[0335] The server receives audio data transmitted from the terminal and converts it into text data using a speech recognition engine. Simultaneously, it uses an emotion engine to analyze the tone and speaking speed of the audio data and evaluate the user's emotional state.

[0336] Step 3:

[0337] The server extracts the information necessary for registration from the converted text data using natural language processing technology. For example, it identifies the user's desired plan and contract terms.

[0338] Step 4:

[0339] The server automatically generates a registration form based on the extracted information and the sentiment evaluation results from the sentiment engine. Emotional states are taken into consideration, and the form content and presentation method are adjusted as needed.

[0340] Step 5:

[0341] The terminal displays the registration form sent from the server to the user and provides an interface that allows the user to review and modify the content. Additional explanations and guides may be provided based on sentiment ratings.

[0342] Step 6:

[0343] The user reviews the provided registration form and makes any necessary corrections. Once the user determines that the operation is complete, they provide instructions on the terminal to confirm the registration.

[0344] Step 7:

[0345] The terminal sends the user's registration confirmation operation to the server. The server saves the final data to the database and completes the registration process. At this time, the information obtained through sentiment evaluation may be used to improve future customer service.

[0346] Step 8:

[0347] The device displays necessary documents and instructions to the user after registration is complete. The user then makes the necessary preparations according to the information provided. Emotional feedback may also be provided at this stage.

[0348] (Example 2)

[0349] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0350] In user-service provider interactions, there is a need for a system that can appropriately consider the user's emotional state and present them with the most relevant information. This challenge is crucial for improving the user experience and streamlining the registration process. In particular, achieving flexible and effective information presentation tailored to the user's emotions is difficult.

[0351] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0352] In this invention, the server includes means for converting acoustic information into text information, means for extracting information necessary for registration from the converted text information, and means for analyzing the user's emotional state from the acoustic information. This enables the presentation of appropriate information based on the user's emotions and a smooth registration process.

[0353] "Acquisition method" refers to a function for collecting the dialogue between the user and the service provider as acoustic information.

[0354] "Conversion means" refers to a function for converting collected acoustic information into textual information.

[0355] "Extraction means" refers to a function for identifying and extracting information necessary for registration from the converted character information.

[0356] "Generation means" refers to a function that automatically creates a registration screen based on specified information.

[0357] "Presentation method" refers to a function that displays a generated registration screen to the user and prompts them to confirm the contents.

[0358] "Analysis means" refers to a function that evaluates and identifies the user's emotional state based on acoustic information.

[0359] "Adjustment mechanism" refers to a function that appropriately modifies the information displayed based on the analyzed emotional information.

[0360] "Completion mechanism" refers to a function that allows the user to finish the registration process after confirming the content.

[0361] This system effectively manages user-service provider interactions and provides information optimized based on the user's emotions. Its main components are programs that implement means for acquiring acoustic information, converting it to text, extracting necessary information, analyzing emotional states, and adjusting displayed content.

[0362] First, the user initiates a conversation with the service provider using their device. The device incorporates a mechanism for acquiring acoustic information, which collects the conversation in real time and sends it to the server. The server then converts the received acoustic information into text using a "speech recognition engine." Specifically, "Google Speech-to-Text" is one such speech recognition engine that can be used.

[0363] Next, the server uses a "natural language processing tool" to extract the information necessary for registration from the converted text information. Examples of such tools include "NLTK". The server is also equipped with an "emotion analysis engine" for sentiment analysis, which analyzes the user's emotional state using software such as "IBM Watson Tone Analyzer". Sentiment analysis is performed based on parameters such as voice tone and speaking speed.

[0364] The analyzed emotional information is then processed on a server, and instructions for displaying information tailored to the user's emotions are sent to the device. For example, if it is detected that the user is feeling "anxious" when applying for a new communication plan, the device will receive instructions from the server and display a screen offering additional explanations. In this way, the user experience is improved by providing appropriate feedback according to the user's emotions.

[0365] As a concrete example, when the prompt "Explain how to display additional information if the emotion extracted from the voice is determined to be anxiety" is input to the generating AI model, the system executes a process to provide the user, who is feeling anxious, with additional explanations about the procedure. This allows the user to proceed with the procedure with peace of mind.

[0366] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0367] Step 1:

[0368] The device records the conversation between the user and the service provider in real time and collects it as acoustic information. The input is the conversational audio, and the output is digital acoustic data. Specifically, it captures the audio signal through the device's microphone and saves it as digital data.

[0369] Step 2:

[0370] The terminal transmits the collected acoustic data to the server. Data transmission takes place via network communication, with acoustic data as the input and data transfer to the server as the output. Specifically, the terminal uses a communication protocol to send data to the server.

[0371] Step 3:

[0372] The server converts received audio data into text information using a speech recognition engine. The input to this process is audio data, and the output is text data. Specifically, the server analyzes the audio signal and maps it to text through phoneme recognition.

[0373] Step 4:

[0374] The server analyzes the converted text information using natural language processing tools and extracts the information necessary for registration. The input is text data, and the output is the extracted information. Specifically, the server detects keywords and phrases within the text and organizes them as structured data.

[0375] Step 5:

[0376] The server processes acoustic information using an emotion analysis engine to evaluate the user's emotional state. The input is the original acoustic data, and the output is the analyzed emotion information. Specifically, the server analyzes voice tone, speech rate, and emphasis to classify the emotional state.

[0377] Step 6:

[0378] The server sends instructions to the terminal to customize the displayed content based on the analyzed sentiment information. The input is sentiment information, and the output is customization instructions. Specifically, the server instructs the terminal to make appropriate content corrections and transfers the necessary data to the terminal.

[0379] Step 7:

[0380] The terminal receives instructions from the server and displays customized information to the user. Input is the customization instructions, and output is the presentation of information to the user. Specifically, the terminal updates the screen display, allowing the user to view additional information and guides.

[0381] (Application Example 2)

[0382] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0383] In the user-processor-based registration process, there is a challenge in providing appropriate information based on the user's emotional state, resulting in insufficient improvement of the user experience. Furthermore, there is difficulty in responding flexibly to users who experience anxiety or stress, taking their emotions into consideration.

[0384] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0385] In this invention, the server includes emotion analysis means for analyzing the tone and speaking speed of voice information to evaluate the user's emotional state, adjustment means for adjusting the presented content based on the user's emotional information, and means for presenting additional explanations or guides when the user is evaluated as being in an anxious state. This enables the presentation of information in accordance with the user's emotions, improving the user experience and streamlining the registration process.

[0386] "Acquisition means" refers to the means of acquiring the conversation between the user and the processor as audio information.

[0387] "Conversion means" refers to means for converting the acquired audio information into text information.

[0388] "Extraction means" refers to means for extracting information necessary for registration from the converted character information.

[0389] "Generation means" refers to means for automatically generating registration forms based on extracted information.

[0390] "Presentation means" refers to a means of presenting the generated registration form to the user and allowing them to confirm its contents.

[0391] "Completion method" refers to the means used to complete the registration process after the content has been verified.

[0392] "Emotional analysis means" refers to a method for evaluating a user's emotional state by analyzing the tone and speaking speed of voice information.

[0393] "Adjustment means" are means for adjusting the presented content based on the user's emotional information.

[0394] This invention is a system that acquires conversations between a user and a processor as audio information, converts it into text information, and extracts necessary registration data. This system incorporates speech recognition and sentiment analysis technologies and was developed to improve the user experience.

[0395] First, the user engages in conversation using a device such as a smartphone or a home robot. This device is equipped with a microphone and internet connectivity to capture the audio information of the conversation. The server receives this audio information and uses the Google Speech-to-Text API as software for speech recognition. Here, the audio information is converted into text information.

