System

Abstract

A system is provided.SOLUTION: A system, comprising: means for a user to input presentation materials; means for the user to record a presentation practice video; means for a server to analyze the presentation materials and the presentation practice video; means for the server to identify specific improvements based on the analysis results; means for the server to generate feedback animations based on the improvements; and means for the server to provide the feedback animations to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Traditional presentation practice methods rely on self-evaluation and subjective feedback from colleagues, making it difficult to improve objectively and efficiently. Furthermore, because specific areas for improvement are not clear, it is difficult to improve quality no matter how many times you practice. Furthermore, it is difficult to approach the presentation with final confidence and peace of mind on the day of the presentation. [Means for solving the problem]

[0005] To solve this problem, the present invention provides the following means. The system includes a means for a user to input presentation materials, a means for the user to record a presentation practice video, a server to analyze the presentation materials and the presentation practice video, a means for the server to identify specific areas for improvement based on the analysis results, a means for the server to generate a feedback video based on the areas for improvement, and a means for the server to provide the feedback video to the user. The system also includes a means for the user to practice the presentation again based on the feedback video and upload the re-recorded presentation practice video to the server. The system also includes a means for the server to generate a final checklist and points to note for the presentation and provide them to the user. This allows the quality of presentations to be improved efficiently and objectively, enabling participants to present with confidence on the day.

[0006] "User" refers to any individual or organization that delivers a presentation and seeks to improve its quality by using the system.

[0007] "Presentation materials" refers to the format of slides and document files used in presentations, including PowerPoint files and PDF files.

[0008] "Presentation practice video" refers to a video file in which a user records a rehearsal of a presentation.

[0009] A "terminal" is a device that allows users to input presentation materials, record presentation practice videos, and check feedback videos, and refers to devices such as PCs and smartphones.

[0010] "Server" refers to a centralized control device for analyzing presentation materials and practice videos, and generating and providing feedback.

[0011] "Analyzing" refers to analyzing the contents of presentation materials and practice videos and evaluating the performance.

[0012] "Improvements" refers to specific corrections or changes needed to improve the quality of your presentation.

[0013] "Feedback Video" refers to a video file generated by the server that visually shows specific improvements to the user's presentation.

[0014] A "checklist" is a document that lists the things to pay attention to and procedures to follow on the day of the presentation.

[0015] "Points to note" refers to points or advice that you should pay particular attention to when giving a presentation. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

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

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

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

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0031] 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.

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

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] This invention is a system that aims to enable users to efficiently improve the quality of their presentations. This system is composed of a series of processes: the user inputs presentation materials, practices the presentation based on those materials, the server analyzes the content, and provides feedback on areas for improvement.

[0038] System configuration

[0039] The system consists of the following main components:

[0040] 1. User's device: This is the device used to input presentation materials, record practice videos, and check feedback videos.

[0041] 2. Server: A device that analyzes the received presentation materials and practice videos, and generates and manages feedback.

[0042] User Flow

[0043] 1. User enters presentation materials:

[0044] Users upload PowerPoint files or presentation materials in PDF format to the server via their terminal.

[0045] For example, a user uploads a presentation document introducing a new product that the user has created to the application.

[0046] 2. User records a practice video of their presentation:

[0047] The user uses the device's camera function to record the presentation practice.

[0048] For example, a user rehearses a presentation at home and records the rehearsal on video.

[0049] 3. The server analyzes the presentation materials and practice video:

[0050] The server analyzes the presentation materials received and evaluates the structure and content of the slides.

[0051] The server analyzes the presentation practice video and evaluates performance such as facial expressions, pronunciation, posture, and gestures.

[0052] For example, the server analyzes the volume, intonation, and eye movements of the user's voice and compares them with certain standards.

[0053] 4. The server identifies specific areas for improvement:

[0054] Based on the analysis results, the server lists specific areas for improvement for each element of the presentation.

[0055] For example, identify advice such as "Look more at the audience on slide 3" or "Increase your intonation."

[0056] 5. The server generates the feedback video:

[0057] The server creates a feedback video that reflects the improvements.

[0058] For example, a video can be generated that overlays the user's video to show areas for improvement.

[0059] 6. The server provides the feedback video:

[0060] The server transmits the generated feedback video to the user's terminal.

[0061] For example, the user plays the feedback video on the device and identifies specific areas for improvement.

[0062] 7. User re-practices:

[0063] The user practices the presentation again based on the feedback video and records a new video.

[0064] For example, the user may incorporate the improvements suggested, re-record the presentation, and upload it to the server.

[0065] 8. The server provides a final checklist and notes:

[0066] The server generates a final checklist for the presentation and points to be noted on the day, and provides it to the user.

[0067] For example, make a list of final check points such as "keep your voice tone consistent" and "move your eyes when changing slides."

[0068] In this way, the system of the present invention provides specific feedback that allows users to efficiently improve the quality of their presentation, allowing them to approach the day of the presentation with confidence.

[0069] The processing flow will be explained below.

[0070] Step 1:

[0071] The user inputs the presentation materials. The user prepares the materials to be used in the presentation, such as PowerPoint files or PDF files, and uploads the files to the presentation application using the device.

[0072] Step 2:

[0073] The device sends the presentation materials received from the user to the server, where the files are uploaded to the server using a secure protocol.

[0074] Step 3:

[0075] The server receives the presentation materials and begins analyzing them. The server evaluates the text content, slide structure, visual elements, etc. of the materials and performs an initial analysis based on the presentation quality criteria.

[0076] Step 4:

[0077] A user records a practice video of a presentation. A user uses the device's camera to record a rehearsal of a presentation at home or in the office.

[0078] Step 5:

[0079] Users can save and upload recorded presentation practice videos to their devices. Users select the video file in the application and send it to the server.

[0080] Step 6:

[0081] The server receives the presentation practice video and passes it to an analysis tool to evaluate facial expression recognition, speech analysis, posture detection, and gestures.

[0082] Step 7:

[0083] The server identifies areas for improvement based on the video analysis results. It compares the user's performance with standard presentation metrics and lists specific areas for improvement, such as "correcting eye position" and "adjusting voice tone."

[0084] Step 8:

[0085] The server generates a feedback video, which includes points for improvement based on the analysis results, and provides it to the user in a format that is easy to understand.

[0086] Step 9:

[0087] The server sends the generated feedback video to the terminal, where it is displayed in the user's application.

[0088] Step 10:

[0089] The user checks the feedback video. They watch the feedback video on their device and understand the specific areas for improvement.

[0090] Step 11:

[0091] The user practices the presentation again based on the feedback video. They then record a new practice video, keeping in mind the areas for improvement.

[0092] Step 12:

[0093] The user uploads a new presentation practice video to the device, which then sends the video to the server again via the device, ready to receive further feedback.

[0094] Step 13:

[0095] The server generates a final checklist and points to note for the presentation. Based on the final analysis results, the server creates a list of points that the user should pay attention to on the day of the presentation and a list of points to note for optimal performance.

[0096] Step 14:

[0097] The server sends the final checklist and notes to the terminal, which is displayed in the user's application and serves as a final confirmation.

[0098] Step 15:

[0099] The user reviews the final checklist and points to note. Using the information provided, the user makes final preparations for the presentation, allowing them to present with confidence.

[0100] Example 1

[0101] 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."

[0102] Conventional presentation practice systems require users to practice unilaterally, making it difficult for them to receive effective feedback. This makes it difficult for users to objectively evaluate the quality of their presentations and identify specific areas for improvement. The present invention aims to provide a system that allows users to efficiently improve the quality of their presentations through specific feedback provided by a server when practicing a presentation.

[0103] 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.

[0104] In this invention, the server includes means for a user to input presentation materials, means for a user to record a presentation practice video, means for the server to analyze the presentation materials and the presentation practice video, means for the server to identify specific areas for improvement based on the analysis results, means for the server to generate a feedback video based on the areas for improvement, means for the server to provide the feedback video to the user, and means for the server to send a link to the feedback video to the user, so that the user can receive specific feedback after practicing their presentation and practice again based on that feedback.

[0105] "User" refers to a person who creates presentation materials and practices them.

[0106] "Presentation materials" refers to slides and document files (e.g., PowerPoint files or PDF format) used to explain the contents of the presentation.

[0107] "Presentation practice video" refers to a video recorded by a user practicing a presentation.

[0108] "Server" refers to an information processing device for analyzing presentation materials and practice videos and providing feedback.

[0109] "Means for Analysis" refers to the software and algorithms used by the Server to analyze and evaluate the content of presentation materials and practice videos.

[0110] "Means for identifying areas for improvement" refers to the algorithms and software that the server uses to list specific areas for improvement in the presentation based on the analysis results.

[0111] "Feedback video" refers to a video provided to a user in which specific improvements are added as an overlay to the user's presentation practice video.

[0112] "Means for sending a link" refers to the means (e.g., email or in-app notification) for notifying the user of the URL of the feedback video generated by the server.

[0113] The present invention is a system that aims to enable users to efficiently improve the quality of their presentations, and a series of processes are carried out through cooperation between the user's terminal and a server. Detailed embodiments will be described below.

[0114] 1. System Configuration

[0115] The system mainly consists of the following components:

[0116] User's device: A device used to input presentation materials, record practice videos, and check feedback videos. This can be a PC or smartphone.

[0117] Server: An information processing device that analyzes the received presentation materials and practice videos, and generates and manages feedback.

[0118] 2. Hardware and Software Used

[0119] On the user's device:

[0120] Devices (PC, smartphone)

[0121] Management applications (e.g. cloud storage apps, camera apps)

[0122] Recording application (e.g. standard camera app)

[0123] server:

[0124] Server with high-performance CPU and RAM

[0125] Analysis software (e.g., natural language processing tools, image analysis tools)

[0126] AI models (e.g., generative AI, machine learning algorithms)

[0127] Video editing software (e.g., video editing tools, overlay adding functions)

[0128] Data transmission software (e.g., cloud storage, distribution software)

[0129] 3. Example of operation

[0130] The user enters the presentation materials

[0131] Users upload presentation materials (e.g., slides introducing new products) to the system using their own terminals. Once uploaded, the materials are stored on the server.

[0132] Users record practice videos for their presentations

[0133] Users can record their presentation rehearsals using a camera app at home or in the office, press the "Start Recording" button to practice, and then press the "Stop Recording" button when they're done. They can then upload the video to the system.

[0134] The server analyzes the presentation materials and practice videos.

[0135] The server receives the materials and analyzes the content of the slides using natural language processing tools, while for videos, it uses image and audio analysis tools to evaluate the user's facial expressions, speech, posture, and gestures.

[0136] For example, it analyzes the volume and intonation of the user's voice and eye movements and compares them with pre-set standards.

[0137] The server identifies specific areas for improvement

[0138] The server runs an AI model based on the analyzed data and generates a list of specific improvements to the presentation, such as "focus your gaze more on the audience on the third slide" or "improve your intonation."

[0139] The server generates the feedback video

[0140] The server uses video editing software to generate a feedback video with overlays of improvements, for example adding a suggestion to "smile more" to the user's video.

[0141] The server provides the feedback video

[0142] Once the feedback video is generated, the server will upload it to the cloud storage and send the link to the user, who can click the link to play the feedback video.

[0143] The user practices again based on the feedback video.

[0144] The user watches the feedback video, understands what needs to be improved, and practices the presentation again. The newly recorded video is then uploaded to the server again.

[0145] 4. Example prompts for generative AI models

[0146] Below is an example of a prompt sentence to input to the generative AI model.

[0147] "Analyze the practice video of the presentation and provide suggestions for improvement. Please point out specific areas that need improvement (e.g., eye contact, vocalization, gestures) and generate a feedback video."

[0148] As described above, the system of the present invention provides specific feedback to users to help them efficiently improve the quality of their presentations, allowing them to approach the day of their presentation with confidence.

[0149] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0150] Step 1:

[0151] The user enters the presentation materials

[0152] Input: Presentation materials (PowerPoint files or PDF format)

[0153] Specific operation: The user uses the device to open the management application, clicks the "Select File" button, selects the presentation material to upload, and then clicks the "Upload" button.

[0154] Data processing / calculation: Uploaded files are sent to the server and stored there.

[0155] Output: The presentation materials are saved on the server.

[0156] Step 2:

[0157] Users record practice videos for their presentations

[0158] Input: Presentation practice video

[0159] Specific operation: The user opens the camera app on their device, clicks the "Start Recording" button, starts speaking, and then clicks the "Stop Recording" button when the rehearsal is over. The recorded video is then uploaded to the system.

[0160] Data processing / calculation: The recorded video file is sent from the device to the server and stored on the server.

[0161] Output: The presentation practice video will be saved on the server.

[0162] Step 3:

[0163] The server analyzes the presentation materials and practice videos.

[0164] Input: Presentation materials, Presentation practice video

[0165] Specific behavior:

[0166] The server receives the presentation materials and uses natural language processing (NLP) tools to analyze the content of the slides, for example, analyzing the frequency of important keywords and the structure of the slides.

[0167] For presentation practice videos, image and audio analysis tools are used to evaluate the user's facial expressions, clarity of speech, posture, and gestures.

[0168] Data processing / calculation: Generate analysis results of presentation materials and practice videos (e.g., voice volume, intonation, eye movements).

[0169] Output: Analysis results

[0170] Step 4:

[0171] The server identifies specific areas for improvement

[0172] Input: Analysis results

[0173] Specific actions: The server runs the AI ​​model based on the analysis results and lists specific improvements for each element of the presentation, such as "focus your eyes more on the audience on the third slide" or "improve your intonation."

[0174] Data processing / calculation: Using the analysis results, an algorithm is run to extract areas for improvement.

[0175] Output: Identified improvements

[0176] Step 5:

[0177] The server generates the feedback video

[0178] Input: Identified areas for improvement, Presentation practice video

[0179] What it does: The server uses video editing software to generate a feedback video by overlaying identified areas for improvement onto the presentation practice video, for example, by overlaying a suggestion like "Smile more."

[0180] Data processing / calculation: Create a feedback video with improvements added as an overlay.

[0181] Output: Feedback video

[0182] Step 6:

[0183] The server provides the feedback video

[0184] Input: Feedback video

[0185] Specific operation: The server uploads the generated feedback video to cloud storage and notifies the user of the link, which the user can click to play the feedback video.

[0186] Data processing / calculation: Uploading videos to cloud storage and generating links.

[0187] Output: Feedback video link

[0188] Step 7:

[0189] The user re-practices

[0190] Input: Feedback video

[0191] Specific actions: Based on the feedback video, the user practices the presentation again, incorporating specific improvements. The newly recorded video is then uploaded to the server again.

[0192] Data processing / calculation: Generate a new practice video that reflects the improvements and upload it to the server.

[0193] Output: New presentation practice video

[0194] Step 8:

[0195] The server provides a final checklist and points to note

[0196] Input: Final presentation practice video, analysis results

[0197] Specific operation: Based on the final analysis results, the server generates a final checklist and points to note for the presentation, such as "keep your voice consistent" and "move your eyes when changing slides."

[0198] Data processing / calculation: Automatic generation of final checklist and notes.

[0199] Output: Final checklist and notes PDF

[0200] Through these steps, the system provides users with the feedback and support they need to efficiently improve the quality of their presentations.

[0201] (Application example 1)

[0202] 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."

[0203] Conventional systems for improving the quality of presentations have the drawback of making it difficult for users to receive specific feedback in real time when practicing their presentations, making it difficult to practice and improve efficiently.In particular, in factories and other workplaces, it is necessary to explain new processes and provide training on operation methods quickly and accurately, and real-time feedback is required.

[0204] 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.

[0205] In this invention, the server includes means for a user to input presentation materials, means for the user to record a presentation practice video, means for the server to analyze the presentation materials and the presentation practice video, means for the server to identify specific areas for improvement based on the analysis results, means for the server to generate a feedback video based on the areas for improvement, means for the server to provide the feedback video to the user, and means for the user to check the feedback in real time. As a result, when a user practices a presentation, the recorded video can be analyzed on the spot and feedback indicating specific areas for improvement can be provided in real time, allowing the quality of the presentation to be improved quickly and efficiently.

[0206] "User" refers to the individual or entity who inputs presentation materials and records practice videos.

[0207] "Presentation materials" refers to digital files that contain documents, slides, charts, etc. that illustrate the content of a presentation.

[0208] "Presentation practice video" refers to footage of a presentation that a user has recorded for practice purposes.

[0209] "Server" refers to a computer system that analyzes presentation materials and practice videos, identifies areas for improvement, and generates and provides feedback videos.

[0210] "Analysis" refers to the process of evaluating and examining the content of the presentation materials and practice video to identify areas for improvement.

[0211] "Improvements" refers to changes or modifications that may be required to improve the quality of the user's presentation.

[0212] "Feedback video" refers to a video generated by the server that includes specific advice and comments on the user's presentation.

[0213] "Real-time feedback" refers to feedback provided instantly while a user is performing a practice presentation.

[0214] This invention is a system for improving the quality of presentations, which handles everything from inputting presentation materials to providing feedback. This system mainly consists of the following elements:

[0215] 1. On the user's device:

[0216] First, the user uploads presentation materials to the server via their device. Presentation materials can be slides, PDFs, images, etc., and the user can send them from their device to the server. Next, the user uses the device's camera function to record a practice video for the presentation. The recorded video is automatically uploaded to the server.

[0217] 2. Server:

[0218] The server analyzes the received presentation materials and practice videos, including slide content evaluation, voice volume and intonation, eye movements, posture, and gestures. Based on these analysis results, the server uses a generative AI model to identify specific areas for improvement.

[0219] 3. Providing Feedback:

[0220] Based on the analysis results, the server generates a feedback video containing specific areas for improvement. This feedback video is then provided to the user's device. The user can also view the feedback in real time by wearing smart glasses. This allows the user to understand the areas for improvement on the spot and immediately incorporate them into their practice.

[0221] A specific example is a training session on how to operate a new process in a factory. Factory workers wear smart glasses and record themselves demonstrating the operation of the new process. The recorded video is uploaded to a server, which analyzes the video content and provides specific feedback on areas for improvement. The feedback is displayed in real time on the smart glasses, allowing the workers to immediately implement the improvements.

[0222] Example prompt sentence:

[0223] "When training factory workers on a new assembly process, create a demo system that allows them to record themselves using smart glasses and provide real-time feedback on areas for improvement. The system would analyze the video, evaluate assembly accuracy and efficiency, and provide specific feedback on the smart glasses."

[0224] This system not only improves the quality of presentations quickly and efficiently, but also effectively supports the learning of new processes in factories and other workplaces.

[0225] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0226] Step 1:

[0227] User uploads presentation materials

[0228] First, the user selects presentation materials from their own device and uploads them to the server. The input is the presentation material file (slides, PDF, etc.) saved on the user's device, and the output is the same material saved on the server. Data processing involves transferring the material file to the server, checking the file format, and converting it into an analyzable format.

[0229] Step 2:

[0230] Users record practice videos for their presentations

[0231] A user uses the device's camera to record a presentation practice video. Once recording is complete, the video file is uploaded to the server. The input is the video feed recorded by the camera, and the output is the practice video file stored on the server. Data processing involves compressing and formatting the video for efficient transfer to the server.

[0232] Step 3:

[0233] The server analyzes the presentation materials and practice videos.

[0234] The server analyzes the uploaded presentation materials and practice videos. The input is the presentation materials and practice videos stored on the server, and the output is the analysis results. Data calculation involves using a generative AI model to evaluate the content of the slides, analyze the volume and intonation of the voice, eye movements, posture, and gestures.

[0235] Step 4:

[0236] The server identifies specific areas for improvement

[0237] The server extracts specific improvement points based on the analysis results. The input is the analysis results obtained in step 3, and the output is a list of improvement points. Data calculation is to compare the analysis data with the good performance standards of the existing presentation and identify the differences.

[0238] Step 5:

[0239] The server generates the feedback video

[0240] The server generates a feedback video that reflects specific improvements. The input is a list of improvements and the original practice video, and the output is the feedback video. Data processing involves adding graphics and text indicating the improvements as an overlay on the original practice video.

[0241] Step 6:

[0242] The server provides the feedback video

[0243] The server provides the generated feedback video to the user. The input is the feedback video, and the output is a feedback video link that can be played on the user's device. The data processing involves converting the feedback video into an appropriate format and uploading it to cloud storage for user access.

[0244] Step 7:

[0245] Users practice again based on feedback

[0246] The user reviews the feedback video, reflects the improvements, practices the presentation again, and records the video. The input is the feedback video and the newly recorded practice video, and the output is the re-uploaded practice video. Data calculation involves adjusting the practice content based on the improvements suggested by the user.

[0247] Step 8:

[0248] The server provides a final checklist and points to note

[0249] The server analyzes the user's final presentation practice video and provides a final checklist and points to note. The input is the final practice video, and the output is the final checklist and a list of points to note. The data calculation analyzes the final practice video and once again confirms the necessary improvements and points to note.

