system

Abstract

Provide a system. A means for capturing a user's video and audio; means for transmitting user video and audio data to a server in real time; A means for the server to analyze the video data and recognize facial expressions and gestures; means for the server to analyze the voice data and evaluate speaking rate, volume, and tone; A means for the server to generate feedback based on the analysis result and transmit it to the terminal; The system includes a means for a user to receive playback feedback.

Description

[Technical Field]

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

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

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

[0004] In conventional presentation practice methods, third-party feedback is essential for users to evaluate their own speaking style and expressiveness. However, this approach does not provide real-time feedback, making it difficult to make rapid improvements. Furthermore, practicing answering questions is difficult without a third party, which can lead to a decline in the quality of practice. This poses the problem of requiring time and effort for users to improve their presentation skills. [Means for solving the problem]

[0005] The present invention provides a system that supports a user's presentation practice in real time and provides prompt feedback. The system includes a means for capturing a user's video and audio and a means for transmitting the user's video and audio data to a server in real time. The server has a means for analyzing the video data and recognizing facial expressions and gestures, and a means for analyzing the audio data and evaluating speaking rate, volume, and tone. The server also includes a means for generating feedback based on the analysis results and transmitting the feedback to a terminal. The server further has a means for automatically generating questions based on the presentation content and transmitting them to the terminal, and a means for the user to capture and transmit answers to the questions to the server. The server then analyzes the answers and evaluates them for appropriateness and clarity. Finally, the server performs an overall evaluation of the user's presentation and generates a detailed feedback report. The terminal displays the report to the user, and provides a means for saving and sharing the report. This allows the user to identify areas for improvement in real time and quickly acquire high-quality presentation skills.

[0006] "User" refers to a person who uses the system to practice a presentation.

[0007] "Video" refers to visual data captured through a user's camera.

[0008] "Audio" refers to auditory data captured through a user's microphone.

[0009] "Server" refers to a computer on the Internet that receives video and audio data, analyzes it, and generates feedback.

[0010] A "terminal" is a device that is directly operated by a user, such as a personal computer or smartphone.

[0011] "Capturing" refers to taking in and recording data such as video and audio.

[0012] "Real-time" refers to processing occurring almost immediately with little delay.

[0013] "Analyzing" refers to breaking down data and understanding and evaluating its structure and meaning.

[0014] "Facial expression" refers to emotions expressed by the user's facial movements.

[0015] A "gesture" refers to an action that conveys meaning through a user's hand or body movement.

[0016] "Speech rate" refers to the number of words a user speaks within a given period of time.

[0017] "Volume" refers to the loudness of a sound.

[0018] "Tone" refers to the pitch or quality of a voice.

[0019] "Feedback" refers to advice and evaluation provided to the user based on the analysis results.

[0020] "Automatic generation" refers to the process by which a computer automatically creates information based on specific algorithms or rules.

[0021] A "question" refers to a question or problem posed to a user.

[0022] An "answer" refers to a response a user makes to a question.

[0023] "Relevance" refers to the degree to which the answer matches what was asked of it.

[0024] "Clarity" refers to how clear or unambiguous the answer is.

[0025] "Comprehensive evaluation" refers to a multifaceted evaluation of the overall performance of the presentation.

[0026] "Feedback report" refers to a document that summarizes the analysis results and evaluation. [Brief explanation of the drawings]

[0027] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0028] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0029] First, the terms used in the following description will be explained.

[0030] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0031] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0032] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0033] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0034] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0035] [First embodiment]

[0036] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0037] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0038] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0039] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0040] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0041] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0042] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0043] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0044] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0045] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0046] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0047] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0048] The present invention is a system for users to practice presentations, which includes capturing, analyzing, and generating feedback from video and audio data. To use the system of the present invention, the user, the terminal, and the server each play their respective roles.

[0049] Program processing

[0050] 1. Initial Setup:

[0051] When a user logs in to the system, the device requests permission to use the camera and microphone. If the user grants permission, the device activates the camera and microphone and becomes ready.

[0052] For example, a user enters a username and password on a login screen, and the device sends this to the server. The server authenticates the user, and if successful, displays the dashboard.

[0053] 2. Start your presentation:

[0054] When the user clicks the "Start Presentation Practice" button, the device will activate the camera and microphone and begin capturing video and audio.

[0055] The device streams this data to the server in real time.

[0056] 3. Analysis and Evaluation:

[0057] The server analyzes the received video data and recognizes facial expressions and gestures. For example, it analyzes facial and hand movements to infer the user's emotions and intentions.

[0058] The server analyzes the audio data and evaluates the speaking rate, volume, and tone, for example, whether the speaking rate is appropriate and how the tone of the voice is perceived by the listener.

[0059] 4. Feedback generation:

[0060] The server generates feedback based on the analysis results and sends it to the device, displaying real-time feedback such as warnings about speech rate and advice about facial expressions.

[0061] For example, the server generates advice such as "You're speaking too fast. Please speak a little more slowly," and displays this to the user via the terminal.

[0062] 5. Question simulation:

[0063] The server analyzes the content of the user's presentation and automatically generates related questions, which the terminal presents to the user, who then answers them.

[0064] The user's answers are sent to a server, which evaluates them for appropriateness and clarity. For example, a question might be generated: "What is the source of the data on this slide?", and the server analyzes the data captured as the user answers.

[0065] 6. Overall evaluation and detailed report:

[0066] The server evaluates the user's overall presentation and generates a detailed feedback report that the device displays to the user and allows them to save and share the report.

[0067] For example, the server could generate a detailed report as an overall assessment, saying, "The presentation is well-structured, but it does not adequately address questions. Please add specific data and examples," and provide this to the user via the terminal.

[0068] As described above, the system of the present invention provides real-time analysis and feedback through a series of processes to help users improve their presentation skills, allowing them to quickly identify their weaknesses and make effective improvements.

[0069] The processing flow will be explained below.

[0070] Step 1:

[0071] The user enters their username and password at the system login screen.

[0072] The terminal sends the input information to the server.

[0073] The server authenticates the user. If authentication is successful, it displays the dashboard. If authentication fails, it returns an error message.

[0074] Step 2:

[0075] The device asks the user for permission to use the camera and microphone.

[0076] If the user grants permission, the device will activate the camera and microphone and become ready.

[0077] Step 3:

[0078] The user clicks the "Start Practice Presentation" button.

[0079] The device will activate the camera and microphone and begin capturing video and audio.

[0080] Step 4:

[0081] The device streams the captured video and audio data to the server in real time.

[0082] Step 5:

[0083] The server analyzes the video data it receives and recognizes facial expressions and gestures.

[0084] For example, facial movements can be analyzed to identify emotions (such as joy, anger, sadness, and happiness), and hand movements can be used to identify the emphasis of a presentation.

[0085] Step 6:

[0086] The server analyzes the audio data and evaluates speaking rate, volume, and tone.

[0087] For example, it analyzes the speaking rate (words per minute), whether the volume is appropriate, and how emotionally expressive the tone of the voice is.

[0088] Step 7:

[0089] The server generates feedback based on the analysis results and sends it to the device.

[0090] As real-time feedback, advice such as "You're speaking too fast. Please speak a little more slowly" is displayed.

[0091] Step 8:

[0092] The server automatically generates questions based on the presentation content.

[0093] For example, generate questions such as "What is the data source for this slide?"

[0094] The terminal presents the generated question to the user.

[0095] Step 9:

[0096] The user answers the questions.

[0097] The device captures the answers and records them as audio data.

[0098] The device sends the response data to the server in real time.

[0099] Step 10:

[0100] The server analyzes the response data and evaluates it for relevance and clarity.

[0101] For example, generate feedback such as, "The answer is unclear. Let me give you a concrete example."

[0102] Step 11:

[0103] The server evaluates the user's overall presentation and generates a detailed feedback report.

[0104] The device displays the generated report to the user and provides options to save or share it.

[0105] In this way, all processing steps in the system are continuous, providing users with real-time feedback and practice opportunities to improve their presentation skills.

[0106] Example 1

[0107] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0108] Modern presentations are extremely important in business and education, and mastering effective presentation techniques is essential. However, there are limited ways to effectively practice and self-evaluate presentations. In particular, it is difficult to receive objective, real-time feedback, making it difficult to obtain specific advice for self-improvement. Furthermore, while it is important to prepare for and improve the ability to respond to questions and answers about presentation content, there is a lack of systems that support this.

[0109] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0110] In this invention, the server includes means for analyzing a user's video data and recognizing facial expressions and gestures, means for analyzing audio data and evaluating speaking speed, volume, and tone, means for generating feedback based on the analysis results and sending it to the terminal, means for automatically generating questions based on the presentation content, and means for analyzing the question data, conducting a comprehensive evaluation, and generating a detailed report. This allows users to effectively practice presentations and receive specific feedback in real time. It also improves their ability to respond to questions and answers, and allows them to self-evaluate and identify areas for improvement through the detailed feedback report.

[0111] A "user" is a person who uses the system to practice a presentation.

[0112] A "terminal" is a user-operated computing device that captures and displays video and audio.

[0113] A "server" is a remote computer system that analyzes video and audio data and generates and presents results.

[0114] "Video" is visual data captured using a camera to capture the user's facial expressions and gestures.

[0115] "Speech" is auditory data captured using a microphone to record what a user says, the rate, volume, and tone of speech.

[0116] "Capture means" refers to a method or device for recording video and audio using a camera and microphone.

[0117] "Real-time transmission means" refers to communication technologies and protocols for transmitting captured data to a server in real time.

[0118] "Analysis means" refers to technology that processes video and audio data using AI models or other methods to identify and evaluate facial expressions, gestures, speaking rate, volume, and tone.

[0119] "Feedback generator" refers to algorithms and systems that generate specific improvements and advice for users based on the analyzed data.

[0120] "Automatic question generation means" refers to a technology that analyzes the content of a presentation and automatically generates related questions based on that analysis.

[0121] "Summary evaluation tool" refers to the techniques and processes for evaluating the entire presentation and generating a detailed feedback report.

[0122] "Terminal display means" refers to the functions and software of the terminal for displaying feedback and reports sent from the server to the user.

[0123] "Storage and sharing means" refers to methods and techniques for storing the generated detailed report on a terminal and sharing it with other users or systems as needed.

[0124] The present invention is a comprehensive support system for users to practice presentations, which includes capturing video and audio data, analyzing them in real time, generating feedback, simulating questions and answers, and generating a comprehensive evaluation and detailed report. The specific implementation of this system is described below.

[0125] This system involves the user, the terminal, and the server, each playing their respective roles. Before a user can start practicing their presentation, they must first log in to the system. The terminal is equipped with a camera and microphone, which are used to capture the user's video and audio. For example, the hardware used includes a common webcam and microphone.

[0126] When a user logs in, the device requests permission to use the camera and microphone. If the user allows this, the device activates the camera and microphone and becomes ready. When the user clicks the "Start Presentation Practice" button, the device begins capturing video and audio and streams the data to the server in real time.

[0127] The server uses an AI model to analyze the received video and audio data. Specifically, frameworks such as OpenCV and TENSORFLOW® are used for video analysis to recognize facial expressions and gestures. For audio analysis, the server uses the Google® Speech-to-Text API and other tools to evaluate speaking speed, volume, and tone. Based on the analysis results, the server generates real-time feedback and sends specific advice to the device, such as "You're speaking too fast. Please speak a little more slowly."

[0128] The device displays the received feedback to the user in real time, allowing the user to immediately try to improve based on this feedback. The server also analyzes the presentation content and automatically generates related questions. For example, it creates a question such as "What is the source of the data on this slide?" and presents it to the user via the device. When the user responds to the question, the data is captured again and sent to the server. The server analyzes the user's response and evaluates its appropriateness and clarity.

[0129] Once the practice is complete, the server evaluates the entire presentation and generates a detailed feedback report. This report includes evaluations of speaking speed, volume, facial expressions, gestures, and responses to questions. For example, the report may provide specific advice such as, "The presentation is well-structured, but your vocal tone is monotonous, so you need to improve it." The device displays this detailed report to the user, and the user can save and share it.

[0130] Examples of prompts include:

[0131] "To start practicing your presentation, simply log in to the system and grant permission for your camera and microphone. Once you press the "Start Practice Presentation" button, the system will automatically capture your video and audio and provide you with real-time feedback, including warnings about speaking speed and advice on appropriate facial expressions."

[0132] By taking all of these into consideration, the system of the present invention allows users to efficiently improve their presentation skills.

[0133] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0134] Step 1:

[0135] A user logs in to the system.

[0136] The user enters their username and password as input. The device sends this to the server, which then performs authentication. If authentication is successful, the server returns a login success response to the device, and the device displays the dashboard screen. It also displays a pop-up requesting the user's permission to use the camera and microphone.

[0137] Specifically, the terminal sends the authentication information entered by the user to the server, and the server refers to a database to verify the information and return the authentication result.

[0138] Step 2:

[0139] The user begins practicing the presentation.

[0140] As input, the user clicks the "Start Presentation Practice" button on the dashboard screen. The device detects this click event, activates the camera and microphone, and begins capturing video and audio.

[0141] Specifically, the device acquires the camera video stream and microphone audio stream and prepares to send them to the server in real time.

[0142] Step 3:

[0143] The device streams video and audio data to the server in real time.

[0144] As input, the device sends captured video and audio data in real time to a server that receives the data and prepares it for analysis.

[0145] Specifically, the server temporarily stores the received streaming data and formats it for passing to the analysis process.

[0146] Step 4:

[0147] The server analyzes the video data and recognizes facial expressions and gestures.

[0148] The input is video data sent to a server, which analyzes the video data using AI models (e.g., OpenCV or TensorFlow) to recognize facial expressions and hand gestures.

[0149] Specifically, the server applies a facial recognition algorithm to each video frame to detect and classify specific facial expressions (e.g., smile, worried face) and gestures (e.g., hand movements), and stores the analysis results in a database.

[0150] Step 5:

[0151] The server analyzes the audio data and evaluates speaking rate, volume, and tone.

[0152] The input is audio data sent to the server, which uses speech recognition technology (e.g., Google Speech-to-Text API) to convert the audio data into text, and then analyzes the speech rate, volume, tone, etc.

[0153] Specifically, the server analyzes the audio data, calculates the speech rate for each segment, measures the average volume and fluctuations, and performs tone analysis. The analysis results are stored in a database.

[0154] Step 6:

[0155] The server generates feedback based on the analysis results and sends it to the device.

[0156] The server takes as input the analysis results stored in it, runs a feedback generation algorithm on these results, and generates advice for the user (e.g., you speak too fast, try speaking more slowly), and sends the generated feedback to the device.

[0157] Specifically, the server analyzes the analysis results, generates a warning message based on a specific criterion (e.g., when the speech rate exceeds a certain value), and sends it to the terminal as feedback.

[0158] Step 7:

[0159] The device displays real-time feedback to the user.

[0160] As input, the feedback data sent from the server arrives at the terminal, which analyzes this data and displays it to the user in real time.

[0161] Specifically, the device displays the feedback message in a pop-up window or notification bar, allowing the user to immediately check its contents.

[0162] Step 8:

[0163] The server automatically generates questions based on the presentation content and sends them to the terminal.

[0164] As input, the server receives the analyzed presentation content data, and then uses natural language generation technology to automatically generate relevant questions (e.g., "What is the data source for this slide?") and send them to the device.

[0165] Specifically, the server automatically analyzes the presentation content, extracts keywords, and executes an algorithm to generate related questions based on the keywords.

[0166] Step 9:

[0167] The user captures answers to questions and sends them to the server.

[0168] The input is the user's response data (video and audio) to questions displayed on the terminal. When the user responds, the terminal captures the video and audio and sends them to the server.

[0169] Specifically, the terminal captures the user's answers in real time, generates data packets to be sent to the server, and sends them.

[0170] Step 10:

[0171] The server analyzes the answers and rates them for relevance and clarity.

[0172] The input is the user's answer data sent to the server, which uses an AI model to match the content of the answer with the presentation and evaluate it for appropriateness and clarity.

[0173] Specifically, the server converts the response content into text, checks the corresponding keywords and context, and evaluates the consistency and detail of the information.

[0174] Step 11:

[0175] The server provides an overall evaluation of the user's presentation and generates a detailed feedback report.

[0176] As input, it receives all the analysis results, and the server performs an overall evaluation based on these results and generates a detailed feedback report (e.g., the presentation is well-structured, but the voice tone is monotonous and should be improved).

[0177] Specifically, the server collects the results of each analysis step, executes a comprehensive evaluation algorithm, generates a detailed feedback report, and stores it in a database.

[0178] Step 12:

[0179] The device displays the report to the user, who can save and share it.

[0180] As input, there is a detailed feedback report sent by the server, which the device displays to the user and allows the user to save or share it as needed.

[0181] Specifically, the terminal receives the report data, displays the feedback content on a dedicated display screen, and provides save and share buttons.

[0182] (Application example 1)

[0183] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0184] In recent years, the customer service skills of store clerks in brick-and-mortar stores have become an important factor directly linked to customer satisfaction. However, current training methods make it difficult for store clerks to objectively evaluate their own customer service skills and identify specific areas for improvement. To solve this problem, a method is needed to effectively train store clerks and obtain feedback in real time.

[0185] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0186] In this invention, the server includes means for capturing video and audio of the user, means for transmitting the user's video and audio data to the server in real time, means for the server to analyze the video data and recognize facial expressions and gestures, means for the server to analyze the audio data and evaluate speaking speed, volume, and tone, means for the server to generate feedback based on the analysis results and transmit it to the terminal, means for the user to receive the feedback that is played back, and means for the server to automatically generate questions based on the content of the user's customer service and transmit them to the terminal. This enables store clerks to evaluate their own customer service skills in real time and identify specific areas for improvement.

[0187] "User" refers to a store clerk who uses this system to practice customer service.

[0188] "Device" means a smartphone, tablet, or similar device that a User logs in to and uses to capture and transmit video and audio data to a Server in real time.

[0189] "Server" refers to a computer system that analyzes received video and audio data, generates feedback and questions, and sends them to the terminal.

[0190] "Video Data" refers to captured visual information, including a user's facial expressions and gestures.

[0191] "Voice data" refers to captured voice information including the user's speaking rate, volume, and tone.

[0192] "Feedback" refers to advice and evaluations that the server generates based on the analysis results and provides to the user.

[0193] "Question" refers to a question that the server automatically generates based on the content of the customer service provided to the user and presents to the user for confirmation or evaluation.

[0194] "Capture" refers to the process of recording video and audio and transmitting them as data in real time from a device to a server.

[0195] "Analysis" refers to the process by which the server processes the received video and audio data and evaluates the user's facial expressions, gestures, speech rate, volume, and tone.

[0196] "Gestures" refer to the movements of the user's hands and body, and analyzing these movements can be used to infer the user's intentions and emotions.

[0197] A "feedback report" refers to a report in which the server evaluates the user's overall customer service and lists detailed areas for improvement and advice.

[0198] "Storage" refers to the device recording the generated feedback report or analysis results so that the user can refer to them later.

[0199] "Sharing" refers to a user sharing the generated feedback report or analysis results with other users or administrators online.

[0200] This invention is a system for improving the customer service skills of store clerks in brick-and-mortar stores, and includes capturing, analyzing, and generating feedback on video and audio data of users (store clerks). The system for implementing this invention consists of a terminal used by the user and a server that processes data.

[0201] Initial Setup

[0202] A user logs in to a device and gives permission to use the camera and microphone. The device then activates the camera and microphone and begins capturing video and audio data. For example, the user enters a username and password on the login screen, and the device sends this to the server. The server authenticates the user, and if successful, displays a dashboard.

[0203] Start of customer service practice

[0204] When the user clicks the "Start Customer Service Practice" button, the device activates the camera and microphone and starts capturing video and audio. The device streams this data to the server in real time.

[0205] Analysis and Evaluation

[0206] The server analyzes the received video data and recognizes facial expressions and gestures. Specifically, it uses OpenCV and dlib to detect facial landmarks and analyze facial expressions based on these. The server also analyzes audio data and evaluates speech rate, volume, and tone. It uses Librosa to extract audio features and evaluates them using a machine learning model.

[0207] Generate feedback

[0208] The server generates feedback based on the analysis results and sends it to the device. Real-time feedback is displayed to the user, providing advice on speech rate and facial expressions. For example, specific advice such as "You're speaking too fast. Please speak a little more slowly" is provided.

[0209] Question simulation

[0210] The server analyzes the user's customer service and automatically generates relevant questions. The device presents the questions to the user, who answers them. The user's answers are sent to the server, which evaluates their appropriateness and clarity. For example, a question such as "Please tell me about the features of this product" may be generated.

[0211] Overall rating and detailed report

[0212] The server evaluates the user's overall customer service and generates a detailed feedback report. The device displays this report to the user, who can save and share it. For example, the server may generate a detailed report stating, "The customer service attitude was good, but detailed product information was insufficient. Please add specific data and examples."

[0213] Hardware and software used

[0214] The system uses a smartphone or tablet, camera, and microphone as hardware, and Python, OpenCV, dlib, librosa, scikit-learn, and generative AI models as software.

[0215] Examples and prompts

[0216] As a concrete example, by inputting the following prompt sentence into the generative AI model, it is possible to provide specific advice to the user.

[0217] "User speaks too fast. Generate advice to speak more slowly."

[0218] "Infer emotions from the user's facial expressions and generate advice to help them make a good impression while serving customers."

[0219] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0220] Step 1:

[0221] A user logs in to a device and grants permission to use the camera and microphone. Username and password are required as input. The device sends this information to the server, which authenticates the user and displays the dashboard if successful. The output is that the user has successfully logged in.

[0222] Step 2:

[0223] The user clicks the "Start customer service practice" button. The user's click event is required as input. The device activates the camera and microphone and starts capturing video and audio. The output is the captured video and audio data.

[0224] Step 3:

[0225] The device streams captured video and audio data to the server in real time. As input, video and audio data are required. The device transmits these data to the server in real time. The output is the data streamed in real time.