[0396] From the converted text information, the system extracts the information necessary for registration. Furthermore, the server uses an emotion analysis engine to analyze the tone and speaking speed of the voice information and evaluate the user's emotional state. Based on this analysis, instructions are sent to the terminal to adjust the displayed content based on the user's emotional information.

[0397] As a concrete example, imagine a user asking a consumer robot, "What should we do today?" The robot analyzes the tone of the conversation and detects a feeling of boredom. In this case, the robot provides a user-friendly service by suggesting a new activity that will stimulate the user's interest. An example of a prompt in this scenario would be, "Analyze the emotion from the tone of voice and generate a response that suggests an action appropriate to the mood."

[0398] This system allows terminals and servers to recognize specific emotional states of individual users and provide more personalized information. In this way, the user experience is improved, and the registration process and daily operations become more efficient.

[0399] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0400] Step 1:

[0401] The device acquires the user's voice via a microphone. The input is audio data, which is then converted to a digital format and prepared for transmission to the server. The output is digital audio data.

[0402] Step 2:

[0403] The server receives digital audio data and performs speech recognition using the Google Speech-to-Text API. The input is digital audio data, and speech recognition generates text data. The output is the converted text data.

[0404] Step 3:

[0405] This process extracts the necessary registration information from text data generated by the server. The input is text data, and information analysis is performed to identify and extract the required data fields. The output is the extracted registration information.

[0406] Step 4:

[0407] The server uses an emotion analysis engine to evaluate the user's emotional state based on the tone and speaking speed of the voice data. The input is digital voice data, and the voice features are analyzed to generate emotion data. The output is the user's emotional state data.

[0408] Step 5:

[0409] The server generates instructions to adjust the presented content based on the user's emotional state data. The input consists of emotional state data and extracted registration information, and the server performs data processing to optimize information presentation. The output is adjustment instruction data.

[0410] Step 6:

[0411] The terminal receives adjustment instruction data sent from the server and displays information optimized for the user based on that data. The input is the adjustment instruction data, which provides appropriate information on the user interface. The output is the customized information displayed on the user interface.

[0412] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0413] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0414] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0415] [Third Embodiment]

[0416] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0417] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0418] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0419] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0420] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0421] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0422] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0423] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0424] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0425] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0426] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0427] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0428] The present invention is a system that utilizes real-time conversations between users and processors in the registration process, and its embodiments are described below.

[0429] First, the user converses with a processor, either face-to-face or remotely, through a device equipped with a microphone. The device captures this conversation as audio data and sends it to a server. This function ensures that the user's requests and information are accurately digitized.

[0430] Next, the server uses speech recognition technology to convert the received audio data into text data. At this stage, noise reduction and speech clarity are performed to generate highly accurate text data. The converted text is then analyzed using natural language processing technology to extract the information necessary for registration (e.g., contract details and plan selection).

[0431] The server automatically creates a registration form based on the extracted information. This form is properly filled with the necessary fields for the contract and is designed for the user to review later. The terminal presents this registration form to the user, allowing them to review and modify the contract details.

[0432] Users use the terminal interface to review and modify the presented registration form, ultimately completing the registration process. This system allows users to quickly provide the necessary information, and enables processors to perform registration work efficiently.

[0433] As a concrete example, consider a scenario where a user wants to purchase a new smartphone. In this case, the user communicates with a staff member through the device and communicates their desired plan. The server processes this information in real time and automatically generates a registration form that includes the user's selected plan and options. The device then presents the generated form to the user, who confirms it and then confirms the registration.

[0434] This system significantly reduces errors and time losses associated with traditional manual processes, improving the accuracy and speed of customer service.

[0435] The following describes the processing flow.

[0436] Step 1:

[0437] The terminal captures the conversation between the user and the processor as audio data in real time. The terminal's microphone captures the audio and prepares to send the recorded audio data to the server.

[0438] Step 2:

[0439] The server receives the audio data sent from the terminal. It uses a speech recognition engine to convert this audio data into text. During this process, noise is removed and the clarity of the audio is maintained.

[0440] Step 3:

[0441] The server analyzes the converted text data using natural language processing technology and extracts the information necessary for registration. For example, it identifies information such as the subscriber's name, selected plan, and options.

[0442] Step 4:

[0443] The server automatically generates a registration form based on the extracted information. This form includes the necessary registration fields and is designed for user confirmation.

[0444] Step 5:

[0445] The terminal displays a registration form sent from the server to the user. The user can view, enter, or modify the registration details through the terminal's display.

[0446] Step 6:

[0447] The user reviews the information on the provided registration form and makes any necessary corrections. Once corrections are complete, they perform an action on their device to confirm the registration.

[0448] Step 7:

[0449] The terminal receives the user's registration confirmation and sends the final registration information to the server. The server saves the information to the database and completes the registration process.

[0450] Step 8:

[0451] The terminal will present the user with necessary documents and instructions after registration is complete. The user will review these and make the necessary preparations.

[0452] (Example 1)

[0453] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0454] Traditional conversation-based registration procedures are often performed manually, making them prone to errors in information entry and omissions. Furthermore, manual processing is time-consuming, leading to decreased efficiency. Additionally, accurately registering information provided by users through dialogue is difficult, resulting in a lack of process reliability.

[0455] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0456] In this invention, the server includes means for collecting acoustic information, means for converting the acoustic information into document information, and means for extracting necessary information from the document information. This makes it possible to accurately digitize the interaction between the user and the processor in real time and to perform the registration procedure quickly and accurately.

[0457] "Acoustic information" refers to all audio data, including conversations between the user and the processor.

[0458] "Document information" refers to character data converted from acoustic information.

[0459] "Means of collection" refers to the devices and technologies used to capture acoustic information in real time.

[0460] "Means of conversion" refers to speech recognition technology used to convert acoustic information into document information.

[0461] "Means of extraction" refers to a technology or device for identifying and extracting information necessary for registration procedures from document information.

[0462] "Fill-in document" refers to a registration form that is automatically generated based on the extracted information.

[0463] "Interface" refers to a user interface that allows users to review and modify documents they have filled out.

[0464] "Noise reduction" is the process of removing unwanted background noise from acoustic information.

[0465] "Speech clarification" refers to processing that improves the clarity of speech within acoustic information.

[0466] This invention relates to a virtual registration system that efficiently facilitates registration procedures based on dialogue between a user and a processor. Specific embodiments are described below.

[0467] First, the user converses with the processor using a device equipped with a microphone. The device collects this conversation as acoustic information and transmits it to the server in real time. This collection utilizes a voice recognition microphone and dedicated software built into the device. The acoustic information is digitized and transmitted via a secure communication protocol, thus guaranteeing data security.

[0468] The server uses speech recognition technology to convert the received acoustic information into document information. Specifically, the speech recognition engine performs noise reduction and speech clarity to convert the acoustic data into highly accurate text data. This technology can also utilize cloud-based speech recognition services.

[0469] The converted document information is analyzed by a natural language processing engine, and the information necessary for registration is extracted. Based on pre-configured keywords and phrases, the system accurately identifies contract-related items (e.g., contract details and plan selection) and stores them in the database.

[0470] Subsequently, the server automatically generates a form using the extracted information. This form is presented on a terminal equipped with a user interface for the user to review or modify their registration. This interface is designed to be intuitive and easy to use, allowing users to easily make any necessary corrections.

[0471] As a concrete example, consider a case where a user signs up for a new communication service. In this scenario, the user communicates with a service representative via their device and communicates their desired plan. The AI ​​model generates a form containing this information in real time and automatically presents the details of the plan the user has selected. The user then reviews the document and officially completes the registration process.