[0250] 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.

[0251] The present invention is a system that allows users to efficiently improve the quality of their presentations, and in particular provides more advanced feedback by combining it with an emotion engine that recognizes the user's emotions.

[0252] System configuration

[0253] The system consists of the following main components:

[0254] 1. User's device: This is the device used to input presentation materials, record practice videos, and check feedback videos and emotional feedback.

[0255] 2. Server: A device that analyzes presentation materials, practice videos, and user emotional data, and generates and manages feedback.

[0256] 3. Emotion engine: It has the function to recognize the user's emotions and generate feedback accordingly.

[0257] User Flow

[0258] 1. User enters presentation materials:

[0259] Users upload PowerPoint files or presentation materials in PDF format to the server via their terminals.

[0260] For example, a user uploads a presentation document introducing a new product that the user has created to the application.

[0261] 2. User records a practice video of their presentation:

[0262] Users use the device's camera to record their presentation rehearsals, and the device also collects emotional data such as facial expressions and tone of voice.

[0263] For example, a user rehearses at home, records the rehearsal on video, and simultaneously collects emotional data.

[0264] 3. The server analyzes the presentation materials and practice video:

[0265] The server analyzes the content of the presentation materials and practice videos received, evaluating the structure, content, and performance of the slides. The emotion engine also analyzes the user's emotions.

[0266] For example, the server analyzes the user's emotions from the volume of their voice, intonation, eye movements, and facial expressions, and compares them with standard presentation metrics.

[0267] 4. The server identifies specific areas for improvement and emotional feedback:

[0268] Based on the analysis results, the server identifies specific areas for improvement for each element of the presentation, while the emotion engine provides optimal emotional feedback based on the user's emotional data.

[0269] For example, in addition to corrections such as "correct your gaze position" and "adjust your tone of voice," it identifies emotion-based advice such as "try to relax a bit more."

[0270] 5. The server generates the feedback video and emotional feedback:

[0271] The server creates a feedback video that reflects the improvements and simultaneously generates a video that includes emotional feedback.

[0272] For example, it generates a video that overlays areas for improvement on the user's video and adds emotion-based comments such as "Speak with more confidence here."

[0273] 6. The server provides the feedback video:

[0274] The server sends the generated feedback video to the user's device, where the user can view the video and understand specific improvements and emotional feedback.

[0275] 7. User re-practices:

[0276] The user practices the presentation again based on the feedback video and emotional feedback, records a new video, and recollects emotional data.

[0277] 8. The server provides a final checklist and notes for the presentation:

[0278] The server generates a checklist of points to note on the day of the presentation based on the final analysis results and emotional feedback, and sends it to the user.

[0279] In this way, the system of the present invention provides not only specific feedback but also emotional feedback to highly improve the user's presentation skills, supporting them to approach the day of the presentation with confidence.

[0280] The processing flow will be explained below.

[0281] Step 1:

[0282] The user inputs the presentation materials. The user prepares the presentation materials in PowerPoint or PDF format and uploads the files to the presentation application using the terminal.

[0283] Step 2:

[0284] The device sends the presentation materials received from the user to the server, where the files are uploaded to the server using a secure protocol.

[0285] Step 3:

[0286] The server receives the presentation materials and begins analyzing them. The server evaluates the text content, slide structure, visual elements, etc. of the materials and performs an initial analysis based on the presentation quality criteria.

[0287] Step 4:

[0288] The user records a video of their presentation practice. The user rehearses their presentation at home or in the office using the device's camera. At the same time, the device also collects emotional data such as the user's facial expressions and tone of voice.

[0289] Step 5:

[0290] Users can save and upload recorded presentation practice videos to their devices. Users select the video file in the application and send it to the server.

[0291] Step 6:

[0292] The server receives the presentation practice video. The server passes the video to the analysis tool, which performs facial expression recognition, speech analysis, posture detection, and gesture evaluation. At the same time, the emotion engine analyzes the user's emotional data.

[0293] Step 7:

[0294] The server identifies areas for improvement based on the video analysis results. The server analyzes the user's performance and lists specific areas for improvement, such as "correcting the position of your gaze" and "adjusting the tone of your voice." The emotion engine also provides emotion-based advice, such as "try to relax," based on the user's emotional data.

[0295] Step 8:

[0296] The server generates a feedback video and emotional feedback. The server creates a feedback video that reflects the points for improvement and also generates a video that includes emotional feedback. For example, in addition to specific points for improvement such as "It would be good to raise your eye contact here," the server incorporates emotional advice such as "Speak with more confidence" into the feedback video.

[0297] Step 9:

[0298] The server sends the generated feedback video to the terminal, where it is displayed in the user's application.

[0299] Step 10:

[0300] The user reviews the feedback video. They watch the feedback video on their device and understand the specific improvements and emotional feedback.

[0301] Step 11:

[0302] The user practices the presentation again based on the feedback video and emotional feedback. With the areas for improvement in mind, the user re-records the presentation, and the device again collects the video and emotional data.

[0303] Step 12:

[0304] The user saves a new presentation practice video on the device, uploads it, and then sends the video back to the server via the device, ready to receive further feedback.

[0305] Step 13:

[0306] The server generates a final checklist and points to note for the presentation. Based on the final analysis results and emotional feedback, the server lists points to note on the day of the presentation and provides them to the user.

[0307] Step 14:

[0308] The server sends the final checklist and notes to the terminal, which is displayed in the user's application and serves as a final confirmation.

[0309] Step 15:

[0310] The user reviews the final checklist and points to note. Using the information provided, the user makes final preparations for the presentation, allowing them to present with confidence.

[0311] Example 2

[0312] 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."

[0313] Conventional presentation practice systems lack the functionality to provide specific feedback and advice based on emotional data specifically designed to improve users' performance. As a result, users have to spend time and effort to improve the quality of their presentations, making it difficult to make effective improvements.

[0314] The identification process by the identification 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 analyzing the presentation materials and the presentation practice video, means for identifying specific improvements and emotional feedback based on the analysis results, and means for generating a feedback video that reflects the specific improvements and emotional feedback. This enables the user to quickly and efficiently receive specific feedback and emotional advice to effectively improve the quality of their presentation.

[0315] "User" refers to a person who uses the system to create and improve presentation materials.

[0316] "Means for inputting presentation materials" refers to the function that allows users to upload PowerPoint files or PDF format presentation materials to the server via their terminal.

[0317] "Means for recording a presentation practice video" refers to a function that allows a user to use the camera function of the device to record a presentation practice and save the video data.

[0318] "Server" refers to a central processing unit for analyzing presentation materials and presentation practice videos and generating and providing feedback.

[0319] "Means for analyzing presentation materials and presentation practice videos" refers to the function of analyzing the materials and videos received by the server and evaluating the slide structure, content, and performance.

[0320] "Means for identifying specific areas for improvement and emotional feedback" refers to a function in which the server identifies areas for improvement and emotional feedback for each element of the user's presentation based on the analysis results.

[0321] "Means for generating a feedback video that reflects specific areas for improvement and emotional feedback" refers to a function in which the server generates a presentation practice video of the user by overlaying specific areas for improvement and emotional feedback on the user's presentation practice video based on the analysis results.

[0322] The "means for providing a feedback video to a user" refers to a function for transmitting a feedback video generated by a server to a user terminal, allowing the user to view the video.

[0323] "Means for uploading the re-recorded presentation practice video and emotional data to the server" refers to a function that allows the user to practice the presentation again and send the video and emotional data to the server.

[0324] "Means for generating a final checklist and points to note for the presentation and providing it to the user" refers to the function by which the server generates a checklist summarizing points to note on the day of the presentation based on the final analysis results and emotional feedback, and provides it to the user.

[0325] This invention is a system that allows users to efficiently improve the quality of their presentations, and in particular, by combining it with an emotion engine that recognizes the user's emotions, it provides more advanced feedback. The system of this invention supports the improvement of presentation skills by evaluating the user's presentation practice from multiple angles and providing creative feedback.

[0326] System configuration

[0327] The system consists of the following main components:

[0328] 1. User's device: This is the device used to input presentation materials, record practice videos, and check feedback videos and emotional feedback.

[0329] 2. Server: A device that analyzes presentation materials, practice videos, and user emotional data, and generates and manages feedback.

[0330] 3. Emotion engine: It has the function to recognize the user's emotions and generate feedback accordingly.

[0331] Hardware and software used

[0332] User's device: smartphone, tablet, or computer (with camera function)

[0333] Server: High-performance analysis server (e.g. AWS EC2)

[0334] Emotion engine: Emotion recognition software (e.g. Microsoft Azure Emotion API)

[0335] Example of operation

[0336] User enters presentation material:

[0337] First, the user uploads the presentation materials from the device to the server. Using the application on the device, the user clicks the "Upload Materials" button, selects a PowerPoint file or a PDF file, and uploads it. For example, this is the case when the user uploads presentation materials for introducing a new product.

[0338] User records a practice presentation video:

[0339] Next, the user uses the device's camera function to record the presentation rehearsal. During the recording, the device simultaneously collects emotional data such as the user's facial expressions and tone of voice. For example, a user may rehearse a new product introduction at home and record the rehearsal on video.

[0340] The server analyzes the presentation and practice video:

[0341] Uploaded presentation materials and practice videos are sent to a server, which analyzes their content. The server uses AI analysis software to evaluate the structure and content of the slides and the user's performance (e.g., voice volume, eye movements, facial expressions), and an emotion engine analyzes the user's emotions.

[0342] The server identifies specific areas for improvement and sentiment-based feedback:

[0343] Based on the analysis results, the server identifies specific areas for improvement for each element of the presentation. At the same time, the emotion engine provides optimal emotional feedback based on the user's emotional data. For example, it provides technical corrections such as "correct your eye position" or "adjust your tone of voice" as well as emotional advice such as "try to relax a bit more."

[0344] The server generates the feedback video and emotional feedback:

[0345] The server then creates a feedback video that reflects these improvements and generates a video that includes emotional feedback. Specifically, the server overlays the video to indicate the areas for improvement and adds comments such as "Speak more confidently here."

[0346] The server provides the feedback video:

[0347] The generated feedback video is sent from the server to the user's device, where the user can view the feedback video on the device and understand the specific improvements and emotional feedback. For example, the user can play the video on the application and view the provided feedback.

[0348] User re-practices:

[0349] Based on the feedback, users practice their presentations again, record new practice videos, and recollect emotion data, thereby further improving their presentation skills.

[0350] Example prompts for generative AI models

[0351] "Please provide feedback on my presentation. Analyze the video and materials below and give me specific improvements and emotionally-driven advice."

[0352] In this way, the system of the present invention provides not only specific feedback but also emotional feedback to highly improve the user's presentation skills, supporting them to approach the day of the presentation with confidence.

[0353] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0354] Step 1:

[0355] The device accepts the user's presentation materials. The user uploads presentation materials in PowerPoint or PDF format through the device's application (input). The device sends these materials to the server (output). Specifically, the user opens the application, clicks the "Upload Materials" button, selects the presentation materials from the file selection dialog, and begins uploading.

[0356] Step 2:

[0357] The device records a video of the user practicing their presentation. The user uses the device's camera function to record their presentation rehearsal, and emotional data is automatically collected (input). The recorded video and emotional data are saved on the device (output). Specifically, the user presses the "Start Recording" button to start the presentation, and once recording is complete, presses the "Stop Recording" button to save the video.

[0358] Step 3:

[0359] The server analyzes the presentation materials and practice video. The server receives the presentation materials, practice video, and emotional data sent from the device (input). The server uses AI analysis software to evaluate the slide structure, content, and user performance (volume of voice, eye movement, facial expression), and analyzes emotions using an emotion engine (data processing and data calculation). The analysis results are generated (output). Specifically, the server launches the AI ​​analysis software and takes in the uploaded materials and video as input data.

[0360] Step 4:

[0361] The server identifies specific areas for improvement and emotional feedback. Based on the analysis results, the server identifies specific areas for improvement and emotional feedback for each element of the user's presentation (input). For example, technical corrections such as "correct your gaze position" or "adjust your tone of voice" and emotional advice such as "try to relax a bit more" are generated (output). The server creates feedback data based on this data (data processing).

[0362] Step 5:

[0363] The server generates a feedback video and emotional feedback. Based on the feedback data, the server adds improvements and emotional feedback as an overlay to the user's practice video (input). Specifically, the server launches video editing software and adds text and graphics indicating areas for improvement, as well as emotional feedback as text (data processing). Finally, a feedback video is generated (output).

[0364] Step 6:

[0365] The server provides the feedback video to the user. The server then sends the generated feedback video to the user's device (input and output). Specifically, the server uploads the feedback video to cloud storage and sends a download link to the user via email or in-app notification. The user clicks the link to watch the video.

[0366] Step 7:

[0367] The user practices the presentation again. The user practices the presentation again based on the feedback video and emotional feedback and records a new practice video (input). The device records a new video and collects emotional data again (output). Specifically, the user presses the "Start Recording" button again, rehearses, and presses the "Stop Recording" button to save the video.

[0368] Step 8:

[0369] The server provides a final checklist and important points for the presentation. The server reanalyzes the newly uploaded video and emotion data, and generates a checklist summarizing important points for the presentation day based on the final analysis results (input and data processing). The server provides this checklist to the user (output). Specifically, the server sends the generated checklist to the user via email or in-app notification.

[0370] (Application example 2)

[0371] 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."

[0372] Conventional presentation practice systems do not provide specific feedback to improve users' emotions or performance, resulting in limited quality practice. Furthermore, in the food delivery industry, there are insufficient training methods for delivery staff to effectively introduce food and services, making it difficult to improve the user experience.

[0373] The specification processing by the specification 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 a user to input presentation materials, means for a user to record a presentation practice video, means for the server to analyze the presentation materials and the presentation practice video, means for the server to identify specific areas for improvement based on the analysis results, means for the server to generate a feedback video based on the areas for improvement, means for the server to provide the feedback video to the user, means for delivery staff to record and upload explanations of dishes and service introductions, and means for the server to analyze the videos and provide advice on improving hospitality. This makes it possible to improve not only the quality of presentations but also the quality of food delivery service.

[0374] A "user" is an entity that creates presentation materials and records a practice video.

[0375] "Presentation materials" refers to information such as documents, charts, slides, etc. that a user uses to give a presentation.

[0376] "Presentation practice video" refers to video data that records a user practicing a presentation.

[0377] "Server" refers to the computer system that analyzes the presentation materials and presentation practice videos and generates and provides feedback.

[0378] "Means for analyzing" refers to a method or device for evaluating and analyzing the content of presentation materials and presentation practice videos received by the server.

[0379] The means for identifying "specific areas for improvement" refers to a method or device for finding specific advice or instructions for improving the quality of the presentation based on the analysis results.

[0380] The "means for generating a feedback video" refers to a method or device by which the server creates a feedback video that reflects the analysis results and improvements.

[0381] The "means for providing a feedback video" refers to a method or device for transmitting the feedback video generated by the server to the user's terminal so that the user can view it.

[0382] "Delivery staff" refers to people who deliver food and provide services in food delivery services.

[0383] "Means for recording and uploading descriptions of dishes and service introductions" refers to a method or device by which delivery staff record descriptions of dishes and service contents and upload the videos to a server.

[0384] "Means for providing advice to improve hospitality" refers to a method or device in which a server analyzes uploaded videos and generates and provides specific advice to delivery staff to provide better service.

[0385] This invention is a system that allows users to efficiently improve the quality of their presentations, and in particular provides feedback on presentation skills and emotions by combining an emotion engine that recognizes the user's emotions. Furthermore, to improve the quality of food delivery services, the system includes a function that analyzes introductory videos of delivery staff and provides specific advice for improving the service.

[0386] System configuration

[0387] The system consists of the following main components:

[0388] 1. User's device

[0389] This device is used to input presentation materials and record practice videos. Users upload PowerPoint files and PDF format presentation materials to the server through the device. The device is also equipped with a camera function to record and upload practice videos.

[0390] 2. Server

[0391] This is a computer system that receives and analyzes presentation materials and practice videos. The server has the following functions:

[0392] Data analysis: Analyze the content of the presentation materials and practice videos received to evaluate their structure and performance.

[0393] Emotion Engine: Recognizes user emotions in training videos and analyzes emotion data.

[0394] Feedback generation: Based on the analysis results, specific areas for improvement are identified and a feedback video is generated that reflects these areas.

[0395] Video provision: Send feedback videos to the user's device and provide feedback for improvement.

[0396] 3. Delivery staff

[0397] This person records videos explaining the dishes and services and uploads them to a server, which analyzes the videos and provides advice on how to improve the service.

[0398] Example

[0399] 1. Inputting presentation materials

[0400] Consider an example where a user uploads a presentation document for introducing a new product from a terminal to a server. The user uses a PowerPoint file or a PDF.

[0401] 2. Record a practice video of your presentation

[0402] The user rehearses at home and records the rehearsal on video, while the device simultaneously collects emotional data such as facial expressions and tone of voice.

[0403] 3. Data analysis and feedback generation

[0404] The server analyzes the presentation materials and practice videos it receives, and analyzes the user's emotions based on the volume of their voice, intonation, eye movements, and facial expressions, and compares them with standard presentation indicators. Based on the results of this analysis, it generates specific improvements (e.g., "correct your eye position" or "adjust your tone of voice") and emotion-based advice (e.g., "try to relax a bit more").

[0405] 4. Providing feedback videos

[0406] The server creates a feedback video that reflects the analysis results and overlays it on the user's video to show areas for improvement. It also adds emotional comments such as "Try to speak more confidently here."

[0407] Food delivery application example

[0408] Delivery staff record and upload their explanations of the dishes and the service they provide. The server analyzes the videos and generates specific advice for delivery staff to provide better service (e.g., "serve customers with a smile" or "explain the key points of the dishes clearly").

[0409] Hardware and software used

[0410] Hardware: User devices (smartphones, tablets, PCs), cameras, servers

[0411] Software: Emotion recognition API (e.g., Google Cloud Vision, Amazon Rekognition), video analysis software (e.g., OpenCV)

[0412] Prompt Sentence Examples

[0413] Video analysis results:

[0414] Gaze position: 60% camera direction

[0415] Confidence level: 45%

[0416] Emotional feedback example:

[0417] Turn your gaze more towards the camera.

[0418] Try to speak more confidently.

[0419] It is expected that this system will improve the quality of presentations and service provision, providing users and customers with a more satisfying experience.

[0420] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0421] Step 1:

[0422] A means for users to input presentation materials

[0423] A user uploads a presentation document in PowerPoint or PDF format to the server via their device. The input is the presentation document file, which the server receives. Specifically, the user opens the application and clicks the "Upload Presentation Document" button.

[0424] Step 2:

[0425] A way for users to record practice videos of their presentations

[0426] The user uses the device's camera function to record a presentation rehearsal. The device also collects emotional data such as the user's facial expressions and tone of voice. The input is a video file and emotional data, and the output is a recorded video file. Specifically, the user presses the "Start Recording" button, gives the presentation, and then presses the "Stop Recording" button.

[0427] Step 3:

[0428] A means for the server to analyze presentation materials and presentation practice videos

[0429] The server analyzes the received presentation materials and practice video content and evaluates the slide structure, content, and performance. At the same time, the emotion engine analyzes the user's emotions. The input is the presentation material file and the recorded video file, and the output is the analyzed data. Specifically, the server calls the emotion recognition API and analyzes the user's emotional data. It also uses video analysis software such as OpenCV to analyze the video's movements.

[0430] Step 4:

[0431] A means for the server to identify specific areas for improvement

[0432] Based on the analysis results, the server identifies specific areas for improvement for each element of the presentation. The input is the analysis data, and the output is specific improvement suggestions. Specifically, the server compares the analysis data with standard presentation indicators and derives specific areas for improvement related to eye gaze position, tone of voice, and facial expressions.

[0433] Step 5:

[0434] A means for the server to generate feedback videos based on improvements

[0435] The server creates a feedback video that reflects the improvements and overlays them on the user's video. It also adds emotional comments. The input is the recorded video file and the improvement proposal data, and the output is the feedback video. Specifically, the server uses video editing software to add an overlay to the video and insert the comments.

[0436] Step 6:

[0437] A means by which the server provides feedback videos to the user

[0438] The server sends the generated feedback video to the user's device. The input is the feedback video file, and the output is the feedback video sent to the user's device. Specifically, the server sends a notification to the user's device and displays a message saying "A new feedback video is ready."

[0439] Step 7:

[0440] A way for users to practice their presentations again based on the feedback video

[0441] The user reviews the feedback video, understands the specific areas for improvement and emotional feedback, and then practices the presentation again. The input is the feedback video, and the output is a re-recorded presentation practice video. Specifically, the user watches the feedback video, presses the "Start Re-Practice" button, and practices again, noting the areas for improvement.