[0226] Step 4:

[0227] The server analyzes the received video data and recognizes facial expressions and gestures. Real-time video data is required as input. The server uses OpenCV and dlib to detect facial landmarks and analyze facial expressions. The output is the recognized facial expression and gesture data.

[0228] Step 5:

[0229] The server analyzes the audio data and evaluates the speaking rate, volume, and tone. Real-time audio data is required as input. The server uses Librosa to extract audio features and evaluates them using a machine learning model. The output is the evaluated speaking rate, volume, and tone data.

[0230] Step 6:

[0231] The server generates feedback based on the analysis results and sends it to the device. The analysis results of facial expressions and voice are required as input. The server generates feedback based on this and sends advice in text format to the device. The output is the text data of the generated feedback.

[0232] Step 7:

[0233] The terminal displays the received feedback to the user. As input, it requires feedback data sent from the server. The terminal displays the data on the screen and provides real-time advice to the user. The output is the feedback displayed to the user.

[0234] Step 8:

[0235] The server automatically generates questions based on the user's customer service and sends them to the terminal. The real-time customer service content is required as input. The server uses a generative AI model to generate appropriate questions. The output is the text data of the generated questions.

[0236] Step 9:

[0237] The terminal displays the presented question to the user, and the user answers. Question data sent from the server is required as input. The terminal displays the question on the screen, and the user answers by typing or speaking. The output is the user's answer data.

[0238] Step 10:

[0239] The user's answer data is sent to the server, which evaluates its appropriateness and clarity. As input, the user's answer data is required. The server evaluates the quality of the answer using an evaluation algorithm. The output is the evaluation result data.

[0240] Step 11:

[0241] The server evaluates the user's overall customer service, generates a detailed feedback report, and sends it to the terminal. All analysis results and evaluation data are required as input. The server performs an integrated evaluation and creates a detailed report. The output is the detailed feedback report data.

[0242] Step 12:

[0243] The terminal displays the report to the user and allows the report to be saved and shared. As input, a detailed feedback report sent from the server is required. The terminal displays the report on the screen and the user can save it or share it with other users or administrators. The output is a feedback report that helps the user improve their customer service skills.

[0244] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0245] The present invention is a system for users to practice presentations, and includes all processes from capturing video and audio data to analyzing and generating feedback. The present invention also incorporates an emotion engine to recognize the user's emotions and provide feedback based on the emotions.

[0246] Program processing

[0247] 1. Initial Setup:

[0248] A user logs in to the system. The device requests permission to use the camera and microphone. If the user grants permission, the device activates the camera and microphone and becomes ready.

[0249] For example, a user enters a username and password on a login screen, and the device sends this to the server. The server authenticates the user, and if successful, displays the dashboard.

[0250] 2. Start your presentation:

[0251] When the user clicks the "Start Presentation Practice" button, the device will activate the camera and microphone and begin capturing video and audio.

[0252] The device streams this data to the server in real time.

[0253] 3. Analysis and Evaluation:

[0254] The server analyzes the received video data and recognizes facial expressions and gestures, analyzing facial movements and hand movements to determine the emphasis of the presentation.

[0255] The server analyzes the audio data and evaluates the speech rate, volume, and tone, including the words per minute, whether the speech rate is appropriate, and how emotional the tone of the voice is.

[0256] 4. How the Emotion Engine Works:

[0257] The server's emotion engine analyzes the video data and recognizes the user's emotions (joy, anger, sadness, happiness, etc.). For example, if there are many smiling faces, it is judged to be a positive emotion, and if there are many tense expressions, it is judged to be a negative emotion.

[0258] 5. Feedback Generation:

[0259] The server generates feedback based on the analysis results and emotion recognition and sends it to the device, displaying real-time feedback such as "You're speaking too fast. Please speak a little more slowly."

[0260] This includes feedback from an emotion engine, which generates advice such as, "You're not smiling enough. Express more emotion."

[0261] 6. Question simulation:

[0262] The server analyzes the content of the user's presentation and automatically generates related questions, which the terminal presents to the user, who then answers them.

[0263] The user's answers are sent to a server, which evaluates them for appropriateness and clarity. For example, a question might be generated: "What is the source of the data on this slide?", and the server analyzes the data captured as the user answers.

[0264] 7. Overall evaluation and detailed report:

[0265] The server evaluates the user's overall presentation and generates a detailed feedback report that the device displays to the user, allowing them to save and share the report.

[0266] The report also includes emotional trends analyzed by the emotion engine, offering advice such as, "You remained nervous throughout the presentation. Try some relaxation techniques."

[0267] As described above, the system of the present invention provides real-time analysis of video and audio data, emotion recognition using an emotion engine, and detailed feedback to improve users' presentation skills, allowing users to instantly improve their performance and acquire effective presentation skills.

[0268] The processing flow will be explained below.

[0269] Step 1:

[0270] The user enters their username and password at the system login screen.

[0271] The terminal sends the input information to the server.

[0272] The server authenticates the user and displays the dashboard if authentication is successful, otherwise it returns an error message.

[0273] Step 2:

[0274] The device asks the user for permission to use the camera and microphone.

[0275] If the user grants permission, the device will activate the camera and microphone and become ready.

[0276] Step 3:

[0277] The user clicks the "Start Practice Presentation" button.

[0278] The device will activate the camera and microphone and begin capturing video and audio.

[0279] Step 4:

[0280] The device streams the captured video and audio data to the server in real time.

[0281] Step 5:

[0282] The server analyzes the video data it receives and recognizes facial expressions and gestures.

[0283] For example, facial movements can be analyzed to identify emotions (e.g., joy, anger, sadness, happiness), and hand movements can be analyzed to identify the emphasis of a presentation.

[0284] Step 6:

[0285] The server analyzes the received voice data and evaluates the speaking rate, volume, and tone.

[0286] Specifically, it analyzes speaking rate (number of words spoken per minute), volume (whether the voice is at an appropriate volume), and tone (how much emotion is expressed).

[0287] Step 7:

[0288] The server's emotion engine analyzes the video data and recognizes the user's emotions.

[0289] For example, frequent smiles are judged as positive emotions, while frequent frowns are judged as negative emotions.

[0290] Step 8:

[0291] The server generates feedback based on the analysis results and emotion recognition and sends it to the device.

[0292] Real-time feedback is displayed, including advice such as "You're speaking too fast. Speak a little more slowly," and emotion-based advice such as "You don't smile enough. Express more emotion."

[0293] Step 9:

[0294] The server automatically generates questions based on the presentation content.

[0295] For example, generate a question like, "What is the data source for this slide?"

[0296] The terminal presents the generated question to the user.

[0297] Step 10:

[0298] The user answers the questions.

[0299] The device captures the answers and records them as audio data.

[0300] The device sends the response data to the server in real time.

[0301] Step 11:

[0302] The server analyzes the response data and evaluates it for relevance and clarity.

[0303] For example, generate feedback such as, "The answer is unclear. Let me give you a concrete example."

[0304] Step 12:

[0305] The server evaluates the user's overall presentation and generates a detailed feedback report.

[0306] The device displays the generated report to the user and provides options to save or share it.

[0307] The report also includes emotional trends analyzed by the emotion engine, offering advice such as, "You remained nervous throughout the presentation. Try some relaxation techniques."

[0308] In this way, all processing steps in the system are performed continuously, allowing users to receive real-time feedback to improve their presentation skills and effectively practice.

[0309] Example 2

[0310] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0311] Conventional presentation practice systems are limited to basic capture and feedback functions for the user's video and audio, and lack the ability to recognize emotions or provide detailed feedback based on those emotions. As a result, users often feel limited in their ability to improve their emotional expression and presentation skills. Furthermore, the lack of question simulation and detailed reporting functions results in insufficient evaluation of the overall presentation. To address these issues, a system with emotion recognition and detailed feedback functions is needed.

[0312] The specification processing by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for capturing the user's video and audio, means for transmitting the user's video and audio data in real time, means for analyzing the video data to recognize facial expressions and gestures, means for analyzing the audio data to evaluate speaking speed, volume, and tone, means for recognizing the user's emotions using an emotion engine, and means for generating and transmitting feedback based on the analysis results and emotion recognition in real time. This allows the user to receive real-time feedback during the presentation practice process and instantly improve their performance and emotional expression. In addition, the question simulation and detailed report function allow the user to evaluate the entire presentation, allowing the user to identify more specific areas for improvement.

[0313] "Capture" refers to the process of capturing video or audio data.

[0314] "Real-time transmission" refers to the process of transmitting captured data immediately without delay.

[0315] "Analysis" refers to the process of extracting information from acquired data using specific algorithms.

[0316] "Facial expression recognition" refers to the process of identifying a user's facial expression from video data.

[0317] "Gesture recognition" refers to the process of identifying a user's hand and body movements from video data.

[0318] "Speech rate" refers to the number of words a user speaks within a given period of time.

[0319] "Volume" refers to the volume of the user's speech.

[0320] "Tone" refers to the pitch and quality of the user's voice.

[0321] "Emotion engine" refers to technology that identifies a user's emotions from video or audio data.

[0322] "Feedback" refers to evaluations and advice provided to users based on the analysis results.

[0323] "Automatic question generation" refers to the automatic creation of related questions based on the content of the presentation.

[0324] "Appropriateness" refers to the degree to which the user's answer matches the content and intent of the presentation.

[0325] "Clarity" refers to the degree to which the user's response is clear and easy to understand.

[0326] A "detailed feedback report" refers to a report that includes evaluations and sentiment analysis results for the entire presentation.

[0327] MODE FOR CARRYING OUT THE INVENTION

[0328] The present invention is a system that allows users to effectively practice presentations and includes all processes from capturing video and audio data to analyzing it and generating feedback. Furthermore, by incorporating an emotion engine, this system has the advantage of being able to recognize the user's emotions and provide feedback based on those emotions. Specific embodiments for implementing the present invention are described below.

[0329] System Configuration

[0330] This system consists of a user's device (personal computer, smartphone, tablet, etc.) and a server. The device is equipped with a camera and microphone, which are used to capture video and audio data. The server analyzes the data received in real time and generates feedback. Specific examples of hardware and software include:

[0331] Camera: A device used to capture a user's image (e.g., a webcam, a smartphone's built-in camera)

[0332] Microphone: A device used to capture the user's voice (e.g., a headset, a smartphone's built-in microphone)

[0333] Terminal: A device that captures video and audio data and transmits it to a server (e.g., a personal computer, smartphone, or tablet).

[0334] Server: Computing resources (e.g., cloud servers) for analyzing data and generating feedback

[0335] Emotion engine: Software for recognizing user emotions (e.g., Microsoft® Azure® Emotion API)

[0336] Speech analysis software: a program for analyzing voice data (e.g., Google Speech-to-Text API)

[0337] Video analysis software: A program for analyzing video data (e.g., OpenCV)

[0338] Processing Flow

[0339] The system process flow involves the following steps:

[0340] 1. Initial Setup:

[0341] The user logs in to the system and the device asks for permission to use the camera and microphone. If the user grants permission, the device activates the camera and microphone and becomes ready.

[0342] 2. Start your presentation:

[0343] When a user clicks the "Start Presentation Practice" button, the device activates the camera and microphone and starts capturing video and audio. The device streams this data to the server in real time.

[0344] 3. Data Analysis:

[0345] The server analyzes the received video data in real time and recognizes facial expressions and gestures. For example, facial recognition and gesture recognition are performed using OpenCV.

[0346] At the same time, the audio data is analyzed to evaluate speaking rate, volume, and tone, using the Google Speech-to-Text API.

[0347] 4. Emotion recognition:

[0348] The server's emotion engine analyzes the user's emotions, using Microsoft Azure Emotion API and other tools to recognize emotions such as joy, anger, sadness, and happiness in real time.

[0349] 5. Feedback Generation:

[0350] The server generates feedback based on the analysis results and emotion recognition and sends it to the device, providing real-time feedback on how to adjust speech rate and volume, as well as advice on improving gestures and facial expressions.

[0351] 6. Question simulation:

[0352] The server analyzes the content of the user's presentation and automatically generates related questions, such as "What is the source of the data on this slide?", and presents them to the user via their device.

[0353] 7. Overall evaluation and detailed report:

[0354] The server evaluates the user's overall presentation and generates a detailed feedback report, including information on the overall presentation structure, speaking rate, volume, emotional trends, and appropriateness of gestures. The report is then displayed to the user on the device, and can be saved or shared.

[0355] Examples of prompts:

[0356] What is the topic of your presentation?

[0357] Please briefly explain the contents of this slide.

[0358] "What is the data source for the slides?"

[0359] "What questions do you anticipate?"

[0360] "What are the most important points of your presentation?"

[0361] This system allows users to receive real-time feedback during their presentation practice, enabling them to instantly improve their skills and emotional expression. Detailed feedback reports also provide an overall evaluation of the presentation and specific areas for improvement. As a result, users can acquire effective presentation skills.

[0362] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0363] Processing steps and specific operations

[0364] Step 1: Initial Setup

[0365] A user logs in to the system.

[0366] Input: Username and Password

[0367] Output: Authentication result (success or failure)

[0368] How it works: The user enters their username and password on the login screen. The device sends this information to the server, which checks it against a database (e.g., MySQL®) and performs authentication. If authentication is successful, the dashboard is displayed. Next, a pop-up appears requesting permission to use the camera and microphone; if the user grants permission, the camera and microphone are turned on.

[0369] Step 2: Start your presentation

[0370] The user clicks the "Start Practice Presentation" button.

[0371] Input: User click action

[0372] Output: Start capturing video and audio

[0373] How it works: When the user clicks the button, the device reactivates the camera and microphone and begins capturing video and audio. The captured data is streamed to the server in real time.

[0374] Step 3: Analyze and evaluate video and audio data

[0375] The server analyzes the received video data.

[0376] Input: Video data

[0377] Output: Facial expression and gesture recognition results

[0378] How it works: The server uses a facial recognition algorithm (e.g., OpenCV) to analyze the user's facial expressions and gestures, identifying facial and hand movements and determining the emphasis of the presentation.

[0379] The server analyzes the audio data.

[0380] Input: Audio data

[0381] Output: Speech rate, volume, and tone evaluation results

[0382] How it works: The server uses speech analysis software (e.g., the Google Speech-to-Text API) to analyze the audio data and evaluate the speech rate, volume, and tone. It determines the speech rate (words per minute), whether the volume is appropriate, and how emotional the tone is.

[0383] Step 4: Emotion Engine in Action

[0384] The server's emotion engine analyzes the video data.

[0385] Input: Video data

[0386] Output: User emotion recognition results

[0387] How it works: Using the server's emotion engine (for example, Microsoft Azure Emotion API), the system recognizes and evaluates the user's emotions (joy, anger, sadness, happiness, etc.) from video data. For example, if there are many smiling faces, it is judged to have positive emotions, and if there are many tense expressions, it is judged to have negative emotions.

[0388] Step 5: Generate feedback

[0389] The server generates feedback based on the analysis results and emotion recognition.

[0390] Input: Video and audio analysis results and emotion recognition results

[0391] Output: Feedback message

[0392] How it works: Based on the analysis results and emotion recognition, the server generates real-time feedback to the user, providing specific advice such as "You're speaking too fast. Please speak a little more slowly."

[0393] Step 6: Simulate the Question

[0394] The server automatically generates questions based on the presentation content.

[0395] Input: Presentation content data

[0396] Output: Question list

[0397] How it works: The server analyzes the presentation content and automatically generates relevant questions. These questions are then presented to the user via their device, with specific questions such as "What is the source of the data on this slide?"

[0398] Step 7: Capture and evaluate responses

[0399] The user answers the question.

[0400] Input: User's answer (video and audio)

[0401] Output: Response data

[0402] How it works: The user answers questions. The answers are captured by the device and sent to the server, which analyzes the data and evaluates the appropriateness and clarity of the answers.

[0403] Step 8: Overall evaluation and detailed report

[0404] The server gives an overall evaluation of the user's presentation.

[0405] Input: All analysis results and feedback data

[0406] Output: Detailed feedback report

[0407] How it works: The server evaluates the user's overall presentation and generates a detailed feedback report that includes information on the presentation's structure, speaking rate, volume, emotional trends, and appropriateness of gestures. The report is displayed to the user via their device. The user can save and share the report.

[0408] (Application example 2)

[0409] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0410] In today's virtual stores, it is difficult for salespeople to practice their customer service skills efficiently and effectively. In particular, there is a need for a method to improve their ability to respond to specific questions while receiving real-time feedback. Furthermore, there is a lack of methods to recognize emotions during customer service and provide advice based on those emotions.

[0411] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for capturing video and audio of the user, means for transmitting the video and audio to the server, means for analyzing the video data to recognize facial expressions and movements, means for analyzing the audio data to evaluate speaking speed, volume, and tone of voice, means for generating feedback based on the analysis results and transmitting the feedback to the terminal, and means for a salesperson to pose simulated questions as a virtual customer and capture and evaluate the answers. This enables salespeople to efficiently and effectively improve their customer service skills and improve their ability to respond to specific questions while receiving real-time feedback.

[0412] "User" refers to the person or role that operates the system and provides video and audio data.

[0413] "Video and audio capture means" refers to a combination of hardware and software for obtaining video and audio data of a user.

[0414] "Means for transmitting to the server in real time" refers to a communication means for transferring the acquired video and audio data to the server immediately without delay.

[0415] "Server" refers to a central processing unit for performing the process of data analysis and feedback generation.

[0416] "Means for recognizing facial expressions and movements" refers to algorithms or software that analyze video data to recognize the user's facial expressions and body movements.

[0417] "Means for assessing speaking rate, volume, and tone of voice" refers to algorithms or software that analyzes audio data and assesses speaking rate, volume, and tone of voice.

[0418] "Means for generating and transmitting feedback based on the analysis results to the terminal" refers to a system for generating feedback based on data analysis and transmitting it to the user's device.

[0419] "Salesperson" refers to the person or role that serves customers in a virtual store.

[0420] The "means for presenting simulated questions to a virtual customer and capturing and evaluating the responses" is a means for automatically generating questions that a virtual customer might ask, obtaining the user's responses to those questions, and evaluating their appropriateness and clarity.

[0421] The present invention is a system for improving the customer service skills of salespeople in a virtual store. The system of the present invention captures video and audio data of users (salespeople) and transmits them to a server in real time to analyze the salespeople's customer service performance and provide feedback.

[0422] Hardware and software used

[0423] 1. Hardware

[0424] Camera: Used to capture video of the user.

[0425] Microphone: Used to capture the user's voice.

[0426] Smartphones and head-mounted displays (HMDs): Used as the user's devices to display feedback, etc.

[0427] 2. Software

[0428] Emotion engine: Analyzes the user's video data, recognizes and evaluates facial expressions and movements.

[0429] Voice Analysis Module: Analyzes the user's voice data and evaluates speaking rate, volume, and tone of voice.

[0430] Feedback generation module: Generates feedback based on the analysis results and sends it to the device.

[0431] Question generation module: simulates questions from virtual customers and presents them to the user.

[0432] Evaluation module: Evaluates user responses and analyzes their appropriateness and clarity.

[0433] How it works

[0434] 1. User Preparation

[0435] The system is ready when the user logs in to the system and gives permission to use the camera and microphone. Specifically, the user enters their username and password on the terminal, and the system performs authentication.

[0436] 2. Start customer service practice

[0437] When the user presses the "Start customer service practice" button, the camera and microphone are activated and video and audio capture begins. The data is sent to the server in real time.

[0438] 3. Data Analysis

[0439] The server analyzes the received video data and recognizes facial expressions and movements. The emotion engine analyzes the user's emotions and identifies feelings such as tension or joy.

[0440] The server analyzes the audio data and evaluates speaking rate, volume, and tone of voice, which is done by the audio analysis module.

[0441] 4. Feedback Generation

[0442] Based on the analysis results, the feedback generation module generates appropriate feedback, which is sent to the terminal and displayed to the user in real time.

[0443] 5. Question Simulation

[0444] The question generation module automatically generates questions based on the customer service content and displays them on the terminal. The user captures the answers and sends them to the server.

[0445] 6. Overall evaluation and report

[0446] The server evaluates the user's overall customer service and generates a detailed feedback report, which is displayed on the device and can be saved or shared.

[0447] Specific examples

[0448] As a specific example, this system can be used in souvenir shops at tourist spots or virtual stores of home appliances to help sales staff improve their specific customer service skills.

[0449] Prompt Sentence Examples

[0450] We are developing an application for virtual store salespeople to practice customer service. The system uses a camera and microphone to capture video and audio, and analyzes and provides feedback on the salespeople's customer service skills and emotions in real time. Please explain how this system works.

[0451] The system of the present invention helps salespeople efficiently and effectively improve their customer service skills, improving their ability to respond to specific questions while receiving real-time feedback.

[0452] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0453] Step 1: Initial Setup

[0454] A user logs in to the system and gives permission to use the camera and microphone. This causes the device to activate the camera and microphone and enter a ready state. The input data is the user's login information, and the output is the camera and microphone activation readiness.

[0455] Step 2: Start practicing customer service

[0456] When the user presses the "Start customer service practice" button, the device activates the camera and microphone and begins capturing video and audio. The captured data is sent to the server in real time. The input data is the user's operation, and the output is streaming video and audio data.

[0457] Step 3: Analyzing the video data

[0458] The server analyzes the received video data and recognizes facial expressions and movements. Specifically, it analyzes facial movements and hand gestures. The input data is video frames, and the output is the recognition results of facial expressions and movements. An emotion engine is used to identify emotions.

[0459] Step 4: Analyzing the audio data

[0460] The server analyzes the received audio data and evaluates the speaking rate, volume, and tone of voice. Specifically, it analyzes the speaking rate, volume, and tone of voice. The input data is an audio stream, and the output is the evaluation results of the speaking rate, volume, and tone of voice.

[0461] Step 5: Generate feedback

[0462] The server generates feedback based on the analysis of the video and audio data and sends it to the device. For example, it may include specific advice such as "You're speaking too fast. Speak a little more slowly" or "You don't smile enough. Express more emotion." The input data is the analysis results, and the output is the feedback message.