[0472] An example of a prompt message would be, "I'd like to discuss my preferred communication plan; I'd like a 20GB monthly data plan with an international calling option." This system allows users to proceed with the process quickly and accurately, while also improving the efficiency of the processing staff.

[0473] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0474] Step 1:

[0475] The terminal acquires acoustic information via a microphone through conversation between the user and the processor. The input is the user's voice, which is converted into a digital signal in real time. As output, digitized acoustic data is generated. This data is prepared to be sent to the server in a later processing step.

[0476] Step 2:

[0477] The terminal transmits the acquired acoustic data to the server using a secure communication protocol. The input is digital acoustic data, which is transmitted in an encrypted format. As output, the server receives acoustic information that can be decrypted in real time.

[0478] Step 3:

[0479] The server converts received acoustic information into document information using speech recognition technology. The input is digital acoustic data, which undergoes noise reduction and speech clarification. The output is effectively converted, high-precision text data.

[0480] Step 4:

[0481] The server analyzes document information based on natural language processing and extracts the information necessary for registration. The input is text data, and important information is identified based on specific keywords and phrases. The output is a dataset containing the information necessary for the registration process.

[0482] Step 5:

[0483] The server automatically generates a form using the extracted information. The input is an organized dataset, and a form is created based on this data with the necessary fields for the contract appropriately filled in. The output is a completed form that should be presented to the user.

[0484] Step 6:

[0485] The terminal presents the generated form to the user and provides an interface for the user to review and modify it. The input is form data from the server. This interface allows the user to intuitively manipulate the form and modify information as needed. The output is the final version of the form, reviewed by the user.

[0486] Step 7:

[0487] The user reviews the final version of the document through the terminal interface and completes the registration process. The input is a user-confirmed process, and the user confirms their intention to complete registration by pressing the "Register" button after final confirmation. As output, the server stores the final registration data, including all necessary information.

[0488] (Application Example 1)

[0489] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0490] In traditional commercial transactions, the reliance on paper documents and manual data entry for customer-employee conversations in stores led to problems such as information discrepancies and delays in procedures. Furthermore, the time-consuming process of creating and verifying registration forms often resulted in concerns about decreased customer satisfaction. Therefore, there is a need to establish technology that automatically and in real-time analyzes conversation content and generates order forms.

[0491] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0492] In this invention, the server includes acquisition means for acquiring the conversation between the user and the processor as audio data, conversion means for converting the audio data into text data, and extraction means for extracting information necessary for registration from the converted text data. This enables rapid digital processing of voice-based user requests and the generation of accurate order forms.

[0493] "Acquisition means" refers to a mechanism for acquiring conversations between the user and the processor as audio data.

[0494] "Conversion means" refers to technology for converting acquired audio data into text data.

[0495] "Extraction means" refers to a method for identifying and extracting information necessary for registration from converted character data.

[0496] "Generation method" refers to the process of automatically creating registration forms and order forms based on extracted information.

[0497] A "presentation means" is a means of showing the generated form to the user and providing an interface for them to confirm its contents.

[0498] A "completion mechanism" is a function that allows users to complete the registration process after reviewing the contents of a form.

[0499] "Commercial transactions" refer to all business processes related to the purchase and sale of goods and services.

[0500] An "order form" is an electronic form used by customers for final confirmation, reflecting their product selections and specified conditions in commercial transactions.

[0501] The embodiment for carrying out this invention is a system mainly consisting of a user-operated terminal and a server.

[0502] First, the terminal is equipped with a microphone and captures the conversation between the user and the processor as audio data. This audio data is sent from the terminal to the server. The server uses speech recognition technology such as Google Cloud Speech-to-Text to convert the audio data into text data. The converted text data is then processed using natural language processing with Python's NLTK or spaCy to extract the information necessary for registration.

[0503] Next, the server automatically generates a registration form using a web framework such as Flask or Django based on the extracted information. The generated form is then presented to the user's device. The user can use the device's interface to review and modify the form's contents before completing the registration process.

[0504] As a concrete example, consider a scenario where a user wants to order a red sweater at a clothing store. In this case, the terminal converts the user's voice, "I'm looking for a red sweater in size M," into text data, extracting the information "red sweater" and "size M." Based on this, an order form is generated and presented to the user.

[0505] An example of a prompt for a generative AI model would be: "Analyze the following conversation and extract the product category and size: 'I'm looking for a red sweater in size M.'"

[0506] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0507] Step 1:

[0508] The terminal captures the conversation between the user and the processor as audio data via the microphone. The input is real-time audio. After acquiring this audio data, the terminal prepares to send it to the server. The output is audio data in a transmittable format.

[0509] Step 2:

[0510] The server converts the audio data received from the terminal into text data using the Google Cloud Speech-to-Text API. The input is audio data, a speech recognition algorithm is applied to it, and the output is a corresponding string. Noise reduction is also performed in this step to improve the conversion accuracy.

[0511] Step 3:

[0512] The server performs natural language processing on the converted character data using Python's NLTK and spaCy. The input is character data, and the server extracts the information necessary for registration (e.g., product name and specifications) through text analysis. The output is a set of the extracted information. In this specific operation, keywords are extracted from the text and organized into structured data.

[0513] Step 4:

[0514] The server dynamically generates a registration form using Flask or Django based on the extracted information. The input is the extracted information, which is used to create a form that includes the order conditions required by the user. The output is the HTML of the generated registration form.

[0515] Step 5:

[0516] The terminal presents the generated registration form to the user. The input is an HTML form received from the server, and the output is a visual interface displayed on the user's screen. Specifically, the user can review the form contents and modify them if necessary.

[0517] Step 6:

[0518] The user reviews and modifies the form and confirms its contents. The input is the registration form reviewed by the user, and the output is the confirmed registration information. The user's specific action is to press the confirmation button, which completes the registration process.

[0519] Step 7:

[0520] The server stores the confirmed registration information and, if necessary, presents the user with relevant documents and notes. Input is the confirmed data after registration, and output is the stored data and notifications to the user regarding points to confirm. In this step, information is stored in the database, and the user is shown the next action.

[0521] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0522] This invention is a system that acquires conversations between users and processors as audio data, converts it to text, extracts necessary information, and reflects it in the registration process. In addition, it incorporates an emotion engine that analyzes the user's emotions. The aim of this system is to further improve user support and to more accurately understand user needs.

[0523] First, the user uses a device to have a voice conversation with the processor. The device acquires this voice data and sends it to the server. The server uses a speech recognition engine to convert the voice data into text and extracts the information necessary for registration from the converted text. In this process, an emotion engine analyzes the tone and speaking speed of the voice data and evaluates the user's emotional state.

[0524] The emotion engine identifies the user's emotional state, such as "anxiety" or "reassurance," and transmits this information to the server. Based on this emotion information, the server sends instructions to the terminal to customize the displayed content. For example, if the system detects that the user is feeling anxious, it can present additional explanations or guides during the registration form process.

[0525] For example, suppose a user is applying for a new communication plan and the system detects that they have concerns about data capacity or fees. In this case, the device, based on instructions from the server, displays a screen providing additional explanations to the user, guiding them to proceed with the process with confidence. If positive emotions are detected, the system can simply provide standard information to ensure a smooth process.

[0526] This system allows processors to take the user's emotional state into account when responding, improving the user experience and streamlining the registration process. With its immediate feedback based on emotion analysis and flexible response capabilities, this system can be a crucial tool for increasing user satisfaction.

[0527] The following describes the processing flow.