[0442] Step 8:

[0443] How to upload the re-recorded presentation practice video to the server

[0444] The user uploads the re-recorded presentation practice video to the server and re-analyzes it. The input is the re-recorded presentation practice video, and the specific operation is for the user to click the "Upload re-practice video" button.

[0445] This embodiment improves the quality of presentation and service delivery, providing a more satisfying experience for users and customers.

[0446] 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.

[0447] 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.

[0448] 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.

[0449] [Second embodiment]

[0450] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0451] 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.

[0452] 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).

[0453] 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.

[0454] 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.

[0455] 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).

[0456] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0457] 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.

[0458] 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.

[0459] 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.

[0460] 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.

[0461] 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."

[0462] This invention is a system that aims to enable users to efficiently improve the quality of their presentations. This system is composed of a series of processes: the user inputs presentation materials, practices the presentation based on those materials, the server analyzes the content, and provides feedback on areas for improvement.

[0463] System configuration

[0464] The system consists of the following main components:

[0465] 1. User's device: This is the device used to input presentation materials, record practice videos, and check feedback videos.

[0466] 2. Server: A device that analyzes the received presentation materials and practice videos, and generates and manages feedback.

[0467] User Flow

[0468] 1. User enters presentation materials:

[0469] Users upload PowerPoint files or presentation materials in PDF format to the server via their terminal.

[0470] For example, a user uploads a presentation document introducing a new product that the user has created to the application.

[0471] 2. User records a practice video of their presentation:

[0472] The user uses the device's camera function to record the presentation practice.

[0473] For example, a user rehearses a presentation at home and records the rehearsal on video.

[0474] 3. The server analyzes the presentation materials and practice video:

[0475] The server analyzes the presentation materials received and evaluates the structure and content of the slides.

[0476] The server analyzes the presentation practice video and evaluates performance such as facial expressions, pronunciation, posture, and gestures.

[0477] For example, the server analyzes the volume, intonation, and eye movements of the user's voice and compares them with certain standards.

[0478] 4. The server identifies specific areas for improvement:

[0479] Based on the analysis results, the server lists specific areas for improvement for each element of the presentation.

[0480] For example, identify advice such as "Look more at the audience on slide 3" or "Increase your intonation."

[0481] 5. The server generates the feedback video:

[0482] The server creates a feedback video that reflects the improvements.

[0483] For example, a video can be generated that overlays the user's video to show areas for improvement.

[0484] 6. The server provides the feedback video:

[0485] The server transmits the generated feedback video to the user's terminal.

[0486] For example, the user plays the feedback video on the device and identifies specific areas for improvement.

[0487] 7. User re-practices:

[0488] The user practices the presentation again based on the feedback video and records a new video.

[0489] For example, the user may incorporate the improvements suggested, re-record the presentation, and upload it to the server.

[0490] 8. The server provides a final checklist and notes:

[0491] The server generates a final checklist for the presentation and points to be noted on the day, and provides it to the user.

[0492] For example, make a list of final check points such as "keep your voice tone consistent" and "move your eyes when changing slides."

[0493] In this way, the system of the present invention provides specific feedback that allows users to efficiently improve the quality of their presentation, allowing them to approach the day of the presentation with confidence.

[0494] The processing flow will be explained below.

[0495] Step 1:

[0496] The user inputs the presentation materials. The user prepares the materials to be used in the presentation, such as PowerPoint files or PDF files, and uploads the files to the presentation application using the device.

[0497] Step 2:

[0498] The device sends the presentation materials received from the user to the server, where the files are uploaded to the server using a secure protocol.

[0499] Step 3:

[0500] The server receives the presentation materials and begins analyzing them. The server evaluates the text content, slide structure, visual elements, etc. of the materials and performs an initial analysis based on the presentation quality criteria.

[0501] Step 4:

[0502] A user records a practice video of a presentation. A user uses the device's camera to record a rehearsal of a presentation at home or in the office.

[0503] Step 5:

[0504] Users can save and upload recorded presentation practice videos to their devices. Users select the video file in the application and send it to the server.

[0505] Step 6:

[0506] The server receives the presentation practice video and passes it to an analysis tool to evaluate facial expression recognition, speech analysis, posture detection, and gestures.

[0507] Step 7:

[0508] The server identifies areas for improvement based on the video analysis results. It compares the user's performance with standard presentation metrics and lists specific areas for improvement, such as "correcting eye position" and "adjusting voice tone."

[0509] Step 8:

[0510] The server generates a feedback video, which includes points for improvement based on the analysis results, and provides it to the user in a format that is easy to understand.

[0511] Step 9:

[0512] The server sends the generated feedback video to the terminal, where it is displayed in the user's application.

[0513] Step 10:

[0514] The user checks the feedback video. They watch the feedback video on their device and understand the specific areas for improvement.

[0515] Step 11:

[0516] The user practices the presentation again based on the feedback video. They then record a new practice video, keeping in mind the areas for improvement.

[0517] Step 12:

[0518] The user uploads a new presentation practice video to the device, which then sends the video to the server again via the device, ready to receive further feedback.

[0519] Step 13:

[0520] The server generates a final checklist and points to note for the presentation. Based on the final analysis results, the server creates a list of points that the user should pay attention to on the day of the presentation and a list of points to note for optimal performance.

[0521] Step 14:

[0522] The server sends the final checklist and notes to the terminal, which is displayed in the user's application and serves as a final confirmation.

[0523] Step 15:

[0524] The user reviews the final checklist and points to note. Using the information provided, the user makes final preparations for the presentation, allowing them to present with confidence.

[0525] Example 1

[0526] 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."

[0527] Conventional presentation practice systems require users to practice unilaterally, making it difficult for them to receive effective feedback. This makes it difficult for users to objectively evaluate the quality of their presentations and identify specific areas for improvement. The present invention aims to provide a system that allows users to efficiently improve the quality of their presentations through specific feedback provided by a server when practicing a presentation.

[0528] 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.

[0529] In this invention, the server includes means for a user to input presentation materials, means for a user to record a presentation practice video, means for the server to analyze the presentation materials and the presentation practice video, means for the server to identify specific areas for improvement based on the analysis results, means for the server to generate a feedback video based on the areas for improvement, means for the server to provide the feedback video to the user, and means for the server to send a link to the feedback video to the user, so that the user can receive specific feedback after practicing their presentation and practice again based on that feedback.

[0530] "User" refers to a person who creates presentation materials and practices them.

[0531] "Presentation materials" refers to slides and document files (e.g., PowerPoint files or PDF format) used to explain the contents of the presentation.

[0532] "Presentation practice video" refers to a video recorded by a user practicing a presentation.

[0533] "Server" refers to an information processing device for analyzing presentation materials and practice videos and providing feedback.

[0534] "Means for Analysis" refers to the software and algorithms used by the Server to analyze and evaluate the content of presentation materials and practice videos.

[0535] "Means for identifying areas for improvement" refers to the algorithms and software that the server uses to list specific areas for improvement in the presentation based on the analysis results.

[0536] "Feedback video" refers to a video provided to a user in which specific improvements are added as an overlay to the user's presentation practice video.

[0537] "Means for sending a link" refers to the means (e.g., email or in-app notification) for notifying the user of the URL of the feedback video generated by the server.

[0538] The present invention is a system that aims to enable users to efficiently improve the quality of their presentations, and a series of processes are carried out through cooperation between the user's terminal and a server. Detailed embodiments will be described below.

[0539] 1. System Configuration

[0540] The system mainly consists of the following components:

[0541] User's device: A device used to input presentation materials, record practice videos, and check feedback videos. This can be a PC or smartphone.

[0542] Server: An information processing device that analyzes the received presentation materials and practice videos, and generates and manages feedback.

[0543] 2. Hardware and Software Used

[0544] On the user's device:

[0545] Devices (PC, smartphone)

[0546] Management applications (e.g. cloud storage apps, camera apps)

[0547] Recording application (e.g. standard camera app)

[0548] server:

[0549] Server with high-performance CPU and RAM

[0550] Analysis software (e.g., natural language processing tools, image analysis tools)

[0551] AI models (e.g., generative AI, machine learning algorithms)

[0552] Video editing software (e.g., video editing tools, overlay adding functions)

[0553] Data transmission software (e.g., cloud storage, distribution software)

[0554] 3. Example of operation

[0555] The user enters the presentation materials

[0556] Users upload presentation materials (e.g., slides introducing new products) to the system using their own terminals. Once uploaded, the materials are stored on the server.

[0557] Users record practice videos for their presentations

[0558] Users can record their presentation rehearsals using a camera app at home or in the office, press the "Start Recording" button to practice, and then press the "Stop Recording" button when they're done. They can then upload the video to the system.

[0559] The server analyzes the presentation materials and practice videos.

[0560] The server receives the materials and analyzes the content of the slides using natural language processing tools, while for videos, it uses image and audio analysis tools to evaluate the user's facial expressions, speech, posture, and gestures.

[0561] For example, it analyzes the volume and intonation of the user's voice and eye movements and compares them with pre-set standards.

[0562] The server identifies specific areas for improvement

[0563] The server runs an AI model based on the analyzed data and generates a list of specific improvements to the presentation, such as "focus your gaze more on the audience on the third slide" or "improve your intonation."

[0564] The server generates the feedback video

[0565] The server uses video editing software to generate a feedback video with overlays of improvements, for example adding a suggestion to "smile more" to the user's video.

[0566] The server provides the feedback video

[0567] Once the feedback video is generated, the server will upload it to the cloud storage and send the link to the user, who can click the link to play the feedback video.

[0568] The user practices again based on the feedback video.

[0569] The user watches the feedback video, understands what needs to be improved, and practices the presentation again. The newly recorded video is then uploaded to the server again.

[0570] 4. Example prompts for generative AI models

[0571] Below is an example of a prompt sentence to input to the generative AI model.

[0572] "Analyze the practice video of the presentation and provide suggestions for improvement. Please point out specific areas that need improvement (e.g., eye contact, vocalization, gestures) and generate a feedback video."

[0573] As described above, the system of the present invention provides specific feedback to users to help them efficiently improve the quality of their presentations, allowing them to approach the day of their presentation with confidence.

[0574] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0575] Step 1:

[0576] The user enters the presentation materials

[0577] Input: Presentation materials (PowerPoint files or PDF format)

[0578] Specific operation: The user uses the device to open the management application, clicks the "Select File" button, selects the presentation material to upload, and then clicks the "Upload" button.

[0579] Data processing / calculation: Uploaded files are sent to the server and stored there.

[0580] Output: The presentation materials are saved on the server.

[0581] Step 2:

[0582] Users record practice videos for their presentations

[0583] Input: Presentation practice video

[0584] Specific operation: The user opens the camera app on their device, clicks the "Start Recording" button, starts speaking, and then clicks the "Stop Recording" button when the rehearsal is over. The recorded video is then uploaded to the system.

[0585] Data processing / calculation: The recorded video file is sent from the device to the server and stored on the server.

[0586] Output: The presentation practice video will be saved on the server.

[0587] Step 3:

[0588] The server analyzes the presentation materials and practice videos.

[0589] Input: Presentation materials, Presentation practice video

[0590] Specific behavior:

[0591] The server receives the presentation materials and uses natural language processing (NLP) tools to analyze the content of the slides, for example, analyzing the frequency of important keywords and the structure of the slides.

[0592] For presentation practice videos, image and audio analysis tools are used to evaluate the user's facial expressions, clarity of speech, posture, and gestures.

[0593] Data processing / calculation: Generate analysis results of presentation materials and practice videos (e.g., voice volume, intonation, eye movements).

[0594] Output: Analysis results

[0595] Step 4:

[0596] The server identifies specific areas for improvement

[0597] Input: Analysis results

[0598] Specific actions: The server runs the AI ​​model based on the analysis results and lists specific improvements for each element of the presentation, such as "focus your eyes more on the audience on the third slide" or "improve your intonation."

[0599] Data processing / calculation: Using the analysis results, an algorithm is run to extract areas for improvement.

[0600] Output: Identified improvements

[0601] Step 5:

[0602] The server generates the feedback video

[0603] Input: Identified areas for improvement, Presentation practice video

[0604] What it does: The server uses video editing software to generate a feedback video by overlaying identified areas for improvement onto the presentation practice video, for example, by overlaying a suggestion like "Smile more."

[0605] Data processing / calculation: Create a feedback video with improvements added as an overlay.

[0606] Output: Feedback video

[0607] Step 6:

[0608] The server provides the feedback video

[0609] Input: Feedback video

[0610] Specific operation: The server uploads the generated feedback video to cloud storage and notifies the user of the link, which the user can click to play the feedback video.

[0611] Data processing / calculation: Uploading videos to cloud storage and generating links.

[0612] Output: Feedback video link

[0613] Step 7:

[0614] The user re-practices

[0615] Input: Feedback video

[0616] Specific actions: Based on the feedback video, the user practices the presentation again, incorporating specific improvements. The newly recorded video is then uploaded to the server again.

[0617] Data processing / calculation: Generate a new practice video that reflects the improvements and upload it to the server.

[0618] Output: New presentation practice video

[0619] Step 8:

[0620] The server provides a final checklist and points to note

[0621] Input: Final presentation practice video, analysis results

[0622] Specific operation: Based on the final analysis results, the server generates a final checklist and points to note for the presentation, such as "keep your voice consistent" and "move your eyes when changing slides."

[0623] Data processing / calculation: Automatic generation of final checklist and notes.

[0624] Output: Final checklist and notes PDF

[0625] Through these steps, the system provides users with the feedback and support they need to efficiently improve the quality of their presentations.

[0626] (Application example 1)

[0627] 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."

[0628] Conventional systems for improving the quality of presentations have the drawback of making it difficult for users to receive specific feedback in real time when practicing their presentations, making it difficult to practice and improve efficiently.In particular, in factories and other workplaces, it is necessary to explain new processes and provide training on operation methods quickly and accurately, and real-time feedback is required.

[0629] 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.

[0630] In this invention, the server includes means for a user to input presentation materials, means for the user to record a presentation practice video, means for the server to analyze the presentation materials and the presentation practice video, means for the server to identify specific areas for improvement based on the analysis results, means for the server to generate a feedback video based on the areas for improvement, means for the server to provide the feedback video to the user, and means for the user to check the feedback in real time. As a result, when a user practices a presentation, the recorded video can be analyzed on the spot and feedback indicating specific areas for improvement can be provided in real time, allowing the quality of the presentation to be improved quickly and efficiently.

[0631] "User" refers to the individual or entity who inputs presentation materials and records practice videos.

[0632] "Presentation materials" refers to digital files that contain documents, slides, charts, etc. that illustrate the content of a presentation.

[0633] "Presentation practice video" refers to footage of a presentation that a user has recorded for practice purposes.

[0634] "Server" refers to a computer system that analyzes presentation materials and practice videos, identifies areas for improvement, and generates and provides feedback videos.

[0635] "Analysis" refers to the process of evaluating and examining the content of the presentation materials and practice video to identify areas for improvement.

[0636] "Improvements" refers to changes or modifications that may be required to improve the quality of the user's presentation.

[0637] "Feedback video" refers to a video generated by the server that includes specific advice and comments on the user's presentation.

[0638] "Real-time feedback" refers to feedback provided instantly while a user is performing a practice presentation.

[0639] This invention is a system for improving the quality of presentations, which handles everything from inputting presentation materials to providing feedback. This system mainly consists of the following elements:

[0640] 1. On the user's device:

[0641] First, the user uploads presentation materials to the server via their device. Presentation materials can be slides, PDFs, images, etc., and the user can send them from their device to the server. Next, the user uses the device's camera function to record a practice video for the presentation. The recorded video is automatically uploaded to the server.

[0642] 2. Server:

[0643] The server analyzes the received presentation materials and practice videos, including slide content evaluation, voice volume and intonation, eye movements, posture, and gestures. Based on these analysis results, the server uses a generative AI model to identify specific areas for improvement.

[0644] 3. Providing Feedback:

[0645] Based on the analysis results, the server generates a feedback video containing specific areas for improvement. This feedback video is then provided to the user's device. The user can also view the feedback in real time by wearing smart glasses. This allows the user to understand the areas for improvement on the spot and immediately incorporate them into their practice.

[0646] A specific example is a training session on how to operate a new process in a factory. Factory workers wear smart glasses and record themselves demonstrating the operation of the new process. The recorded video is uploaded to a server, which analyzes the video content and provides specific feedback on areas for improvement. The feedback is displayed in real time on the smart glasses, allowing the workers to immediately implement the improvements.

[0647] Example prompt sentence:

[0648] "When training factory workers on a new assembly process, create a demo system that allows them to record themselves using smart glasses and provide real-time feedback on areas for improvement. The system would analyze the video, evaluate assembly accuracy and efficiency, and provide specific feedback on the smart glasses."

[0649] This system not only improves the quality of presentations quickly and efficiently, but also effectively supports the learning of new processes in factories and other workplaces.

[0650] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0651] Step 1:

[0652] User uploads presentation materials

[0653] First, the user selects presentation materials from their own device and uploads them to the server. The input is the presentation material file (slides, PDF, etc.) saved on the user's device, and the output is the same material saved on the server. Data processing involves transferring the material file to the server, checking the file format, and converting it into an analyzable format.

[0654] Step 2:

[0655] Users record practice videos for their presentations

[0656] A user uses the device's camera to record a presentation practice video. Once recording is complete, the video file is uploaded to the server. The input is the video feed recorded by the camera, and the output is the practice video file stored on the server. Data processing involves compressing and formatting the video for efficient transfer to the server.

[0657] Step 3:

[0658] The server analyzes the presentation materials and practice videos.

[0659] The server analyzes the uploaded presentation materials and practice videos. The input is the presentation materials and practice videos stored on the server, and the output is the analysis results. Data calculation involves using a generative AI model to evaluate the content of the slides, analyze the volume and intonation of the voice, eye movements, posture, and gestures.

[0660] Step 4:

[0661] The server identifies specific areas for improvement

[0662] The server extracts specific improvement points based on the analysis results. The input is the analysis results obtained in step 3, and the output is a list of improvement points. Data calculation is to compare the analysis data with the good performance standards of the existing presentation and identify the differences.

[0663] Step 5:

[0664] The server generates the feedback video

[0665] The server generates a feedback video that reflects specific improvements. The input is a list of improvements and the original practice video, and the output is the feedback video. Data processing involves adding graphics and text indicating the improvements as an overlay on the original practice video.

[0666] Step 6:

[0667] The server provides the feedback video

[0668] The server provides the generated feedback video to the user. The input is the feedback video, and the output is a feedback video link that can be played on the user's device. The data processing involves converting the feedback video into an appropriate format and uploading it to cloud storage for user access.

[0669] Step 7:

[0670] Users practice again based on feedback

[0671] The user reviews the feedback video, reflects the improvements, practices the presentation again, and records the video. The input is the feedback video and the newly recorded practice video, and the output is the re-uploaded practice video. Data calculation involves adjusting the practice content based on the improvements suggested by the user.

[0672] Step 8:

[0673] The server provides a final checklist and points to note

[0674] The server analyzes the user's final presentation practice video and provides a final checklist and points to note. The input is the final practice video, and the output is the final checklist and a list of points to note. The data calculation analyzes the final practice video and once again confirms the necessary improvements and points to note.

[0675] 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.

[0676] The present invention is a system that allows users to efficiently improve the quality of their presentations, and in particular provides more advanced feedback by combining it with an emotion engine that recognizes the user's emotions.

[0677] System configuration

[0678] The system consists of the following main components:

[0679] 1. User's device: This is the device used to input presentation materials, record practice videos, and check feedback videos and emotional feedback.

[0680] 2. Server: A device that analyzes presentation materials, practice videos, and user emotional data, and generates and manages feedback.

[0681] 3. Emotion engine: It has the function to recognize the user's emotions and generate feedback accordingly.

[0682] User Flow

[0683] 1. User enters presentation materials:

[0684] Users upload PowerPoint files or presentation materials in PDF format to the server via their terminals.

[0685] For example, a user uploads a presentation document introducing a new product that the user has created to the application.

[0686] 2. User records a practice video of their presentation:

[0687] Users use the device's camera to record their presentation rehearsals, and the device also collects emotional data such as facial expressions and tone of voice.

[0688] For example, a user rehearses at home, records the rehearsal on video, and simultaneously collects emotional data.

[0689] 3. The server analyzes the presentation materials and practice video:

[0690] The server analyzes the content of the presentation materials and practice videos received, evaluating the structure, content, and performance of the slides. The emotion engine also analyzes the user's emotions.

[0691] For example, the server analyzes the user's emotions from the volume of their voice, intonation, eye movements, and facial expressions, and compares them with standard presentation metrics.

[0692] 4. The server identifies specific areas for improvement and emotional feedback:

[0693] Based on the analysis results, the server identifies specific areas for improvement for each element of the presentation, while the emotion engine provides optimal emotional feedback based on the user's emotional data.