[0463] Step 6: Simulate the Question

[0464] The server automatically generates questions for virtual customers based on the customer service content and sends them to the terminal. The user provides answers to the questions, and the answers are captured by the server. The input data is the customer service content, and the output is the generated questions and their answers.

[0465] Step 7: Evaluate your responses

[0466] The server analyzes the user's answers and evaluates them for appropriateness and clarity. For example, it determines whether the answer to the question "What is the data source for this slide?" is appropriate. The input data is the user's answers, and the output is the evaluation result.

[0467] Step 8: Overall evaluation and report generation

[0468] The server evaluates the entire customer service and generates a detailed feedback report. The report includes good points and areas for improvement during the customer service, as well as emotional trends analyzed by the emotion engine. This report is displayed on the terminal and can be saved and shared by the user. The input data are all analysis results, and the output is a feedback report.

[0469] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0470] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0471] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0472] [Second embodiment]

[0473] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0474] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0475] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0476] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0477] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0478] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0479] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0480] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0481] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0482] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0483] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0484] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0485] The present invention is a system for users to practice presentations, which includes capturing, analyzing, and generating feedback from video and audio data. To use the system of the present invention, the user, the terminal, and the server each play their respective roles.

[0486] Program processing

[0487] 1. Initial Setup:

[0488] When a user logs in to the system, the device requests permission to use the camera and microphone. If the user grants permission, the device activates the camera and microphone and becomes ready.

[0489] For example, a user enters a username and password on a login screen, and the device sends this to the server. The server authenticates the user, and if successful, displays the dashboard.

[0490] 2. Start your presentation:

[0491] When the user clicks the "Start Presentation Practice" button, the device will activate the camera and microphone and begin capturing video and audio.

[0492] The device streams this data to the server in real time.

[0493] 3. Analysis and Evaluation:

[0494] The server analyzes the received video data and recognizes facial expressions and gestures. For example, it analyzes facial and hand movements to infer the user's emotions and intentions.

[0495] The server analyzes the audio data and evaluates the speaking rate, volume, and tone, for example, whether the speaking rate is appropriate and how the tone of the voice is perceived by the listener.

[0496] 4. Feedback generation:

[0497] The server generates feedback based on the analysis results and sends it to the device, displaying real-time feedback such as warnings about speech rate and advice about facial expressions.

[0498] For example, the server generates advice such as "You're speaking too fast. Please speak a little more slowly," and displays this to the user via the terminal.

[0499] 5. Question simulation:

[0500] The server analyzes the content of the user's presentation and automatically generates related questions, which the terminal presents to the user, who then answers them.

[0501] The user's answers are sent to a server, which evaluates them for appropriateness and clarity. For example, a question might be generated: "What is the source of the data on this slide?", and the server analyzes the data captured as the user answers.

[0502] 6. Overall evaluation and detailed report:

[0503] The server evaluates the user's overall presentation and generates a detailed feedback report that the device displays to the user and allows them to save and share the report.

[0504] For example, the server could generate a detailed report as an overall assessment, saying, "The presentation is well-structured, but it does not adequately address questions. Please add specific data and examples," and provide this to the user via the terminal.

[0505] As described above, the system of the present invention provides real-time analysis and feedback through a series of processes to help users improve their presentation skills, allowing them to quickly identify their weaknesses and make effective improvements.

[0506] The processing flow will be explained below.

[0507] Step 1:

[0508] The user enters their username and password at the system login screen.

[0509] The terminal sends the input information to the server.

[0510] The server authenticates the user. If authentication is successful, it displays the dashboard. If authentication fails, it returns an error message.

[0511] Step 2:

[0512] The device asks the user for permission to use the camera and microphone.

[0513] If the user grants permission, the device will activate the camera and microphone and become ready.

[0514] Step 3:

[0515] The user clicks the "Start Practice Presentation" button.

[0516] The device will activate the camera and microphone and begin capturing video and audio.

[0517] Step 4:

[0518] The device streams the captured video and audio data to the server in real time.

[0519] Step 5:

[0520] The server analyzes the video data it receives and recognizes facial expressions and gestures.

[0521] For example, facial movements can be analyzed to identify emotions (such as joy, anger, sadness, and happiness), and hand movements can be used to identify the emphasis of a presentation.

[0522] Step 6:

[0523] The server analyzes the audio data and evaluates speaking rate, volume, and tone.

[0524] For example, it analyzes the speaking rate (words per minute), whether the volume is appropriate, and how emotionally expressive the tone of the voice is.

[0525] Step 7:

[0526] The server generates feedback based on the analysis results and sends it to the device.

[0527] As real-time feedback, advice such as "You're speaking too fast. Please speak a little more slowly" is displayed.

[0528] Step 8:

[0529] The server automatically generates questions based on the presentation content.

[0530] For example, generate questions such as "What is the data source for this slide?"

[0531] The terminal presents the generated question to the user.

[0532] Step 9:

[0533] The user answers the questions.

[0534] The device captures the answers and records them as audio data.

[0535] The device sends the response data to the server in real time.

[0536] Step 10:

[0537] The server analyzes the response data and evaluates it for relevance and clarity.

[0538] For example, generate feedback such as, "The answer is unclear. Let me give you a concrete example."

[0539] Step 11:

[0540] The server evaluates the user's overall presentation and generates a detailed feedback report.

[0541] The device displays the generated report to the user and provides options to save or share it.

[0542] In this way, all processing steps in the system are continuous, providing users with real-time feedback and practice opportunities to improve their presentation skills.

[0543] Example 1

[0544] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0545] Modern presentations are extremely important in business and education, and mastering effective presentation techniques is essential. However, there are limited ways to effectively practice and self-evaluate presentations. In particular, it is difficult to receive objective, real-time feedback, making it difficult to obtain specific advice for self-improvement. Furthermore, while it is important to prepare for and improve the ability to respond to questions and answers about presentation content, there is a lack of systems that support this.

[0546] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0547] In this invention, the server includes means for analyzing a user's video data and recognizing facial expressions and gestures, means for analyzing audio data and evaluating speaking speed, volume, and tone, means for generating feedback based on the analysis results and sending it to the terminal, means for automatically generating questions based on the presentation content, and means for analyzing the question data, conducting a comprehensive evaluation, and generating a detailed report. This allows users to effectively practice presentations and receive specific feedback in real time. It also improves their ability to respond to questions and answers, and allows them to self-evaluate and identify areas for improvement through the detailed feedback report.

[0548] A "user" is a person who uses the system to practice a presentation.

[0549] A "terminal" is a user-operated computing device that captures and displays video and audio.

[0550] A "server" is a remote computer system that analyzes video and audio data and generates and presents results.

[0551] "Video" is visual data captured using a camera to capture the user's facial expressions and gestures.

[0552] "Speech" is auditory data captured using a microphone to record what a user says, the rate, volume, and tone of speech.

[0553] "Capture means" refers to a method or device for recording video and audio using a camera and microphone.

[0554] "Real-time transmission means" refers to communication technologies and protocols for transmitting captured data to a server in real time.

[0555] "Analysis means" refers to technology that processes video and audio data using AI models or other methods to identify and evaluate facial expressions, gestures, speaking rate, volume, and tone.

[0556] "Feedback generator" refers to algorithms and systems that generate specific improvements and advice for users based on the analyzed data.

[0557] "Automatic question generation means" refers to a technology that analyzes the content of a presentation and automatically generates related questions based on that analysis.

[0558] "Summary evaluation tool" refers to the techniques and processes for evaluating the entire presentation and generating a detailed feedback report.

[0559] "Terminal display means" refers to the functions and software of the terminal for displaying feedback and reports sent from the server to the user.

[0560] "Storage and sharing means" refers to methods and techniques for storing the generated detailed report on a terminal and sharing it with other users or systems as needed.

[0561] The present invention is a comprehensive support system for users to practice presentations, which includes capturing video and audio data, analyzing them in real time, generating feedback, simulating questions and answers, and generating a comprehensive evaluation and detailed report. The specific implementation of this system is described below.

[0562] This system involves the user, the terminal, and the server, each playing their respective roles. Before a user can start practicing their presentation, they must first log in to the system. The terminal is equipped with a camera and microphone, which are used to capture the user's video and audio. For example, the hardware used includes a common webcam and microphone.

[0563] When a user logs in, the device requests permission to use the camera and microphone. If the user allows this, the device activates the camera and microphone and becomes ready. When the user clicks the "Start Presentation Practice" button, the device begins capturing video and audio and streams the data to the server in real time.

[0564] The server uses AI models to analyze the received video and audio data. Specifically, frameworks such as OpenCV and TensorFlow are used for video analysis to recognize facial expressions and gestures. The audio analysis uses the Google Speech-to-Text API and other tools to evaluate speaking speed, volume, and tone. Based on the analysis results, the server generates real-time feedback and sends specific advice to the device, such as "You're speaking too fast. Please speak a little more slowly."

[0565] The device displays the received feedback to the user in real time, allowing the user to immediately try to improve based on this feedback. The server also analyzes the presentation content and automatically generates related questions. For example, it creates a question such as "What is the source of the data on this slide?" and presents it to the user via the device. When the user responds to the question, the data is captured again and sent to the server. The server analyzes the user's response and evaluates its appropriateness and clarity.

[0566] Once the practice is complete, the server evaluates the entire presentation and generates a detailed feedback report. This report includes evaluations of speaking speed, volume, facial expressions, gestures, and responses to questions. For example, the report may provide specific advice such as, "The presentation is well-structured, but your vocal tone is monotonous, so you need to improve it." The device displays this detailed report to the user, and the user can save and share it.

[0567] Examples of prompts include:

[0568] "To start practicing your presentation, simply log in to the system and grant permission for your camera and microphone. Once you press the "Start Practice Presentation" button, the system will automatically capture your video and audio and provide you with real-time feedback, including warnings about speaking speed and advice on appropriate facial expressions."

[0569] By taking all of these into consideration, the system of the present invention allows users to efficiently improve their presentation skills.

[0570] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0571] Step 1:

[0572] A user logs in to the system.

[0573] The user enters their username and password as input. The device sends this to the server, which then performs authentication. If authentication is successful, the server returns a login success response to the device, and the device displays the dashboard screen. It also displays a pop-up requesting the user's permission to use the camera and microphone.

[0574] Specifically, the terminal sends the authentication information entered by the user to the server, and the server refers to a database to verify the information and return the authentication result.

[0575] Step 2:

[0576] The user begins practicing the presentation.

[0577] As input, the user clicks the "Start Presentation Practice" button on the dashboard screen. The device detects this click event, activates the camera and microphone, and begins capturing video and audio.

[0578] Specifically, the device acquires the camera video stream and microphone audio stream and prepares to send them to the server in real time.

[0579] Step 3:

[0580] The device streams video and audio data to the server in real time.

[0581] As input, the device sends captured video and audio data in real time to a server that receives the data and prepares it for analysis.

[0582] Specifically, the server temporarily stores the received streaming data and formats it for passing to the analysis process.

[0583] Step 4:

[0584] The server analyzes the video data and recognizes facial expressions and gestures.

[0585] The input is video data sent to a server, which analyzes the video data using AI models (e.g., OpenCV or TensorFlow) to recognize facial expressions and hand gestures.

[0586] Specifically, the server applies a facial recognition algorithm to each video frame to detect and classify specific facial expressions (e.g., smile, worried face) and gestures (e.g., hand movements), and stores the analysis results in a database.

[0587] Step 5:

[0588] The server analyzes the audio data and evaluates speaking rate, volume, and tone.

[0589] The input is audio data sent to the server, which uses speech recognition technology (e.g., Google Speech-to-Text API) to convert the audio data into text, and then analyzes the speech rate, volume, tone, etc.

[0590] Specifically, the server analyzes the audio data, calculates the speech rate for each segment, measures the average volume and fluctuations, and performs tone analysis. The analysis results are stored in a database.

[0591] Step 6:

[0592] The server generates feedback based on the analysis results and sends it to the device.

[0593] The server takes as input the analysis results stored in it, runs a feedback generation algorithm on these results, and generates advice for the user (e.g., you speak too fast, try speaking more slowly), and sends the generated feedback to the device.

[0594] Specifically, the server analyzes the analysis results, generates a warning message based on a specific criterion (e.g., when the speech rate exceeds a certain value), and sends it to the terminal as feedback.

[0595] Step 7:

[0596] The device displays real-time feedback to the user.

[0597] As input, the feedback data sent from the server arrives at the terminal, which analyzes this data and displays it to the user in real time.

[0598] Specifically, the device displays the feedback message in a pop-up window or notification bar, allowing the user to immediately check its contents.

[0599] Step 8:

[0600] The server automatically generates questions based on the presentation content and sends them to the terminal.

[0601] As input, the server receives the analyzed presentation content data, and then uses natural language generation technology to automatically generate relevant questions (e.g., "What is the data source for this slide?") and send them to the device.

[0602] Specifically, the server automatically analyzes the presentation content, extracts keywords, and executes an algorithm to generate related questions based on the keywords.

[0603] Step 9:

[0604] The user captures answers to questions and sends them to the server.

[0605] The input is the user's response data (video and audio) to questions displayed on the terminal. When the user responds, the terminal captures the video and audio and sends them to the server.

[0606] Specifically, the terminal captures the user's answers in real time, generates data packets to be sent to the server, and sends them.

[0607] Step 10:

[0608] The server analyzes the answers and rates them for relevance and clarity.

[0609] The input is the user's answer data sent to the server, which uses an AI model to match the content of the answer with the presentation and evaluate it for appropriateness and clarity.

[0610] Specifically, the server converts the response content into text, checks the corresponding keywords and context, and evaluates the consistency and detail of the information.

[0611] Step 11:

[0612] The server provides an overall evaluation of the user's presentation and generates a detailed feedback report.

[0613] As input, it receives all the analysis results, and the server performs an overall evaluation based on these results and generates a detailed feedback report (e.g., the presentation is well-structured, but the voice tone is monotonous and should be improved).

[0614] Specifically, the server collects the results of each analysis step, executes a comprehensive evaluation algorithm, generates a detailed feedback report, and stores it in a database.

[0615] Step 12:

[0616] The device displays the report to the user, who can save and share it.

[0617] As input, there is a detailed feedback report sent by the server, which the device displays to the user and allows the user to save or share it as needed.

[0618] Specifically, the terminal receives the report data, displays the feedback content on a dedicated display screen, and provides save and share buttons.

[0619] (Application example 1)

[0620] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0621] In recent years, the customer service skills of store clerks in brick-and-mortar stores have become an important factor directly linked to customer satisfaction. However, current training methods make it difficult for store clerks to objectively evaluate their own customer service skills and identify specific areas for improvement. To solve this problem, a method is needed to effectively train store clerks and obtain feedback in real time.

[0622] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0623] In this invention, the server includes means for capturing video and audio of the user, means for transmitting the user's video and audio data to the server in real time, means for the server to analyze the video data and recognize facial expressions and gestures, means for the server to analyze the audio data and evaluate speaking speed, volume, and tone, means for the server to generate feedback based on the analysis results and transmit it to the terminal, means for the user to receive the feedback that is played back, and means for the server to automatically generate questions based on the content of the user's customer service and transmit them to the terminal. This enables store clerks to evaluate their own customer service skills in real time and identify specific areas for improvement.

[0624] "User" refers to a store clerk who uses this system to practice customer service.

[0625] "Device" means a smartphone, tablet, or similar device that a User logs in to and uses to capture and transmit video and audio data to a Server in real time.

[0626] "Server" refers to a computer system that analyzes received video and audio data, generates feedback and questions, and sends them to the terminal.

[0627] "Video Data" refers to captured visual information, including a user's facial expressions and gestures.

[0628] "Voice data" refers to captured voice information including the user's speaking rate, volume, and tone.

[0629] "Feedback" refers to advice and evaluations that the server generates based on the analysis results and provides to the user.

[0630] "Question" refers to a question that the server automatically generates based on the content of the customer service provided to the user and presents to the user for confirmation or evaluation.

[0631] "Capture" refers to the process of recording video and audio and transmitting them as data in real time from a device to a server.

[0632] "Analysis" refers to the process by which the server processes the received video and audio data and evaluates the user's facial expressions, gestures, speech rate, volume, and tone.

[0633] "Gestures" refer to the movements of the user's hands and body, and analyzing these movements can be used to infer the user's intentions and emotions.

[0634] A "feedback report" refers to a report in which the server evaluates the user's overall customer service and lists detailed areas for improvement and advice.

[0635] "Storage" refers to the device recording the generated feedback report or analysis results so that the user can refer to them later.

[0636] "Sharing" refers to a user sharing the generated feedback report or analysis results with other users or administrators online.

[0637] This invention is a system for improving the customer service skills of store clerks in brick-and-mortar stores, and includes capturing, analyzing, and generating feedback on video and audio data of users (store clerks). The system for implementing this invention consists of a terminal used by the user and a server that processes data.

[0638] Initial Setup

[0639] A user logs in to a device and gives permission to use the camera and microphone. The device then activates the camera and microphone and begins capturing video and audio data. For example, the user enters a username and password on the login screen, and the device sends this to the server. The server authenticates the user, and if successful, displays a dashboard.

[0640] Start of customer service practice

[0641] When the user clicks the "Start Customer Service Practice" button, the device activates the camera and microphone and starts capturing video and audio. The device streams this data to the server in real time.

[0642] Analysis and Evaluation

[0643] The server analyzes the received video data and recognizes facial expressions and gestures. Specifically, it uses OpenCV and dlib to detect facial landmarks and analyze facial expressions based on these. The server also analyzes audio data and evaluates speech rate, volume, and tone. It uses Librosa to extract audio features and evaluates them using a machine learning model.

[0644] Generate feedback

[0645] The server generates feedback based on the analysis results and sends it to the device. Real-time feedback is displayed to the user, providing advice on speech rate and facial expressions. For example, specific advice such as "You're speaking too fast. Please speak a little more slowly" is provided.

[0646] Question simulation

[0647] The server analyzes the user's customer service and automatically generates relevant questions. The device presents the questions to the user, who answers them. The user's answers are sent to the server, which evaluates their appropriateness and clarity. For example, a question such as "Please tell me about the features of this product" may be generated.

[0648] Overall rating and detailed report

[0649] The server evaluates the user's overall customer service and generates a detailed feedback report. The device displays this report to the user, who can save and share it. For example, the server may generate a detailed report stating, "The customer service attitude was good, but detailed product information was insufficient. Please add specific data and examples."

[0650] Hardware and software used

[0651] The system uses a smartphone or tablet, camera, and microphone as hardware, and Python, OpenCV, dlib, librosa, scikit-learn, and generative AI models as software.

[0652] Examples and prompts

[0653] As a concrete example, by inputting the following prompt sentence into the generative AI model, it is possible to provide specific advice to the user.

[0654] "User speaks too fast. Generate advice to speak more slowly."

[0655] "Infer emotions from the user's facial expressions and generate advice to help them make a good impression while serving customers."

[0656] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0657] Step 1:

[0658] A user logs in to a device and grants permission to use the camera and microphone. Username and password are required as input. The device sends this information to the server, which authenticates the user and displays the dashboard if successful. The output is that the user has successfully logged in.

[0659] Step 2:

[0660] The user clicks the "Start customer service practice" button. The user's click event is required as input. The device activates the camera and microphone and starts capturing video and audio. The output is the captured video and audio data.

[0661] Step 3:

[0662] The device streams captured video and audio data to the server in real time. As input, video and audio data are required. The device transmits these data to the server in real time. The output is the data streamed in real time.

[0663] Step 4:

[0664] The server analyzes the received video data and recognizes facial expressions and gestures. Real-time video data is required as input. The server uses OpenCV and dlib to detect facial landmarks and analyze facial expressions. The output is the recognized facial expression and gesture data.

[0665] Step 5:

[0666] The server analyzes the audio data and evaluates the speaking rate, volume, and tone. Real-time audio data is required as input. The server uses Librosa to extract audio features and evaluates them using a machine learning model. The output is the evaluated speaking rate, volume, and tone data.

[0667] Step 6:

[0668] The server generates feedback based on the analysis results and sends it to the device. The analysis results of facial expressions and voice are required as input. The server generates feedback based on this and sends advice in text format to the device. The output is the text data of the generated feedback.

[0669] Step 7:

[0670] The terminal displays the received feedback to the user. As input, it requires feedback data sent from the server. The terminal displays the data on the screen and provides real-time advice to the user. The output is the feedback displayed to the user.

[0671] Step 8:

[0672] The server automatically generates questions based on the user's customer service and sends them to the terminal. The real-time customer service content is required as input. The server uses a generative AI model to generate appropriate questions. The output is the text data of the generated questions.

[0673] Step 9:

[0674] The terminal displays the presented question to the user, and the user answers. Question data sent from the server is required as input. The terminal displays the question on the screen, and the user answers by typing or speaking. The output is the user's answer data.

[0675] Step 10:

[0676] The user's answer data is sent to the server, which evaluates its appropriateness and clarity. As input, the user's answer data is required. The server evaluates the quality of the answer using an evaluation algorithm. The output is the evaluation result data.

[0677] Step 11:

[0678] The server evaluates the user's overall customer service, generates a detailed feedback report, and sends it to the terminal. All analysis results and evaluation data are required as input. The server performs an integrated evaluation and creates a detailed report. The output is the detailed feedback report data.

[0679] Step 12:

[0680] The terminal displays the report to the user and allows the report to be saved and shared. As input, a detailed feedback report sent from the server is required. The terminal displays the report on the screen and the user can save it or share it with other users or administrators. The output is a feedback report that helps the user improve their customer service skills.

[0681] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0682] The present invention is a system for users to practice presentations, and includes all processes from capturing video and audio data to analyzing and generating feedback. The present invention also incorporates an emotion engine to recognize the user's emotions and provide feedback based on the emotions.

[0683] Program processing

[0684] 1. Initial Setup:

[0685] A user logs in to the system. The device requests permission to use the camera and microphone. If the user grants permission, the device activates the camera and microphone and becomes ready.