[0528] Step 1:

[0529] The terminal captures the conversation between the user and the processor as audio data via the microphone. This audio data is also used as information for sentiment analysis and is sent to the server.

[0530] Step 2:

[0531] The server receives audio data transmitted from the terminal and converts it into text data using a speech recognition engine. Simultaneously, it uses an emotion engine to analyze the tone and speaking speed of the audio data and evaluate the user's emotional state.

[0532] Step 3:

[0533] The server extracts the information necessary for registration from the converted text data using natural language processing technology. For example, it identifies the user's desired plan and contract terms.

[0534] Step 4:

[0535] The server automatically generates a registration form based on the extracted information and the sentiment evaluation results from the sentiment engine. Emotional states are taken into consideration, and the form content and presentation method are adjusted as needed.

[0536] Step 5:

[0537] The terminal displays the registration form sent from the server to the user and provides an interface that allows the user to review and modify the content. Additional explanations and guides may be provided based on sentiment ratings.

[0538] Step 6:

[0539] The user reviews the provided registration form and makes any necessary corrections. Once the user determines that the operation is complete, they provide instructions on the terminal to confirm the registration.

[0540] Step 7:

[0541] The terminal sends the user's registration confirmation operation to the server. The server saves the final data to the database and completes the registration process. At this time, the information obtained through sentiment evaluation may be used to improve future customer service.

[0542] Step 8:

[0543] The device displays necessary documents and instructions to the user after registration is complete. The user then makes the necessary preparations according to the information provided. Emotional feedback may also be provided at this stage.

[0544] (Example 2)

[0545] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0546] In user-service provider interactions, there is a need for a system that can appropriately consider the user's emotional state and present them with the most relevant information. This challenge is crucial for improving the user experience and streamlining the registration process. In particular, achieving flexible and effective information presentation tailored to the user's emotions is difficult.

[0547] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0548] In this invention, the server includes means for converting acoustic information into text information, means for extracting information necessary for registration from the converted text information, and means for analyzing the user's emotional state from the acoustic information. This enables the presentation of appropriate information based on the user's emotions and a smooth registration process.

[0549] "Acquisition method" refers to a function for collecting the dialogue between the user and the service provider as acoustic information.

[0550] "Conversion means" refers to a function for converting collected acoustic information into textual information.

[0551] "Extraction means" refers to a function for identifying and extracting information necessary for registration from the converted character information.

[0552] "Generation means" refers to a function that automatically creates a registration screen based on specified information.

[0553] "Presentation method" refers to a function that displays a generated registration screen to the user and prompts them to confirm the contents.

[0554] "Analysis means" refers to a function that evaluates and identifies the user's emotional state based on acoustic information.

[0555] "Adjustment mechanism" refers to a function that appropriately modifies the information displayed based on the analyzed emotional information.

[0556] "Completion mechanism" refers to a function that allows the user to finish the registration process after confirming the content.

[0557] This system effectively manages user-service provider interactions and provides information optimized based on the user's emotions. Its main components are programs that implement means for acquiring acoustic information, converting it to text, extracting necessary information, analyzing emotional states, and adjusting displayed content.

[0558] First, the user initiates a conversation with the service provider using their device. The device incorporates a mechanism for acquiring acoustic information, which collects the conversation in real time and sends it to the server. The server then converts the received acoustic information into text using a "speech recognition engine." Specifically, "Google Speech-to-Text" is one such speech recognition engine that can be used.

[0559] Next, the server uses a "natural language processing tool" to extract the information necessary for registration from the converted text information. Examples of such tools include "NLTK". The server is also equipped with an "emotion analysis engine" for sentiment analysis, which analyzes the user's emotional state using software such as "IBM Watson Tone Analyzer". Sentiment analysis is performed based on parameters such as voice tone and speaking speed.

[0560] The analyzed emotional information is then processed on a server, and instructions for displaying information tailored to the user's emotions are sent to the device. For example, if it is detected that the user is feeling "anxious" when applying for a new communication plan, the device will receive instructions from the server and display a screen offering additional explanations. In this way, the user experience is improved by providing appropriate feedback according to the user's emotions.

[0561] As a concrete example, when the prompt "Explain how to display additional information if the emotion extracted from the voice is determined to be anxiety" is input to the generating AI model, the system executes a process to provide the user, who is feeling anxious, with additional explanations about the procedure. This allows the user to proceed with the procedure with peace of mind.

[0562] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0563] Step 1:

[0564] The device records the conversation between the user and the service provider in real time and collects it as acoustic information. The input is the conversational audio, and the output is digital acoustic data. Specifically, it captures the audio signal through the device's microphone and saves it as digital data.

[0565] Step 2:

[0566] The terminal transmits the collected acoustic data to the server. Data transmission takes place via network communication, with acoustic data as the input and data transfer to the server as the output. Specifically, the terminal uses a communication protocol to send data to the server.

[0567] Step 3:

[0568] The server converts received audio data into text information using a speech recognition engine. The input to this process is audio data, and the output is text data. Specifically, the server analyzes the audio signal and maps it to text through phoneme recognition.

[0569] Step 4:

[0570] The server analyzes the converted text information using natural language processing tools and extracts the information necessary for registration. The input is text data, and the output is the extracted information. Specifically, the server detects keywords and phrases within the text and organizes them as structured data.

[0571] Step 5:

[0572] The server processes acoustic information using an emotion analysis engine to evaluate the user's emotional state. The input is the original acoustic data, and the output is the analyzed emotion information. Specifically, the server analyzes voice tone, speech rate, and emphasis to classify the emotional state.

[0573] Step 6:

[0574] The server sends instructions to the terminal to customize the displayed content based on the analyzed sentiment information. The input is sentiment information, and the output is customization instructions. Specifically, the server instructs the terminal to make appropriate content corrections and transfers the necessary data to the terminal.

[0575] Step 7:

[0576] The terminal receives instructions from the server and displays customized information to the user. Input is the customization instructions, and output is the presentation of information to the user. Specifically, the terminal updates the screen display, allowing the user to view additional information and guides.

[0577] (Application Example 2)

[0578] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0579] In the user-processor-based registration process, there is a challenge in providing appropriate information based on the user's emotional state, resulting in insufficient improvement of the user experience. Furthermore, there is difficulty in responding flexibly to users who experience anxiety or stress, taking their emotions into consideration.

[0580] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0581] In this invention, the server includes emotion analysis means for analyzing the tone and speaking speed of voice information to evaluate the user's emotional state, adjustment means for adjusting the presented content based on the user's emotional information, and means for presenting additional explanations or guides when the user is evaluated as being in an anxious state. This enables the presentation of information in accordance with the user's emotions, improving the user experience and streamlining the registration process.

[0582] "Acquisition means" refers to the means of acquiring the conversation between the user and the processor as audio information.

[0583] "Conversion means" refers to means for converting the acquired audio information into text information.

[0584] "Extraction means" refers to means for extracting information necessary for registration from the converted character information.

[0585] "Generation means" refers to means for automatically generating registration forms based on extracted information.

[0586] "Presentation means" refers to a means of presenting the generated registration form to the user and allowing them to confirm its contents.

[0587] "Completion method" refers to the means used to complete the registration process after the content has been verified.

[0588] "Emotional analysis means" refers to a method for evaluating a user's emotional state by analyzing the tone and speaking speed of voice information.

[0589] "Adjustment means" are means for adjusting the presented content based on the user's emotional information.

[0590] This invention is a system that acquires conversations between a user and a processor as audio information, converts it into text information, and extracts necessary registration data. This system incorporates speech recognition and sentiment analysis technologies and was developed to improve the user experience.