[0694] For example, in addition to corrections such as "correct your gaze position" and "adjust your tone of voice," it identifies emotion-based advice such as "try to relax a bit more."

[0695] 5. The server generates the feedback video and emotional feedback:

[0696] The server creates a feedback video that reflects the improvements and simultaneously generates a video that includes emotional feedback.

[0697] For example, it generates a video that overlays areas for improvement on the user's video and adds emotion-based comments such as "Speak with more confidence here."

[0698] 6. The server provides the feedback video:

[0699] The server sends the generated feedback video to the user's device, where the user can view the video and understand specific improvements and emotional feedback.

[0700] 7. User re-practices:

[0701] The user practices the presentation again based on the feedback video and emotional feedback, records a new video, and recollects emotional data.

[0702] 8. The server provides a final checklist and notes for the presentation:

[0703] The server generates a checklist of points to note on the day of the presentation based on the final analysis results and emotional feedback, and sends it to the user.

[0704] In this way, the system of the present invention provides not only specific feedback but also emotional feedback to highly improve the user's presentation skills, supporting them to approach the day of the presentation with confidence.

[0705] The processing flow will be explained below.

[0706] Step 1:

[0707] The user inputs the presentation materials. The user prepares the presentation materials in PowerPoint or PDF format and uploads the files to the presentation application using the terminal.

[0708] Step 2:

[0709] The device sends the presentation materials received from the user to the server, where the files are uploaded to the server using a secure protocol.

[0710] Step 3:

[0711] The server receives the presentation materials and begins analyzing them. The server evaluates the text content, slide structure, visual elements, etc. of the materials and performs an initial analysis based on the presentation quality criteria.

[0712] Step 4:

[0713] The user records a video of their presentation practice. The user rehearses their presentation at home or in the office using the device's camera. At the same time, the device also collects emotional data such as the user's facial expressions and tone of voice.

[0714] Step 5:

[0715] Users can save and upload recorded presentation practice videos to their devices. Users select the video file in the application and send it to the server.

[0716] Step 6:

[0717] The server receives the presentation practice video. The server passes the video to the analysis tool, which performs facial expression recognition, speech analysis, posture detection, and gesture evaluation. At the same time, the emotion engine analyzes the user's emotional data.

[0718] Step 7:

[0719] The server identifies areas for improvement based on the video analysis results. The server analyzes the user's performance and lists specific areas for improvement, such as "correcting the position of your gaze" and "adjusting the tone of your voice." The emotion engine also provides emotion-based advice, such as "try to relax," based on the user's emotional data.

[0720] Step 8:

[0721] The server generates a feedback video and emotional feedback. The server creates a feedback video that reflects the points for improvement and also generates a video that includes emotional feedback. For example, in addition to specific points for improvement such as "It would be good to raise your eye contact here," the server incorporates emotional advice such as "Speak with more confidence" into the feedback video.

[0722] Step 9:

[0723] The server sends the generated feedback video to the terminal, where it is displayed in the user's application.

[0724] Step 10:

[0725] The user reviews the feedback video. They watch the feedback video on their device and understand the specific improvements and emotional feedback.

[0726] Step 11:

[0727] The user practices the presentation again based on the feedback video and emotional feedback. With the areas for improvement in mind, the user re-records the presentation, and the device again collects the video and emotional data.

[0728] Step 12:

[0729] The user saves a new presentation practice video on the device, uploads it, and then sends the video back to the server via the device, ready to receive further feedback.

[0730] Step 13:

[0731] The server generates a final checklist and points to note for the presentation. Based on the final analysis results and emotional feedback, the server lists points to note on the day of the presentation and provides them to the user.

[0732] Step 14:

[0733] The server sends the final checklist and notes to the terminal, which is displayed in the user's application and serves as a final confirmation.

[0734] Step 15:

[0735] The user reviews the final checklist and points to note. Using the information provided, the user makes final preparations for the presentation, allowing them to present with confidence.

[0736] Example 2

[0737] 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."

[0738] Conventional presentation practice systems lack the functionality to provide specific feedback and advice based on emotional data specifically designed to improve users' performance. As a result, users have to spend time and effort to improve the quality of their presentations, making it difficult to make effective improvements.

[0739] The identification process by the identification 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 analyzing the presentation materials and the presentation practice video, means for identifying specific improvements and emotional feedback based on the analysis results, and means for generating a feedback video that reflects the specific improvements and emotional feedback. This enables the user to quickly and efficiently receive specific feedback and emotional advice to effectively improve the quality of their presentation.

[0740] "User" refers to a person who uses the system to create and improve presentation materials.

[0741] "Means for inputting presentation materials" refers to the function that allows users to upload PowerPoint files or PDF format presentation materials to the server via their terminal.

[0742] "Means for recording a presentation practice video" refers to a function that allows a user to use the camera function of the device to record a presentation practice and save the video data.

[0743] "Server" refers to a central processing unit for analyzing presentation materials and presentation practice videos and generating and providing feedback.

[0744] "Means for analyzing presentation materials and presentation practice videos" refers to the function of analyzing the materials and videos received by the server and evaluating the slide structure, content, and performance.

[0745] "Means for identifying specific areas for improvement and emotional feedback" refers to a function in which the server identifies areas for improvement and emotional feedback for each element of the user's presentation based on the analysis results.

[0746] "Means for generating a feedback video that reflects specific areas for improvement and emotional feedback" refers to a function in which the server generates a presentation practice video of the user by overlaying specific areas for improvement and emotional feedback on the user's presentation practice video based on the analysis results.

[0747] The "means for providing a feedback video to a user" refers to a function for transmitting a feedback video generated by a server to a user terminal, allowing the user to view the video.

[0748] "Means for uploading the re-recorded presentation practice video and emotional data to the server" refers to a function that allows the user to practice the presentation again and send the video and emotional data to the server.

[0749] "Means for generating a final checklist and points to note for the presentation and providing it to the user" refers to the function by which the server generates a checklist summarizing points to note on the day of the presentation based on the final analysis results and emotional feedback, and provides it to the user.

[0750] This invention is a system that allows users to efficiently improve the quality of their presentations, and in particular, by combining it with an emotion engine that recognizes the user's emotions, it provides more advanced feedback. The system of this invention supports the improvement of presentation skills by evaluating the user's presentation practice from multiple angles and providing creative feedback.

[0751] System configuration

[0752] The system consists of the following main components:

[0753] 1. User's device: This is the device used to input presentation materials, record practice videos, and check feedback videos and emotional feedback.

[0754] 2. Server: A device that analyzes presentation materials, practice videos, and user emotional data, and generates and manages feedback.

[0755] 3. Emotion engine: It has the function to recognize the user's emotions and generate feedback accordingly.

[0756] Hardware and software used

[0757] User's device: smartphone, tablet, or computer (with camera function)

[0758] Server: High-performance analysis server (e.g. AWS EC2)

[0759] Emotion engine: Emotion recognition software (e.g. Microsoft Azure Emotion API)

[0760] Example of operation

[0761] User enters presentation material:

[0762] First, the user uploads the presentation materials from the device to the server. Using the application on the device, the user clicks the "Upload Materials" button, selects a PowerPoint file or a PDF file, and uploads it. For example, this is the case when the user uploads presentation materials for introducing a new product.

[0763] User records a practice presentation video:

[0764] Next, the user uses the device's camera function to record the presentation rehearsal. During the recording, the device simultaneously collects emotional data such as the user's facial expressions and tone of voice. For example, a user may rehearse a new product introduction at home and record the rehearsal on video.

[0765] The server analyzes the presentation and practice video:

[0766] Uploaded presentation materials and practice videos are sent to a server, which analyzes their content. The server uses AI analysis software to evaluate the structure and content of the slides and the user's performance (e.g., voice volume, eye movements, facial expressions), and an emotion engine analyzes the user's emotions.

[0767] The server identifies specific areas for improvement and sentiment-based feedback:

[0768] Based on the analysis results, the server identifies specific areas for improvement for each element of the presentation. At the same time, the emotion engine provides optimal emotional feedback based on the user's emotional data. For example, it provides technical corrections such as "correct your eye position" or "adjust your tone of voice" as well as emotional advice such as "try to relax a bit more."

[0769] The server generates the feedback video and emotional feedback:

[0770] The server then creates a feedback video that reflects these improvements and generates a video that includes emotional feedback. Specifically, the server overlays the video to indicate the areas for improvement and adds comments such as "Speak more confidently here."

[0771] The server provides the feedback video:

[0772] The generated feedback video is sent from the server to the user's device, where the user can view the feedback video on the device and understand the specific improvements and emotional feedback. For example, the user can play the video on the application and view the provided feedback.

[0773] User re-practices:

[0774] Based on the feedback, users practice their presentations again, record new practice videos, and recollect emotion data, thereby further improving their presentation skills.

[0775] Example prompts for generative AI models

[0776] "Please provide feedback on my presentation. Analyze the video and materials below and give me specific improvements and emotionally-driven advice."

[0777] In this way, the system of the present invention provides not only specific feedback but also emotional feedback to highly improve the user's presentation skills, supporting them to approach the day of the presentation with confidence.

[0778] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0779] Step 1:

[0780] The device accepts the user's presentation materials. The user uploads presentation materials in PowerPoint or PDF format through the device's application (input). The device sends these materials to the server (output). Specifically, the user opens the application, clicks the "Upload Materials" button, selects the presentation materials from the file selection dialog, and begins uploading.

[0781] Step 2:

[0782] The device records a video of the user practicing their presentation. The user uses the device's camera function to record their presentation rehearsal, and emotional data is automatically collected (input). The recorded video and emotional data are saved on the device (output). Specifically, the user presses the "Start Recording" button to start the presentation, and once recording is complete, presses the "Stop Recording" button to save the video.

[0783] Step 3:

[0784] The server analyzes the presentation materials and practice video. The server receives the presentation materials, practice video, and emotional data sent from the device (input). The server uses AI analysis software to evaluate the slide structure, content, and user performance (volume of voice, eye movement, facial expression), and analyzes emotions using an emotion engine (data processing and data calculation). The analysis results are generated (output). Specifically, the server launches the AI ​​analysis software and takes in the uploaded materials and video as input data.

[0785] Step 4:

[0786] The server identifies specific areas for improvement and emotional feedback. Based on the analysis results, the server identifies specific areas for improvement and emotional feedback for each element of the user's presentation (input). For example, technical corrections such as "correct your gaze position" or "adjust your tone of voice" and emotional advice such as "try to relax a bit more" are generated (output). The server creates feedback data based on this data (data processing).

[0787] Step 5:

[0788] The server generates a feedback video and emotional feedback. Based on the feedback data, the server adds improvements and emotional feedback as an overlay to the user's practice video (input). Specifically, the server launches video editing software and adds text and graphics indicating areas for improvement, as well as emotional feedback as text (data processing). Finally, a feedback video is generated (output).

[0789] Step 6:

[0790] The server provides the feedback video to the user. The server then sends the generated feedback video to the user's device (input and output). Specifically, the server uploads the feedback video to cloud storage and sends a download link to the user via email or in-app notification. The user clicks the link to watch the video.

[0791] Step 7:

[0792] The user practices the presentation again. The user practices the presentation again based on the feedback video and emotional feedback and records a new practice video (input). The device records a new video and collects emotional data again (output). Specifically, the user presses the "Start Recording" button again, rehearses, and presses the "Stop Recording" button to save the video.

[0793] Step 8:

[0794] The server provides a final checklist and important points for the presentation. The server reanalyzes the newly uploaded video and emotion data, and generates a checklist summarizing important points for the presentation day based on the final analysis results (input and data processing). The server provides this checklist to the user (output). Specifically, the server sends the generated checklist to the user via email or in-app notification.

[0795] (Application example 2)

[0796] 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."

[0797] Conventional presentation practice systems do not provide specific feedback to improve users' emotions or performance, resulting in limited quality practice. Furthermore, in the food delivery industry, there are insufficient training methods for delivery staff to effectively introduce food and services, making it difficult to improve the user experience.

[0798] The specification processing by the specification 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 a user to input presentation materials, means for a user to record a presentation practice video, means for the server to analyze the presentation materials and the presentation practice video, means for the server to identify specific areas for improvement based on the analysis results, means for the server to generate a feedback video based on the areas for improvement, means for the server to provide the feedback video to the user, means for delivery staff to record and upload explanations of dishes and service introductions, and means for the server to analyze the videos and provide advice on improving hospitality. This makes it possible to improve not only the quality of presentations but also the quality of food delivery service.

[0799] A "user" is an entity that creates presentation materials and records a practice video.

[0800] "Presentation materials" refers to information such as documents, charts, slides, etc. that a user uses to give a presentation.

[0801] "Presentation practice video" refers to video data that records a user practicing a presentation.

[0802] "Server" refers to the computer system that analyzes the presentation materials and presentation practice videos and generates and provides feedback.

[0803] "Means for analyzing" refers to a method or device for evaluating and analyzing the content of presentation materials and presentation practice videos received by the server.

[0804] The means for identifying "specific areas for improvement" refers to a method or device for finding specific advice or instructions for improving the quality of the presentation based on the analysis results.

[0805] The "means for generating a feedback video" refers to a method or device by which the server creates a feedback video that reflects the analysis results and improvements.

[0806] The "means for providing a feedback video" refers to a method or device for transmitting the feedback video generated by the server to the user's terminal so that the user can view it.

[0807] "Delivery staff" refers to people who deliver food and provide services in food delivery services.

[0808] "Means for recording and uploading descriptions of dishes and service introductions" refers to a method or device by which delivery staff record descriptions of dishes and service contents and upload the videos to a server.

[0809] "Means for providing advice to improve hospitality" refers to a method or device in which a server analyzes uploaded videos and generates and provides specific advice to delivery staff to provide better service.

[0810] This invention is a system that allows users to efficiently improve the quality of their presentations, and in particular provides feedback on presentation skills and emotions by combining an emotion engine that recognizes the user's emotions. Furthermore, to improve the quality of food delivery services, the system includes a function that analyzes introductory videos of delivery staff and provides specific advice for improving the service.

[0811] System configuration

[0812] The system consists of the following main components:

[0813] 1. User's device

[0814] This device is used to input presentation materials and record practice videos. Users upload PowerPoint files and PDF format presentation materials to the server through the device. The device is also equipped with a camera function to record and upload practice videos.

[0815] 2. Server

[0816] This is a computer system that receives and analyzes presentation materials and practice videos. The server has the following functions:

[0817] Data analysis: Analyze the content of the presentation materials and practice videos received to evaluate their structure and performance.

[0818] Emotion Engine: Recognizes user emotions in training videos and analyzes emotion data.

[0819] Feedback generation: Based on the analysis results, specific areas for improvement are identified and a feedback video is generated that reflects these areas.

[0820] Video provision: Send feedback videos to the user's device and provide feedback for improvement.

[0821] 3. Delivery staff

[0822] This person records videos explaining the dishes and services and uploads them to a server, which analyzes the videos and provides advice on how to improve the service.

[0823] Example

[0824] 1. Inputting presentation materials

[0825] Consider an example where a user uploads a presentation document for introducing a new product from a terminal to a server. The user uses a PowerPoint file or a PDF.

[0826] 2. Record a practice video of your presentation

[0827] The user rehearses at home and records the rehearsal on video, while the device simultaneously collects emotional data such as facial expressions and tone of voice.

[0828] 3. Data analysis and feedback generation

[0829] The server analyzes the presentation materials and practice videos it receives, and analyzes the user's emotions based on the volume of their voice, intonation, eye movements, and facial expressions, and compares them with standard presentation indicators. Based on the results of this analysis, it generates specific improvements (e.g., "correct your eye position" or "adjust your tone of voice") and emotion-based advice (e.g., "try to relax a bit more").

[0830] 4. Providing feedback videos

[0831] The server creates a feedback video that reflects the analysis results and overlays it on the user's video to show areas for improvement. It also adds emotional comments such as "Try to speak more confidently here."

[0832] Food delivery application example

[0833] Delivery staff record and upload their explanations of the dishes and the service they provide. The server analyzes the videos and generates specific advice for delivery staff to provide better service (e.g., "serve customers with a smile" or "explain the key points of the dishes clearly").

[0834] Hardware and software used

[0835] Hardware: User devices (smartphones, tablets, PCs), cameras, servers

[0836] Software: Emotion recognition API (e.g., Google Cloud Vision, Amazon Rekognition), video analysis software (e.g., OpenCV)

[0837] Prompt Sentence Examples

[0838] Video analysis results:

[0839] Gaze position: 60% camera direction

[0840] Confidence level: 45%

[0841] Emotional feedback example:

[0842] Turn your gaze more towards the camera.

[0843] Try to speak more confidently.

[0844] It is expected that this system will improve the quality of presentations and service provision, providing users and customers with a more satisfying experience.

[0845] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0846] Step 1:

[0847] A means for users to input presentation materials

[0848] A user uploads a presentation document in PowerPoint or PDF format to the server via their device. The input is the presentation document file, which the server receives. Specifically, the user opens the application and clicks the "Upload Presentation Document" button.

[0849] Step 2:

[0850] A way for users to record practice videos of their presentations

[0851] The user uses the device's camera function to record a presentation rehearsal. The device also collects emotional data such as the user's facial expressions and tone of voice. The input is a video file and emotional data, and the output is a recorded video file. Specifically, the user presses the "Start Recording" button, gives the presentation, and then presses the "Stop Recording" button.

[0852] Step 3:

[0853] A means for the server to analyze presentation materials and presentation practice videos

[0854] The server analyzes the received presentation materials and practice video content and evaluates the slide structure, content, and performance. At the same time, the emotion engine analyzes the user's emotions. The input is the presentation material file and the recorded video file, and the output is the analyzed data. Specifically, the server calls the emotion recognition API and analyzes the user's emotional data. It also uses video analysis software such as OpenCV to analyze the video's movements.

[0855] Step 4:

[0856] A means for the server to identify specific areas for improvement

[0857] Based on the analysis results, the server identifies specific areas for improvement for each element of the presentation. The input is the analysis data, and the output is specific improvement suggestions. Specifically, the server compares the analysis data with standard presentation indicators and derives specific areas for improvement related to eye gaze position, tone of voice, and facial expressions.

[0858] Step 5:

[0859] A means for the server to generate feedback videos based on improvements

[0860] The server creates a feedback video that reflects the improvements and overlays them on the user's video. It also adds emotional comments. The input is the recorded video file and the improvement proposal data, and the output is the feedback video. Specifically, the server uses video editing software to add an overlay to the video and insert the comments.

[0861] Step 6:

[0862] A means by which the server provides feedback videos to the user

[0863] The server sends the generated feedback video to the user's device. The input is the feedback video file, and the output is the feedback video sent to the user's device. Specifically, the server sends a notification to the user's device and displays a message saying "A new feedback video is ready."

[0864] Step 7:

[0865] A way for users to practice their presentations again based on the feedback video

[0866] The user reviews the feedback video, understands the specific areas for improvement and emotional feedback, and then practices the presentation again. The input is the feedback video, and the output is a re-recorded presentation practice video. Specifically, the user watches the feedback video, presses the "Start Re-Practice" button, and practices again, noting the areas for improvement.

[0867] Step 8:

[0868] How to upload the re-recorded presentation practice video to the server

[0869] The user uploads the re-recorded presentation practice video to the server and re-analyzes it. The input is the re-recorded presentation practice video, and the specific operation is for the user to click the "Upload re-practice video" button.

[0870] This embodiment improves the quality of presentation and service delivery, providing a more satisfying experience for users and customers.

[0871] 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.

[0872] 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.

[0873] 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.

[0874] [Third embodiment]

[0875] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0876] 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.

[0877] 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).

[0878] 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.

[0879] 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.

[0880] 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).

[0881] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0882] 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.

[0883] 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.

[0884] 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.

[0885] 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.

[0886] 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."

[0887] This invention is a system that aims to enable users to efficiently improve the quality of their presentations. This system is composed of a series of processes: the user inputs presentation materials, practices the presentation based on those materials, the server analyzes the content, and provides feedback on areas for improvement.

[0888] System configuration

[0889] The system consists of the following main components:

[0890] 1. User's device: This is the device used to input presentation materials, record practice videos, and check feedback videos.

[0891] 2. Server: A device that analyzes the received presentation materials and practice videos, and generates and manages feedback.

[0892] User Flow

[0893] 1. User enters presentation materials:

[0894] Users upload PowerPoint files or presentation materials in PDF format to the server via their terminal.

[0895] For example, a user uploads a presentation document introducing a new product that the user has created to the application.

[0896] 2. User records a practice video of their presentation:

[0897] The user uses the device's camera function to record the presentation practice.

[0898] For example, a user rehearses a presentation at home and records the rehearsal on video.