[0686] For example, a user enters a username and password on a login screen, and the device sends this to the server. The server authenticates the user, and if successful, displays the dashboard.

[0687] 2. Start your presentation:

[0688] When the user clicks the "Start Presentation Practice" button, the device will activate the camera and microphone and begin capturing video and audio.

[0689] The device streams this data to the server in real time.

[0690] 3. Analysis and Evaluation:

[0691] The server analyzes the received video data and recognizes facial expressions and gestures, analyzing facial movements and hand movements to determine the emphasis of the presentation.

[0692] The server analyzes the audio data and evaluates the speech rate, volume, and tone, including the words per minute, whether the speech rate is appropriate, and how emotional the tone of the voice is.

[0693] 4. How the Emotion Engine Works:

[0694] The server's emotion engine analyzes the video data and recognizes the user's emotions (joy, anger, sadness, happiness, etc.). For example, if there are many smiling faces, it is judged to be a positive emotion, and if there are many tense expressions, it is judged to be a negative emotion.

[0695] 5. Feedback Generation:

[0696] The server generates feedback based on the analysis results and emotion recognition and sends it to the device, displaying real-time feedback such as "You're speaking too fast. Please speak a little more slowly."

[0697] This includes feedback from an emotion engine, which generates advice such as, "You're not smiling enough. Express more emotion."

[0698] 6. Question simulation:

[0699] The server analyzes the content of the user's presentation and automatically generates related questions, which the terminal presents to the user, who then answers them.

[0700] The user's answers are sent to a server, which evaluates them for appropriateness and clarity. For example, a question might be generated: "What is the source of the data on this slide?", and the server analyzes the data captured as the user answers.

[0701] 7. Overall evaluation and detailed report:

[0702] The server evaluates the user's overall presentation and generates a detailed feedback report that the device displays to the user, allowing them to save and share the report.

[0703] The report also includes emotional trends analyzed by the emotion engine, offering advice such as, "You remained nervous throughout the presentation. Try some relaxation techniques."

[0704] As described above, the system of the present invention provides real-time analysis of video and audio data, emotion recognition using an emotion engine, and detailed feedback to improve users' presentation skills, allowing users to instantly improve their performance and acquire effective presentation skills.

[0705] The processing flow will be explained below.

[0706] Step 1:

[0707] The user enters their username and password at the system login screen.

[0708] The terminal sends the input information to the server.

[0709] The server authenticates the user and displays the dashboard if authentication is successful, otherwise it returns an error message.

[0710] Step 2:

[0711] The device asks the user for permission to use the camera and microphone.

[0712] If the user grants permission, the device will activate the camera and microphone and become ready.

[0713] Step 3:

[0714] The user clicks the "Start Practice Presentation" button.

[0715] The device will activate the camera and microphone and begin capturing video and audio.

[0716] Step 4:

[0717] The device streams the captured video and audio data to the server in real time.

[0718] Step 5:

[0719] The server analyzes the video data it receives and recognizes facial expressions and gestures.

[0720] For example, facial movements can be analyzed to identify emotions (e.g., joy, anger, sadness, happiness), and hand movements can be analyzed to identify the emphasis of a presentation.

[0721] Step 6:

[0722] The server analyzes the received voice data and evaluates the speaking rate, volume, and tone.

[0723] Specifically, it analyzes speaking rate (number of words spoken per minute), volume (whether the voice is at an appropriate volume), and tone (how much emotion is expressed).

[0724] Step 7:

[0725] The server's emotion engine analyzes the video data and recognizes the user's emotions.

[0726] For example, frequent smiles are judged as positive emotions, while frequent frowns are judged as negative emotions.

[0727] Step 8:

[0728] The server generates feedback based on the analysis results and emotion recognition and sends it to the device.

[0729] Real-time feedback is displayed, including advice such as "You're speaking too fast. Speak a little more slowly," and emotion-based advice such as "You don't smile enough. Express more emotion."

[0730] Step 9:

[0731] The server automatically generates questions based on the presentation content.

[0732] For example, generate a question like, "What is the data source for this slide?"

[0733] The terminal presents the generated question to the user.

[0734] Step 10:

[0735] The user answers the questions.

[0736] The device captures the answers and records them as audio data.

[0737] The device sends the response data to the server in real time.

[0738] Step 11:

[0739] The server analyzes the response data and evaluates it for relevance and clarity.

[0740] For example, generate feedback such as, "The answer is unclear. Let me give you a concrete example."

[0741] Step 12:

[0742] The server evaluates the user's overall presentation and generates a detailed feedback report.

[0743] The device displays the generated report to the user and provides options to save or share it.

[0744] The report also includes emotional trends analyzed by the emotion engine, offering advice such as, "You remained nervous throughout the presentation. Try some relaxation techniques."

[0745] In this way, all processing steps in the system are performed continuously, allowing users to receive real-time feedback to improve their presentation skills and effectively practice.

[0746] Example 2

[0747] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0748] Conventional presentation practice systems are limited to basic capture and feedback functions for the user's video and audio, and lack the ability to recognize emotions or provide detailed feedback based on those emotions. As a result, users often feel limited in their ability to improve their emotional expression and presentation skills. Furthermore, the lack of question simulation and detailed reporting functions results in insufficient evaluation of the overall presentation. To address these issues, a system with emotion recognition and detailed feedback functions is needed.

[0749] The specification processing by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for capturing the user's video and audio, means for transmitting the user's video and audio data in real time, means for analyzing the video data to recognize facial expressions and gestures, means for analyzing the audio data to evaluate speaking speed, volume, and tone, means for recognizing the user's emotions using an emotion engine, and means for generating and transmitting feedback based on the analysis results and emotion recognition in real time. This allows the user to receive real-time feedback during the presentation practice process and instantly improve their performance and emotional expression. In addition, the question simulation and detailed report function allow the user to evaluate the entire presentation, allowing the user to identify more specific areas for improvement.

[0750] "Capture" refers to the process of capturing video or audio data.

[0751] "Real-time transmission" refers to the process of transmitting captured data immediately without delay.

[0752] "Analysis" refers to the process of extracting information from acquired data using specific algorithms.

[0753] "Facial expression recognition" refers to the process of identifying a user's facial expression from video data.

[0754] "Gesture recognition" refers to the process of identifying a user's hand and body movements from video data.

[0755] "Speech rate" refers to the number of words a user speaks within a given period of time.

[0756] "Volume" refers to the volume of the user's speech.

[0757] "Tone" refers to the pitch and quality of the user's voice.

[0758] "Emotion engine" refers to technology that identifies a user's emotions from video or audio data.

[0759] "Feedback" refers to evaluations and advice provided to users based on the analysis results.

[0760] "Automatic question generation" refers to the automatic creation of related questions based on the content of the presentation.

[0761] "Appropriateness" refers to the degree to which the user's answer matches the content and intent of the presentation.

[0762] "Clarity" refers to the degree to which the user's response is clear and easy to understand.

[0763] A "detailed feedback report" refers to a report that includes evaluations and sentiment analysis results for the entire presentation.

[0764] MODE FOR CARRYING OUT THE INVENTION

[0765] The present invention is a system that allows users to effectively practice presentations and includes all processes from capturing video and audio data to analyzing it and generating feedback. Furthermore, by incorporating an emotion engine, this system has the advantage of being able to recognize the user's emotions and provide feedback based on those emotions. Specific embodiments for implementing the present invention are described below.

[0766] System Configuration

[0767] This system consists of a user's device (personal computer, smartphone, tablet, etc.) and a server. The device is equipped with a camera and microphone, which are used to capture video and audio data. The server analyzes the data received in real time and generates feedback. Specific examples of hardware and software include:

[0768] Camera: A device used to capture a user's image (e.g., a webcam, a smartphone's built-in camera)

[0769] Microphone: A device used to capture the user's voice (e.g., a headset, a smartphone's built-in microphone)

[0770] Terminal: A device that captures video and audio data and transmits it to a server (e.g., a personal computer, smartphone, or tablet).

[0771] Server: Computing resources (e.g., cloud servers) for analyzing data and generating feedback

[0772] Emotion engine: Software for recognizing user emotions (e.g., Microsoft Azure Emotion API)

[0773] Speech analysis software: a program for analyzing voice data (e.g., Google Speech-to-Text API)

[0774] Video analysis software: A program for analyzing video data (e.g., OpenCV)

[0775] Processing Flow

[0776] The system process flow involves the following steps:

[0777] 1. Initial Setup:

[0778] The user logs in to the system and the device asks for permission to use the camera and microphone. If the user grants permission, the device activates the camera and microphone and becomes ready.

[0779] 2. Start your presentation:

[0780] When a user clicks the "Start Presentation Practice" button, the device activates the camera and microphone and starts capturing video and audio. The device streams this data to the server in real time.

[0781] 3. Data Analysis:

[0782] The server analyzes the received video data in real time and recognizes facial expressions and gestures. For example, facial recognition and gesture recognition are performed using OpenCV.

[0783] At the same time, the audio data is analyzed to evaluate speaking rate, volume, and tone, using the Google Speech-to-Text API.

[0784] 4. Emotion recognition:

[0785] The server's emotion engine analyzes the user's emotions, using Microsoft Azure Emotion API and other tools to recognize emotions such as joy, anger, sadness, and happiness in real time.

[0786] 5. Feedback Generation:

[0787] The server generates feedback based on the analysis results and emotion recognition and sends it to the device, providing real-time feedback on how to adjust speech rate and volume, as well as advice on improving gestures and facial expressions.

[0788] 6. Question simulation:

[0789] The server analyzes the content of the user's presentation and automatically generates related questions, such as "What is the source of the data on this slide?", and presents them to the user via their device.

[0790] 7. Overall evaluation and detailed report:

[0791] The server evaluates the user's overall presentation and generates a detailed feedback report, including information on the overall presentation structure, speaking rate, volume, emotional trends, and appropriateness of gestures. The report is then displayed to the user on the device, and can be saved or shared.

[0792] Examples of prompts:

[0793] What is the topic of your presentation?

[0794] Please briefly explain the contents of this slide.

[0795] "What is the data source for the slides?"

[0796] "What questions do you anticipate?"

[0797] "What are the most important points of your presentation?"

[0798] This system allows users to receive real-time feedback during their presentation practice, enabling them to instantly improve their skills and emotional expression. Detailed feedback reports also provide an overall evaluation of the presentation and specific areas for improvement. As a result, users can acquire effective presentation skills.

[0799] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0800] Processing steps and specific operations

[0801] Step 1: Initial Setup

[0802] A user logs in to the system.

[0803] Input: Username and Password

[0804] Output: Authentication result (success or failure)

[0805] How it works: The user enters their username and password on the login screen. The device sends this information to the server, which checks it against a database (e.g., MySQL) and authenticates them. If authentication is successful, the dashboard is displayed. Next, a popup appears requesting permission to use the camera and microphone; if the user grants permission, the camera and microphone are turned on.

[0806] Step 2: Start your presentation

[0807] The user clicks the "Start Practice Presentation" button.

[0808] Input: User click action

[0809] Output: Start capturing video and audio

[0810] How it works: When the user clicks the button, the device reactivates the camera and microphone and begins capturing video and audio. The captured data is streamed to the server in real time.

[0811] Step 3: Analyze and evaluate video and audio data

[0812] The server analyzes the received video data.

[0813] Input: Video data

[0814] Output: Facial expression and gesture recognition results

[0815] How it works: The server uses a facial recognition algorithm (e.g., OpenCV) to analyze the user's facial expressions and gestures, identifying facial and hand movements and determining the emphasis of the presentation.

[0816] The server analyzes the audio data.

[0817] Input: Audio data

[0818] Output: Speech rate, volume, and tone evaluation results

[0819] How it works: The server uses speech analysis software (e.g., the Google Speech-to-Text API) to analyze the audio data and evaluate the speech rate, volume, and tone. It determines the speech rate (words per minute), whether the volume is appropriate, and how emotional the tone is.

[0820] Step 4: Emotion Engine in Action

[0821] The server's emotion engine analyzes the video data.

[0822] Input: Video data

[0823] Output: User emotion recognition results

[0824] How it works: Using the server's emotion engine (for example, Microsoft Azure Emotion API), the system recognizes and evaluates the user's emotions (joy, anger, sadness, happiness, etc.) from video data. For example, if there are many smiling faces, it is judged to have positive emotions, and if there are many tense expressions, it is judged to have negative emotions.

[0825] Step 5: Generate feedback

[0826] The server generates feedback based on the analysis results and emotion recognition.

[0827] Input: Video and audio analysis results and emotion recognition results

[0828] Output: Feedback message

[0829] How it works: Based on the analysis results and emotion recognition, the server generates real-time feedback to the user, providing specific advice such as "You're speaking too fast. Please speak a little more slowly."

[0830] Step 6: Simulate the Question

[0831] The server automatically generates questions based on the presentation content.

[0832] Input: Presentation content data

[0833] Output: Question list

[0834] How it works: The server analyzes the presentation content and automatically generates relevant questions. These questions are then presented to the user via their device, with specific questions such as "What is the source of the data on this slide?"

[0835] Step 7: Capture and evaluate responses

[0836] The user answers the question.

[0837] Input: User's answer (video and audio)

[0838] Output: Response data

[0839] How it works: The user answers questions. The answers are captured by the device and sent to the server, which analyzes the data and evaluates the appropriateness and clarity of the answers.

[0840] Step 8: Overall evaluation and detailed report

[0841] The server gives an overall evaluation of the user's presentation.

[0842] Input: All analysis results and feedback data

[0843] Output: Detailed feedback report

[0844] How it works: The server evaluates the user's overall presentation and generates a detailed feedback report that includes information on the presentation's structure, speaking rate, volume, emotional trends, and appropriateness of gestures. The report is displayed to the user via their device. The user can save and share the report.

[0845] (Application example 2)

[0846] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0847] In today's virtual stores, it is difficult for salespeople to practice their customer service skills efficiently and effectively. In particular, there is a need for a method to improve their ability to respond to specific questions while receiving real-time feedback. Furthermore, there is a lack of methods to recognize emotions during customer service and provide advice based on those emotions.

[0848] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for capturing video and audio of the user, means for transmitting the video and audio to the server, means for analyzing the video data to recognize facial expressions and movements, means for analyzing the audio data to evaluate speaking speed, volume, and tone of voice, means for generating feedback based on the analysis results and transmitting the feedback to the terminal, and means for a salesperson to pose simulated questions as a virtual customer and capture and evaluate the answers. This enables salespeople to efficiently and effectively improve their customer service skills and improve their ability to respond to specific questions while receiving real-time feedback.

[0849] "User" refers to the person or role that operates the system and provides video and audio data.

[0850] "Video and audio capture means" refers to a combination of hardware and software for obtaining video and audio data of a user.

[0851] "Means for transmitting to the server in real time" refers to a communication means for transferring the acquired video and audio data to the server immediately without delay.

[0852] "Server" refers to a central processing unit for performing the process of data analysis and feedback generation.

[0853] "Means for recognizing facial expressions and movements" refers to algorithms or software that analyze video data to recognize the user's facial expressions and body movements.

[0854] "Means for assessing speaking rate, volume, and tone of voice" refers to algorithms or software that analyzes audio data and assesses speaking rate, volume, and tone of voice.

[0855] "Means for generating and transmitting feedback based on the analysis results to the terminal" refers to a system for generating feedback based on data analysis and transmitting it to the user's device.

[0856] "Salesperson" refers to the person or role that serves customers in a virtual store.

[0857] The "means for presenting simulated questions to a virtual customer and capturing and evaluating the responses" is a means for automatically generating questions that a virtual customer might ask, obtaining the user's responses to those questions, and evaluating their appropriateness and clarity.

[0858] The present invention is a system for improving the customer service skills of salespeople in a virtual store. The system of the present invention captures video and audio data of users (salespeople) and transmits them to a server in real time to analyze the salespeople's customer service performance and provide feedback.

[0859] Hardware and software used

[0860] 1. Hardware

[0861] Camera: Used to capture video of the user.

[0862] Microphone: Used to capture the user's voice.

[0863] Smartphones and head-mounted displays (HMDs): Used as the user's devices to display feedback, etc.

[0864] 2. Software

[0865] Emotion engine: Analyzes the user's video data, recognizes and evaluates facial expressions and movements.

[0866] Voice Analysis Module: Analyzes the user's voice data and evaluates speaking rate, volume, and tone of voice.

[0867] Feedback generation module: Generates feedback based on the analysis results and sends it to the device.

[0868] Question generation module: simulates questions from virtual customers and presents them to the user.

[0869] Evaluation module: Evaluates user responses and analyzes their appropriateness and clarity.

[0870] How it works

[0871] 1. User Preparation

[0872] The system is ready when the user logs in to the system and gives permission to use the camera and microphone. Specifically, the user enters their username and password on the terminal, and the system performs authentication.

[0873] 2. Start customer service practice

[0874] When the user presses the "Start customer service practice" button, the camera and microphone are activated and video and audio capture begins. The data is sent to the server in real time.

[0875] 3. Data Analysis

[0876] The server analyzes the received video data and recognizes facial expressions and movements. The emotion engine analyzes the user's emotions and identifies feelings such as tension or joy.

[0877] The server analyzes the audio data and evaluates speaking rate, volume, and tone of voice, which is done by the audio analysis module.

[0878] 4. Feedback Generation

[0879] Based on the analysis results, the feedback generation module generates appropriate feedback, which is sent to the terminal and displayed to the user in real time.

[0880] 5. Question Simulation

[0881] The question generation module automatically generates questions based on the customer service content and displays them on the terminal. The user captures the answers and sends them to the server.

[0882] 6. Overall evaluation and report

[0883] The server evaluates the user's overall customer service and generates a detailed feedback report, which is displayed on the device and can be saved or shared.

[0884] Specific examples

[0885] As a specific example, this system can be used in souvenir shops at tourist spots or virtual stores of home appliances to help sales staff improve their specific customer service skills.

[0886] Prompt Sentence Examples

[0887] We are developing an application for virtual store salespeople to practice customer service. The system uses a camera and microphone to capture video and audio, and analyzes and provides feedback on the salespeople's customer service skills and emotions in real time. Please explain how this system works.

[0888] The system of the present invention helps salespeople efficiently and effectively improve their customer service skills, improving their ability to respond to specific questions while receiving real-time feedback.

[0889] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0890] Step 1: Initial Setup

[0891] A user logs in to the system and gives permission to use the camera and microphone. This causes the device to activate the camera and microphone and enter a ready state. The input data is the user's login information, and the output is the camera and microphone activation readiness.

[0892] Step 2: Start practicing customer service

[0893] When the user presses the "Start customer service practice" button, the device activates the camera and microphone and begins capturing video and audio. The captured data is sent to the server in real time. The input data is the user's operation, and the output is streaming video and audio data.

[0894] Step 3: Analyzing the video data

[0895] The server analyzes the received video data and recognizes facial expressions and movements. Specifically, it analyzes facial movements and hand gestures. The input data is video frames, and the output is the recognition results of facial expressions and movements. An emotion engine is used to identify emotions.

[0896] Step 4: Analyzing the audio data

[0897] The server analyzes the received audio data and evaluates the speaking rate, volume, and tone of voice. Specifically, it analyzes the speaking rate, volume, and tone of voice. The input data is an audio stream, and the output is the evaluation results of the speaking rate, volume, and tone of voice.

[0898] Step 5: Generate feedback

[0899] The server generates feedback based on the analysis of the video and audio data and sends it to the device. For example, it may include specific advice such as "You're speaking too fast. Speak a little more slowly" or "You don't smile enough. Express more emotion." The input data is the analysis results, and the output is the feedback message.

[0900] Step 6: Simulate the Question

[0901] The server automatically generates questions for virtual customers based on the customer service content and sends them to the terminal. The user provides answers to the questions, and the answers are captured by the server. The input data is the customer service content, and the output is the generated questions and their answers.

[0902] Step 7: Evaluate your responses

[0903] The server analyzes the user's answers and evaluates them for appropriateness and clarity. For example, it determines whether the answer to the question "What is the data source for this slide?" is appropriate. The input data is the user's answers, and the output is the evaluation result.

[0904] Step 8: Overall evaluation and report generation

[0905] The server evaluates the entire customer service and generates a detailed feedback report. The report includes good points and areas for improvement during the customer service, as well as emotional trends analyzed by the emotion engine. This report is displayed on the terminal and can be saved and shared by the user. The input data are all analysis results, and the output is a feedback report.

[0906] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0907] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0908] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0909] [Third embodiment]

[0910] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0911] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0912] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0913] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0914] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0915] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0916] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0917] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0918] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0919] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0920] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0921] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0922] The present invention is a system for users to practice presentations, which includes capturing, analyzing, and generating feedback from video and audio data. To use the system of the present invention, the user, the terminal, and the server each play their respective roles.

[0923] Program processing

[0924] 1. Initial Setup:

[0925] When a user logs in to the system, the device requests permission to use the camera and microphone. If the user grants permission, the device activates the camera and microphone and becomes ready.

[0926] For example, a user enters a username and password on a login screen, and the device sends this to the server. The server authenticates the user, and if successful, displays the dashboard.

[0927] 2. Start your presentation:

[0928] When the user clicks the "Start Presentation Practice" button, the device will activate the camera and microphone and begin capturing video and audio.

[0929] The device streams this data to the server in real time.

[0930] 3. Analysis and Evaluation:

[0931] The server analyzes the received video data and recognizes facial expressions and gestures. For example, it analyzes facial and hand movements to infer the user's emotions and intentions.

[0932] The server analyzes the audio data and evaluates the speaking rate, volume, and tone, for example, whether the speaking rate is appropriate and how the tone of the voice is perceived by the listener.

[0933] 4. Feedback generation:

[0934] The server generates feedback based on the analysis results and sends it to the device, displaying real-time feedback such as warnings about speech rate and advice about facial expressions.

[0935] For example, the server generates advice such as "You're speaking too fast. Please speak a little more slowly," and displays this to the user via the terminal.

[0936] 5. Question simulation:

[0937] The server analyzes the content of the user's presentation and automatically generates related questions, which the terminal presents to the user, who then answers them.