[0591] First, the user engages in conversation using a device such as a smartphone or a home robot. This device is equipped with a microphone and internet connectivity to capture the audio information of the conversation. The server receives this audio information and uses the Google Speech-to-Text API as software for speech recognition. Here, the audio information is converted into text information.

[0592] From the converted text information, the system extracts the information necessary for registration. Furthermore, the server uses an emotion analysis engine to analyze the tone and speaking speed of the voice information and evaluate the user's emotional state. Based on this analysis, instructions are sent to the terminal to adjust the displayed content based on the user's emotional information.

[0593] As a concrete example, imagine a user asking a consumer robot, "What should we do today?" The robot analyzes the tone of the conversation and detects a feeling of boredom. In this case, the robot provides a user-friendly service by suggesting a new activity that will stimulate the user's interest. An example of a prompt in this scenario would be, "Analyze the emotion from the tone of voice and generate a response that suggests an action appropriate to the mood."

[0594] This system allows terminals and servers to recognize specific emotional states of individual users and provide more personalized information. In this way, the user experience is improved, and the registration process and daily operations become more efficient.

[0595] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0596] Step 1:

[0597] The device acquires the user's voice via a microphone. The input is audio data, which is then converted to a digital format and prepared for transmission to the server. The output is digital audio data.

[0598] Step 2:

[0599] The server receives digital audio data and performs speech recognition using the Google Speech-to-Text API. The input is digital audio data, and speech recognition generates text data. The output is the converted text data.

[0600] Step 3:

[0601] This process extracts the necessary registration information from text data generated by the server. The input is text data, and information analysis is performed to identify and extract the required data fields. The output is the extracted registration information.

[0602] Step 4:

[0603] The server uses an emotion analysis engine to evaluate the user's emotional state based on the tone and speaking speed of the voice data. The input is digital voice data, and the voice features are analyzed to generate emotion data. The output is the user's emotional state data.

[0604] Step 5:

[0605] The server generates instructions to adjust the presented content based on the user's emotional state data. The input consists of emotional state data and extracted registration information, and the server performs data processing to optimize information presentation. The output is adjustment instruction data.

[0606] Step 6:

[0607] The terminal receives adjustment instruction data sent from the server and displays information optimized for the user based on that data. The input is the adjustment instruction data, which provides appropriate information on the user interface. The output is the customized information displayed on the user interface.

[0608] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0609] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0610] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0611] [Fourth Embodiment]

[0612] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0613] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0614] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0615] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0616] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0617] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0618] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0619] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0620] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0621] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0622] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0623] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0624] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0625] The present invention is a system that utilizes real-time conversations between users and processors in the registration process, and its embodiments are described below.

[0626] First, the user converses with a processor, either face-to-face or remotely, through a device equipped with a microphone. The device captures this conversation as audio data and sends it to a server. This function ensures that the user's requests and information are accurately digitized.

[0627] Next, the server uses speech recognition technology to convert the received audio data into text data. At this stage, noise reduction and speech clarity are performed to generate highly accurate text data. The converted text is then analyzed using natural language processing technology to extract the information necessary for registration (e.g., contract details and plan selection).

[0628] The server automatically creates a registration form based on the extracted information. This form is properly filled with the necessary fields for the contract and is designed for the user to review later. The terminal presents this registration form to the user, allowing them to review and modify the contract details.

[0629] Users use the terminal interface to review and modify the presented registration form, ultimately completing the registration process. This system allows users to quickly provide the necessary information, and enables processors to perform registration work efficiently.

[0630] As a concrete example, consider a scenario where a user wants to purchase a new smartphone. In this case, the user communicates with a staff member through the device and communicates their desired plan. The server processes this information in real time and automatically generates a registration form that includes the user's selected plan and options. The device then presents the generated form to the user, who confirms it and then confirms the registration.

[0631] This system significantly reduces errors and time losses associated with traditional manual processes, improving the accuracy and speed of customer service.

[0632] The following describes the processing flow.

[0633] Step 1:

[0634] The terminal captures the conversation between the user and the processor as audio data in real time. The terminal's microphone captures the audio and prepares to send the recorded audio data to the server.

[0635] Step 2:

[0636] The server receives the audio data sent from the terminal. It uses a speech recognition engine to convert this audio data into text. During this process, noise is removed and the clarity of the audio is maintained.

[0637] Step 3:

[0638] The server analyzes the converted text data using natural language processing technology and extracts the information necessary for registration. For example, it identifies information such as the subscriber's name, selected plan, and options.

[0639] Step 4:

[0640] The server automatically generates a registration form based on the extracted information. This form includes the necessary registration fields and is designed for user confirmation.

[0641] Step 5:

[0642] The terminal displays a registration form sent from the server to the user. The user can view, enter, or modify the registration details through the terminal's display.

[0643] Step 6:

[0644] The user reviews the information on the provided registration form and makes any necessary corrections. Once corrections are complete, they perform an action on their device to confirm the registration.

[0645] Step 7:

[0646] The terminal receives the user's registration confirmation and sends the final registration information to the server. The server saves the information to the database and completes the registration process.

[0647] Step 8:

[0648] The terminal will present the user with necessary documents and instructions after registration is complete. The user will review these and make the necessary preparations.

[0649] (Example 1)

[0650] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0651] Traditional conversation-based registration procedures are often performed manually, making them prone to errors in information entry and omissions. Furthermore, manual processing is time-consuming, leading to decreased efficiency. Additionally, accurately registering information provided by users through dialogue is difficult, resulting in a lack of process reliability.

[0652] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0653] In this invention, the server includes means for collecting acoustic information, means for converting the acoustic information into document information, and means for extracting necessary information from the document information. This makes it possible to accurately digitize the interaction between the user and the processor in real time and to perform the registration procedure quickly and accurately.

[0654] "Acoustic information" refers to all audio data, including conversations between the user and the processor.

[0655] "Document information" refers to character data converted from acoustic information.

[0656] "Means of collection" refers to the devices and technologies used to capture acoustic information in real time.

[0657] "Means of conversion" refers to speech recognition technology used to convert acoustic information into document information.

[0658] "Means of extraction" refers to a technology or device for identifying and extracting information necessary for registration procedures from document information.

[0659] "Fill-in document" refers to a registration form that is automatically generated based on the extracted information.

[0660] "Interface" refers to a user interface that allows users to review and modify documents they have filled out.

[0661] "Noise reduction" is the process of removing unwanted background noise from acoustic information.

[0662] "Speech clarification" refers to processing that improves the clarity of speech within acoustic information.

[0663] This invention relates to a virtual registration system that efficiently facilitates registration procedures based on dialogue between a user and a processor. Specific embodiments are described below.

[0664] First, the user converses with the processor using a device equipped with a microphone. The device collects this conversation as acoustic information and transmits it to the server in real time. This collection utilizes a voice recognition microphone and dedicated software built into the device. The acoustic information is digitized and transmitted via a secure communication protocol, thus guaranteeing data security.

[0665] The server uses speech recognition technology to convert the received acoustic information into document information. Specifically, the speech recognition engine performs noise reduction and speech clarity to convert the acoustic data into highly accurate text data. This technology can also utilize cloud-based speech recognition services.

[0666] The converted document information is analyzed by a natural language processing engine, and the information necessary for registration is extracted. Based on pre-configured keywords and phrases, the system accurately identifies contract-related items (e.g., contract details and plan selection) and stores them in the database.

[0667] Subsequently, the server automatically generates a form using the extracted information. This form is presented on a terminal equipped with a user interface for the user to review or modify their registration. This interface is designed to be intuitive and easy to use, allowing users to easily make any necessary corrections.