[0899] 3. The server analyzes the presentation materials and practice video:

[0900] The server analyzes the presentation materials received and evaluates the structure and content of the slides.

[0901] The server analyzes the presentation practice video and evaluates performance such as facial expressions, pronunciation, posture, and gestures.

[0902] For example, the server analyzes the volume, intonation, and eye movements of the user's voice and compares them with certain standards.

[0903] 4. The server identifies specific areas for improvement:

[0904] Based on the analysis results, the server lists specific areas for improvement for each element of the presentation.

[0905] For example, identify advice such as "Look more at the audience on slide 3" or "Increase your intonation."

[0906] 5. The server generates the feedback video:

[0907] The server creates a feedback video that reflects the improvements.

[0908] For example, a video can be generated that overlays the user's video to show areas for improvement.

[0909] 6. The server provides the feedback video:

[0910] The server transmits the generated feedback video to the user's terminal.

[0911] For example, the user plays the feedback video on the device and identifies specific areas for improvement.

[0912] 7. User re-practices:

[0913] The user practices the presentation again based on the feedback video and records a new video.

[0914] For example, the user may incorporate the improvements suggested, re-record the presentation, and upload it to the server.

[0915] 8. The server provides a final checklist and notes:

[0916] The server generates a final checklist for the presentation and points to be noted on the day, and provides it to the user.

[0917] For example, make a list of final check points such as "keep your voice tone consistent" and "move your eyes when changing slides."

[0918] In this way, the system of the present invention provides specific feedback that allows users to efficiently improve the quality of their presentation, allowing them to approach the day of the presentation with confidence.

[0919] The processing flow will be explained below.

[0920] Step 1:

[0921] The user inputs the presentation materials. The user prepares the materials to be used in the presentation, such as PowerPoint files or PDF files, and uploads the files to the presentation application using the device.

[0922] Step 2:

[0923] The device sends the presentation materials received from the user to the server, where the files are uploaded to the server using a secure protocol.

[0924] Step 3:

[0925] The server receives the presentation materials and begins analyzing them. The server evaluates the text content, slide structure, visual elements, etc. of the materials and performs an initial analysis based on the presentation quality criteria.

[0926] Step 4:

[0927] A user records a practice video of a presentation. A user uses the device's camera to record a rehearsal of a presentation at home or in the office.

[0928] Step 5:

[0929] Users can save and upload recorded presentation practice videos to their devices. Users select the video file in the application and send it to the server.

[0930] Step 6:

[0931] The server receives the presentation practice video and passes it to an analysis tool to evaluate facial expression recognition, speech analysis, posture detection, and gestures.

[0932] Step 7:

[0933] The server identifies areas for improvement based on the video analysis results. It compares the user's performance with standard presentation metrics and lists specific areas for improvement, such as "correcting eye position" and "adjusting voice tone."

[0934] Step 8:

[0935] The server generates a feedback video, which includes points for improvement based on the analysis results, and provides it to the user in a format that is easy to understand.

[0936] Step 9:

[0937] The server sends the generated feedback video to the terminal, where it is displayed in the user's application.

[0938] Step 10:

[0939] The user checks the feedback video. They watch the feedback video on their device and understand the specific areas for improvement.

[0940] Step 11:

[0941] The user practices the presentation again based on the feedback video. They then record a new practice video, keeping in mind the areas for improvement.

[0942] Step 12:

[0943] The user uploads a new presentation practice video to the device, which then sends the video to the server again via the device, ready to receive further feedback.

[0944] Step 13:

[0945] The server generates a final checklist and points to note for the presentation. Based on the final analysis results, the server creates a list of points that the user should pay attention to on the day of the presentation and a list of points to note for optimal performance.

[0946] Step 14:

[0947] The server sends the final checklist and notes to the terminal, which is displayed in the user's application and serves as a final confirmation.

[0948] Step 15:

[0949] The user reviews the final checklist and points to note. Using the information provided, the user makes final preparations for the presentation, allowing them to present with confidence.

[0950] Example 1

[0951] 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."

[0952] Conventional presentation practice systems require users to practice unilaterally, making it difficult for them to receive effective feedback. This makes it difficult for users to objectively evaluate the quality of their presentations and identify specific areas for improvement. The present invention aims to provide a system that allows users to efficiently improve the quality of their presentations through specific feedback provided by a server when practicing a presentation.

[0953] 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.

[0954] In this invention, the server includes means for a user to input presentation materials, means for a user to record a presentation practice video, means for the server to analyze the presentation materials and the presentation practice video, means for the server to identify specific areas for improvement based on the analysis results, means for the server to generate a feedback video based on the areas for improvement, means for the server to provide the feedback video to the user, and means for the server to send a link to the feedback video to the user, so that the user can receive specific feedback after practicing their presentation and practice again based on that feedback.

[0955] "User" refers to a person who creates presentation materials and practices them.

[0956] "Presentation materials" refers to slides and document files (e.g., PowerPoint files or PDF format) used to explain the contents of the presentation.

[0957] "Presentation practice video" refers to a video recorded by a user practicing a presentation.

[0958] "Server" refers to an information processing device for analyzing presentation materials and practice videos and providing feedback.

[0959] "Means for Analysis" refers to the software and algorithms used by the Server to analyze and evaluate the content of presentation materials and practice videos.

[0960] "Means for identifying areas for improvement" refers to the algorithms and software that the server uses to list specific areas for improvement in the presentation based on the analysis results.

[0961] "Feedback video" refers to a video provided to a user in which specific improvements are added as an overlay to the user's presentation practice video.

[0962] "Means for sending a link" refers to the means (e.g., email or in-app notification) for notifying the user of the URL of the feedback video generated by the server.

[0963] The present invention is a system that aims to enable users to efficiently improve the quality of their presentations, and a series of processes are carried out through cooperation between the user's terminal and a server. Detailed embodiments will be described below.

[0964] 1. System Configuration

[0965] The system mainly consists of the following components:

[0966] User's device: A device used to input presentation materials, record practice videos, and check feedback videos. This can be a PC or smartphone.

[0967] Server: An information processing device that analyzes the received presentation materials and practice videos, and generates and manages feedback.

[0968] 2. Hardware and Software Used

[0969] On the user's device:

[0970] Devices (PC, smartphone)

[0971] Management applications (e.g. cloud storage apps, camera apps)

[0972] Recording application (e.g. standard camera app)

[0973] server:

[0974] Server with high-performance CPU and RAM

[0975] Analysis software (e.g., natural language processing tools, image analysis tools)

[0976] AI models (e.g., generative AI, machine learning algorithms)

[0977] Video editing software (e.g., video editing tools, overlay adding functions)

[0978] Data transmission software (e.g., cloud storage, distribution software)

[0979] 3. Example of operation

[0980] The user enters the presentation materials

[0981] Users upload presentation materials (e.g., slides introducing new products) to the system using their own terminals. Once uploaded, the materials are stored on the server.

[0982] Users record practice videos for their presentations

[0983] Users can record their presentation rehearsals using a camera app at home or in the office, press the "Start Recording" button to practice, and then press the "Stop Recording" button when they're done. They can then upload the video to the system.

[0984] The server analyzes the presentation materials and practice videos.

[0985] The server receives the materials and analyzes the content of the slides using natural language processing tools, while for videos, it uses image and audio analysis tools to evaluate the user's facial expressions, speech, posture, and gestures.

[0986] For example, it analyzes the volume and intonation of the user's voice and eye movements and compares them with pre-set standards.

[0987] The server identifies specific areas for improvement

[0988] The server runs an AI model based on the analyzed data and generates a list of specific improvements to the presentation, such as "focus your gaze more on the audience on the third slide" or "improve your intonation."

[0989] The server generates the feedback video

[0990] The server uses video editing software to generate a feedback video with overlays of improvements, for example adding a suggestion to "smile more" to the user's video.

[0991] The server provides the feedback video

[0992] Once the feedback video is generated, the server will upload it to the cloud storage and send the link to the user, who can click the link to play the feedback video.

[0993] The user practices again based on the feedback video.

[0994] The user watches the feedback video, understands what needs to be improved, and practices the presentation again. The newly recorded video is then uploaded to the server again.

[0995] 4. Example prompts for generative AI models

[0996] Below is an example of a prompt sentence to input to the generative AI model.

[0997] "Analyze the practice video of the presentation and provide suggestions for improvement. Please point out specific areas that need improvement (e.g., eye contact, vocalization, gestures) and generate a feedback video."

[0998] As described above, the system of the present invention provides specific feedback to users to help them efficiently improve the quality of their presentations, allowing them to approach the day of their presentation with confidence.

[0999] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1000] Step 1:

[1001] The user enters the presentation materials

[1002] Input: Presentation materials (PowerPoint files or PDF format)

[1003] Specific operation: The user uses the device to open the management application, clicks the "Select File" button, selects the presentation material to upload, and then clicks the "Upload" button.

[1004] Data processing / calculation: Uploaded files are sent to the server and stored there.

[1005] Output: The presentation materials are saved on the server.

[1006] Step 2:

[1007] Users record practice videos for their presentations

[1008] Input: Presentation practice video

[1009] Specific operation: The user opens the camera app on their device, clicks the "Start Recording" button, starts speaking, and then clicks the "Stop Recording" button when the rehearsal is over. The recorded video is then uploaded to the system.

[1010] Data processing / calculation: The recorded video file is sent from the device to the server and stored on the server.

[1011] Output: The presentation practice video will be saved on the server.

[1012] Step 3:

[1013] The server analyzes the presentation materials and practice videos.

[1014] Input: Presentation materials, Presentation practice video

[1015] Specific behavior:

[1016] The server receives the presentation materials and uses natural language processing (NLP) tools to analyze the content of the slides, for example, analyzing the frequency of important keywords and the structure of the slides.

[1017] For presentation practice videos, image and audio analysis tools are used to evaluate the user's facial expressions, clarity of speech, posture, and gestures.

[1018] Data processing / calculation: Generate analysis results of presentation materials and practice videos (e.g., voice volume, intonation, eye movements).

[1019] Output: Analysis results

[1020] Step 4:

[1021] The server identifies specific areas for improvement

[1022] Input: Analysis results

[1023] Specific actions: The server runs the AI ​​model based on the analysis results and lists specific improvements for each element of the presentation, such as "focus your eyes more on the audience on the third slide" or "improve your intonation."

[1024] Data processing / calculation: Using the analysis results, an algorithm is run to extract areas for improvement.

[1025] Output: Identified improvements

[1026] Step 5:

[1027] The server generates the feedback video

[1028] Input: Identified areas for improvement, Presentation practice video

[1029] What it does: The server uses video editing software to generate a feedback video by overlaying identified areas for improvement onto the presentation practice video, for example, by overlaying a suggestion like "Smile more."

[1030] Data processing / calculation: Create a feedback video with improvements added as an overlay.

[1031] Output: Feedback video

[1032] Step 6:

[1033] The server provides the feedback video

[1034] Input: Feedback video

[1035] Specific operation: The server uploads the generated feedback video to cloud storage and notifies the user of the link, which the user can click to play the feedback video.

[1036] Data processing / calculation: Uploading videos to cloud storage and generating links.

[1037] Output: Feedback video link

[1038] Step 7:

[1039] The user re-practices

[1040] Input: Feedback video

[1041] Specific actions: Based on the feedback video, the user practices the presentation again, incorporating specific improvements. The newly recorded video is then uploaded to the server again.

[1042] Data processing / calculation: Generate a new practice video that reflects the improvements and upload it to the server.

[1043] Output: New presentation practice video

[1044] Step 8:

[1045] The server provides a final checklist and points to note

[1046] Input: Final presentation practice video, analysis results

[1047] Specific operation: Based on the final analysis results, the server generates a final checklist and points to note for the presentation, such as "keep your voice consistent" and "move your eyes when changing slides."

[1048] Data processing / calculation: Automatic generation of final checklist and notes.

[1049] Output: Final checklist and notes PDF

[1050] Through these steps, the system provides users with the feedback and support they need to efficiently improve the quality of their presentations.

[1051] (Application example 1)

[1052] 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."

[1053] Conventional systems for improving the quality of presentations have the drawback of making it difficult for users to receive specific feedback in real time when practicing their presentations, making it difficult to practice and improve efficiently.In particular, in factories and other workplaces, it is necessary to explain new processes and provide training on operation methods quickly and accurately, and real-time feedback is required.

[1054] 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.

[1055] In this invention, the server includes means for a user to input presentation materials, means for the user to record a presentation practice video, means for the server to analyze the presentation materials and the presentation practice video, means for the server to identify specific areas for improvement based on the analysis results, means for the server to generate a feedback video based on the areas for improvement, means for the server to provide the feedback video to the user, and means for the user to check the feedback in real time. As a result, when a user practices a presentation, the recorded video can be analyzed on the spot and feedback indicating specific areas for improvement can be provided in real time, allowing the quality of the presentation to be improved quickly and efficiently.

[1056] "User" refers to the individual or entity who inputs presentation materials and records practice videos.

[1057] "Presentation materials" refers to digital files that contain documents, slides, charts, etc. that illustrate the content of a presentation.

[1058] "Presentation practice video" refers to footage of a presentation that a user has recorded for practice purposes.

[1059] "Server" refers to a computer system that analyzes presentation materials and practice videos, identifies areas for improvement, and generates and provides feedback videos.

[1060] "Analysis" refers to the process of evaluating and examining the content of the presentation materials and practice video to identify areas for improvement.

[1061] "Improvements" refers to changes or modifications that may be required to improve the quality of the user's presentation.

[1062] "Feedback video" refers to a video generated by the server that includes specific advice and comments on the user's presentation.

[1063] "Real-time feedback" refers to feedback provided instantly while a user is performing a practice presentation.

[1064] This invention is a system for improving the quality of presentations, which handles everything from inputting presentation materials to providing feedback. This system mainly consists of the following elements:

[1065] 1. On the user's device:

[1066] First, the user uploads presentation materials to the server via their device. Presentation materials can be slides, PDFs, images, etc., and the user can send them from their device to the server. Next, the user uses the device's camera function to record a practice video for the presentation. The recorded video is automatically uploaded to the server.

[1067] 2. Server:

[1068] The server analyzes the received presentation materials and practice videos, including slide content evaluation, voice volume and intonation, eye movements, posture, and gestures. Based on these analysis results, the server uses a generative AI model to identify specific areas for improvement.

[1069] 3. Providing Feedback:

[1070] Based on the analysis results, the server generates a feedback video containing specific areas for improvement. This feedback video is then provided to the user's device. The user can also view the feedback in real time by wearing smart glasses. This allows the user to understand the areas for improvement on the spot and immediately incorporate them into their practice.

[1071] A specific example is a training session on how to operate a new process in a factory. Factory workers wear smart glasses and record themselves demonstrating the operation of the new process. The recorded video is uploaded to a server, which analyzes the video content and provides specific feedback on areas for improvement. The feedback is displayed in real time on the smart glasses, allowing the workers to immediately implement the improvements.

[1072] Example prompt sentence:

[1073] "When training factory workers on a new assembly process, create a demo system that allows them to record themselves using smart glasses and provide real-time feedback on areas for improvement. The system would analyze the video, evaluate assembly accuracy and efficiency, and provide specific feedback on the smart glasses."

[1074] This system not only improves the quality of presentations quickly and efficiently, but also effectively supports the learning of new processes in factories and other workplaces.

[1075] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1076] Step 1:

[1077] User uploads presentation materials

[1078] First, the user selects presentation materials from their own device and uploads them to the server. The input is the presentation material file (slides, PDF, etc.) saved on the user's device, and the output is the same material saved on the server. Data processing involves transferring the material file to the server, checking the file format, and converting it into an analyzable format.

[1079] Step 2:

[1080] Users record practice videos for their presentations

[1081] A user uses the device's camera to record a presentation practice video. Once recording is complete, the video file is uploaded to the server. The input is the video feed recorded by the camera, and the output is the practice video file stored on the server. Data processing involves compressing and formatting the video for efficient transfer to the server.

[1082] Step 3:

[1083] The server analyzes the presentation materials and practice videos.

[1084] The server analyzes the uploaded presentation materials and practice videos. The input is the presentation materials and practice videos stored on the server, and the output is the analysis results. Data calculation involves using a generative AI model to evaluate the content of the slides, analyze the volume and intonation of the voice, eye movements, posture, and gestures.

[1085] Step 4:

[1086] The server identifies specific areas for improvement

[1087] The server extracts specific improvement points based on the analysis results. The input is the analysis results obtained in step 3, and the output is a list of improvement points. Data calculation is to compare the analysis data with the good performance standards of the existing presentation and identify the differences.

[1088] Step 5:

[1089] The server generates the feedback video

[1090] The server generates a feedback video that reflects specific improvements. The input is a list of improvements and the original practice video, and the output is the feedback video. Data processing involves adding graphics and text indicating the improvements as an overlay on the original practice video.

[1091] Step 6:

[1092] The server provides the feedback video

[1093] The server provides the generated feedback video to the user. The input is the feedback video, and the output is a feedback video link that can be played on the user's device. The data processing involves converting the feedback video into an appropriate format and uploading it to cloud storage for user access.

[1094] Step 7:

[1095] Users practice again based on feedback

[1096] The user reviews the feedback video, reflects the improvements, practices the presentation again, and records the video. The input is the feedback video and the newly recorded practice video, and the output is the re-uploaded practice video. Data calculation involves adjusting the practice content based on the improvements suggested by the user.

[1097] Step 8:

[1098] The server provides a final checklist and points to note

[1099] The server analyzes the user's final presentation practice video and provides a final checklist and points to note. The input is the final practice video, and the output is the final checklist and a list of points to note. The data calculation analyzes the final practice video and once again confirms the necessary improvements and points to note.

[1100] 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.

[1101] The present invention is a system that allows users to efficiently improve the quality of their presentations, and in particular provides more advanced feedback by combining it with an emotion engine that recognizes the user's emotions.

[1102] System configuration

[1103] The system consists of the following main components:

[1104] 1. User's device: This is the device used to input presentation materials, record practice videos, and check feedback videos and emotional feedback.

[1105] 2. Server: A device that analyzes presentation materials, practice videos, and user emotional data, and generates and manages feedback.

[1106] 3. Emotion engine: It has the function to recognize the user's emotions and generate feedback accordingly.

[1107] User Flow

[1108] 1. User enters presentation materials:

[1109] Users upload PowerPoint files or presentation materials in PDF format to the server via their terminals.

[1110] For example, a user uploads a presentation document introducing a new product that the user has created to the application.

[1111] 2. User records a practice video of their presentation:

[1112] Users use the device's camera to record their presentation rehearsals, and the device also collects emotional data such as facial expressions and tone of voice.

[1113] For example, a user rehearses at home, records the rehearsal on video, and simultaneously collects emotional data.

[1114] 3. The server analyzes the presentation materials and practice video:

[1115] The server analyzes the content of the presentation materials and practice videos received, evaluating the structure, content, and performance of the slides. The emotion engine also analyzes the user's emotions.

[1116] For example, the server analyzes the user's emotions from the volume of their voice, intonation, eye movements, and facial expressions, and compares them with standard presentation metrics.

[1117] 4. The server identifies specific areas for improvement and emotional feedback:

[1118] Based on the analysis results, the server identifies specific areas for improvement for each element of the presentation, while the emotion engine provides optimal emotional feedback based on the user's emotional data.

[1119] For example, in addition to corrections such as "correct your gaze position" and "adjust your tone of voice," it identifies emotion-based advice such as "try to relax a bit more."

[1120] 5. The server generates the feedback video and emotional feedback:

[1121] The server creates a feedback video that reflects the improvements and simultaneously generates a video that includes emotional feedback.

[1122] For example, it generates a video that overlays areas for improvement on the user's video and adds emotion-based comments such as "Speak with more confidence here."

[1123] 6. The server provides the feedback video:

[1124] The server sends the generated feedback video to the user's device, where the user can view the video and understand specific improvements and emotional feedback.

[1125] 7. User re-practices:

[1126] The user practices the presentation again based on the feedback video and emotional feedback, records a new video, and recollects emotional data.

[1127] 8. The server provides a final checklist and notes for the presentation:

[1128] The server generates a checklist of points to note on the day of the presentation based on the final analysis results and emotional feedback, and sends it to the user.

[1129] In this way, the system of the present invention provides not only specific feedback but also emotional feedback to highly improve the user's presentation skills, supporting them to approach the day of the presentation with confidence.

[1130] The processing flow will be explained below.

[1131] Step 1:

[1132] The user inputs the presentation materials. The user prepares the presentation materials in PowerPoint or PDF format and uploads the files to the presentation application using the terminal.

[1133] Step 2:

[1134] The device sends the presentation materials received from the user to the server, where the files are uploaded to the server using a secure protocol.

[1135] Step 3:

[1136] The server receives the presentation materials and begins analyzing them. The server evaluates the text content, slide structure, visual elements, etc. of the materials and performs an initial analysis based on the presentation quality criteria.