[0938] The user's answers are sent to a server, which evaluates them for appropriateness and clarity. For example, a question might be generated: "What is the source of the data on this slide?", and the server analyzes the data captured as the user answers.

[0939] 6. Overall evaluation and detailed report:

[0940] The server evaluates the user's overall presentation and generates a detailed feedback report that the device displays to the user and allows them to save and share the report.

[0941] For example, the server could generate a detailed report as an overall assessment, saying, "The presentation is well-structured, but it does not adequately address questions. Please add specific data and examples," and provide this to the user via the terminal.

[0942] As described above, the system of the present invention provides real-time analysis and feedback through a series of processes to help users improve their presentation skills, allowing them to quickly identify their weaknesses and make effective improvements.

[0943] The processing flow will be explained below.

[0944] Step 1:

[0945] The user enters their username and password at the system login screen.

[0946] The terminal sends the input information to the server.

[0947] The server authenticates the user. If authentication is successful, it displays the dashboard. If authentication fails, it returns an error message.

[0948] Step 2:

[0949] The device asks the user for permission to use the camera and microphone.

[0950] If the user grants permission, the device will activate the camera and microphone and become ready.

[0951] Step 3:

[0952] The user clicks the "Start Practice Presentation" button.

[0953] The device will activate the camera and microphone and begin capturing video and audio.

[0954] Step 4:

[0955] The device streams the captured video and audio data to the server in real time.

[0956] Step 5:

[0957] The server analyzes the video data it receives and recognizes facial expressions and gestures.

[0958] For example, facial movements can be analyzed to identify emotions (such as joy, anger, sadness, and happiness), and hand movements can be used to identify the emphasis of a presentation.

[0959] Step 6:

[0960] The server analyzes the audio data and evaluates speaking rate, volume, and tone.

[0961] For example, it analyzes the speaking rate (words per minute), whether the volume is appropriate, and how emotionally expressive the tone of the voice is.

[0962] Step 7:

[0963] The server generates feedback based on the analysis results and sends it to the device.

[0964] As real-time feedback, advice such as "You're speaking too fast. Please speak a little more slowly" is displayed.

[0965] Step 8:

[0966] The server automatically generates questions based on the presentation content.

[0967] For example, generate questions such as "What is the data source for this slide?"

[0968] The terminal presents the generated question to the user.

[0969] Step 9:

[0970] The user answers the questions.

[0971] The device captures the answers and records them as audio data.

[0972] The device sends the response data to the server in real time.

[0973] Step 10:

[0974] The server analyzes the response data and evaluates it for relevance and clarity.

[0975] For example, generate feedback such as, "The answer is unclear. Let me give you a concrete example."

[0976] Step 11:

[0977] The server evaluates the user's overall presentation and generates a detailed feedback report.

[0978] The device displays the generated report to the user and provides options to save or share it.

[0979] In this way, all processing steps in the system are continuous, providing users with real-time feedback and practice opportunities to improve their presentation skills.

[0980] Example 1

[0981] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0982] Modern presentations are extremely important in business and education, and mastering effective presentation techniques is essential. However, there are limited ways to effectively practice and self-evaluate presentations. In particular, it is difficult to receive objective, real-time feedback, making it difficult to obtain specific advice for self-improvement. Furthermore, while it is important to prepare for and improve the ability to respond to questions and answers about presentation content, there is a lack of systems that support this.

[0983] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0984] In this invention, the server includes means for analyzing a user's video data and recognizing facial expressions and gestures, means for analyzing audio data and evaluating speaking speed, volume, and tone, means for generating feedback based on the analysis results and sending it to the terminal, means for automatically generating questions based on the presentation content, and means for analyzing the question data, conducting a comprehensive evaluation, and generating a detailed report. This allows users to effectively practice presentations and receive specific feedback in real time. It also improves their ability to respond to questions and answers, and allows them to self-evaluate and identify areas for improvement through the detailed feedback report.

[0985] A "user" is a person who uses the system to practice a presentation.

[0986] A "terminal" is a user-operated computing device that captures and displays video and audio.

[0987] A "server" is a remote computer system that analyzes video and audio data and generates and presents results.

[0988] "Video" is visual data captured using a camera to capture the user's facial expressions and gestures.

[0989] "Speech" is auditory data captured using a microphone to record what a user says, the rate, volume, and tone of speech.

[0990] "Capture means" refers to a method or device for recording video and audio using a camera and microphone.

[0991] "Real-time transmission means" refers to communication technologies and protocols for transmitting captured data to a server in real time.

[0992] "Analysis means" refers to technology that processes video and audio data using AI models or other methods to identify and evaluate facial expressions, gestures, speaking rate, volume, and tone.

[0993] "Feedback generator" refers to algorithms and systems that generate specific improvements and advice for users based on the analyzed data.

[0994] "Automatic question generation means" refers to a technology that analyzes the content of a presentation and automatically generates related questions based on that analysis.

[0995] "Summary evaluation tool" refers to the techniques and processes for evaluating the entire presentation and generating a detailed feedback report.

[0996] "Terminal display means" refers to the functions and software of the terminal for displaying feedback and reports sent from the server to the user.

[0997] "Storage and sharing means" refers to methods and techniques for storing the generated detailed report on a terminal and sharing it with other users or systems as needed.

[0998] The present invention is a comprehensive support system for users to practice presentations, which includes capturing video and audio data, analyzing them in real time, generating feedback, simulating questions and answers, and generating a comprehensive evaluation and detailed report. The specific implementation of this system is described below.

[0999] This system involves the user, the terminal, and the server, each playing their respective roles. Before a user can start practicing their presentation, they must first log in to the system. The terminal is equipped with a camera and microphone, which are used to capture the user's video and audio. For example, the hardware used includes a common webcam and microphone.

[1000] When a user logs in, the device requests permission to use the camera and microphone. If the user allows this, the device activates the camera and microphone and becomes ready. When the user clicks the "Start Presentation Practice" button, the device begins capturing video and audio and streams the data to the server in real time.

[1001] The server uses AI models to analyze the received video and audio data. Specifically, frameworks such as OpenCV and TensorFlow are used for video analysis to recognize facial expressions and gestures. The audio analysis uses the Google Speech-to-Text API and other tools to evaluate speaking speed, volume, and tone. Based on the analysis results, the server generates real-time feedback and sends specific advice to the device, such as "You're speaking too fast. Please speak a little more slowly."

[1002] The device displays the received feedback to the user in real time, allowing the user to immediately try to improve based on this feedback. The server also analyzes the presentation content and automatically generates related questions. For example, it creates a question such as "What is the source of the data on this slide?" and presents it to the user via the device. When the user responds to the question, the data is captured again and sent to the server. The server analyzes the user's response and evaluates its appropriateness and clarity.

[1003] Once the practice is complete, the server evaluates the entire presentation and generates a detailed feedback report. This report includes evaluations of speaking speed, volume, facial expressions, gestures, and responses to questions. For example, the report may provide specific advice such as, "The presentation is well-structured, but your vocal tone is monotonous, so you need to improve it." The device displays this detailed report to the user, and the user can save and share it.

[1004] Examples of prompts include:

[1005] "To start practicing your presentation, simply log in to the system and grant permission for your camera and microphone. Once you press the "Start Practice Presentation" button, the system will automatically capture your video and audio and provide you with real-time feedback, including warnings about speaking speed and advice on appropriate facial expressions."

[1006] By taking all of these into consideration, the system of the present invention allows users to efficiently improve their presentation skills.

[1007] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1008] Step 1:

[1009] A user logs in to the system.

[1010] The user enters their username and password as input. The device sends this to the server, which then performs authentication. If authentication is successful, the server returns a login success response to the device, and the device displays the dashboard screen. It also displays a pop-up requesting the user's permission to use the camera and microphone.

[1011] Specifically, the terminal sends the authentication information entered by the user to the server, and the server refers to a database to verify the information and return the authentication result.

[1012] Step 2:

[1013] The user begins practicing the presentation.

[1014] As input, the user clicks the "Start Presentation Practice" button on the dashboard screen. The device detects this click event, activates the camera and microphone, and begins capturing video and audio.

[1015] Specifically, the device acquires the camera video stream and microphone audio stream and prepares to send them to the server in real time.

[1016] Step 3:

[1017] The device streams video and audio data to the server in real time.

[1018] As input, the device sends captured video and audio data in real time to a server that receives the data and prepares it for analysis.

[1019] Specifically, the server temporarily stores the received streaming data and formats it for passing to the analysis process.

[1020] Step 4:

[1021] The server analyzes the video data and recognizes facial expressions and gestures.

[1022] The input is video data sent to a server, which analyzes the video data using AI models (e.g., OpenCV or TensorFlow) to recognize facial expressions and hand gestures.

[1023] Specifically, the server applies a facial recognition algorithm to each video frame to detect and classify specific facial expressions (e.g., smile, worried face) and gestures (e.g., hand movements), and stores the analysis results in a database.

[1024] Step 5:

[1025] The server analyzes the audio data and evaluates speaking rate, volume, and tone.

[1026] The input is audio data sent to the server, which uses speech recognition technology (e.g., Google Speech-to-Text API) to convert the audio data into text, and then analyzes the speech rate, volume, tone, etc.

[1027] Specifically, the server analyzes the audio data, calculates the speech rate for each segment, measures the average volume and fluctuations, and performs tone analysis. The analysis results are stored in a database.

[1028] Step 6:

[1029] The server generates feedback based on the analysis results and sends it to the device.

[1030] The server takes as input the analysis results stored in it, runs a feedback generation algorithm on these results, and generates advice for the user (e.g., you speak too fast, try speaking more slowly), and sends the generated feedback to the device.

[1031] Specifically, the server analyzes the analysis results, generates a warning message based on a specific criterion (e.g., when the speech rate exceeds a certain value), and sends it to the terminal as feedback.

[1032] Step 7:

[1033] The device displays real-time feedback to the user.

[1034] As input, the feedback data sent from the server arrives at the terminal, which analyzes this data and displays it to the user in real time.

[1035] Specifically, the device displays the feedback message in a pop-up window or notification bar, allowing the user to immediately check its contents.

[1036] Step 8:

[1037] The server automatically generates questions based on the presentation content and sends them to the terminal.

[1038] As input, the server receives the analyzed presentation content data, and then uses natural language generation technology to automatically generate relevant questions (e.g., "What is the data source for this slide?") and send them to the device.

[1039] Specifically, the server automatically analyzes the presentation content, extracts keywords, and executes an algorithm to generate related questions based on the keywords.

[1040] Step 9:

[1041] The user captures answers to questions and sends them to the server.

[1042] The input is the user's response data (video and audio) to questions displayed on the terminal. When the user responds, the terminal captures the video and audio and sends them to the server.

[1043] Specifically, the terminal captures the user's answers in real time, generates data packets to be sent to the server, and sends them.

[1044] Step 10:

[1045] The server analyzes the answers and rates them for relevance and clarity.

[1046] The input is the user's answer data sent to the server, which uses an AI model to match the content of the answer with the presentation and evaluate it for appropriateness and clarity.

[1047] Specifically, the server converts the response content into text, checks the corresponding keywords and context, and evaluates the consistency and detail of the information.

[1048] Step 11:

[1049] The server provides an overall evaluation of the user's presentation and generates a detailed feedback report.

[1050] As input, it receives all the analysis results, and the server performs an overall evaluation based on these results and generates a detailed feedback report (e.g., the presentation is well-structured, but the voice tone is monotonous and should be improved).

[1051] Specifically, the server collects the results of each analysis step, executes a comprehensive evaluation algorithm, generates a detailed feedback report, and stores it in a database.

[1052] Step 12:

[1053] The device displays the report to the user, who can save and share it.

[1054] As input, there is a detailed feedback report sent by the server, which the device displays to the user and allows the user to save or share it as needed.

[1055] Specifically, the terminal receives the report data, displays the feedback content on a dedicated display screen, and provides save and share buttons.

[1056] (Application example 1)

[1057] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1058] In recent years, the customer service skills of store clerks in brick-and-mortar stores have become an important factor directly linked to customer satisfaction. However, current training methods make it difficult for store clerks to objectively evaluate their own customer service skills and identify specific areas for improvement. To solve this problem, a method is needed to effectively train store clerks and obtain feedback in real time.

[1059] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1060] In this invention, the server includes means for capturing video and audio of the user, means for transmitting the user's video and audio data to the server in real time, means for the server to analyze the video data and recognize facial expressions and gestures, means for the server to analyze the audio data and evaluate speaking speed, volume, and tone, means for the server to generate feedback based on the analysis results and transmit it to the terminal, means for the user to receive the feedback that is played back, and means for the server to automatically generate questions based on the content of the user's customer service and transmit them to the terminal. This enables store clerks to evaluate their own customer service skills in real time and identify specific areas for improvement.

[1061] "User" refers to a store clerk who uses this system to practice customer service.

[1062] "Device" means a smartphone, tablet, or similar device that a User logs in to and uses to capture and transmit video and audio data to a Server in real time.

[1063] "Server" refers to a computer system that analyzes received video and audio data, generates feedback and questions, and sends them to the terminal.

[1064] "Video Data" refers to captured visual information, including a user's facial expressions and gestures.

[1065] "Voice data" refers to captured voice information including the user's speaking rate, volume, and tone.

[1066] "Feedback" refers to advice and evaluations that the server generates based on the analysis results and provides to the user.

[1067] "Question" refers to a question that the server automatically generates based on the content of the customer service provided to the user and presents to the user for confirmation or evaluation.

[1068] "Capture" refers to the process of recording video and audio and transmitting them as data in real time from a device to a server.

[1069] "Analysis" refers to the process by which the server processes the received video and audio data and evaluates the user's facial expressions, gestures, speech rate, volume, and tone.

[1070] "Gestures" refer to the movements of the user's hands and body, and analyzing these movements can be used to infer the user's intentions and emotions.

[1071] A "feedback report" refers to a report in which the server evaluates the user's overall customer service and lists detailed areas for improvement and advice.

[1072] "Storage" refers to the device recording the generated feedback report or analysis results so that the user can refer to them later.

[1073] "Sharing" refers to a user sharing the generated feedback report or analysis results with other users or administrators online.

[1074] This invention is a system for improving the customer service skills of store clerks in brick-and-mortar stores, and includes capturing, analyzing, and generating feedback on video and audio data of users (store clerks). The system for implementing this invention consists of a terminal used by the user and a server that processes data.

[1075] Initial Setup

[1076] A user logs in to a device and gives permission to use the camera and microphone. The device then activates the camera and microphone and begins capturing video and audio data. For example, the user enters a username and password on the login screen, and the device sends this to the server. The server authenticates the user, and if successful, displays a dashboard.

[1077] Start of customer service practice

[1078] When the user clicks the "Start Customer Service Practice" button, the device activates the camera and microphone and starts capturing video and audio. The device streams this data to the server in real time.

[1079] Analysis and Evaluation

[1080] The server analyzes the received video data and recognizes facial expressions and gestures. Specifically, it uses OpenCV and dlib to detect facial landmarks and analyze facial expressions based on these. The server also analyzes audio data and evaluates speech rate, volume, and tone. It uses Librosa to extract audio features and evaluates them using a machine learning model.

[1081] Generate feedback

[1082] The server generates feedback based on the analysis results and sends it to the device. Real-time feedback is displayed to the user, providing advice on speech rate and facial expressions. For example, specific advice such as "You're speaking too fast. Please speak a little more slowly" is provided.

[1083] Question simulation

[1084] The server analyzes the user's customer service and automatically generates relevant questions. The device presents the questions to the user, who answers them. The user's answers are sent to the server, which evaluates their appropriateness and clarity. For example, a question such as "Please tell me about the features of this product" may be generated.

[1085] Overall rating and detailed report

[1086] The server evaluates the user's overall customer service and generates a detailed feedback report. The device displays this report to the user, who can save and share it. For example, the server may generate a detailed report stating, "The customer service attitude was good, but detailed product information was insufficient. Please add specific data and examples."

[1087] Hardware and software used

[1088] The system uses a smartphone or tablet, camera, and microphone as hardware, and Python, OpenCV, dlib, librosa, scikit-learn, and generative AI models as software.

[1089] Examples and prompts

[1090] As a concrete example, by inputting the following prompt sentence into the generative AI model, it is possible to provide specific advice to the user.

[1091] "User speaks too fast. Generate advice to speak more slowly."

[1092] "Infer emotions from the user's facial expressions and generate advice to help them make a good impression while serving customers."

[1093] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1094] Step 1:

[1095] A user logs in to a device and grants permission to use the camera and microphone. Username and password are required as input. The device sends this information to the server, which authenticates the user and displays the dashboard if successful. The output is that the user has successfully logged in.

[1096] Step 2:

[1097] The user clicks the "Start customer service practice" button. The user's click event is required as input. The device activates the camera and microphone and starts capturing video and audio. The output is the captured video and audio data.

[1098] Step 3:

[1099] The device streams captured video and audio data to the server in real time. As input, video and audio data are required. The device transmits these data to the server in real time. The output is the data streamed in real time.

[1100] Step 4:

[1101] The server analyzes the received video data and recognizes facial expressions and gestures. Real-time video data is required as input. The server uses OpenCV and dlib to detect facial landmarks and analyze facial expressions. The output is the recognized facial expression and gesture data.

[1102] Step 5:

[1103] The server analyzes the audio data and evaluates the speaking rate, volume, and tone. Real-time audio data is required as input. The server uses Librosa to extract audio features and evaluates them using a machine learning model. The output is the evaluated speaking rate, volume, and tone data.

[1104] Step 6:

[1105] The server generates feedback based on the analysis results and sends it to the device. The analysis results of facial expressions and voice are required as input. The server generates feedback based on this and sends advice in text format to the device. The output is the text data of the generated feedback.

[1106] Step 7:

[1107] The terminal displays the received feedback to the user. As input, it requires feedback data sent from the server. The terminal displays the data on the screen and provides real-time advice to the user. The output is the feedback displayed to the user.

[1108] Step 8:

[1109] The server automatically generates questions based on the user's customer service and sends them to the terminal. The real-time customer service content is required as input. The server uses a generative AI model to generate appropriate questions. The output is the text data of the generated questions.

[1110] Step 9:

[1111] The terminal displays the presented question to the user, and the user answers. Question data sent from the server is required as input. The terminal displays the question on the screen, and the user answers by typing or speaking. The output is the user's answer data.

[1112] Step 10:

[1113] The user's answer data is sent to the server, which evaluates its appropriateness and clarity. As input, the user's answer data is required. The server evaluates the quality of the answer using an evaluation algorithm. The output is the evaluation result data.

[1114] Step 11:

[1115] The server evaluates the user's overall customer service, generates a detailed feedback report, and sends it to the terminal. All analysis results and evaluation data are required as input. The server performs an integrated evaluation and creates a detailed report. The output is the detailed feedback report data.

[1116] Step 12:

[1117] The terminal displays the report to the user and allows the report to be saved and shared. As input, a detailed feedback report sent from the server is required. The terminal displays the report on the screen and the user can save it or share it with other users or administrators. The output is a feedback report that helps the user improve their customer service skills.

[1118] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1119] The present invention is a system for users to practice presentations, and includes all processes from capturing video and audio data to analyzing and generating feedback. The present invention also incorporates an emotion engine to recognize the user's emotions and provide feedback based on the emotions.

[1120] Program processing

[1121] 1. Initial Setup:

[1122] A user logs in to the system. The device requests permission to use the camera and microphone. If the user grants permission, the device activates the camera and microphone and becomes ready.

[1123] For example, a user enters a username and password on a login screen, and the device sends this to the server. The server authenticates the user, and if successful, displays the dashboard.

[1124] 2. Start your presentation:

[1125] When the user clicks the "Start Presentation Practice" button, the device will activate the camera and microphone and begin capturing video and audio.

[1126] The device streams this data to the server in real time.

[1127] 3. Analysis and Evaluation:

[1128] The server analyzes the received video data and recognizes facial expressions and gestures, analyzing facial movements and hand movements to determine the emphasis of the presentation.

[1129] The server analyzes the audio data and evaluates the speech rate, volume, and tone, including the words per minute, whether the speech rate is appropriate, and how emotional the tone of the voice is.

[1130] 4. How the Emotion Engine Works:

[1131] The server's emotion engine analyzes the video data and recognizes the user's emotions (joy, anger, sadness, happiness, etc.). For example, if there are many smiling faces, it is judged to be a positive emotion, and if there are many tense expressions, it is judged to be a negative emotion.

[1132] 5. Feedback Generation:

[1133] The server generates feedback based on the analysis results and emotion recognition and sends it to the device, displaying real-time feedback such as "You're speaking too fast. Please speak a little more slowly."

[1134] This includes feedback from an emotion engine, which generates advice such as, "You're not smiling enough. Express more emotion."

[1135] 6. Question simulation:

[1136] The server analyzes the content of the user's presentation and automatically generates related questions, which the terminal presents to the user, who then answers them.

[1137] The user's answers are sent to a server, which evaluates them for appropriateness and clarity. For example, a question might be generated: "What is the source of the data on this slide?", and the server analyzes the data captured as the user answers.

[1138] 7. Overall evaluation and detailed report:

[1139] The server evaluates the user's overall presentation and generates a detailed feedback report that the device displays to the user, allowing them to save and share the report.

[1140] The report also includes emotional trends analyzed by the emotion engine, offering advice such as, "You remained nervous throughout the presentation. Try some relaxation techniques."

[1141] As described above, the system of the present invention provides real-time analysis of video and audio data, emotion recognition using an emotion engine, and detailed feedback to improve users' presentation skills, allowing users to instantly improve their performance and acquire effective presentation skills.

[1142] The processing flow will be explained below.

[1143] Step 1:

[1144] The user enters their username and password at the system login screen.

[1145] The terminal sends the input information to the server.

[1146] The server authenticates the user and displays the dashboard if authentication is successful, otherwise it returns an error message.

[1147] Step 2:

[1148] The device asks the user for permission to use the camera and microphone.

[1149] If the user grants permission, the device will activate the camera and microphone and become ready.