[0668] As a concrete example, consider a case where a user signs up for a new communication service. In this scenario, the user communicates with a service representative via their device and communicates their desired plan. The AI ​​model generates a form containing this information in real time and automatically presents the details of the plan the user has selected. The user then reviews the document and officially completes the registration process.

[0669] An example of a prompt message would be, "I'd like to discuss my preferred communication plan; I'd like a 20GB monthly data plan with an international calling option." This system allows users to proceed with the process quickly and accurately, while also improving the efficiency of the processing staff.

[0670] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0671] Step 1:

[0672] The terminal acquires acoustic information via a microphone through conversation between the user and the processor. The input is the user's voice, which is converted into a digital signal in real time. As output, digitized acoustic data is generated. This data is prepared to be sent to the server in a later processing step.

[0673] Step 2:

[0674] The terminal transmits the acquired acoustic data to the server using a secure communication protocol. The input is digital acoustic data, which is transmitted in an encrypted format. As output, the server receives acoustic information that can be decrypted in real time.

[0675] Step 3:

[0676] The server converts received acoustic information into document information using speech recognition technology. The input is digital acoustic data, which undergoes noise reduction and speech clarification. The output is effectively converted, high-precision text data.

[0677] Step 4:

[0678] The server analyzes document information based on natural language processing and extracts the information necessary for registration. The input is text data, and important information is identified based on specific keywords and phrases. The output is a dataset containing the information necessary for the registration process.

[0679] Step 5:

[0680] The server automatically generates a form using the extracted information. The input is an organized dataset, and a form is created based on this data with the necessary fields for the contract appropriately filled in. The output is a completed form that should be presented to the user.

[0681] Step 6:

[0682] The terminal presents the generated form to the user and provides an interface for the user to review and modify it. The input is form data from the server. This interface allows the user to intuitively manipulate the form and modify information as needed. The output is the final version of the form, reviewed by the user.

[0683] Step 7:

[0684] The user reviews the final version of the document through the terminal interface and completes the registration process. The input is a user-confirmed process, and the user confirms their intention to complete registration by pressing the "Register" button after final confirmation. As output, the server stores the final registration data, including all necessary information.

[0685] (Application Example 1)

[0686] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0687] In traditional commercial transactions, the reliance on paper documents and manual data entry for customer-employee conversations in stores led to problems such as information discrepancies and delays in procedures. Furthermore, the time-consuming process of creating and verifying registration forms often resulted in concerns about decreased customer satisfaction. Therefore, there is a need to establish technology that automatically and in real-time analyzes conversation content and generates order forms.

[0688] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0689] In this invention, the server includes acquisition means for acquiring the conversation between the user and the processor as audio data, conversion means for converting the audio data into text data, and extraction means for extracting information necessary for registration from the converted text data. This enables rapid digital processing of voice-based user requests and the generation of accurate order forms.

[0690] "Acquisition means" refers to a mechanism for acquiring conversations between the user and the processor as audio data.

[0691] "Conversion means" refers to technology for converting acquired audio data into text data.

[0692] "Extraction means" refers to a method for identifying and extracting information necessary for registration from converted character data.

[0693] "Generation method" refers to the process of automatically creating registration forms and order forms based on extracted information.

[0694] A "presentation means" is a means of showing the generated form to the user and providing an interface for them to confirm its contents.

[0695] A "completion mechanism" is a function that allows users to complete the registration process after reviewing the contents of a form.

[0696] "Commercial transactions" refer to all business processes related to the purchase and sale of goods and services.

[0697] An "order form" is an electronic form used by customers for final confirmation, reflecting their product selections and specified conditions in commercial transactions.

[0698] The embodiment for carrying out this invention is a system mainly consisting of a user-operated terminal and a server.

[0699] First, the terminal is equipped with a microphone and captures the conversation between the user and the processor as audio data. This audio data is sent from the terminal to the server. The server uses speech recognition technology such as Google Cloud Speech-to-Text to convert the audio data into text data. The converted text data is then processed using natural language processing with Python's NLTK or spaCy to extract the information necessary for registration.

[0700] Next, the server automatically generates a registration form using a web framework such as Flask or Django based on the extracted information. The generated form is then presented to the user's device. The user can use the device's interface to review and modify the form's contents before completing the registration process.

[0701] As a concrete example, consider a scenario where a user wants to order a red sweater at a clothing store. In this case, the terminal converts the user's voice, "I'm looking for a red sweater in size M," into text data, extracting the information "red sweater" and "size M." Based on this, an order form is generated and presented to the user.

[0702] An example of a prompt for a generative AI model would be: "Analyze the following conversation and extract the product category and size: 'I'm looking for a red sweater in size M.'"

[0703] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0704] Step 1:

[0705] The terminal captures the conversation between the user and the processor as audio data via the microphone. The input is real-time audio. After acquiring this audio data, the terminal prepares to send it to the server. The output is audio data in a transmittable format.

[0706] Step 2:

[0707] The server converts the audio data received from the terminal into text data using the Google Cloud Speech-to-Text API. The input is audio data, a speech recognition algorithm is applied to it, and the output is a corresponding string. Noise reduction is also performed in this step to improve the conversion accuracy.

[0708] Step 3:

[0709] The server performs natural language processing on the converted character data using Python's NLTK and spaCy. The input is character data, and the server extracts the information necessary for registration (e.g., product name and specifications) through text analysis. The output is a set of the extracted information. In this specific operation, keywords are extracted from the text and organized into structured data.

[0710] Step 4:

[0711] The server dynamically generates a registration form using Flask or Django based on the extracted information. The input is the extracted information, which is used to create a form that includes the order conditions required by the user. The output is the HTML of the generated registration form.

[0712] Step 5:

[0713] The terminal presents the generated registration form to the user. The input is an HTML form received from the server, and the output is a visual interface displayed on the user's screen. Specifically, the user can review the form contents and modify them if necessary.

[0714] Step 6:

[0715] The user reviews and modifies the form and confirms its contents. The input is the registration form reviewed by the user, and the output is the confirmed registration information. The user's specific action is to press the confirmation button, which completes the registration process.

[0716] Step 7:

[0717] The server stores the confirmed registration information and, if necessary, presents the user with relevant documents and notes. Input is the confirmed data after registration, and output is the stored data and notifications to the user regarding points to confirm. In this step, information is stored in the database, and the user is shown the next action.

[0718] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0719] This invention is a system that acquires conversations between users and processors as audio data, converts it to text, extracts necessary information, and reflects it in the registration process. In addition, it incorporates an emotion engine that analyzes the user's emotions. The aim of this system is to further improve user support and to more accurately understand user needs.

[0720] First, the user uses a device to have a voice conversation with the processor. The device acquires this voice data and sends it to the server. The server uses a speech recognition engine to convert the voice data into text and extracts the information necessary for registration from the converted text. In this process, an emotion engine analyzes the tone and speaking speed of the voice data and evaluates the user's emotional state.

[0721] The emotion engine identifies the user's emotional state, such as "anxiety" or "reassurance," and transmits this information to the server. Based on this emotion information, the server sends instructions to the terminal to customize the displayed content. For example, if the system detects that the user is feeling anxious, it can present additional explanations or guides during the registration form process.

[0722] For example, suppose a user is applying for a new communication plan and the system detects that they have concerns about data capacity or fees. In this case, the device, based on instructions from the server, displays a screen providing additional explanations to the user, guiding them to proceed with the process with confidence. If positive emotions are detected, the system can simply provide standard information to ensure a smooth process.

[0723] This system allows processors to take the user's emotional state into account when responding, improving the user experience and streamlining the registration process. With its immediate feedback based on emotion analysis and flexible response capabilities, this system can be a crucial tool for increasing user satisfaction.