[1137] Step 4:

[1138] The user records a video of their presentation practice. The user rehearses their presentation at home or in the office using the device's camera. At the same time, the device also collects emotional data such as the user's facial expressions and tone of voice.

[1139] Step 5:

[1140] Users can save and upload recorded presentation practice videos to their devices. Users select the video file in the application and send it to the server.

[1141] Step 6:

[1142] The server receives the presentation practice video. The server passes the video to the analysis tool, which performs facial expression recognition, speech analysis, posture detection, and gesture evaluation. At the same time, the emotion engine analyzes the user's emotional data.

[1143] Step 7:

[1144] The server identifies areas for improvement based on the video analysis results. The server analyzes the user's performance and lists specific areas for improvement, such as "correcting the position of your gaze" and "adjusting the tone of your voice." The emotion engine also provides emotion-based advice, such as "try to relax," based on the user's emotional data.

[1145] Step 8:

[1146] The server generates a feedback video and emotional feedback. The server creates a feedback video that reflects the points for improvement and also generates a video that includes emotional feedback. For example, in addition to specific points for improvement such as "It would be good to raise your eye contact here," the server incorporates emotional advice such as "Speak with more confidence" into the feedback video.

[1147] Step 9:

[1148] The server sends the generated feedback video to the terminal, where it is displayed in the user's application.

[1149] Step 10:

[1150] The user reviews the feedback video. They watch the feedback video on their device and understand the specific improvements and emotional feedback.

[1151] Step 11:

[1152] The user practices the presentation again based on the feedback video and emotional feedback. With the areas for improvement in mind, the user re-records the presentation, and the device again collects the video and emotional data.

[1153] Step 12:

[1154] The user saves a new presentation practice video on the device, uploads it, and then sends the video back to the server via the device, ready to receive further feedback.

[1155] Step 13:

[1156] The server generates a final checklist and points to note for the presentation. Based on the final analysis results and emotional feedback, the server lists points to note on the day of the presentation and provides them to the user.

[1157] Step 14:

[1158] The server sends the final checklist and notes to the terminal, which is displayed in the user's application and serves as a final confirmation.

[1159] Step 15:

[1160] The user reviews the final checklist and points to note. Using the information provided, the user makes final preparations for the presentation, allowing them to present with confidence.

[1161] Example 2

[1162] 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."

[1163] Conventional presentation practice systems lack the functionality to provide specific feedback and advice based on emotional data specifically designed to improve users' performance. As a result, users have to spend time and effort to improve the quality of their presentations, making it difficult to make effective improvements.

[1164] The identification process by the identification 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 analyzing the presentation materials and the presentation practice video, means for identifying specific improvements and emotional feedback based on the analysis results, and means for generating a feedback video that reflects the specific improvements and emotional feedback. This enables the user to quickly and efficiently receive specific feedback and emotional advice to effectively improve the quality of their presentation.

[1165] "User" refers to a person who uses the system to create and improve presentation materials.

[1166] "Means for inputting presentation materials" refers to the function that allows users to upload PowerPoint files or PDF format presentation materials to the server via their terminal.

[1167] "Means for recording a presentation practice video" refers to a function that allows a user to use the camera function of the device to record a presentation practice and save the video data.

[1168] "Server" refers to a central processing unit for analyzing presentation materials and presentation practice videos and generating and providing feedback.

[1169] "Means for analyzing presentation materials and presentation practice videos" refers to the function of analyzing the materials and videos received by the server and evaluating the slide structure, content, and performance.

[1170] "Means for identifying specific areas for improvement and emotional feedback" refers to a function in which the server identifies areas for improvement and emotional feedback for each element of the user's presentation based on the analysis results.

[1171] "Means for generating a feedback video that reflects specific areas for improvement and emotional feedback" refers to a function in which the server generates a presentation practice video of the user by overlaying specific areas for improvement and emotional feedback on the user's presentation practice video based on the analysis results.

[1172] The "means for providing a feedback video to a user" refers to a function for transmitting a feedback video generated by a server to a user terminal, allowing the user to view the video.

[1173] "Means for uploading the re-recorded presentation practice video and emotional data to the server" refers to a function that allows the user to practice the presentation again and send the video and emotional data to the server.

[1174] "Means for generating a final checklist and points to note for the presentation and providing it to the user" refers to the function by which the server generates a checklist summarizing points to note on the day of the presentation based on the final analysis results and emotional feedback, and provides it to the user.

[1175] This invention is a system that allows users to efficiently improve the quality of their presentations, and in particular, by combining it with an emotion engine that recognizes the user's emotions, it provides more advanced feedback. The system of this invention supports the improvement of presentation skills by evaluating the user's presentation practice from multiple angles and providing creative feedback.

[1176] System configuration

[1177] The system consists of the following main components:

[1178] 1. User's device: This is the device used to input presentation materials, record practice videos, and check feedback videos and emotional feedback.

[1179] 2. Server: A device that analyzes presentation materials, practice videos, and user emotional data, and generates and manages feedback.

[1180] 3. Emotion engine: It has the function to recognize the user's emotions and generate feedback accordingly.

[1181] Hardware and software used

[1182] User's device: smartphone, tablet, or computer (with camera function)

[1183] Server: High-performance analysis server (e.g. AWS EC2)

[1184] Emotion engine: Emotion recognition software (e.g. Microsoft Azure Emotion API)

[1185] Example of operation

[1186] User enters presentation material:

[1187] First, the user uploads the presentation materials from the device to the server. Using the application on the device, the user clicks the "Upload Materials" button, selects a PowerPoint file or a PDF file, and uploads it. For example, this is the case when the user uploads presentation materials for introducing a new product.

[1188] User records a practice presentation video:

[1189] Next, the user uses the device's camera function to record the presentation rehearsal. During the recording, the device simultaneously collects emotional data such as the user's facial expressions and tone of voice. For example, a user may rehearse a new product introduction at home and record the rehearsal on video.

[1190] The server analyzes the presentation and practice video:

[1191] Uploaded presentation materials and practice videos are sent to a server, which analyzes their content. The server uses AI analysis software to evaluate the structure and content of the slides and the user's performance (e.g., voice volume, eye movements, facial expressions), and an emotion engine analyzes the user's emotions.

[1192] The server identifies specific areas for improvement and sentiment-based feedback:

[1193] Based on the analysis results, the server identifies specific areas for improvement for each element of the presentation. At the same time, the emotion engine provides optimal emotional feedback based on the user's emotional data. For example, it provides technical corrections such as "correct your eye position" or "adjust your tone of voice" as well as emotional advice such as "try to relax a bit more."

[1194] The server generates the feedback video and emotional feedback:

[1195] The server then creates a feedback video that reflects these improvements and generates a video that includes emotional feedback. Specifically, the server overlays the video to indicate the areas for improvement and adds comments such as "Speak more confidently here."

[1196] The server provides the feedback video:

[1197] The generated feedback video is sent from the server to the user's device, where the user can view the feedback video on the device and understand the specific improvements and emotional feedback. For example, the user can play the video on the application and view the provided feedback.

[1198] User re-practices:

[1199] Based on the feedback, users practice their presentations again, record new practice videos, and recollect emotion data, thereby further improving their presentation skills.

[1200] Example prompts for generative AI models

[1201] "Please provide feedback on my presentation. Analyze the video and materials below and give me specific improvements and emotionally-driven advice."

[1202] In this way, the system of the present invention provides not only specific feedback but also emotional feedback to highly improve the user's presentation skills, supporting them to approach the day of the presentation with confidence.

[1203] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1204] Step 1:

[1205] The device accepts the user's presentation materials. The user uploads presentation materials in PowerPoint or PDF format through the device's application (input). The device sends these materials to the server (output). Specifically, the user opens the application, clicks the "Upload Materials" button, selects the presentation materials from the file selection dialog, and begins uploading.

[1206] Step 2:

[1207] The device records a video of the user practicing their presentation. The user uses the device's camera function to record their presentation rehearsal, and emotional data is automatically collected (input). The recorded video and emotional data are saved on the device (output). Specifically, the user presses the "Start Recording" button to start the presentation, and once recording is complete, presses the "Stop Recording" button to save the video.

[1208] Step 3:

[1209] The server analyzes the presentation materials and practice video. The server receives the presentation materials, practice video, and emotional data sent from the device (input). The server uses AI analysis software to evaluate the slide structure, content, and user performance (volume of voice, eye movement, facial expression), and analyzes emotions using an emotion engine (data processing and data calculation). The analysis results are generated (output). Specifically, the server launches the AI ​​analysis software and takes in the uploaded materials and video as input data.

[1210] Step 4:

[1211] The server identifies specific areas for improvement and emotional feedback. Based on the analysis results, the server identifies specific areas for improvement and emotional feedback for each element of the user's presentation (input). For example, technical corrections such as "correct your gaze position" or "adjust your tone of voice" and emotional advice such as "try to relax a bit more" are generated (output). The server creates feedback data based on this data (data processing).

[1212] Step 5:

[1213] The server generates a feedback video and emotional feedback. Based on the feedback data, the server adds improvements and emotional feedback as an overlay to the user's practice video (input). Specifically, the server launches video editing software and adds text and graphics indicating areas for improvement, as well as emotional feedback as text (data processing). Finally, a feedback video is generated (output).

[1214] Step 6:

[1215] The server provides the feedback video to the user. The server then sends the generated feedback video to the user's device (input and output). Specifically, the server uploads the feedback video to cloud storage and sends a download link to the user via email or in-app notification. The user clicks the link to watch the video.

[1216] Step 7:

[1217] The user practices the presentation again. The user practices the presentation again based on the feedback video and emotional feedback and records a new practice video (input). The device records a new video and collects emotional data again (output). Specifically, the user presses the "Start Recording" button again, rehearses, and presses the "Stop Recording" button to save the video.

[1218] Step 8:

[1219] The server provides a final checklist and important points for the presentation. The server reanalyzes the newly uploaded video and emotion data, and generates a checklist summarizing important points for the presentation day based on the final analysis results (input and data processing). The server provides this checklist to the user (output). Specifically, the server sends the generated checklist to the user via email or in-app notification.

[1220] (Application example 2)

[1221] 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."

[1222] Conventional presentation practice systems do not provide specific feedback to improve users' emotions or performance, resulting in limited quality practice. Furthermore, in the food delivery industry, there are insufficient training methods for delivery staff to effectively introduce food and services, making it difficult to improve the user experience.

[1223] The specification processing by the specification 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 a user to input presentation materials, means for a user to record a presentation practice video, means for the server to analyze the presentation materials and the presentation practice video, means for the server to identify specific areas for improvement based on the analysis results, means for the server to generate a feedback video based on the areas for improvement, means for the server to provide the feedback video to the user, means for delivery staff to record and upload explanations of dishes and service introductions, and means for the server to analyze the videos and provide advice on improving hospitality. This makes it possible to improve not only the quality of presentations but also the quality of food delivery service.

[1224] A "user" is an entity that creates presentation materials and records a practice video.

[1225] "Presentation materials" refers to information such as documents, charts, slides, etc. that a user uses to give a presentation.

[1226] "Presentation practice video" refers to video data that records a user practicing a presentation.

[1227] "Server" refers to the computer system that analyzes the presentation materials and presentation practice videos and generates and provides feedback.

[1228] "Means for analyzing" refers to a method or device for evaluating and analyzing the content of presentation materials and presentation practice videos received by the server.

[1229] The means for identifying "specific areas for improvement" refers to a method or device for finding specific advice or instructions for improving the quality of the presentation based on the analysis results.

[1230] The "means for generating a feedback video" refers to a method or device by which the server creates a feedback video that reflects the analysis results and improvements.

[1231] The "means for providing a feedback video" refers to a method or device for transmitting the feedback video generated by the server to the user's terminal so that the user can view it.

[1232] "Delivery staff" refers to people who deliver food and provide services in food delivery services.

[1233] "Means for recording and uploading descriptions of dishes and service introductions" refers to a method or device by which delivery staff record descriptions of dishes and service contents and upload the videos to a server.

[1234] "Means for providing advice to improve hospitality" refers to a method or device in which a server analyzes uploaded videos and generates and provides specific advice to delivery staff to provide better service.

[1235] This invention is a system that allows users to efficiently improve the quality of their presentations, and in particular provides feedback on presentation skills and emotions by combining an emotion engine that recognizes the user's emotions. Furthermore, to improve the quality of food delivery services, the system includes a function that analyzes introductory videos of delivery staff and provides specific advice for improving the service.

[1236] System configuration

[1237] The system consists of the following main components:

[1238] 1. User's device

[1239] This device is used to input presentation materials and record practice videos. Users upload PowerPoint files and PDF format presentation materials to the server through the device. The device is also equipped with a camera function to record and upload practice videos.

[1240] 2. Server

[1241] This is a computer system that receives and analyzes presentation materials and practice videos. The server has the following functions:

[1242] Data analysis: Analyze the content of the presentation materials and practice videos received to evaluate their structure and performance.

[1243] Emotion Engine: Recognizes user emotions in training videos and analyzes emotion data.

[1244] Feedback generation: Based on the analysis results, specific areas for improvement are identified and a feedback video is generated that reflects these areas.

[1245] Video provision: Send feedback videos to the user's device and provide feedback for improvement.

[1246] 3. Delivery staff

[1247] This person records videos explaining the dishes and services and uploads them to a server, which analyzes the videos and provides advice on how to improve the service.

[1248] Example

[1249] 1. Inputting presentation materials

[1250] Consider an example where a user uploads a presentation document for introducing a new product from a terminal to a server. The user uses a PowerPoint file or a PDF.

[1251] 2. Record a practice video of your presentation

[1252] The user rehearses at home and records the rehearsal on video, while the device simultaneously collects emotional data such as facial expressions and tone of voice.

[1253] 3. Data analysis and feedback generation

[1254] The server analyzes the presentation materials and practice videos it receives, and analyzes the user's emotions based on the volume of their voice, intonation, eye movements, and facial expressions, and compares them with standard presentation indicators. Based on the results of this analysis, it generates specific improvements (e.g., "correct your eye position" or "adjust your tone of voice") and emotion-based advice (e.g., "try to relax a bit more").

[1255] 4. Providing feedback videos

[1256] The server creates a feedback video that reflects the analysis results and overlays it on the user's video to show areas for improvement. It also adds emotional comments such as "Try to speak more confidently here."

[1257] Food delivery application example

[1258] Delivery staff record and upload their explanations of the dishes and the service they provide. The server analyzes the videos and generates specific advice for delivery staff to provide better service (e.g., "serve customers with a smile" or "explain the key points of the dishes clearly").

[1259] Hardware and software used

[1260] Hardware: User devices (smartphones, tablets, PCs), cameras, servers

[1261] Software: Emotion recognition API (e.g., Google Cloud Vision, Amazon Rekognition), video analysis software (e.g., OpenCV)

[1262] Prompt Sentence Examples

[1263] Video analysis results:

[1264] Gaze position: 60% camera direction

[1265] Confidence level: 45%

[1266] Emotional feedback example:

[1267] Turn your gaze more towards the camera.

[1268] Try to speak more confidently.

[1269] It is expected that this system will improve the quality of presentations and service provision, providing users and customers with a more satisfying experience.

[1270] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1271] Step 1:

[1272] A means for users to input presentation materials

[1273] A user uploads a presentation document in PowerPoint or PDF format to the server via their device. The input is the presentation document file, which the server receives. Specifically, the user opens the application and clicks the "Upload Presentation Document" button.

[1274] Step 2:

[1275] A way for users to record practice videos of their presentations

[1276] The user uses the device's camera function to record a presentation rehearsal. The device also collects emotional data such as the user's facial expressions and tone of voice. The input is a video file and emotional data, and the output is a recorded video file. Specifically, the user presses the "Start Recording" button, gives the presentation, and then presses the "Stop Recording" button.

[1277] Step 3:

[1278] A means for the server to analyze presentation materials and presentation practice videos

[1279] The server analyzes the received presentation materials and practice video content and evaluates the slide structure, content, and performance. At the same time, the emotion engine analyzes the user's emotions. The input is the presentation material file and the recorded video file, and the output is the analyzed data. Specifically, the server calls the emotion recognition API and analyzes the user's emotional data. It also uses video analysis software such as OpenCV to analyze the video's movements.

[1280] Step 4:

[1281] A means for the server to identify specific areas for improvement

[1282] Based on the analysis results, the server identifies specific areas for improvement for each element of the presentation. The input is the analysis data, and the output is specific improvement suggestions. Specifically, the server compares the analysis data with standard presentation indicators and derives specific areas for improvement related to eye gaze position, tone of voice, and facial expressions.

[1283] Step 5:

[1284] A means for the server to generate feedback videos based on improvements

[1285] The server creates a feedback video that reflects the improvements and overlays them on the user's video. It also adds emotional comments. The input is the recorded video file and the improvement proposal data, and the output is the feedback video. Specifically, the server uses video editing software to add an overlay to the video and insert the comments.

[1286] Step 6:

[1287] A means by which the server provides feedback videos to the user

[1288] The server sends the generated feedback video to the user's device. The input is the feedback video file, and the output is the feedback video sent to the user's device. Specifically, the server sends a notification to the user's device and displays a message saying "A new feedback video is ready."

[1289] Step 7:

[1290] A way for users to practice their presentations again based on the feedback video

[1291] The user reviews the feedback video, understands the specific areas for improvement and emotional feedback, and then practices the presentation again. The input is the feedback video, and the output is a re-recorded presentation practice video. Specifically, the user watches the feedback video, presses the "Start Re-Practice" button, and practices again, noting the areas for improvement.

[1292] Step 8:

[1293] How to upload the re-recorded presentation practice video to the server

[1294] The user uploads the re-recorded presentation practice video to the server and re-analyzes it. The input is the re-recorded presentation practice video, and the specific operation is for the user to click the "Upload re-practice video" button.

[1295] This embodiment improves the quality of presentation and service delivery, providing a more satisfying experience for users and customers.

[1296] 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.

[1297] 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.

[1298] 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.

[1299] [Fourth embodiment]

[1300] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1301] 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.

[1302] 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).

[1303] 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.

[1304] 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.

[1305] 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).

[1306] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1307] 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.

[1308] 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.

[1309] 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.

[1310] 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.

[1311] 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.

[1312] 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."

[1313] This invention is a system that aims to enable users to efficiently improve the quality of their presentations. This system is composed of a series of processes: the user inputs presentation materials, practices the presentation based on those materials, the server analyzes the content, and provides feedback on areas for improvement.

[1314] System configuration

[1315] The system consists of the following main components:

[1316] 1. User's device: This is the device used to input presentation materials, record practice videos, and check feedback videos.

[1317] 2. Server: A device that analyzes the received presentation materials and practice videos, and generates and manages feedback.

[1318] User Flow

[1319] 1. User enters presentation materials:

[1320] Users upload PowerPoint files or presentation materials in PDF format to the server via their terminal.

[1321] For example, a user uploads a presentation document introducing a new product that the user has created to the application.

[1322] 2. User records a practice video of their presentation:

[1323] The user uses the device's camera function to record the presentation practice.

[1324] For example, a user rehearses a presentation at home and records the rehearsal on video.

[1325] 3. The server analyzes the presentation materials and practice video:

[1326] The server analyzes the presentation materials received and evaluates the structure and content of the slides.

[1327] The server analyzes the presentation practice video and evaluates performance such as facial expressions, pronunciation, posture, and gestures.

[1328] For example, the server analyzes the volume, intonation, and eye movements of the user's voice and compares them with certain standards.

[1329] 4. The server identifies specific areas for improvement:

[1330] Based on the analysis results, the server lists specific areas for improvement for each element of the presentation.

[1331] For example, identify advice such as "Look more at the audience on slide 3" or "Increase your intonation."

[1332] 5. The server generates the feedback video:

[1333] The server creates a feedback video that reflects the improvements.

[1334] For example, a video can be generated that overlays the user's video to show areas for improvement.

[1335] 6. The server provides the feedback video:

[1336] The server transmits the generated feedback video to the user's terminal.

[1337] For example, the user plays the feedback video on the device and identifies specific areas for improvement.

[1338] 7. User re-practices:

[1339] The user practices the presentation again based on the feedback video and records a new video.

[1340] For example, the user may incorporate the improvements suggested, re-record the presentation, and upload it to the server.

[1341] 8. The server provides a final checklist and notes:

[1342] The server generates a final checklist for the presentation and points to be noted on the day, and provides it to the user.

[1343] For example, make a list of final check points such as "keep your voice tone consistent" and "move your eyes when changing slides."

[1344] In this way, the system of the present invention provides specific feedback that allows users to efficiently improve the quality of their presentation, allowing them to approach the day of the presentation with confidence.

[1345] The processing flow will be explained below.