[1150] Step 3:

[1151] The user clicks the "Start Practice Presentation" button.

[1152] The device will activate the camera and microphone and begin capturing video and audio.

[1153] Step 4:

[1154] The device streams the captured video and audio data to the server in real time.

[1155] Step 5:

[1156] The server analyzes the video data it receives and recognizes facial expressions and gestures.

[1157] For example, facial movements can be analyzed to identify emotions (e.g., joy, anger, sadness, happiness), and hand movements can be analyzed to identify the emphasis of a presentation.

[1158] Step 6:

[1159] The server analyzes the received voice data and evaluates the speaking rate, volume, and tone.

[1160] Specifically, it analyzes speaking rate (number of words spoken per minute), volume (whether the voice is at an appropriate volume), and tone (how much emotion is expressed).

[1161] Step 7:

[1162] The server's emotion engine analyzes the video data and recognizes the user's emotions.

[1163] For example, frequent smiles are judged as positive emotions, while frequent frowns are judged as negative emotions.

[1164] Step 8:

[1165] The server generates feedback based on the analysis results and emotion recognition and sends it to the device.

[1166] Real-time feedback is displayed, including advice such as "You're speaking too fast. Speak a little more slowly," and emotion-based advice such as "You don't smile enough. Express more emotion."

[1167] Step 9:

[1168] The server automatically generates questions based on the presentation content.

[1169] For example, generate a question like, "What is the data source for this slide?"

[1170] The terminal presents the generated question to the user.

[1171] Step 10:

[1172] The user answers the questions.

[1173] The device captures the answers and records them as audio data.

[1174] The device sends the response data to the server in real time.

[1175] Step 11:

[1176] The server analyzes the response data and evaluates it for relevance and clarity.

[1177] For example, generate feedback such as, "The answer is unclear. Let me give you a concrete example."

[1178] Step 12:

[1179] The server evaluates the user's overall presentation and generates a detailed feedback report.

[1180] The device displays the generated report to the user and provides options to save or share it.

[1181] The report also includes emotional trends analyzed by the emotion engine, offering advice such as, "You remained nervous throughout the presentation. Try some relaxation techniques."

[1182] In this way, all processing steps in the system are performed continuously, allowing users to receive real-time feedback to improve their presentation skills and effectively practice.

[1183] Example 2

[1184] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1185] Conventional presentation practice systems are limited to basic capture and feedback functions for the user's video and audio, and lack the ability to recognize emotions or provide detailed feedback based on those emotions. As a result, users often feel limited in their ability to improve their emotional expression and presentation skills. Furthermore, the lack of question simulation and detailed reporting functions results in insufficient evaluation of the overall presentation. To address these issues, a system with emotion recognition and detailed feedback functions is needed.

[1186] The specification processing by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for capturing the user's video and audio, means for transmitting the user's video and audio data in real time, means for analyzing the video data to recognize facial expressions and gestures, means for analyzing the audio data to evaluate speaking speed, volume, and tone, means for recognizing the user's emotions using an emotion engine, and means for generating and transmitting feedback based on the analysis results and emotion recognition in real time. This allows the user to receive real-time feedback during the presentation practice process and instantly improve their performance and emotional expression. In addition, the question simulation and detailed report function allow the user to evaluate the entire presentation, allowing the user to identify more specific areas for improvement.

[1187] "Capture" refers to the process of capturing video or audio data.

[1188] "Real-time transmission" refers to the process of transmitting captured data immediately without delay.

[1189] "Analysis" refers to the process of extracting information from acquired data using specific algorithms.

[1190] "Facial expression recognition" refers to the process of identifying a user's facial expression from video data.

[1191] "Gesture recognition" refers to the process of identifying a user's hand and body movements from video data.

[1192] "Speech rate" refers to the number of words a user speaks within a given period of time.

[1193] "Volume" refers to the volume of the user's speech.

[1194] "Tone" refers to the pitch and quality of the user's voice.

[1195] "Emotion engine" refers to technology that identifies a user's emotions from video or audio data.

[1196] "Feedback" refers to evaluations and advice provided to users based on the analysis results.

[1197] "Automatic question generation" refers to the automatic creation of related questions based on the content of the presentation.

[1198] "Appropriateness" refers to the degree to which the user's answer matches the content and intent of the presentation.

[1199] "Clarity" refers to the degree to which the user's response is clear and easy to understand.

[1200] A "detailed feedback report" refers to a report that includes evaluations and sentiment analysis results for the entire presentation.

[1201] MODE FOR CARRYING OUT THE INVENTION

[1202] The present invention is a system that allows users to effectively practice presentations and includes all processes from capturing video and audio data to analyzing it and generating feedback. Furthermore, by incorporating an emotion engine, this system has the advantage of being able to recognize the user's emotions and provide feedback based on those emotions. Specific embodiments for implementing the present invention are described below.

[1203] System Configuration

[1204] This system consists of a user's device (personal computer, smartphone, tablet, etc.) and a server. The device is equipped with a camera and microphone, which are used to capture video and audio data. The server analyzes the data received in real time and generates feedback. Specific examples of hardware and software include:

[1205] Camera: A device used to capture a user's image (e.g., a webcam, a smartphone's built-in camera)

[1206] Microphone: A device used to capture the user's voice (e.g., a headset, a smartphone's built-in microphone)

[1207] Terminal: A device that captures video and audio data and transmits it to a server (e.g., a personal computer, smartphone, or tablet).

[1208] Server: Computing resources (e.g., cloud servers) for analyzing data and generating feedback

[1209] Emotion engine: Software for recognizing user emotions (e.g., Microsoft Azure Emotion API)

[1210] Speech analysis software: a program for analyzing voice data (e.g., Google Speech-to-Text API)

[1211] Video analysis software: A program for analyzing video data (e.g., OpenCV)

[1212] Processing Flow

[1213] The system process flow involves the following steps:

[1214] 1. Initial Setup:

[1215] The user logs in to the system and the device asks for permission to use the camera and microphone. If the user grants permission, the device activates the camera and microphone and becomes ready.

[1216] 2. Start your presentation:

[1217] When a user clicks the "Start Presentation Practice" button, the device activates the camera and microphone and starts capturing video and audio. The device streams this data to the server in real time.

[1218] 3. Data Analysis:

[1219] The server analyzes the received video data in real time and recognizes facial expressions and gestures. For example, facial recognition and gesture recognition are performed using OpenCV.

[1220] At the same time, the audio data is analyzed to evaluate speaking rate, volume, and tone, using the Google Speech-to-Text API.

[1221] 4. Emotion recognition:

[1222] The server's emotion engine analyzes the user's emotions, using Microsoft Azure Emotion API and other tools to recognize emotions such as joy, anger, sadness, and happiness in real time.

[1223] 5. Feedback Generation:

[1224] The server generates feedback based on the analysis results and emotion recognition and sends it to the device, providing real-time feedback on how to adjust speech rate and volume, as well as advice on improving gestures and facial expressions.

[1225] 6. Question simulation:

[1226] The server analyzes the content of the user's presentation and automatically generates related questions, such as "What is the source of the data on this slide?", and presents them to the user via their device.

[1227] 7. Overall evaluation and detailed report:

[1228] The server evaluates the user's overall presentation and generates a detailed feedback report, including information on the overall presentation structure, speaking rate, volume, emotional trends, and appropriateness of gestures. The report is then displayed to the user on the device, and can be saved or shared.

[1229] Examples of prompts:

[1230] What is the topic of your presentation?

[1231] Please briefly explain the contents of this slide.

[1232] "What is the data source for the slides?"

[1233] "What questions do you anticipate?"

[1234] "What are the most important points of your presentation?"

[1235] This system allows users to receive real-time feedback during their presentation practice, enabling them to instantly improve their skills and emotional expression. Detailed feedback reports also provide an overall evaluation of the presentation and specific areas for improvement. As a result, users can acquire effective presentation skills.

[1236] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1237] Processing steps and specific operations

[1238] Step 1: Initial Setup

[1239] A user logs in to the system.

[1240] Input: Username and Password

[1241] Output: Authentication result (success or failure)

[1242] How it works: The user enters their username and password on the login screen. The device sends this information to the server, which checks it against a database (e.g., MySQL) and authenticates them. If authentication is successful, the dashboard is displayed. Next, a popup appears requesting permission to use the camera and microphone; if the user grants permission, the camera and microphone are turned on.

[1243] Step 2: Start your presentation

[1244] The user clicks the "Start Practice Presentation" button.

[1245] Input: User click action

[1246] Output: Start capturing video and audio

[1247] How it works: When the user clicks the button, the device reactivates the camera and microphone and begins capturing video and audio. The captured data is streamed to the server in real time.

[1248] Step 3: Analyze and evaluate video and audio data

[1249] The server analyzes the received video data.

[1250] Input: Video data

[1251] Output: Facial expression and gesture recognition results

[1252] How it works: The server uses a facial recognition algorithm (e.g., OpenCV) to analyze the user's facial expressions and gestures, identifying facial and hand movements and determining the emphasis of the presentation.

[1253] The server analyzes the audio data.

[1254] Input: Audio data

[1255] Output: Speech rate, volume, and tone evaluation results

[1256] How it works: The server uses speech analysis software (e.g., the Google Speech-to-Text API) to analyze the audio data and evaluate the speech rate, volume, and tone. It determines the speech rate (words per minute), whether the volume is appropriate, and how emotional the tone is.

[1257] Step 4: Emotion Engine in Action

[1258] The server's emotion engine analyzes the video data.

[1259] Input: Video data

[1260] Output: User emotion recognition results

[1261] How it works: Using the server's emotion engine (for example, Microsoft Azure Emotion API), the system recognizes and evaluates the user's emotions (joy, anger, sadness, happiness, etc.) from video data. For example, if there are many smiling faces, it is judged to have positive emotions, and if there are many tense expressions, it is judged to have negative emotions.

[1262] Step 5: Generate feedback

[1263] The server generates feedback based on the analysis results and emotion recognition.

[1264] Input: Video and audio analysis results and emotion recognition results

[1265] Output: Feedback message

[1266] How it works: Based on the analysis results and emotion recognition, the server generates real-time feedback to the user, providing specific advice such as "You're speaking too fast. Please speak a little more slowly."

[1267] Step 6: Simulate the Question

[1268] The server automatically generates questions based on the presentation content.

[1269] Input: Presentation content data

[1270] Output: Question list

[1271] How it works: The server analyzes the presentation content and automatically generates relevant questions. These questions are then presented to the user via their device, with specific questions such as "What is the source of the data on this slide?"

[1272] Step 7: Capture and evaluate responses

[1273] The user answers the question.

[1274] Input: User's answer (video and audio)

[1275] Output: Response data

[1276] How it works: The user answers questions. The answers are captured by the device and sent to the server, which analyzes the data and evaluates the appropriateness and clarity of the answers.

[1277] Step 8: Overall evaluation and detailed report

[1278] The server gives an overall evaluation of the user's presentation.

[1279] Input: All analysis results and feedback data

[1280] Output: Detailed feedback report

[1281] How it works: The server evaluates the user's overall presentation and generates a detailed feedback report that includes information on the presentation's structure, speaking rate, volume, emotional trends, and appropriateness of gestures. The report is displayed to the user via their device. The user can save and share the report.

[1282] (Application example 2)

[1283] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1284] In today's virtual stores, it is difficult for salespeople to practice their customer service skills efficiently and effectively. In particular, there is a need for a method to improve their ability to respond to specific questions while receiving real-time feedback. Furthermore, there is a lack of methods to recognize emotions during customer service and provide advice based on those emotions.

[1285] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for capturing video and audio of the user, means for transmitting the video and audio to the server, means for analyzing the video data to recognize facial expressions and movements, means for analyzing the audio data to evaluate speaking speed, volume, and tone of voice, means for generating feedback based on the analysis results and transmitting the feedback to the terminal, and means for a salesperson to pose simulated questions as a virtual customer and capture and evaluate the answers. This enables salespeople to efficiently and effectively improve their customer service skills and improve their ability to respond to specific questions while receiving real-time feedback.

[1286] "User" refers to the person or role that operates the system and provides video and audio data.

[1287] "Video and audio capture means" refers to a combination of hardware and software for obtaining video and audio data of a user.

[1288] "Means for transmitting to the server in real time" refers to a communication means for transferring the acquired video and audio data to the server immediately without delay.

[1289] "Server" refers to a central processing unit for performing the process of data analysis and feedback generation.

[1290] "Means for recognizing facial expressions and movements" refers to algorithms or software that analyze video data to recognize the user's facial expressions and body movements.

[1291] "Means for assessing speaking rate, volume, and tone of voice" refers to algorithms or software that analyzes audio data and assesses speaking rate, volume, and tone of voice.

[1292] "Means for generating and transmitting feedback based on the analysis results to the terminal" refers to a system for generating feedback based on data analysis and transmitting it to the user's device.

[1293] "Salesperson" refers to the person or role that serves customers in a virtual store.

[1294] The "means for presenting simulated questions to a virtual customer and capturing and evaluating the responses" is a means for automatically generating questions that a virtual customer might ask, obtaining the user's responses to those questions, and evaluating their appropriateness and clarity.

[1295] The present invention is a system for improving the customer service skills of salespeople in a virtual store. The system of the present invention captures video and audio data of users (salespeople) and transmits them to a server in real time to analyze the salespeople's customer service performance and provide feedback.

[1296] Hardware and software used

[1297] 1. Hardware

[1298] Camera: Used to capture video of the user.

[1299] Microphone: Used to capture the user's voice.

[1300] Smartphones and head-mounted displays (HMDs): Used as the user's devices to display feedback, etc.

[1301] 2. Software

[1302] Emotion engine: Analyzes the user's video data, recognizes and evaluates facial expressions and movements.

[1303] Voice Analysis Module: Analyzes the user's voice data and evaluates speaking rate, volume, and tone of voice.

[1304] Feedback generation module: Generates feedback based on the analysis results and sends it to the device.

[1305] Question generation module: simulates questions from virtual customers and presents them to the user.

[1306] Evaluation module: Evaluates user responses and analyzes their appropriateness and clarity.

[1307] How it works

[1308] 1. User Preparation

[1309] The system is ready when the user logs in to the system and gives permission to use the camera and microphone. Specifically, the user enters their username and password on the terminal, and the system performs authentication.

[1310] 2. Start customer service practice

[1311] When the user presses the "Start customer service practice" button, the camera and microphone are activated and video and audio capture begins. The data is sent to the server in real time.

[1312] 3. Data Analysis

[1313] The server analyzes the received video data and recognizes facial expressions and movements. The emotion engine analyzes the user's emotions and identifies feelings such as tension or joy.

[1314] The server analyzes the audio data and evaluates speaking rate, volume, and tone of voice, which is done by the audio analysis module.

[1315] 4. Feedback Generation

[1316] Based on the analysis results, the feedback generation module generates appropriate feedback, which is sent to the terminal and displayed to the user in real time.

[1317] 5. Question Simulation

[1318] The question generation module automatically generates questions based on the customer service content and displays them on the terminal. The user captures the answers and sends them to the server.

[1319] 6. Overall evaluation and report

[1320] The server evaluates the user's overall customer service and generates a detailed feedback report, which is displayed on the device and can be saved or shared.

[1321] Specific examples

[1322] As a specific example, this system can be used in souvenir shops at tourist spots or virtual stores of home appliances to help sales staff improve their specific customer service skills.

[1323] Prompt Sentence Examples

[1324] We are developing an application for virtual store salespeople to practice customer service. The system uses a camera and microphone to capture video and audio, and analyzes and provides feedback on the salespeople's customer service skills and emotions in real time. Please explain how this system works.

[1325] The system of the present invention helps salespeople efficiently and effectively improve their customer service skills, improving their ability to respond to specific questions while receiving real-time feedback.

[1326] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1327] Step 1: Initial Setup

[1328] A user logs in to the system and gives permission to use the camera and microphone. This causes the device to activate the camera and microphone and enter a ready state. The input data is the user's login information, and the output is the camera and microphone activation readiness.

[1329] Step 2: Start practicing customer service

[1330] When the user presses the "Start customer service practice" button, the device activates the camera and microphone and begins capturing video and audio. The captured data is sent to the server in real time. The input data is the user's operation, and the output is streaming video and audio data.

[1331] Step 3: Analyzing the video data

[1332] The server analyzes the received video data and recognizes facial expressions and movements. Specifically, it analyzes facial movements and hand gestures. The input data is video frames, and the output is the recognition results of facial expressions and movements. An emotion engine is used to identify emotions.

[1333] Step 4: Analyzing the audio data

[1334] The server analyzes the received audio data and evaluates the speaking rate, volume, and tone of voice. Specifically, it analyzes the speaking rate, volume, and tone of voice. The input data is an audio stream, and the output is the evaluation results of the speaking rate, volume, and tone of voice.

[1335] Step 5: Generate feedback

[1336] The server generates feedback based on the analysis of the video and audio data and sends it to the device. For example, it may include specific advice such as "You're speaking too fast. Speak a little more slowly" or "You don't smile enough. Express more emotion." The input data is the analysis results, and the output is the feedback message.

[1337] Step 6: Simulate the Question

[1338] The server automatically generates questions for virtual customers based on the customer service content and sends them to the terminal. The user provides answers to the questions, and the answers are captured by the server. The input data is the customer service content, and the output is the generated questions and their answers.

[1339] Step 7: Evaluate your responses

[1340] The server analyzes the user's answers and evaluates them for appropriateness and clarity. For example, it determines whether the answer to the question "What is the data source for this slide?" is appropriate. The input data is the user's answers, and the output is the evaluation result.

[1341] Step 8: Overall evaluation and report generation

[1342] The server evaluates the entire customer service and generates a detailed feedback report. The report includes good points and areas for improvement during the customer service, as well as emotional trends analyzed by the emotion engine. This report is displayed on the terminal and can be saved and shared by the user. The input data are all analysis results, and the output is a feedback report.

[1343] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1344] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1345] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1346] [Fourth embodiment]

[1347] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1348] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1349] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1350] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1351] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1352] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1353] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1354] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1355] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1356] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1357] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1358] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1359] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1360] The present invention is a system for users to practice presentations, which includes capturing, analyzing, and generating feedback from video and audio data. To use the system of the present invention, the user, the terminal, and the server each play their respective roles.

[1361] Program processing

[1362] 1. Initial Setup:

[1363] When a user logs in to the system, the device requests permission to use the camera and microphone. If the user grants permission, the device activates the camera and microphone and becomes ready.

[1364] For example, a user enters a username and password on a login screen, and the device sends this to the server. The server authenticates the user, and if successful, displays the dashboard.

[1365] 2. Start your presentation:

[1366] When the user clicks the "Start Presentation Practice" button, the device will activate the camera and microphone and begin capturing video and audio.

[1367] The device streams this data to the server in real time.

[1368] 3. Analysis and Evaluation:

[1369] The server analyzes the received video data and recognizes facial expressions and gestures. For example, it analyzes facial and hand movements to infer the user's emotions and intentions.

[1370] The server analyzes the audio data and evaluates the speaking rate, volume, and tone, for example, whether the speaking rate is appropriate and how the tone of the voice is perceived by the listener.

[1371] 4. Feedback generation:

[1372] The server generates feedback based on the analysis results and sends it to the device, displaying real-time feedback such as warnings about speech rate and advice about facial expressions.

[1373] For example, the server generates advice such as "You're speaking too fast. Please speak a little more slowly," and displays this to the user via the terminal.

[1374] 5. Question simulation:

[1375] The server analyzes the content of the user's presentation and automatically generates related questions, which the terminal presents to the user, who then answers them.

[1376] The user's answers are sent to a server, which evaluates them for appropriateness and clarity. For example, a question might be generated: "What is the source of the data on this slide?", and the server analyzes the data captured as the user answers.

[1377] 6. Overall evaluation and detailed report:

[1378] The server evaluates the user's overall presentation and generates a detailed feedback report that the device displays to the user and allows them to save and share the report.

[1379] For example, the server could generate a detailed report as an overall assessment, saying, "The presentation is well-structured, but it does not adequately address questions. Please add specific data and examples," and provide this to the user via the terminal.

[1380] As described above, the system of the present invention provides real-time analysis and feedback through a series of processes to help users improve their presentation skills, allowing them to quickly identify their weaknesses and make effective improvements.

[1381] The processing flow will be explained below.

[1382] Step 1:

[1383] The user enters their username and password at the system login screen.

[1384] The terminal sends the input information to the server.

[1385] The server authenticates the user. If authentication is successful, it displays the dashboard. If authentication fails, it returns an error message.

[1386] Step 2:

[1387] The device asks the user for permission to use the camera and microphone.

[1388] If the user grants permission, the device will activate the camera and microphone and become ready.

[1389] Step 3:

[1390] The user clicks the "Start Practice Presentation" button.

[1391] The device will activate the camera and microphone and begin capturing video and audio.

[1392] Step 4:

[1393] The device streams the captured video and audio data to the server in real time.

[1394] Step 5:

[1395] The server analyzes the video data it receives and recognizes facial expressions and gestures.

[1396] For example, facial movements can be analyzed to identify emotions (such as joy, anger, sadness, and happiness), and hand movements can be used to identify the emphasis of a presentation.

[1397] Step 6:

[1398] The server analyzes the audio data and evaluates speaking rate, volume, and tone.

[1399] For example, it analyzes the speaking rate (words per minute), whether the volume is appropriate, and how emotionally expressive the tone of the voice is.

[1400] Step 7:

[1401] The server generates feedback based on the analysis results and sends it to the device.

[1402] As real-time feedback, advice such as "You're speaking too fast. Please speak a little more slowly" is displayed.

[1403] Step 8:

[1404] The server automatically generates questions based on the presentation content.

[1405] For example, generate questions such as "What is the data source for this slide?"

[1406] The terminal presents the generated question to the user.

[1407] Step 9:

[1408] The user answers the questions.

[1409] The device captures the answers and records them as audio data.

[1410] The device sends the response data to the server in real time.

[1411] Step 10:

[1412] The server analyzes the response data and evaluates it for relevance and clarity.