[0724] The following describes the processing flow.

[0725] Step 1:

[0726] The terminal captures the conversation between the user and the processor as audio data via the microphone. This audio data is also used as information for sentiment analysis and is sent to the server.

[0727] Step 2:

[0728] The server receives audio data transmitted from the terminal and converts it into text data using a speech recognition engine. Simultaneously, it uses an emotion engine to analyze the tone and speaking speed of the audio data and evaluate the user's emotional state.

[0729] Step 3:

[0730] The server extracts the information necessary for registration from the converted text data using natural language processing technology. For example, it identifies the user's desired plan and contract terms.

[0731] Step 4:

[0732] The server automatically generates a registration form based on the extracted information and the sentiment evaluation results from the sentiment engine. Emotional states are taken into consideration, and the form content and presentation method are adjusted as needed.

[0733] Step 5:

[0734] The terminal displays the registration form sent from the server to the user and provides an interface that allows the user to review and modify the content. Additional explanations and guides may be provided based on sentiment ratings.

[0735] Step 6:

[0736] The user reviews the provided registration form and makes any necessary corrections. Once the user determines that the operation is complete, they provide instructions on the terminal to confirm the registration.

[0737] Step 7:

[0738] The terminal sends the user's registration confirmation operation to the server. The server saves the final data to the database and completes the registration process. At this time, the information obtained through sentiment evaluation may be used to improve future customer service.

[0739] Step 8:

[0740] The device displays necessary documents and instructions to the user after registration is complete. The user then makes the necessary preparations according to the information provided. Emotional feedback may also be provided at this stage.

[0741] (Example 2)

[0742] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0743] In user-service provider interactions, there is a need for a system that can appropriately consider the user's emotional state and present them with the most relevant information. This challenge is crucial for improving the user experience and streamlining the registration process. In particular, achieving flexible and effective information presentation tailored to the user's emotions is difficult.

[0744] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0745] In this invention, the server includes means for converting acoustic information into text information, means for extracting information necessary for registration from the converted text information, and means for analyzing the user's emotional state from the acoustic information. This enables the presentation of appropriate information based on the user's emotions and a smooth registration process.

[0746] "Acquisition method" refers to a function for collecting the dialogue between the user and the service provider as acoustic information.

[0747] "Conversion means" refers to a function for converting collected acoustic information into textual information.

[0748] "Extraction means" refers to a function for identifying and extracting information necessary for registration from the converted character information.

[0749] "Generation means" refers to a function that automatically creates a registration screen based on specified information.

[0750] "Presentation method" refers to a function that displays a generated registration screen to the user and prompts them to confirm the contents.

[0751] "Analysis means" refers to a function that evaluates and identifies the user's emotional state based on acoustic information.

[0752] "Adjustment mechanism" refers to a function that appropriately modifies the information displayed based on the analyzed emotional information.

[0753] "Completion mechanism" refers to a function that allows the user to finish the registration process after confirming the content.

[0754] This system effectively manages user-service provider interactions and provides information optimized based on the user's emotions. Its main components are programs that implement means for acquiring acoustic information, converting it to text, extracting necessary information, analyzing emotional states, and adjusting displayed content.

[0755] First, the user initiates a conversation with the service provider using their device. The device incorporates a mechanism for acquiring acoustic information, which collects the conversation in real time and sends it to the server. The server then converts the received acoustic information into text using a "speech recognition engine." Specifically, "Google Speech-to-Text" is one such speech recognition engine that can be used.

[0756] Next, the server uses a "natural language processing tool" to extract the information necessary for registration from the converted text information. Examples of such tools include "NLTK". The server is also equipped with an "emotion analysis engine" for sentiment analysis, which analyzes the user's emotional state using software such as "IBM Watson Tone Analyzer". Sentiment analysis is performed based on parameters such as voice tone and speaking speed.

[0757] The analyzed emotional information is then processed on a server, and instructions for displaying information tailored to the user's emotions are sent to the device. For example, if it is detected that the user is feeling "anxious" when applying for a new communication plan, the device will receive instructions from the server and display a screen offering additional explanations. In this way, the user experience is improved by providing appropriate feedback according to the user's emotions.

[0758] As a concrete example, when the prompt "Explain how to display additional information if the emotion extracted from the voice is determined to be anxiety" is input to the generating AI model, the system executes a process to provide the user, who is feeling anxious, with additional explanations about the procedure. This allows the user to proceed with the procedure with peace of mind.

[0759] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0760] Step 1:

[0761] The device records the conversation between the user and the service provider in real time and collects it as acoustic information. The input is the conversational audio, and the output is digital acoustic data. Specifically, it captures the audio signal through the device's microphone and saves it as digital data.

[0762] Step 2:

[0763] The terminal transmits the collected acoustic data to the server. Data transmission takes place via network communication, with acoustic data as the input and data transfer to the server as the output. Specifically, the terminal uses a communication protocol to send data to the server.

[0764] Step 3:

[0765] The server converts received audio data into text information using a speech recognition engine. The input to this process is audio data, and the output is text data. Specifically, the server analyzes the audio signal and maps it to text through phoneme recognition.

[0766] Step 4:

[0767] The server analyzes the converted text information using natural language processing tools and extracts the information necessary for registration. The input is text data, and the output is the extracted information. Specifically, the server detects keywords and phrases within the text and organizes them as structured data.

[0768] Step 5:

[0769] The server processes acoustic information using an emotion analysis engine to evaluate the user's emotional state. The input is the original acoustic data, and the output is the analyzed emotion information. Specifically, the server analyzes voice tone, speech rate, and emphasis to classify the emotional state.

[0770] Step 6:

[0771] The server sends instructions to the terminal to customize the displayed content based on the analyzed sentiment information. The input is sentiment information, and the output is customization instructions. Specifically, the server instructs the terminal to make appropriate content corrections and transfers the necessary data to the terminal.

[0772] Step 7:

[0773] The terminal receives instructions from the server and displays customized information to the user. Input is the customization instructions, and output is the presentation of information to the user. Specifically, the terminal updates the screen display, allowing the user to view additional information and guides.

[0774] (Application Example 2)

[0775] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0776] In the user-processor-based registration process, there is a challenge in providing appropriate information based on the user's emotional state, resulting in insufficient improvement of the user experience. Furthermore, there is difficulty in responding flexibly to users who experience anxiety or stress, taking their emotions into consideration.

[0777] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0778] In this invention, the server includes emotion analysis means for analyzing the tone and speaking speed of voice information to evaluate the user's emotional state, adjustment means for adjusting the presented content based on the user's emotional information, and means for presenting additional explanations or guides when the user is evaluated as being in an anxious state. This enables the presentation of information in accordance with the user's emotions, improving the user experience and streamlining the registration process.

[0779] "Acquisition means" refers to the means of acquiring the conversation between the user and the processor as audio information.

[0780] "Conversion means" refers to means for converting the acquired audio information into text information.

[0781] "Extraction means" refers to means for extracting information necessary for registration from the converted character information.

[0782] "Generation means" refers to means for automatically generating registration forms based on extracted information.

[0783] "Presentation means" refers to a means of presenting the generated registration form to the user and allowing them to confirm its contents.

[0784] "Completion method" refers to the means used to complete the registration process after the content has been verified.

[0785] "Emotional analysis means" refers to a method for evaluating a user's emotional state by analyzing the tone and speaking speed of voice information.

[0786] "Adjustment means" are means for adjusting the presented content based on the user's emotional information.

[0787] This invention is a system that acquires conversations between a user and a processor as audio information, converts it into text information, and extracts necessary registration data. This system incorporates speech recognition and sentiment analysis technologies and was developed to improve the user experience.