[1346] Step 1:

[1347] The user inputs the presentation materials. The user prepares the materials to be used in the presentation, such as PowerPoint files or PDF files, and uploads the files to the presentation application using the device.

[1348] Step 2:

[1349] The device sends the presentation materials received from the user to the server, where the files are uploaded to the server using a secure protocol.

[1350] Step 3:

[1351] The server receives the presentation materials and begins analyzing them. The server evaluates the text content, slide structure, visual elements, etc. of the materials and performs an initial analysis based on the presentation quality criteria.

[1352] Step 4:

[1353] A user records a practice video of a presentation. A user uses the device's camera to record a rehearsal of a presentation at home or in the office.

[1354] Step 5:

[1355] Users can save and upload recorded presentation practice videos to their devices. Users select the video file in the application and send it to the server.

[1356] Step 6:

[1357] The server receives the presentation practice video and passes it to an analysis tool to evaluate facial expression recognition, speech analysis, posture detection, and gestures.

[1358] Step 7:

[1359] The server identifies areas for improvement based on the video analysis results. It compares the user's performance with standard presentation metrics and lists specific areas for improvement, such as "correcting eye position" and "adjusting voice tone."

[1360] Step 8:

[1361] The server generates a feedback video, which includes points for improvement based on the analysis results, and provides it to the user in a format that is easy to understand.

[1362] Step 9:

[1363] The server sends the generated feedback video to the terminal, where it is displayed in the user's application.

[1364] Step 10:

[1365] The user checks the feedback video. They watch the feedback video on their device and understand the specific areas for improvement.

[1366] Step 11:

[1367] The user practices the presentation again based on the feedback video. They then record a new practice video, keeping in mind the areas for improvement.

[1368] Step 12:

[1369] The user uploads a new presentation practice video to the device, which then sends the video to the server again via the device, ready to receive further feedback.

[1370] Step 13:

[1371] The server generates a final checklist and points to note for the presentation. Based on the final analysis results, the server creates a list of points that the user should pay attention to on the day of the presentation and a list of points to note for optimal performance.

[1372] Step 14:

[1373] The server sends the final checklist and notes to the terminal, which is displayed in the user's application and serves as a final confirmation.

[1374] Step 15:

[1375] The user reviews the final checklist and points to note. Using the information provided, the user makes final preparations for the presentation, allowing them to present with confidence.

[1376] Example 1

[1377] 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."

[1378] Conventional presentation practice systems require users to practice unilaterally, making it difficult for them to receive effective feedback. This makes it difficult for users to objectively evaluate the quality of their presentations and identify specific areas for improvement. The present invention aims to provide a system that allows users to efficiently improve the quality of their presentations through specific feedback provided by a server when practicing a presentation.

[1379] 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.

[1380] In this invention, the server includes means for a user to input presentation materials, means for a user to record a presentation practice video, means for the server to analyze the presentation materials and the presentation practice video, means for the server to identify specific areas for improvement based on the analysis results, means for the server to generate a feedback video based on the areas for improvement, means for the server to provide the feedback video to the user, and means for the server to send a link to the feedback video to the user, so that the user can receive specific feedback after practicing their presentation and practice again based on that feedback.

[1381] "User" refers to a person who creates presentation materials and practices them.

[1382] "Presentation materials" refers to slides and document files (e.g., PowerPoint files or PDF format) used to explain the contents of the presentation.

[1383] "Presentation practice video" refers to a video recorded by a user practicing a presentation.

[1384] "Server" refers to an information processing device for analyzing presentation materials and practice videos and providing feedback.

[1385] "Means for Analysis" refers to the software and algorithms used by the Server to analyze and evaluate the content of presentation materials and practice videos.

[1386] "Means for identifying areas for improvement" refers to the algorithms and software that the server uses to list specific areas for improvement in the presentation based on the analysis results.

[1387] "Feedback video" refers to a video provided to a user in which specific improvements are added as an overlay to the user's presentation practice video.

[1388] "Means for sending a link" refers to the means (e.g., email or in-app notification) for notifying the user of the URL of the feedback video generated by the server.

[1389] The present invention is a system that aims to enable users to efficiently improve the quality of their presentations, and a series of processes are carried out through cooperation between the user's terminal and a server. Detailed embodiments will be described below.

[1390] 1. System Configuration

[1391] The system mainly consists of the following components:

[1392] User's device: A device used to input presentation materials, record practice videos, and check feedback videos. This can be a PC or smartphone.

[1393] Server: An information processing device that analyzes the received presentation materials and practice videos, and generates and manages feedback.

[1394] 2. Hardware and Software Used

[1395] On the user's device:

[1396] Devices (PC, smartphone)

[1397] Management applications (e.g. cloud storage apps, camera apps)

[1398] Recording application (e.g. standard camera app)

[1399] server:

[1400] Server with high-performance CPU and RAM

[1401] Analysis software (e.g., natural language processing tools, image analysis tools)

[1402] AI models (e.g., generative AI, machine learning algorithms)

[1403] Video editing software (e.g., video editing tools, overlay adding functions)

[1404] Data transmission software (e.g., cloud storage, distribution software)

[1405] 3. Example of operation

[1406] The user enters the presentation materials

[1407] Users upload presentation materials (e.g., slides introducing new products) to the system using their own terminals. Once uploaded, the materials are stored on the server.

[1408] Users record practice videos for their presentations

[1409] Users can record their presentation rehearsals using a camera app at home or in the office, press the "Start Recording" button to practice, and then press the "Stop Recording" button when they're done. They can then upload the video to the system.

[1410] The server analyzes the presentation materials and practice videos.

[1411] The server receives the materials and analyzes the content of the slides using natural language processing tools, while for videos, it uses image and audio analysis tools to evaluate the user's facial expressions, speech, posture, and gestures.

[1412] For example, it analyzes the volume and intonation of the user's voice and eye movements and compares them with pre-set standards.

[1413] The server identifies specific areas for improvement

[1414] The server runs an AI model based on the analyzed data and generates a list of specific improvements to the presentation, such as "focus your gaze more on the audience on the third slide" or "improve your intonation."

[1415] The server generates the feedback video

[1416] The server uses video editing software to generate a feedback video with overlays of improvements, for example adding a suggestion to "smile more" to the user's video.

[1417] The server provides the feedback video

[1418] Once the feedback video is generated, the server will upload it to the cloud storage and send the link to the user, who can click the link to play the feedback video.

[1419] The user practices again based on the feedback video.

[1420] The user watches the feedback video, understands what needs to be improved, and practices the presentation again. The newly recorded video is then uploaded to the server again.

[1421] 4. Example prompts for generative AI models

[1422] Below is an example of a prompt sentence to input to the generative AI model.

[1423] "Analyze the practice video of the presentation and provide suggestions for improvement. Please point out specific areas that need improvement (e.g., eye contact, vocalization, gestures) and generate a feedback video."

[1424] As described above, the system of the present invention provides specific feedback to users to help them efficiently improve the quality of their presentations, allowing them to approach the day of their presentation with confidence.

[1425] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1426] Step 1:

[1427] The user enters the presentation materials

[1428] Input: Presentation materials (PowerPoint files or PDF format)

[1429] Specific operation: The user uses the device to open the management application, clicks the "Select File" button, selects the presentation material to upload, and then clicks the "Upload" button.

[1430] Data processing / calculation: Uploaded files are sent to the server and stored there.

[1431] Output: The presentation materials are saved on the server.

[1432] Step 2:

[1433] Users record practice videos for their presentations

[1434] Input: Presentation practice video

[1435] Specific operation: The user opens the camera app on their device, clicks the "Start Recording" button, starts speaking, and then clicks the "Stop Recording" button when the rehearsal is over. The recorded video is then uploaded to the system.

[1436] Data processing / calculation: The recorded video file is sent from the device to the server and stored on the server.

[1437] Output: The presentation practice video will be saved on the server.

[1438] Step 3:

[1439] The server analyzes the presentation materials and practice videos.

[1440] Input: Presentation materials, Presentation practice video

[1441] Specific behavior:

[1442] The server receives the presentation materials and uses natural language processing (NLP) tools to analyze the content of the slides, for example, analyzing the frequency of important keywords and the structure of the slides.

[1443] For presentation practice videos, image and audio analysis tools are used to evaluate the user's facial expressions, clarity of speech, posture, and gestures.

[1444] Data processing / calculation: Generate analysis results of presentation materials and practice videos (e.g., voice volume, intonation, eye movements).

[1445] Output: Analysis results

[1446] Step 4:

[1447] The server identifies specific areas for improvement

[1448] Input: Analysis results

[1449] Specific actions: The server runs the AI ​​model based on the analysis results and lists specific improvements for each element of the presentation, such as "focus your eyes more on the audience on the third slide" or "improve your intonation."

[1450] Data processing / calculation: Using the analysis results, an algorithm is run to extract areas for improvement.

[1451] Output: Identified improvements

[1452] Step 5:

[1453] The server generates the feedback video

[1454] Input: Identified areas for improvement, Presentation practice video

[1455] What it does: The server uses video editing software to generate a feedback video by overlaying identified areas for improvement onto the presentation practice video, for example, by overlaying a suggestion like "Smile more."

[1456] Data processing / calculation: Create a feedback video with improvements added as an overlay.

[1457] Output: Feedback video

[1458] Step 6:

[1459] The server provides the feedback video

[1460] Input: Feedback video

[1461] Specific operation: The server uploads the generated feedback video to cloud storage and notifies the user of the link, which the user can click to play the feedback video.

[1462] Data processing / calculation: Uploading videos to cloud storage and generating links.

[1463] Output: Feedback video link

[1464] Step 7:

[1465] The user re-practices

[1466] Input: Feedback video

[1467] Specific actions: Based on the feedback video, the user practices the presentation again, incorporating specific improvements. The newly recorded video is then uploaded to the server again.

[1468] Data processing / calculation: Generate a new practice video that reflects the improvements and upload it to the server.

[1469] Output: New presentation practice video

[1470] Step 8:

[1471] The server provides a final checklist and points to note

[1472] Input: Final presentation practice video, analysis results

[1473] Specific operation: Based on the final analysis results, the server generates a final checklist and points to note for the presentation, such as "keep your voice consistent" and "move your eyes when changing slides."

[1474] Data processing / calculation: Automatic generation of final checklist and notes.

[1475] Output: Final checklist and notes PDF

[1476] Through these steps, the system provides users with the feedback and support they need to efficiently improve the quality of their presentations.

[1477] (Application example 1)

[1478] 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."

[1479] Conventional systems for improving the quality of presentations have the drawback of making it difficult for users to receive specific feedback in real time when practicing their presentations, making it difficult to practice and improve efficiently.In particular, in factories and other workplaces, it is necessary to explain new processes and provide training on operation methods quickly and accurately, and real-time feedback is required.

[1480] 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.

[1481] In this invention, the server includes means for a user to input presentation materials, means for the user to record a presentation practice video, means for the server to analyze the presentation materials and the presentation practice video, means for the server to identify specific areas for improvement based on the analysis results, means for the server to generate a feedback video based on the areas for improvement, means for the server to provide the feedback video to the user, and means for the user to check the feedback in real time. As a result, when a user practices a presentation, the recorded video can be analyzed on the spot and feedback indicating specific areas for improvement can be provided in real time, allowing the quality of the presentation to be improved quickly and efficiently.

[1482] "User" refers to the individual or entity who inputs presentation materials and records practice videos.

[1483] "Presentation materials" refers to digital files that contain documents, slides, charts, etc. that illustrate the content of a presentation.

[1484] "Presentation practice video" refers to footage of a presentation that a user has recorded for practice purposes.

[1485] "Server" refers to a computer system that analyzes presentation materials and practice videos, identifies areas for improvement, and generates and provides feedback videos.

[1486] "Analysis" refers to the process of evaluating and examining the content of the presentation materials and practice video to identify areas for improvement.

[1487] "Improvements" refers to changes or modifications that may be required to improve the quality of the user's presentation.

[1488] "Feedback video" refers to a video generated by the server that includes specific advice and comments on the user's presentation.

[1489] "Real-time feedback" refers to feedback provided instantly while a user is performing a practice presentation.

[1490] This invention is a system for improving the quality of presentations, which handles everything from inputting presentation materials to providing feedback. This system mainly consists of the following elements:

[1491] 1. On the user's device:

[1492] First, the user uploads presentation materials to the server via their device. Presentation materials can be slides, PDFs, images, etc., and the user can send them from their device to the server. Next, the user uses the device's camera function to record a practice video for the presentation. The recorded video is automatically uploaded to the server.

[1493] 2. Server:

[1494] The server analyzes the received presentation materials and practice videos, including slide content evaluation, voice volume and intonation, eye movements, posture, and gestures. Based on these analysis results, the server uses a generative AI model to identify specific areas for improvement.

[1495] 3. Providing Feedback:

[1496] Based on the analysis results, the server generates a feedback video containing specific areas for improvement. This feedback video is then provided to the user's device. The user can also view the feedback in real time by wearing smart glasses. This allows the user to understand the areas for improvement on the spot and immediately incorporate them into their practice.

[1497] A specific example is a training session on how to operate a new process in a factory. Factory workers wear smart glasses and record themselves demonstrating the operation of the new process. The recorded video is uploaded to a server, which analyzes the video content and provides specific feedback on areas for improvement. The feedback is displayed in real time on the smart glasses, allowing the workers to immediately implement the improvements.

[1498] Example prompt sentence:

[1499] "When training factory workers on a new assembly process, create a demo system that allows them to record themselves using smart glasses and provide real-time feedback on areas for improvement. The system would analyze the video, evaluate assembly accuracy and efficiency, and provide specific feedback on the smart glasses."

[1500] This system not only improves the quality of presentations quickly and efficiently, but also effectively supports the learning of new processes in factories and other workplaces.

[1501] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1502] Step 1:

[1503] User uploads presentation materials

[1504] First, the user selects presentation materials from their own device and uploads them to the server. The input is the presentation material file (slides, PDF, etc.) saved on the user's device, and the output is the same material saved on the server. Data processing involves transferring the material file to the server, checking the file format, and converting it into an analyzable format.

[1505] Step 2:

[1506] Users record practice videos for their presentations

[1507] A user uses the device's camera to record a presentation practice video. Once recording is complete, the video file is uploaded to the server. The input is the video feed recorded by the camera, and the output is the practice video file stored on the server. Data processing involves compressing and formatting the video for efficient transfer to the server.

[1508] Step 3:

[1509] The server analyzes the presentation materials and practice videos.

[1510] The server analyzes the uploaded presentation materials and practice videos. The input is the presentation materials and practice videos stored on the server, and the output is the analysis results. Data calculation involves using a generative AI model to evaluate the content of the slides, analyze the volume and intonation of the voice, eye movements, posture, and gestures.

[1511] Step 4:

[1512] The server identifies specific areas for improvement

[1513] The server extracts specific improvement points based on the analysis results. The input is the analysis results obtained in step 3, and the output is a list of improvement points. Data calculation is to compare the analysis data with the good performance standards of the existing presentation and identify the differences.

[1514] Step 5:

[1515] The server generates the feedback video

[1516] The server generates a feedback video that reflects specific improvements. The input is a list of improvements and the original practice video, and the output is the feedback video. Data processing involves adding graphics and text indicating the improvements as an overlay on the original practice video.

[1517] Step 6:

[1518] The server provides the feedback video

[1519] The server provides the generated feedback video to the user. The input is the feedback video, and the output is a feedback video link that can be played on the user's device. The data processing involves converting the feedback video into an appropriate format and uploading it to cloud storage for user access.

[1520] Step 7:

[1521] Users practice again based on feedback

[1522] The user reviews the feedback video, reflects the improvements, practices the presentation again, and records the video. The input is the feedback video and the newly recorded practice video, and the output is the re-uploaded practice video. Data calculation involves adjusting the practice content based on the improvements suggested by the user.

[1523] Step 8:

[1524] The server provides a final checklist and points to note

[1525] The server analyzes the user's final presentation practice video and provides a final checklist and points to note. The input is the final practice video, and the output is the final checklist and a list of points to note. The data calculation analyzes the final practice video and once again confirms the necessary improvements and points to note.

[1526] 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.

[1527] The present invention is a system that allows users to efficiently improve the quality of their presentations, and in particular provides more advanced feedback by combining it with an emotion engine that recognizes the user's emotions.

[1528] System configuration

[1529] The system consists of the following main components:

[1530] 1. User's device: This is the device used to input presentation materials, record practice videos, and check feedback videos and emotional feedback.

[1531] 2. Server: A device that analyzes presentation materials, practice videos, and user emotional data, and generates and manages feedback.

[1532] 3. Emotion engine: It has the function to recognize the user's emotions and generate feedback accordingly.

[1533] User Flow

[1534] 1. User enters presentation materials:

[1535] Users upload PowerPoint files or presentation materials in PDF format to the server via their terminals.

[1536] For example, a user uploads a presentation document introducing a new product that the user has created to the application.

[1537] 2. User records a practice video of their presentation:

[1538] Users use the device's camera to record their presentation rehearsals, and the device also collects emotional data such as facial expressions and tone of voice.

[1539] For example, a user rehearses at home, records the rehearsal on video, and simultaneously collects emotional data.

[1540] 3. The server analyzes the presentation materials and practice video:

[1541] The server analyzes the content of the presentation materials and practice videos received, evaluating the structure, content, and performance of the slides. The emotion engine also analyzes the user's emotions.

[1542] For example, the server analyzes the user's emotions from the volume of their voice, intonation, eye movements, and facial expressions, and compares them with standard presentation metrics.

[1543] 4. The server identifies specific areas for improvement and emotional feedback:

[1544] Based on the analysis results, the server identifies specific areas for improvement for each element of the presentation, while the emotion engine provides optimal emotional feedback based on the user's emotional data.

[1545] For example, in addition to corrections such as "correct your gaze position" and "adjust your tone of voice," it identifies emotion-based advice such as "try to relax a bit more."

[1546] 5. The server generates the feedback video and emotional feedback:

[1547] The server creates a feedback video that reflects the improvements and simultaneously generates a video that includes emotional feedback.

[1548] For example, it generates a video that overlays areas for improvement on the user's video and adds emotion-based comments such as "Speak with more confidence here."

[1549] 6. The server provides the feedback video:

[1550] The server sends the generated feedback video to the user's device, where the user can view the video and understand specific improvements and emotional feedback.

[1551] 7. User re-practices:

[1552] The user practices the presentation again based on the feedback video and emotional feedback, records a new video, and recollects emotional data.

[1553] 8. The server provides a final checklist and notes for the presentation:

[1554] The server generates a checklist of points to note on the day of the presentation based on the final analysis results and emotional feedback, and sends it to the user.

[1555] In this way, the system of the present invention provides not only specific feedback but also emotional feedback to highly improve the user's presentation skills, supporting them to approach the day of the presentation with confidence.

[1556] The processing flow will be explained below.

[1557] Step 1:

[1558] The user inputs the presentation materials. The user prepares the presentation materials in PowerPoint or PDF format and uploads the files to the presentation application using the terminal.

[1559] Step 2:

[1560] The device sends the presentation materials received from the user to the server, where the files are uploaded to the server using a secure protocol.

[1561] Step 3:

[1562] The server receives the presentation materials and begins analyzing them. The server evaluates the text content, slide structure, visual elements, etc. of the materials and performs an initial analysis based on the presentation quality criteria.

[1563] Step 4:

[1564] The user records a video of their presentation practice. The user rehearses their presentation at home or in the office using the device's camera. At the same time, the device also collects emotional data such as the user's facial expressions and tone of voice.

[1565] Step 5:

[1566] Users can save and upload recorded presentation practice videos to their devices. Users select the video file in the application and send it to the server.

[1567] Step 6:

[1568] The server receives the presentation practice video. The server passes the video to the analysis tool, which performs facial expression recognition, speech analysis, posture detection, and gesture evaluation. At the same time, the emotion engine analyzes the user's emotional data.

[1569] Step 7:

[1570] The server identifies areas for improvement based on the video analysis results. The server analyzes the user's performance and lists specific areas for improvement, such as "correcting the position of your gaze" and "adjusting the tone of your voice." The emotion engine also provides emotion-based advice, such as "try to relax," based on the user's emotional data.

[1571] Step 8:

[1572] The server generates a feedback video and emotional feedback. The server creates a feedback video that reflects the points for improvement and also generates a video that includes emotional feedback. For example, in addition to specific points for improvement such as "It would be good to raise your eye contact here," the server incorporates emotional advice such as "Speak with more confidence" into the feedback video.

[1573] Step 9:

[1574] The server sends the generated feedback video to the terminal, where it is displayed in the user's application.

[1575] Step 10:

[1576] The user reviews the feedback video. They watch the feedback video on their device and understand the specific improvements and emotional feedback.

[1577] Step 11:

[1578] The user practices the presentation again based on the feedback video and emotional feedback. With the areas for improvement in mind, the user re-records the presentation, and the device again collects the video and emotional data.