[1413] For example, generate feedback such as, "The answer is unclear. Let me give you a concrete example."

[1414] Step 11:

[1415] The server evaluates the user's overall presentation and generates a detailed feedback report.

[1416] The device displays the generated report to the user and provides options to save or share it.

[1417] In this way, all processing steps in the system are continuous, providing users with real-time feedback and practice opportunities to improve their presentation skills.

[1418] Example 1

[1419] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1420] Modern presentations are extremely important in business and education, and mastering effective presentation techniques is essential. However, there are limited ways to effectively practice and self-evaluate presentations. In particular, it is difficult to receive objective, real-time feedback, making it difficult to obtain specific advice for self-improvement. Furthermore, while it is important to prepare for and improve the ability to respond to questions and answers about presentation content, there is a lack of systems that support this.

[1421] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1422] In this invention, the server includes means for analyzing a user's video data and recognizing facial expressions and gestures, means for analyzing audio data and evaluating speaking speed, volume, and tone, means for generating feedback based on the analysis results and sending it to the terminal, means for automatically generating questions based on the presentation content, and means for analyzing the question data, conducting a comprehensive evaluation, and generating a detailed report. This allows users to effectively practice presentations and receive specific feedback in real time. It also improves their ability to respond to questions and answers, and allows them to self-evaluate and identify areas for improvement through the detailed feedback report.

[1423] A "user" is a person who uses the system to practice a presentation.

[1424] A "terminal" is a user-operated computing device that captures and displays video and audio.

[1425] A "server" is a remote computer system that analyzes video and audio data and generates and presents results.

[1426] "Video" is visual data captured using a camera to capture the user's facial expressions and gestures.

[1427] "Speech" is auditory data captured using a microphone to record what a user says, the rate, volume, and tone of speech.

[1428] "Capture means" refers to a method or device for recording video and audio using a camera and microphone.

[1429] "Real-time transmission means" refers to communication technologies and protocols for transmitting captured data to a server in real time.

[1430] "Analysis means" refers to technology that processes video and audio data using AI models or other methods to identify and evaluate facial expressions, gestures, speech rate, volume, and tone.

[1431] "Feedback generator" refers to algorithms and systems that generate specific improvements and advice for users based on the analyzed data.

[1432] "Automatic question generation means" refers to a technology that analyzes the content of a presentation and automatically generates related questions based on that analysis.

[1433] "Summary evaluation tool" refers to the techniques and processes for evaluating the entire presentation and generating a detailed feedback report.

[1434] "Terminal display means" refers to the functions and software of the terminal for displaying feedback and reports sent from the server to the user.

[1435] "Storage and sharing means" refers to methods and techniques for storing the generated detailed report on a terminal and sharing it with other users or systems as needed.

[1436] The present invention is a comprehensive support system for users to practice presentations, which includes capturing video and audio data, analyzing them in real time, generating feedback, simulating questions and answers, and generating a comprehensive evaluation and detailed report. The specific implementation of this system is described below.

[1437] This system involves the user, the terminal, and the server, each playing their respective roles. Before a user can start practicing their presentation, they must first log in to the system. The terminal is equipped with a camera and microphone, which are used to capture the user's video and audio. For example, the hardware used includes a common webcam and microphone.

[1438] When a user logs in, the device requests permission to use the camera and microphone. If the user allows this, the device activates the camera and microphone and becomes ready. When the user clicks the "Start Presentation Practice" button, the device begins capturing video and audio and streams the data to the server in real time.

[1439] The server uses AI models to analyze the received video and audio data. Specifically, frameworks such as OpenCV and TensorFlow are used for video analysis to recognize facial expressions and gestures. The audio analysis uses the Google Speech-to-Text API and other tools to evaluate speaking speed, volume, and tone. Based on the analysis results, the server generates real-time feedback and sends specific advice to the device, such as "You're speaking too fast. Please speak a little more slowly."

[1440] The device displays the received feedback to the user in real time, allowing the user to immediately try to improve based on this feedback. The server also analyzes the presentation content and automatically generates related questions. For example, it creates a question such as "What is the source of the data on this slide?" and presents it to the user via the device. When the user responds to the question, the data is captured again and sent to the server. The server analyzes the user's response and evaluates its appropriateness and clarity.

[1441] Once the practice is complete, the server evaluates the entire presentation and generates a detailed feedback report. This report includes evaluations of speaking speed, volume, facial expressions, gestures, and responses to questions. For example, the report may provide specific advice such as, "The presentation is well-structured, but your vocal tone is monotonous, so you need to improve it." The device displays this detailed report to the user, and the user can save and share it.

[1442] Examples of prompts include:

[1443] "To start practicing your presentation, simply log in to the system and grant permission for your camera and microphone. Once you press the "Start Practice Presentation" button, the system will automatically capture your video and audio and provide you with real-time feedback, including warnings about speaking speed and advice on appropriate facial expressions."

[1444] By taking all of these into consideration, the system of the present invention allows users to efficiently improve their presentation skills.

[1445] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1446] Step 1:

[1447] A user logs in to the system.

[1448] The user enters their username and password as input. The device sends this to the server, which then performs authentication. If authentication is successful, the server returns a login success response to the device, and the device displays the dashboard screen. It also displays a pop-up requesting the user's permission to use the camera and microphone.

[1449] Specifically, the terminal sends the authentication information entered by the user to the server, and the server refers to a database to verify the information and return the authentication result.

[1450] Step 2:

[1451] The user begins practicing the presentation.

[1452] As input, the user clicks the "Start Presentation Practice" button on the dashboard screen. The device detects this click event, activates the camera and microphone, and begins capturing video and audio.

[1453] Specifically, the device acquires the camera video stream and microphone audio stream and prepares to send them to the server in real time.

[1454] Step 3:

[1455] The device streams video and audio data to the server in real time.

[1456] As input, the device sends captured video and audio data in real time to a server that receives the data and prepares it for analysis.

[1457] Specifically, the server temporarily stores the received streaming data and formats it for passing to the analysis process.

[1458] Step 4:

[1459] The server analyzes the video data and recognizes facial expressions and gestures.

[1460] The input is video data sent to a server, which analyzes the video data using AI models (e.g., OpenCV or TensorFlow) to recognize facial expressions and hand gestures.

[1461] Specifically, the server applies a facial recognition algorithm to each video frame to detect and classify specific facial expressions (e.g., smile, worried face) and gestures (e.g., hand movements), and stores the analysis results in a database.

[1462] Step 5:

[1463] The server analyzes the audio data and evaluates speaking rate, volume, and tone.

[1464] The input is audio data sent to the server, which uses speech recognition technology (e.g., Google Speech-to-Text API) to convert the audio data into text, and then analyzes the speech rate, volume, tone, etc.

[1465] Specifically, the server analyzes the audio data, calculates the speech rate for each segment, measures the average volume and fluctuations, and performs tone analysis. The analysis results are stored in a database.

[1466] Step 6:

[1467] The server generates feedback based on the analysis results and sends it to the device.

[1468] The server takes as input the analysis results stored in it, runs a feedback generation algorithm on these results, and generates advice for the user (e.g., you speak too fast, try speaking more slowly), and sends the generated feedback to the device.

[1469] Specifically, the server analyzes the analysis results, generates a warning message based on a specific criterion (e.g., when the speech rate exceeds a certain value), and sends it to the terminal as feedback.

[1470] Step 7:

[1471] The device displays real-time feedback to the user.

[1472] As input, the feedback data sent from the server arrives at the terminal, which analyzes this data and displays it to the user in real time.

[1473] Specifically, the device displays the feedback message in a pop-up window or notification bar, allowing the user to immediately check its contents.

[1474] Step 8:

[1475] The server automatically generates questions based on the presentation content and sends them to the terminal.

[1476] As input, the server receives the analyzed presentation content data, and then uses natural language generation technology to automatically generate relevant questions (e.g., "What is the data source for this slide?") and send them to the device.

[1477] Specifically, the server automatically analyzes the presentation content, extracts keywords, and executes an algorithm to generate related questions based on the keywords.

[1478] Step 9:

[1479] The user captures answers to questions and sends them to the server.

[1480] The input is the user's response data (video and audio) to questions displayed on the terminal. When the user responds, the terminal captures the video and audio and sends them to the server.

[1481] Specifically, the terminal captures the user's answers in real time, generates data packets to be sent to the server, and sends them.

[1482] Step 10:

[1483] The server analyzes the answers and rates them for relevance and clarity.

[1484] The input is the user's answer data sent to the server, which uses an AI model to match the content of the answer with the presentation and evaluate it for appropriateness and clarity.

[1485] Specifically, the server converts the response content into text, checks the corresponding keywords and context, and evaluates the consistency and detail of the information.

[1486] Step 11:

[1487] The server provides an overall evaluation of the user's presentation and generates a detailed feedback report.

[1488] As input, it receives all the analysis results, and the server performs an overall evaluation based on these results and generates a detailed feedback report (e.g., the presentation is well-structured, but the voice tone is monotonous and should be improved).

[1489] Specifically, the server collects the results of each analysis step, executes a comprehensive evaluation algorithm, generates a detailed feedback report, and stores it in a database.

[1490] Step 12:

[1491] The device displays the report to the user, who can save and share it.

[1492] As input, there is a detailed feedback report sent by the server, which the device displays to the user and allows the user to save or share it as needed.

[1493] Specifically, the terminal receives the report data, displays the feedback content on a dedicated display screen, and provides save and share buttons.

[1494] (Application example 1)

[1495] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1496] In recent years, the customer service skills of store clerks in brick-and-mortar stores have become an important factor directly linked to customer satisfaction. However, current training methods make it difficult for store clerks to objectively evaluate their own customer service skills and identify specific areas for improvement. To solve this problem, a method is needed to effectively train store clerks and obtain feedback in real time.

[1497] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1498] In this invention, the server includes means for capturing video and audio of the user, means for transmitting the user's video and audio data to the server in real time, means for the server to analyze the video data and recognize facial expressions and gestures, means for the server to analyze the audio data and evaluate speaking speed, volume, and tone, means for the server to generate feedback based on the analysis results and transmit it to the terminal, means for the user to receive the feedback that is played back, and means for the server to automatically generate questions based on the content of the user's customer service and transmit them to the terminal. This enables store clerks to evaluate their own customer service skills in real time and identify specific areas for improvement.

[1499] "User" refers to a store clerk who uses this system to practice customer service.

[1500] "Device" means a smartphone, tablet, or similar device that a User logs in to and uses to capture and transmit video and audio data to a Server in real time.

[1501] "Server" refers to a computer system that analyzes received video and audio data, generates feedback and questions, and sends them to the terminal.

[1502] "Video Data" refers to captured visual information, including a user's facial expressions and gestures.

[1503] "Voice data" refers to captured voice information including the user's speaking rate, volume, and tone.

[1504] "Feedback" refers to advice and evaluations that the server generates based on the analysis results and provides to the user.

[1505] "Question" refers to a question that the server automatically generates based on the content of the customer service provided to the user and presents to the user for confirmation or evaluation.

[1506] "Capture" refers to the process of recording video and audio and transmitting them as data in real time from a device to a server.

[1507] "Analysis" refers to the process by which the server processes the received video and audio data and evaluates the user's facial expressions, gestures, speech rate, volume, and tone.

[1508] "Gestures" refer to the movements of the user's hands and body, and analyzing these movements can be used to infer the user's intentions and emotions.

[1509] A "feedback report" refers to a report in which the server evaluates the user's overall customer service and lists detailed areas for improvement and advice.

[1510] "Storage" refers to the device recording the generated feedback report or analysis results so that the user can refer to them later.

[1511] "Sharing" refers to a user sharing the generated feedback report or analysis results with other users or administrators online.

[1512] This invention is a system for improving the customer service skills of store clerks in brick-and-mortar stores, and includes capturing, analyzing, and generating feedback on video and audio data of users (store clerks). The system for implementing this invention consists of a terminal used by the user and a server that processes data.

[1513] Initial Setup

[1514] A user logs in to a device and gives permission to use the camera and microphone. The device then activates the camera and microphone and begins capturing video and audio data. For example, the user enters a username and password on the login screen, and the device sends this to the server. The server authenticates the user, and if successful, displays a dashboard.

[1515] Start of customer service practice

[1516] When the user clicks the "Start Customer Service Practice" button, the device activates the camera and microphone and starts capturing video and audio. The device streams this data to the server in real time.

[1517] Analysis and Evaluation

[1518] The server analyzes the received video data and recognizes facial expressions and gestures. Specifically, it uses OpenCV and dlib to detect facial landmarks and analyze facial expressions based on these. The server also analyzes audio data and evaluates speech rate, volume, and tone. It uses Librosa to extract audio features and evaluates them using a machine learning model.

[1519] Generate feedback

[1520] The server generates feedback based on the analysis results and sends it to the device. Real-time feedback is displayed to the user, providing advice on speech rate and facial expressions. For example, specific advice such as "You're speaking too fast. Please speak a little more slowly" is provided.

[1521] Question simulation

[1522] The server analyzes the user's customer service and automatically generates relevant questions. The device presents the questions to the user, who answers them. The user's answers are sent to the server, which evaluates their appropriateness and clarity. For example, a question such as "Please tell me about the features of this product" may be generated.

[1523] Overall rating and detailed report

[1524] The server evaluates the user's overall customer service and generates a detailed feedback report. The device displays this report to the user, who can save and share it. For example, the server may generate a detailed report stating, "The customer service attitude was good, but detailed product information was insufficient. Please add specific data and examples."

[1525] Hardware and software used

[1526] The system uses a smartphone or tablet, camera, and microphone as hardware, and Python, OpenCV, dlib, librosa, scikit-learn, and generative AI models as software.

[1527] Examples and prompts

[1528] As a concrete example, by inputting the following prompt sentence into the generative AI model, it is possible to provide specific advice to the user.

[1529] "User speaks too fast. Generate advice to speak more slowly."

[1530] "Infer emotions from the user's facial expressions and generate advice to help them make a good impression while serving customers."

[1531] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1532] Step 1:

[1533] A user logs in to a device and grants permission to use the camera and microphone. Username and password are required as input. The device sends this information to the server, which authenticates the user and displays the dashboard if successful. The output is that the user has successfully logged in.

[1534] Step 2:

[1535] The user clicks the "Start customer service practice" button. The user's click event is required as input. The device activates the camera and microphone and starts capturing video and audio. The output is the captured video and audio data.

[1536] Step 3:

[1537] The device streams captured video and audio data to the server in real time. As input, video and audio data are required. The device transmits these data to the server in real time. The output is the data streamed in real time.

[1538] Step 4:

[1539] The server analyzes the received video data and recognizes facial expressions and gestures. Real-time video data is required as input. The server uses OpenCV and dlib to detect facial landmarks and analyze facial expressions. The output is the recognized facial expression and gesture data.

[1540] Step 5:

[1541] The server analyzes the audio data and evaluates the speaking rate, volume, and tone. Real-time audio data is required as input. The server uses Librosa to extract audio features and evaluates them using a machine learning model. The output is the evaluated speaking rate, volume, and tone data.

[1542] Step 6:

[1543] The server generates feedback based on the analysis results and sends it to the device. The analysis results of facial expressions and voice are required as input. The server generates feedback based on this and sends advice in text format to the device. The output is the text data of the generated feedback.

[1544] Step 7:

[1545] The terminal displays the received feedback to the user. As input, it requires feedback data sent from the server. The terminal displays the data on the screen and provides real-time advice to the user. The output is the feedback displayed to the user.

[1546] Step 8:

[1547] The server automatically generates questions based on the user's customer service and sends them to the terminal. The real-time customer service content is required as input. The server uses a generative AI model to generate appropriate questions. The output is the text data of the generated questions.

[1548] Step 9:

[1549] The terminal displays the presented question to the user, and the user answers. Question data sent from the server is required as input. The terminal displays the question on the screen, and the user answers by typing or speaking. The output is the user's answer data.

[1550] Step 10:

[1551] The user's answer data is sent to the server, which evaluates its appropriateness and clarity. As input, the user's answer data is required. The server evaluates the quality of the answer using an evaluation algorithm. The output is the evaluation result data.

[1552] Step 11:

[1553] The server evaluates the user's overall customer service, generates a detailed feedback report, and sends it to the terminal. All analysis results and evaluation data are required as input. The server performs an integrated evaluation and creates a detailed report. The output is the detailed feedback report data.

[1554] Step 12:

[1555] The terminal displays the report to the user and allows the report to be saved and shared. As input, a detailed feedback report sent from the server is required. The terminal displays the report on the screen and the user can save it or share it with other users or administrators. The output is a feedback report that helps the user improve their customer service skills.

[1556] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1557] The present invention is a system for users to practice presentations, and includes all processes from capturing video and audio data to analyzing and generating feedback. The present invention also incorporates an emotion engine to recognize the user's emotions and provide feedback based on the emotions.

[1558] Program processing

[1559] 1. Initial Setup:

[1560] A user logs in to the system. The device requests permission to use the camera and microphone. If the user grants permission, the device activates the camera and microphone and becomes ready.

[1561] For example, a user enters a username and password on a login screen, and the device sends this to the server. The server authenticates the user, and if successful, displays the dashboard.

[1562] 2. Start your presentation:

[1563] When the user clicks the "Start Presentation Practice" button, the device will activate the camera and microphone and begin capturing video and audio.

[1564] The device streams this data to the server in real time.

[1565] 3. Analysis and Evaluation:

[1566] The server analyzes the received video data and recognizes facial expressions and gestures, analyzing facial movements and hand movements to determine the emphasis of the presentation.

[1567] The server analyzes the audio data and evaluates the speech rate, volume, and tone, including the words per minute, whether the speech rate is appropriate, and how emotional the tone of the voice is.

[1568] 4. How the Emotion Engine Works:

[1569] The server's emotion engine analyzes the video data and recognizes the user's emotions (joy, anger, sadness, happiness, etc.). For example, if there are many smiling faces, it is judged to be a positive emotion, and if there are many tense expressions, it is judged to be a negative emotion.

[1570] 5. Feedback Generation:

[1571] The server generates feedback based on the analysis results and emotion recognition and sends it to the device, displaying real-time feedback such as "You're speaking too fast. Please speak a little more slowly."

[1572] This includes feedback from an emotion engine, which generates advice such as, "You're not smiling enough. Express more emotion."

[1573] 6. Question simulation:

[1574] The server analyzes the content of the user's presentation and automatically generates related questions, which the terminal presents to the user, who then answers them.

[1575] The user's answers are sent to a server, which evaluates them for appropriateness and clarity. For example, a question might be generated: "What is the source of the data on this slide?", and the server analyzes the data captured as the user answers.

[1576] 7. Overall evaluation and detailed report:

[1577] The server evaluates the user's overall presentation and generates a detailed feedback report that the device displays to the user, allowing them to save and share the report.

[1578] The report also includes emotional trends analyzed by the emotion engine, offering advice such as, "You remained nervous throughout the presentation. Try some relaxation techniques."

[1579] As described above, the system of the present invention provides real-time analysis of video and audio data, emotion recognition using an emotion engine, and detailed feedback to improve users' presentation skills, allowing users to instantly improve their performance and acquire effective presentation skills.

[1580] The processing flow will be explained below.

[1581] Step 1:

[1582] The user enters their username and password at the system login screen.

[1583] The terminal sends the input information to the server.

[1584] The server authenticates the user and displays the dashboard if authentication is successful, otherwise it returns an error message.

[1585] Step 2:

[1586] The device asks the user for permission to use the camera and microphone.

[1587] If the user grants permission, the device will activate the camera and microphone and become ready.

[1588] Step 3:

[1589] The user clicks the "Start Practice Presentation" button.

[1590] The device will activate the camera and microphone and begin capturing video and audio.

[1591] Step 4:

[1592] The device streams the captured video and audio data to the server in real time.

[1593] Step 5:

[1594] The server analyzes the video data it receives and recognizes facial expressions and gestures.

[1595] For example, facial movements can be analyzed to identify emotions (e.g., joy, anger, sadness, happiness), and hand movements can be analyzed to identify the emphasis of a presentation.

[1596] Step 6:

[1597] The server analyzes the received voice data and evaluates the speaking rate, volume, and tone.

[1598] Specifically, it analyzes speaking rate (number of words spoken per minute), volume (whether the voice is at an appropriate volume), and tone (how much emotion is expressed).

[1599] Step 7:

[1600] The server's emotion engine analyzes the video data and recognizes the user's emotions.

[1601] For example, frequent smiles are judged as positive emotions, while frequent frowns are judged as negative emotions.

[1602] Step 8:

[1603] The server generates feedback based on the analysis results and emotion recognition and sends it to the device.

[1604] Real-time feedback is displayed, including advice such as "You're speaking too fast. Speak a little more slowly," and emotion-based advice such as "You don't smile enough. Express more emotion."

[1605] Step 9:

[1606] The server automatically generates questions based on the presentation content.

[1607] For example, generate a question like, "What is the data source for this slide?"

[1608] The terminal presents the generated question to the user.

[1609] Step 10:

[1610] The user answers the questions.

[1611] The device captures the answers and records them as audio data.

[1612] The device sends the response data to the server in real time.

[1613] Step 11:

[1614] The server analyzes the response data and evaluates it for relevance and clarity.

[1615] For example, generate feedback such as, "The answer is unclear. Let me give you a concrete example."

[1616] Step 12:

[1617] The server evaluates the user's overall presentation and generates a detailed feedback report.

[1618] The device displays the generated report to the user and provides options to save or share it.

[1619] The report also includes emotional trends analyzed by the emotion engine, offering advice such as, "You remained nervous throughout the presentation. Try some relaxation techniques."

[1620] In this way, all processing steps in the system are performed continuously, allowing users to receive real-time feedback to improve their presentation skills and effectively practice.

[1621] Example 2

[1622] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1623] Conventional presentation practice systems are limited to basic capture and feedback functions for the user's video and audio, and lack the ability to recognize emotions or provide detailed feedback based on those emotions. As a result, users often feel limited in their ability to improve their emotional expression and presentation skills. Furthermore, the lack of question simulation and detailed reporting functions results in insufficient evaluation of the overall presentation. To address these issues, a system with emotion recognition and detailed feedback functions is needed.