[0788] First, the user engages in conversation using a device such as a smartphone or a home robot. This device is equipped with a microphone and internet connectivity to capture the audio information of the conversation. The server receives this audio information and uses the Google Speech-to-Text API as software for speech recognition. Here, the audio information is converted into text information.

[0789] From the converted text information, the system extracts the information necessary for registration. Furthermore, the server uses an emotion analysis engine to analyze the tone and speaking speed of the voice information and evaluate the user's emotional state. Based on this analysis, instructions are sent to the terminal to adjust the displayed content based on the user's emotional information.

[0790] As a concrete example, imagine a user asking a consumer robot, "What should we do today?" The robot analyzes the tone of the conversation and detects a feeling of boredom. In this case, the robot provides a user-friendly service by suggesting a new activity that will stimulate the user's interest. An example of a prompt in this scenario would be, "Analyze the emotion from the tone of voice and generate a response that suggests an action appropriate to the mood."

[0791] This system allows terminals and servers to recognize specific emotional states of individual users and provide more personalized information. In this way, the user experience is improved, and the registration process and daily operations become more efficient.

[0792] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0793] Step 1:

[0794] The device acquires the user's voice via a microphone. The input is audio data, which is then converted to a digital format and prepared for transmission to the server. The output is digital audio data.

[0795] Step 2:

[0796] The server receives digital audio data and performs speech recognition using the Google Speech-to-Text API. The input is digital audio data, and speech recognition generates text data. The output is the converted text data.

[0797] Step 3:

[0798] This process extracts the necessary registration information from text data generated by the server. The input is text data, and information analysis is performed to identify and extract the required data fields. The output is the extracted registration information.

[0799] Step 4:

[0800] The server uses an emotion analysis engine to evaluate the user's emotional state based on the tone and speaking speed of the voice data. The input is digital voice data, and the voice features are analyzed to generate emotion data. The output is the user's emotional state data.

[0801] Step 5:

[0802] The server generates instructions to adjust the presented content based on the user's emotional state data. The input consists of emotional state data and extracted registration information, and the server performs data processing to optimize information presentation. The output is adjustment instruction data.

[0803] Step 6:

[0804] The terminal receives adjustment instruction data sent from the server and displays information optimized for the user based on that data. The input is the adjustment instruction data, which provides appropriate information on the user interface. The output is the customized information displayed on the user interface.

[0805] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0806] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0807] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0808] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0809] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0810] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0811] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0812] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0813] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0814] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0815] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0816] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0817] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0818] 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.

[0819] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0820] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0821] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0822] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0823] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0824] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0825] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0826] The following is further disclosed regarding the embodiments described above.

[0827] (Claim 1)

[0828] A means for acquiring the conversation between the user and the processor as audio data,

[0829] A conversion means for converting the aforementioned audio data into text data,

[0830] An extraction means for extracting information necessary for registration from the converted character data,

[0831] A generation means for automatically generating a registration form based on extracted information,

[0832] A presentation means that presents the generated registration form to the user and allows them to confirm its contents,

[0833] A means of completing the registration process after confirming the contents,

[0834] A system that includes this.

[0835] (Claim 2)

[0836] The system according to claim 1, wherein the presentation means provides an interface for a user to input or modify information.

[0837] (Claim 3)

[0838] The system according to claim 1, wherein the completion means presents a list of documents and notes required after registration is complete.

[0839] "Example 1"

[0840] (Claim 1)

[0841] A means of collecting user-processor dialogue as acoustic information,

[0842] Means for converting the aforementioned acoustic information into document information,

[0843] A means of extracting information necessary for a procedure from document information,

[0844] A means for automatically generating a document based on the extracted information,

[0845] A means for displaying the generated document to the user and allowing them to confirm its contents,

[0846] A means of providing an interface that allows users to review and modify content,

[0847] A means to complete the procedure after confirmation,

[0848] A system that includes this.

[0849] (Claim 2)

[0850] The system according to claim 1, which presents a list of required documents and points to note after the completion of the aforementioned procedure.

[0851] (Claim 3)

[0852] The system according to claim 1, wherein when converting the aforementioned acoustic information into document information, it performs noise reduction and speech clarification processing.

[0853] "Application Example 1"

[0854] (Claim 1)

[0855] A means for acquiring the conversation between the user and the processor as audio data,

[0856] A conversion means for converting the aforementioned audio data into text data,

[0857] An extraction means for extracting information necessary for registration from the converted character data,

[0858] A generation means for automatically generating a registration form based on extracted information,

[0859] A presentation means that presents the generated registration form to the user and allows them to confirm its contents,

[0860] A means of completing the registration process after confirming the contents,

[0861] The aforementioned presentation means generates an order form based on product selection in a commercial transaction.

[0862] A system that includes this.

[0863] (Claim 2)

[0864] The system according to claim 1, wherein the presentation means provides an interface for the user to input or modify information and to allow the user to confirm the details of an order relating to a commercial transaction.

[0865] (Claim 3)

[0866] The system according to claim 1, wherein the completion means presents details of the order and related notes after registration is complete.

[0867] "Example 2 of combining an emotion engine"

[0868] (Claim 1)

[0869] A means for acquiring the interaction between the user and the service provider as acoustic information,

[0870] A conversion means for converting the aforementioned acoustic information into textual information,

[0871] An extraction means for extracting information necessary for registration from the converted character information,

[0872] A generation means that automatically generates a registration screen based on the extracted information,

[0873] A presentation means that presents the generated registration screen to the user and allows them to confirm the contents,

[0874] An analytical method for analyzing the user's emotional state from acoustic information,

[0875] An adjustment means for adjusting the display content based on the analyzed emotional information,

[0876] A means of completing the registration process after confirming the contents,

[0877] A system that includes this.

[0878] (Claim 2)

[0879] The system according to claim 1, wherein the presentation means provides an interactive operation screen for the user to input or modify information.

[0880] (Claim 3)

[0881] The system according to claim 1, wherein the completion means presents a list of necessary documents and notes after registration is complete.

[0882] "Application example 2 when combining with an emotional engine"

[0883] (Claim 1)

[0884] A means for acquiring the conversation between the user and the processor as audio information,

[0885] A conversion means for converting the aforementioned audio information into text information,

[0886] An extraction means for extracting information necessary for registration from the converted character information,

[0887] A generation means for automatically generating a registration form based on extracted information,

[0888] A presentation means that presents the generated registration form to the user and allows them to confirm its contents,

[0889] A means of completing the registration process after confirming the contents,

[0890] An emotion analysis method that analyzes the tone and speaking speed of voice information to evaluate the user's emotional state,

[0891] An adjustment mechanism that adjusts the presented content based on the user's emotional information,

[0892] A system that includes this.

[0893] (Claim 2)

[0894] The system according to claim 1, wherein the adjustment means provides additional explanations or guidance when it is determined that the user is in an anxious state.

[0895] (Claim 3)

[0896] The system according to claim 1, wherein the completion means provides information tailored to the user's emotions for the purpose of facilitating the registration procedure. [Explanation of symbols]

[0897] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for acquiring the conversation between the user and the processor as audio data, A conversion means for converting the aforementioned audio data into text data, An extraction means for extracting information necessary for registration from the converted character data, A generation means for automatically generating a registration form based on extracted information, A presentation means that presents the generated registration form to the user and allows them to confirm its contents, A means of completing the registration process after confirming the contents, A system that includes this.

2. The system according to claim 1, wherein the presentation means provides an interface for the user to input or modify information.

3. The system according to claim 1, wherein the completion means presents a list of documents and notes required after registration is complete.

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