[1624] The specification processing by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for capturing the user's video and audio, means for transmitting the user's video and audio data in real time, means for analyzing the video data to recognize facial expressions and gestures, means for analyzing the audio data to evaluate speaking speed, volume, and tone, means for recognizing the user's emotions using an emotion engine, and means for generating and transmitting feedback based on the analysis results and emotion recognition in real time. This allows the user to receive real-time feedback during the presentation practice process and instantly improve their performance and emotional expression. In addition, the question simulation and detailed report function allow the user to evaluate the entire presentation, allowing the user to identify more specific areas for improvement.

[1625] "Capture" refers to the process of capturing video or audio data.

[1626] "Real-time transmission" refers to the process of transmitting captured data immediately without delay.

[1627] "Analysis" refers to the process of extracting information from acquired data using specific algorithms.

[1628] "Facial expression recognition" refers to the process of identifying a user's facial expression from video data.

[1629] "Gesture recognition" refers to the process of identifying a user's hand and body movements from video data.

[1630] "Speech rate" refers to the number of words a user speaks within a given period of time.

[1631] "Volume" refers to the volume of the user's speech.

[1632] "Tone" refers to the pitch and quality of the user's voice.

[1633] "Emotion engine" refers to technology that identifies a user's emotions from video or audio data.

[1634] "Feedback" refers to evaluations and advice provided to users based on the analysis results.

[1635] "Automatic question generation" refers to the automatic creation of related questions based on the content of the presentation.

[1636] "Appropriateness" refers to the degree to which the user's answer matches the content and intent of the presentation.

[1637] "Clarity" refers to the degree to which the user's response is clear and easy to understand.

[1638] A "detailed feedback report" refers to a report that includes evaluations and sentiment analysis results for the entire presentation.

[1639] MODE FOR CARRYING OUT THE INVENTION

[1640] The present invention is a system that allows users to effectively practice presentations and includes all processes from capturing video and audio data to analyzing it and generating feedback. Furthermore, by incorporating an emotion engine, this system has the advantage of being able to recognize the user's emotions and provide feedback based on those emotions. Specific embodiments for implementing the present invention are described below.

[1641] System Configuration

[1642] This system consists of a user's device (personal computer, smartphone, tablet, etc.) and a server. The device is equipped with a camera and microphone, which are used to capture video and audio data. The server analyzes the data received in real time and generates feedback. Specific examples of hardware and software include:

[1643] Camera: A device used to capture a user's image (e.g., a webcam, a smartphone's built-in camera)

[1644] Microphone: A device used to capture the user's voice (e.g., a headset, a smartphone's built-in microphone)

[1645] Terminal: A device that captures video and audio data and transmits it to a server (e.g., a personal computer, smartphone, or tablet).

[1646] Server: Computing resources (e.g., cloud servers) for analyzing data and generating feedback

[1647] Emotion engine: Software for recognizing user emotions (e.g., Microsoft Azure Emotion API)

[1648] Speech analysis software: a program for analyzing voice data (e.g., Google Speech-to-Text API)

[1649] Video analysis software: A program for analyzing video data (e.g., OpenCV)

[1650] Processing Flow

[1651] The system process flow involves the following steps:

[1652] 1. Initial Setup:

[1653] The user logs in to the system and the device asks for permission to use the camera and microphone. If the user grants permission, the device activates the camera and microphone and becomes ready.

[1654] 2. Start your presentation:

[1655] When a user clicks the "Start Presentation Practice" button, the device activates the camera and microphone and starts capturing video and audio. The device streams this data to the server in real time.

[1656] 3. Data Analysis:

[1657] The server analyzes the received video data in real time and recognizes facial expressions and gestures. For example, facial recognition and gesture recognition are performed using OpenCV.

[1658] At the same time, the audio data is analyzed to evaluate speaking rate, volume, and tone, using the Google Speech-to-Text API.

[1659] 4. Emotion recognition:

[1660] The server's emotion engine analyzes the user's emotions, using Microsoft Azure Emotion API and other tools to recognize emotions such as joy, anger, sadness, and happiness in real time.

[1661] 5. Feedback Generation:

[1662] The server generates feedback based on the analysis results and emotion recognition and sends it to the device, providing real-time feedback on how to adjust speech rate and volume, as well as advice on improving gestures and facial expressions.

[1663] 6. Question simulation:

[1664] The server analyzes the content of the user's presentation and automatically generates related questions, such as "What is the source of the data on this slide?", and presents them to the user via their device.

[1665] 7. Overall evaluation and detailed report:

[1666] The server evaluates the user's overall presentation and generates a detailed feedback report, including information on the overall presentation structure, speaking rate, volume, emotional trends, and appropriateness of gestures. The report is then displayed to the user on the device, and can be saved or shared.

[1667] Examples of prompts:

[1668] What is the topic of your presentation?

[1669] Please briefly explain the contents of this slide.

[1670] "What is the data source for the slides?"

[1671] "What questions do you anticipate?"

[1672] "What are the most important points of your presentation?"

[1673] This system allows users to receive real-time feedback during their presentation practice, enabling them to instantly improve their skills and emotional expression. Detailed feedback reports also provide an overall evaluation of the presentation and specific areas for improvement. As a result, users can acquire effective presentation skills.

[1674] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1675] Processing steps and specific operations

[1676] Step 1: Initial Setup

[1677] A user logs in to the system.

[1678] Input: Username and Password

[1679] Output: Authentication result (success or failure)

[1680] How it works: The user enters their username and password on the login screen. The device sends this information to the server, which checks it against a database (e.g., MySQL) and authenticates them. If authentication is successful, the dashboard is displayed. Next, a popup appears requesting permission to use the camera and microphone; if the user grants permission, the camera and microphone are turned on.

[1681] Step 2: Start your presentation

[1682] The user clicks the "Start Practice Presentation" button.

[1683] Input: User click action

[1684] Output: Start capturing video and audio

[1685] How it works: When the user clicks the button, the device reactivates the camera and microphone and begins capturing video and audio. The captured data is streamed to the server in real time.

[1686] Step 3: Analyze and evaluate video and audio data

[1687] The server analyzes the received video data.

[1688] Input: Video data

[1689] Output: Facial expression and gesture recognition results

[1690] How it works: The server uses a facial recognition algorithm (e.g., OpenCV) to analyze the user's facial expressions and gestures, identifying facial and hand movements and determining the emphasis of the presentation.

[1691] The server analyzes the audio data.

[1692] Input: Audio data

[1693] Output: Speech rate, volume, and tone evaluation results

[1694] How it works: The server uses speech analysis software (e.g., the Google Speech-to-Text API) to analyze the audio data and evaluate the speech rate, volume, and tone. It determines the speech rate (words per minute), whether the volume is appropriate, and how emotional the tone is.

[1695] Step 4: Emotion Engine in Action

[1696] The server's emotion engine analyzes the video data.

[1697] Input: Video data

[1698] Output: User emotion recognition results

[1699] How it works: Using the server's emotion engine (for example, Microsoft Azure Emotion API), the system recognizes and evaluates the user's emotions (joy, anger, sadness, happiness, etc.) from video data. For example, if there are many smiling faces, it is judged to have positive emotions, and if there are many tense expressions, it is judged to have negative emotions.

[1700] Step 5: Generate feedback

[1701] The server generates feedback based on the analysis results and emotion recognition.

[1702] Input: Video and audio analysis results and emotion recognition results

[1703] Output: Feedback message

[1704] How it works: Based on the analysis results and emotion recognition, the server generates real-time feedback to the user, providing specific advice such as "You're speaking too fast. Please speak a little more slowly."

[1705] Step 6: Simulate the Question

[1706] The server automatically generates questions based on the presentation content.

[1707] Input: Presentation content data

[1708] Output: Question list

[1709] How it works: The server analyzes the presentation content and automatically generates relevant questions. These questions are then presented to the user via their device, with specific questions such as "What is the source of the data on this slide?"

[1710] Step 7: Capture and evaluate responses

[1711] The user answers the question.

[1712] Input: User's answer (video and audio)

[1713] Output: Response data

[1714] How it works: The user answers questions. The answers are captured by the device and sent to the server, which analyzes the data and evaluates the appropriateness and clarity of the answers.

[1715] Step 8: Overall evaluation and detailed report

[1716] The server gives an overall evaluation of the user's presentation.

[1717] Input: All analysis results and feedback data

[1718] Output: Detailed feedback report

[1719] How it works: The server evaluates the user's overall presentation and generates a detailed feedback report that includes information on the presentation's structure, speaking rate, volume, emotional trends, and appropriateness of gestures. The report is displayed to the user via their device. The user can save and share the report.

[1720] (Application example 2)

[1721] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1722] In today's virtual stores, it is difficult for salespeople to practice their customer service skills efficiently and effectively. In particular, there is a need for a method to improve their ability to respond to specific questions while receiving real-time feedback. Furthermore, there is a lack of methods to recognize emotions during customer service and provide advice based on those emotions.

[1723] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for capturing video and audio of the user, means for transmitting the video and audio to the server, means for analyzing the video data to recognize facial expressions and movements, means for analyzing the audio data to evaluate speaking speed, volume, and tone of voice, means for generating feedback based on the analysis results and transmitting the feedback to the terminal, and means for a salesperson to pose simulated questions as a virtual customer and capture and evaluate the answers. This enables salespeople to efficiently and effectively improve their customer service skills and improve their ability to respond to specific questions while receiving real-time feedback.

[1724] "User" refers to the person or role that operates the system and provides video and audio data.

[1725] "Video and audio capture means" refers to a combination of hardware and software for obtaining video and audio data of a user.

[1726] "Means for transmitting to the server in real time" refers to a communication means for transferring the acquired video and audio data to the server immediately without delay.

[1727] "Server" refers to a central processing unit for performing the process of data analysis and feedback generation.

[1728] "Means for recognizing facial expressions and movements" refers to algorithms or software that analyze video data to recognize the user's facial expressions and body movements.

[1729] "Means for assessing speaking rate, volume, and tone of voice" refers to algorithms or software that analyzes audio data and assesses speaking rate, volume, and tone of voice.

[1730] "Means for generating and transmitting feedback based on the analysis results to the terminal" refers to a system for generating feedback based on data analysis and transmitting it to the user's device.

[1731] "Salesperson" refers to the person or role that serves customers in a virtual store.

[1732] The "means for presenting simulated questions to a virtual customer and capturing and evaluating the responses" is a means for automatically generating questions that a virtual customer might ask, obtaining the user's responses to those questions, and evaluating their appropriateness and clarity.

[1733] The present invention is a system for improving the customer service skills of salespeople in a virtual store. The system of the present invention captures video and audio data of users (salespeople) and transmits them to a server in real time to analyze the salespeople's customer service performance and provide feedback.

[1734] Hardware and software used

[1735] 1. Hardware

[1736] Camera: Used to capture video of the user.

[1737] Microphone: Used to capture the user's voice.

[1738] Smartphones and head-mounted displays (HMDs): Used as the user's devices to display feedback, etc.

[1739] 2. Software

[1740] Emotion engine: Analyzes the user's video data, recognizes and evaluates facial expressions and movements.

[1741] Voice Analysis Module: Analyzes the user's voice data and evaluates speaking rate, volume, and tone of voice.

[1742] Feedback generation module: Generates feedback based on the analysis results and sends it to the device.

[1743] Question generation module: simulates questions from virtual customers and presents them to the user.

[1744] Evaluation module: Evaluates user responses and analyzes their appropriateness and clarity.

[1745] How it works

[1746] 1. User Preparation

[1747] The system is ready when the user logs in to the system and gives permission to use the camera and microphone. Specifically, the user enters their username and password on the terminal, and the system performs authentication.

[1748] 2. Start customer service practice

[1749] When the user presses the "Start customer service practice" button, the camera and microphone are activated and video and audio capture begins. The data is sent to the server in real time.

[1750] 3. Data Analysis

[1751] The server analyzes the received video data and recognizes facial expressions and movements. The emotion engine analyzes the user's emotions and identifies feelings such as tension or joy.

[1752] The server analyzes the audio data and evaluates speaking rate, volume, and tone of voice, which is done by the audio analysis module.

[1753] 4. Feedback Generation

[1754] Based on the analysis results, the feedback generation module generates appropriate feedback, which is sent to the terminal and displayed to the user in real time.

[1755] 5. Question Simulation

[1756] The question generation module automatically generates questions based on the customer service content and displays them on the terminal. The user captures the answers and sends them to the server.

[1757] 6. Overall evaluation and report

[1758] The server evaluates the user's overall customer service and generates a detailed feedback report, which is displayed on the device and can be saved or shared.

[1759] Specific examples

[1760] As a specific example, this system can be used in souvenir shops at tourist spots or virtual stores of home appliances to help sales staff improve their specific customer service skills.

[1761] Prompt Sentence Examples

[1762] We are developing an application for virtual store salespeople to practice customer service. The system uses a camera and microphone to capture video and audio, and analyzes and provides feedback on the salespeople's customer service skills and emotions in real time. Please explain how this system works.

[1763] The system of the present invention helps salespeople efficiently and effectively improve their customer service skills, improving their ability to respond to specific questions while receiving real-time feedback.

[1764] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1765] Step 1: Initial Setup

[1766] A user logs in to the system and gives permission to use the camera and microphone. This causes the device to activate the camera and microphone and enter a ready state. The input data is the user's login information, and the output is the camera and microphone activation readiness.

[1767] Step 2: Start practicing customer service

[1768] When the user presses the "Start customer service practice" button, the device activates the camera and microphone and begins capturing video and audio. The captured data is sent to the server in real time. The input data is the user's operation, and the output is streaming video and audio data.

[1769] Step 3: Analyzing the video data

[1770] The server analyzes the received video data and recognizes facial expressions and movements. Specifically, it analyzes facial movements and hand gestures. The input data is video frames, and the output is the recognition results of facial expressions and movements. An emotion engine is used to identify emotions.

[1771] Step 4: Analyzing the audio data

[1772] The server analyzes the received audio data and evaluates the speaking rate, volume, and tone of voice. Specifically, it analyzes the speaking rate, volume, and tone of voice. The input data is an audio stream, and the output is the evaluation results of the speaking rate, volume, and tone of voice.

[1773] Step 5: Generate feedback

[1774] The server generates feedback based on the analysis of the video and audio data and sends it to the device. For example, it may include specific advice such as "You're speaking too fast. Speak a little more slowly" or "You don't smile enough. Express more emotion." The input data is the analysis results, and the output is the feedback message.

[1775] Step 6: Simulate the Question

[1776] The server automatically generates questions for virtual customers based on the customer service content and sends them to the terminal. The user provides answers to the questions, and the answers are captured by the server. The input data is the customer service content, and the output is the generated questions and their answers.

[1777] Step 7: Evaluate your responses

[1778] The server analyzes the user's answers and evaluates them for appropriateness and clarity. For example, it determines whether the answer to the question "What is the data source for this slide?" is appropriate. The input data is the user's answers, and the output is the evaluation result.

[1779] Step 8: Overall evaluation and report generation

[1780] The server evaluates the entire customer service and generates a detailed feedback report. The report includes good points and areas for improvement during the customer service, as well as emotional trends analyzed by the emotion engine. This report is displayed on the terminal and can be saved and shared by the user. The input data are all analysis results, and the output is a feedback report.

[1781] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1782] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1783] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1784] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1785] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1786] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1787] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1788] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1789] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1790] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1791] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1792] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1793] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1794] 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.

[1795] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1796] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1797] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1798] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1799] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1800] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1801] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1802] The following is further disclosed regarding the above embodiment.

[1803] (Claim 1)

[1804] means for capturing video and audio of a user;

[1805] means for transmitting user video and audio data to a server in real time;

[1806] A means for the server to analyze the video data and recognize facial expressions and gestures;

[1807] means for the server to analyze the voice data and evaluate speaking rate, volume, and tone;

[1808] A means for the server to generate feedback based on the analysis result and transmit it to the terminal;

[1809] The system includes a means for a user to receive playback feedback.

[1810] (Claim 2)

[1811] A means for the server to automatically generate questions based on the content of the presentation and send them to the terminal;

[1812] a means for the user to capture and transmit answers to the questions to a server;

[1813] 10. The system of claim 1, wherein the server includes means for analyzing and evaluating the answers for appropriateness and clarity.

[1814] (Claim 3)

[1815] a means for the server to perform an overall evaluation of the user's presentation and generate a detailed feedback report;

[1816] 10. The system of claim 1, wherein the terminal includes means for displaying the report to a user and allowing the report to be saved and shared.

[1817] "Example 1"

[1818] (Claim 1)

[1819] means for capturing video and audio of a user;

[1820] means for transmitting user video and audio data to a server in real time;

[1821] A means for the server to analyze the video data and recognize facial expressions and gestures;

[1822] means for the server to analyze the voice data and evaluate speaking rate, volume, and tone;

[1823] A means for the server to generate feedback based on the analysis result and transmit it to the terminal;

[1824] a means for the user to receive the reproduced feedback;

[1825] a means for automatically generating questions based on the presentation content;

[1826] A means to analyze the data queried, make a comprehensive assessment and generate a detailed report;

[1827] The system includes a means for the device to display detailed reports to the user and for them to be saved and shared.

[1828] (Claim 2)

[1829] A means for the server to automatically generate questions based on the content of the presentation and send them to the terminal;

[1830] a means for the user to capture and transmit answers to the questions to a server;

[1831] 10. The system of claim 1, wherein the server includes means for analyzing and evaluating the answers for appropriateness and clarity.

[1832] (Claim 3)

[1833] a means for the server to perform an overall evaluation of the user's presentation and generate a detailed feedback report;

[1834] 10. The system of claim 1, wherein the terminal includes means for displaying the report to a user and allowing the report to be saved and shared.

[1835] "Application Example 1"

[1836] (Claim 1)

[1837] means for capturing video and audio of a user;

[1838] means for transmitting user video and audio data to a server in real time;

[1839] A means for the server to analyze the video data and recognize facial expressions and gestures;

[1840] means for the server to analyze the voice data and evaluate speaking rate, volume, and tone;

[1841] A means for the server to generate feedback based on the analysis result and transmit it to the terminal;

[1842] A means for the server to automatically generate questions based on the content of the customer service provided to the user and transmit the questions to the terminal;

[1843] The system includes a means for a user to receive playback feedback.

[1844] (Claim 2)

[1845] A means for the server to automatically generate questions based on the content of the customer service provided to the user and transmit the questions to the terminal;

[1846] a means for the user to capture and transmit answers to the questions to a server;

[1847] 10. The system of claim 1, wherein the server includes means for analyzing and evaluating the answers for appropriateness and clarity.

[1848] (Claim 3)

[1849] A means for the server to evaluate the user's overall customer service and generate a detailed feedback report;

[1850] 10. The system of claim 1, wherein the terminal includes means for displaying the report to a user and allowing the report to be saved and shared.

[1851] "Example 2: Combining Emotion Engines"

[1852] (Claim 1)

[1853] means for capturing video and audio of a user;

[1854] means for transmitting user video and audio data to a server in real time;

[1855] A means for the server to analyze the video data and recognize facial expressions and gestures;

[1856] means for the server to analyze the voice data and evaluate speaking rate, volume, and tone;

[1857] A means for the server to recognize the user's emotion using an emotion engine;

[1858] A means for the server to generate feedback based on the analysis results and emotion recognition and transmit the feedback to the terminal;

[1859] A system that includes a means for users to receive real-time feedback.

[1860] (Claim 2)

[1861] A means for the server to automatically generate questions based on the content of the presentation and send them to the terminal;

[1862] a means for the user to capture and transmit answers to the questions to a server;

[1863] 10. The system of claim 1, wherein the server includes means for analyzing and evaluating the answers for appropriateness and clarity.

[1864] (Claim 3)

[1865] a means for the server to perform an overall evaluation of the user's presentation and generate a detailed feedback report;

[1866] 10. The system of claim 1, wherein the terminal includes means for displaying the report to a user and allowing the report to be saved and shared.

[1867] "Application example 2 when combining emotion engines"

[1868] (Claim 1)

[1869] means for capturing video and audio of a user;

[1870] means for transmitting user video and audio data to a server in real time;

[1871] A means for the server to analyze the video data and recognize facial expressions and movements;

[1872] means for the server to analyze the voice data and evaluate the speaking rate, volume, and tone of voice;

[1873] A means for the server to generate feedback based on the analysis result and transmit it to the terminal;

[1874] a means for a salesperson to pose simulated questions as a virtual customer and to capture and evaluate the responses;

[1875] The system includes a means for a user to receive playback feedback.

[1876] (Claim 2)

[1877] A means for the server to automatically generate questions based on the customer service content and send them to the terminal;

[1878] a means for the user to capture and transmit answers to the questions to a server;

[1879] 10. The system of claim 1, wherein the server includes means for analyzing and evaluating the answers for appropriateness and clarity.

[1880] (Claim 3)

[1881] A means for the server to perform a comprehensive evaluation of the user's customer service and generate a detailed feedback report;

[1882] 10. The system of claim 1, wherein the terminal includes means for displaying the report to a user and allowing the report to be saved and shared. [Explanation of symbols]

[1883] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for capturing video and audio of a user; means for transmitting user video and audio data to a server in real time; A means for the server to analyze the video data and recognize facial expressions and gestures; means for the server to analyze the voice data and evaluate speaking rate, volume, and tone; A means for the server to generate feedback based on the analysis result and transmit it to the terminal; The system includes a means for a user to receive playback feedback.

2. A means for the server to automatically generate questions based on the content of the presentation and send them to the terminal; a means for the user to capture and transmit answers to the questions to a server; 10. The system of claim 1, wherein the server includes means for analyzing and evaluating answers for appropriateness and clarity.

3. a means for the server to perform an overall evaluation of the user's presentation and generate a detailed feedback report; 10. The system of claim 1, wherein the terminal includes means for displaying the report to a user and allowing the report to be saved and shared.

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