[1579] Step 12:

[1580] The user saves a new presentation practice video on the device, uploads it, and then sends the video back to the server via the device, ready to receive further feedback.

[1581] Step 13:

[1582] The server generates a final checklist and points to note for the presentation. Based on the final analysis results and emotional feedback, the server lists points to note on the day of the presentation and provides them to the user.

[1583] Step 14:

[1584] The server sends the final checklist and notes to the terminal, which is displayed in the user's application and serves as a final confirmation.

[1585] Step 15:

[1586] The user reviews the final checklist and points to note. Using the information provided, the user makes final preparations for the presentation, allowing them to present with confidence.

[1587] Example 2

[1588] 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."

[1589] Conventional presentation practice systems lack the functionality to provide specific feedback and advice based on emotional data specifically designed to improve users' performance. As a result, users have to spend time and effort to improve the quality of their presentations, making it difficult to make effective improvements.

[1590] The identification process by the identification 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 analyzing the presentation materials and the presentation practice video, means for identifying specific improvements and emotional feedback based on the analysis results, and means for generating a feedback video that reflects the specific improvements and emotional feedback. This enables the user to quickly and efficiently receive specific feedback and emotional advice to effectively improve the quality of their presentation.

[1591] "User" refers to a person who uses the system to create and improve presentation materials.

[1592] "Means for inputting presentation materials" refers to the function that allows users to upload PowerPoint files or PDF format presentation materials to the server via their terminal.

[1593] "Means for recording a presentation practice video" refers to a function that allows a user to use the camera function of the device to record a presentation practice and save the video data.

[1594] "Server" refers to a central processing unit for analyzing presentation materials and presentation practice videos and generating and providing feedback.

[1595] "Means for analyzing presentation materials and presentation practice videos" refers to the function of analyzing the materials and videos received by the server and evaluating the slide structure, content, and performance.

[1596] "Means for identifying specific areas for improvement and emotional feedback" refers to a function in which the server identifies areas for improvement and emotional feedback for each element of the user's presentation based on the analysis results.

[1597] "Means for generating a feedback video that reflects specific areas for improvement and emotional feedback" refers to a function in which the server generates a presentation practice video of the user by overlaying specific areas for improvement and emotional feedback on the user's presentation practice video based on the analysis results.

[1598] The "means for providing a feedback video to a user" refers to a function for transmitting a feedback video generated by a server to a user terminal, allowing the user to view the video.

[1599] "Means for uploading the re-recorded presentation practice video and emotional data to the server" refers to a function that allows the user to practice the presentation again and send the video and emotional data to the server.

[1600] "Means for generating a final checklist and points to note for the presentation and providing it to the user" refers to the function by which the server generates a checklist summarizing points to note on the day of the presentation based on the final analysis results and emotional feedback, and provides it to the user.

[1601] This invention is a system that allows users to efficiently improve the quality of their presentations, and in particular, by combining it with an emotion engine that recognizes the user's emotions, it provides more advanced feedback. The system of this invention supports the improvement of presentation skills by evaluating the user's presentation practice from multiple angles and providing creative feedback.

[1602] System configuration

[1603] The system consists of the following main components:

[1604] 1. User's device: This is the device used to input presentation materials, record practice videos, and check feedback videos and emotional feedback.

[1605] 2. Server: A device that analyzes presentation materials, practice videos, and user emotional data, and generates and manages feedback.

[1606] 3. Emotion engine: It has the function to recognize the user's emotions and generate feedback accordingly.

[1607] Hardware and software used

[1608] User's device: smartphone, tablet, or computer (with camera function)

[1609] Server: High-performance analysis server (e.g. AWS EC2)

[1610] Emotion engine: Emotion recognition software (e.g. Microsoft Azure Emotion API)

[1611] Example of operation

[1612] User enters presentation material:

[1613] First, the user uploads the presentation materials from the device to the server. Using the application on the device, the user clicks the "Upload Materials" button, selects a PowerPoint file or a PDF file, and uploads it. For example, this is the case when the user uploads presentation materials for introducing a new product.

[1614] User records a practice presentation video:

[1615] Next, the user uses the device's camera function to record the presentation rehearsal. During the recording, the device simultaneously collects emotional data such as the user's facial expressions and tone of voice. For example, a user may rehearse a new product introduction at home and record the rehearsal on video.

[1616] The server analyzes the presentation and practice video:

[1617] Uploaded presentation materials and practice videos are sent to a server, which analyzes their content. The server uses AI analysis software to evaluate the structure and content of the slides and the user's performance (e.g., voice volume, eye movements, facial expressions), and an emotion engine analyzes the user's emotions.

[1618] The server identifies specific areas for improvement and sentiment-based feedback:

[1619] Based on the analysis results, the server identifies specific areas for improvement for each element of the presentation. At the same time, the emotion engine provides optimal emotional feedback based on the user's emotional data. For example, it provides technical corrections such as "correct your eye position" or "adjust your tone of voice" as well as emotional advice such as "try to relax a bit more."

[1620] The server generates the feedback video and emotional feedback:

[1621] The server then creates a feedback video that reflects these improvements and generates a video that includes emotional feedback. Specifically, the server overlays the video to indicate the areas for improvement and adds comments such as "Speak more confidently here."

[1622] The server provides the feedback video:

[1623] The generated feedback video is sent from the server to the user's device, where the user can view the feedback video on the device and understand the specific improvements and emotional feedback. For example, the user can play the video on the application and view the provided feedback.

[1624] User re-practices:

[1625] Based on the feedback, users practice their presentations again, record new practice videos, and recollect emotion data, thereby further improving their presentation skills.

[1626] Example prompts for generative AI models

[1627] "Please provide feedback on my presentation. Analyze the video and materials below and give me specific improvements and emotionally-driven advice."

[1628] In this way, the system of the present invention provides not only specific feedback but also emotional feedback to highly improve the user's presentation skills, supporting them to approach the day of the presentation with confidence.

[1629] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1630] Step 1:

[1631] The device accepts the user's presentation materials. The user uploads presentation materials in PowerPoint or PDF format through the device's application (input). The device sends these materials to the server (output). Specifically, the user opens the application, clicks the "Upload Materials" button, selects the presentation materials from the file selection dialog, and begins uploading.

[1632] Step 2:

[1633] The device records a video of the user practicing their presentation. The user uses the device's camera function to record their presentation rehearsal, and emotional data is automatically collected (input). The recorded video and emotional data are saved on the device (output). Specifically, the user presses the "Start Recording" button to start the presentation, and once recording is complete, presses the "Stop Recording" button to save the video.

[1634] Step 3:

[1635] The server analyzes the presentation materials and practice video. The server receives the presentation materials, practice video, and emotional data sent from the device (input). The server uses AI analysis software to evaluate the slide structure, content, and user performance (volume of voice, eye movement, facial expression), and analyzes emotions using an emotion engine (data processing and data calculation). The analysis results are generated (output). Specifically, the server launches the AI ​​analysis software and takes in the uploaded materials and video as input data.

[1636] Step 4:

[1637] The server identifies specific areas for improvement and emotional feedback. Based on the analysis results, the server identifies specific areas for improvement and emotional feedback for each element of the user's presentation (input). For example, technical corrections such as "correct your gaze position" or "adjust your tone of voice" and emotional advice such as "try to relax a bit more" are generated (output). The server creates feedback data based on this data (data processing).

[1638] Step 5:

[1639] The server generates a feedback video and emotional feedback. Based on the feedback data, the server adds improvements and emotional feedback as an overlay to the user's practice video (input). Specifically, the server launches video editing software and adds text and graphics indicating areas for improvement, as well as emotional feedback as text (data processing). Finally, a feedback video is generated (output).

[1640] Step 6:

[1641] The server provides the feedback video to the user. The server then sends the generated feedback video to the user's device (input and output). Specifically, the server uploads the feedback video to cloud storage and sends a download link to the user via email or in-app notification. The user clicks the link to watch the video.

[1642] Step 7:

[1643] The user practices the presentation again. The user practices the presentation again based on the feedback video and emotional feedback and records a new practice video (input). The device records a new video and collects emotional data again (output). Specifically, the user presses the "Start Recording" button again, rehearses, and presses the "Stop Recording" button to save the video.

[1644] Step 8:

[1645] The server provides a final checklist and important points for the presentation. The server reanalyzes the newly uploaded video and emotion data, and generates a checklist summarizing important points for the presentation day based on the final analysis results (input and data processing). The server provides this checklist to the user (output). Specifically, the server sends the generated checklist to the user via email or in-app notification.

[1646] (Application example 2)

[1647] 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."

[1648] Conventional presentation practice systems do not provide specific feedback to improve users' emotions or performance, resulting in limited quality practice. Furthermore, in the food delivery industry, there are insufficient training methods for delivery staff to effectively introduce food and services, making it difficult to improve the user experience.

[1649] The specification processing by the specification 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 a user to input presentation materials, means for a user to record a presentation practice video, means for the server to analyze the presentation materials and the presentation practice video, means for the server to identify specific areas for improvement based on the analysis results, means for the server to generate a feedback video based on the areas for improvement, means for the server to provide the feedback video to the user, means for delivery staff to record and upload explanations of dishes and service introductions, and means for the server to analyze the videos and provide advice on improving hospitality. This makes it possible to improve not only the quality of presentations but also the quality of food delivery service.

[1650] A "user" is an entity that creates presentation materials and records a practice video.

[1651] "Presentation materials" refers to information such as documents, charts, slides, etc. that a user uses to give a presentation.

[1652] "Presentation practice video" refers to video data that records a user practicing a presentation.

[1653] "Server" refers to the computer system that analyzes the presentation materials and presentation practice videos and generates and provides feedback.

[1654] "Means for analyzing" refers to a method or device for evaluating and analyzing the content of presentation materials and presentation practice videos received by the server.

[1655] The means for identifying "specific areas for improvement" refers to a method or device for finding specific advice or instructions for improving the quality of the presentation based on the analysis results.

[1656] The "means for generating a feedback video" refers to a method or device by which the server creates a feedback video that reflects the analysis results and improvements.

[1657] The "means for providing a feedback video" refers to a method or device for transmitting the feedback video generated by the server to the user's terminal so that the user can view it.

[1658] "Delivery staff" refers to people who deliver food and provide services in food delivery services.

[1659] "Means for recording and uploading descriptions of dishes and service introductions" refers to a method or device by which delivery staff record descriptions of dishes and service contents and upload the videos to a server.

[1660] "Means for providing advice to improve hospitality" refers to a method or device in which a server analyzes uploaded videos and generates and provides specific advice to delivery staff to provide better service.

[1661] This invention is a system that allows users to efficiently improve the quality of their presentations, and in particular provides feedback on presentation skills and emotions by combining an emotion engine that recognizes the user's emotions. Furthermore, to improve the quality of food delivery services, the system includes a function that analyzes introductory videos of delivery staff and provides specific advice for improving the service.

[1662] System configuration

[1663] The system consists of the following main components:

[1664] 1. User's device

[1665] This device is used to input presentation materials and record practice videos. Users upload PowerPoint files and PDF format presentation materials to the server through the device. The device is also equipped with a camera function to record and upload practice videos.

[1666] 2. Server

[1667] This is a computer system that receives and analyzes presentation materials and practice videos. The server has the following functions:

[1668] Data analysis: Analyze the content of the presentation materials and practice videos received to evaluate their structure and performance.

[1669] Emotion Engine: Recognizes user emotions in training videos and analyzes emotion data.

[1670] Feedback generation: Based on the analysis results, specific areas for improvement are identified and a feedback video is generated that reflects these areas.

[1671] Video provision: Send feedback videos to the user's device and provide feedback for improvement.

[1672] 3. Delivery staff

[1673] This person records videos explaining the dishes and services and uploads them to a server, which analyzes the videos and provides advice on how to improve the service.

[1674] Example

[1675] 1. Inputting presentation materials

[1676] Consider an example where a user uploads a presentation document for introducing a new product from a terminal to a server. The user uses a PowerPoint file or a PDF.

[1677] 2. Record a practice video of your presentation

[1678] The user rehearses at home and records the rehearsal on video, while the device simultaneously collects emotional data such as facial expressions and tone of voice.

[1679] 3. Data analysis and feedback generation

[1680] The server analyzes the presentation materials and practice videos it receives, and analyzes the user's emotions based on the volume of their voice, intonation, eye movements, and facial expressions, and compares them with standard presentation indicators. Based on the results of this analysis, it generates specific improvements (e.g., "correct your eye position" or "adjust your tone of voice") and emotion-based advice (e.g., "try to relax a bit more").

[1681] 4. Providing feedback videos

[1682] The server creates a feedback video that reflects the analysis results and overlays it on the user's video to show areas for improvement. It also adds emotional comments such as "Try to speak more confidently here."

[1683] Food delivery application example

[1684] Delivery staff record and upload their explanations of the dishes and the service they provide. The server analyzes the videos and generates specific advice for delivery staff to provide better service (e.g., "serve customers with a smile" or "explain the key points of the dishes clearly").

[1685] Hardware and software used

[1686] Hardware: User devices (smartphones, tablets, PCs), cameras, servers

[1687] Software: Emotion recognition API (e.g., Google Cloud Vision, Amazon Rekognition), video analysis software (e.g., OpenCV)

[1688] Prompt Sentence Examples

[1689] Video analysis results:

[1690] Gaze position: 60% camera direction

[1691] Confidence level: 45%

[1692] Emotional feedback example:

[1693] Turn your gaze more towards the camera.

[1694] Try to speak more confidently.

[1695] It is expected that this system will improve the quality of presentations and service provision, providing users and customers with a more satisfying experience.

[1696] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1697] Step 1:

[1698] A means for users to input presentation materials

[1699] A user uploads a presentation document in PowerPoint or PDF format to the server via their device. The input is the presentation document file, which the server receives. Specifically, the user opens the application and clicks the "Upload Presentation Document" button.

[1700] Step 2:

[1701] A way for users to record practice videos of their presentations

[1702] The user uses the device's camera function to record a presentation rehearsal. The device also collects emotional data such as the user's facial expressions and tone of voice. The input is a video file and emotional data, and the output is a recorded video file. Specifically, the user presses the "Start Recording" button, gives the presentation, and then presses the "Stop Recording" button.

[1703] Step 3:

[1704] A means for the server to analyze presentation materials and presentation practice videos

[1705] The server analyzes the received presentation materials and practice video content and evaluates the slide structure, content, and performance. At the same time, the emotion engine analyzes the user's emotions. The input is the presentation material file and the recorded video file, and the output is the analyzed data. Specifically, the server calls the emotion recognition API and analyzes the user's emotional data. It also uses video analysis software such as OpenCV to analyze the video's movements.

[1706] Step 4:

[1707] A means for the server to identify specific areas for improvement

[1708] Based on the analysis results, the server identifies specific areas for improvement for each element of the presentation. The input is the analysis data, and the output is specific improvement suggestions. Specifically, the server compares the analysis data with standard presentation indicators and derives specific areas for improvement related to eye gaze position, tone of voice, and facial expressions.

[1709] Step 5:

[1710] A means for the server to generate feedback videos based on improvements

[1711] The server creates a feedback video that reflects the improvements and overlays them on the user's video. It also adds emotional comments. The input is the recorded video file and the improvement proposal data, and the output is the feedback video. Specifically, the server uses video editing software to add an overlay to the video and insert the comments.

[1712] Step 6:

[1713] A means by which the server provides feedback videos to the user

[1714] The server sends the generated feedback video to the user's device. The input is the feedback video file, and the output is the feedback video sent to the user's device. Specifically, the server sends a notification to the user's device and displays a message saying "A new feedback video is ready."

[1715] Step 7:

[1716] A way for users to practice their presentations again based on the feedback video

[1717] The user reviews the feedback video, understands the specific areas for improvement and emotional feedback, and then practices the presentation again. The input is the feedback video, and the output is a re-recorded presentation practice video. Specifically, the user watches the feedback video, presses the "Start Re-Practice" button, and practices again, noting the areas for improvement.

[1718] Step 8:

[1719] How to upload the re-recorded presentation practice video to the server

[1720] The user uploads the re-recorded presentation practice video to the server and re-analyzes it. The input is the re-recorded presentation practice video, and the specific operation is for the user to click the "Upload re-practice video" button.

[1721] This embodiment improves the quality of presentation and service delivery, providing a more satisfying experience for users and customers.

[1722] 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.

[1723] 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.

[1724] 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.

[1725] 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.

[1726] 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.

[1727] 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.

[1728] 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).

[1729] 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, motorcycles, and other devices, 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.

[1730] 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."

[1731] 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.

[1732] 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).

[1733] 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.

[1734] 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.

[1735] 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.

[1736] 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.

[1737] 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.

[1738] 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.

[1739] 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.

[1740] 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.

[1741] 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.

[1742] 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.

[1743] The following is further disclosed regarding the above embodiment.

[1744] (Claim 1)

[1745] A means for a user to input presentation materials;

[1746] a means for a user to record a presentation practice video;

[1747] A means for the server to analyze the presentation materials and the presentation practice video;

[1748] A means for the server to identify specific areas for improvement based on the analysis results;

[1749] A means for the server to generate a feedback video based on the improvements;

[1750] The system includes a means for the server to provide the feedback video to the user.

[1751] (Claim 2)

[1752] A means for users to practice their presentation again based on the feedback video;

[1753] 10. The system of claim 1, further comprising means for uploading the re-recorded presentation practice video to a server.

[1754] (Claim 3)

[1755] 10. The system of claim 1, further comprising means for the server to generate a final checklist and notes for the presentation and provide it to the user.

[1756] "Example 1"

[1757] (Claim 1)

[1758] a means for a user to input presentation materials;

[1759] means for a user to record a presentation practice video;

[1760] means for the server to analyze the presentation materials and the presentation practice video;

[1761] A means for the server to identify specific areas for improvement based on the analysis results;

[1762] A means for the server to generate a feedback video based on the improvements;

[1763] a means for the server to provide a feedback video to the user;

[1764] The system includes a means for the server to send a link to the feedback video to the user.

[1765] (Claim 2)

[1766] A means for the user to practice the presentation again based on the feedback video;

[1767] 10. The system of claim 1, further comprising means for uploading the re-recorded presentation practice video to a server.

[1768] (Claim 3)

[1769] 10. The system of claim 1, further comprising means for the server to generate a final checklist and notes for the presentation and provide it to the user.

[1770] "Application Example 1"

[1771] (Claim 1)

[1772] a means for a user to input presentation materials;

[1773] means for a user to record a presentation practice video;

[1774] means for the server to analyze the presentation materials and the presentation practice video;

[1775] A means for the server to identify specific areas for improvement based on the analysis results;

[1776] A means for the server to generate a feedback video based on the improvements;

[1777] a means for the server to provide a feedback video to the user;

[1778] A way for users to see feedback in real time;

[1779] A system including:

[1780] (Claim 2)

[1781] A means for the user to practice the presentation again based on the feedback video;

[1782] 10. The system of claim 1, further comprising means for uploading the re-recorded presentation practice video to a server.

[1783] (Claim 3)

[1784] 10. The system of claim 1, further comprising means for the server to generate a final checklist and notes for the presentation and provide it to the user.

[1785] "Example 2: Combining Emotion Engines"

[1786] (Claim 1)

[1787] A means for a user to input presentation materials;

[1788] a means for a user to record a presentation practice video;

[1789] A means for the server to analyze the presentation materials and the presentation practice video;

[1790] a means for the server to identify specific improvements and sentiment-based feedback based on the analysis results;

[1791] A means for the server to generate a feedback video that reflects specific improvements and emotional feedback;

[1792] The system includes a means for the server to provide the feedback video to the user.

[1793] (Claim 2)

[1794] A means for users to practice their presentation again based on the feedback video;

[1795] 10. The system of claim 1, further comprising means for uploading the re-recorded presentation practice video and emotion data to a server.

[1796] (Claim 3)

[1797] 10. The system of claim 1, further comprising means for the server to generate a final checklist and notes for the presentation and provide it to the user.

[1798] "Application example 2 when combining emotion engines"

[1799] (Claim 1)

[1800] A means for a user to input presentation materials;

[1801] a means for a user to record a presentation practice video;

[1802] A means for the server to analyze the presentation materials and the presentation practice video;

[1803] A means for the server to identify specific areas for improvement based on the analysis results;

[1804] A means for the server to generate a feedback video based on the improvements;

[1805] a means for the server to provide a feedback video to the user;

[1806] A way for delivery staff to record and upload explanations of dishes and service introductions,

[1807] The system includes a means for the server to analyze the video and provide advice on how to improve hospitality.

[1808] (Claim 2)

[1809] A means for users to practice their presentation again based on the feedback video;

[1810] 10. The system of claim 1, further comprising means for uploading the re-recorded presentation practice video to a server.

[1811] (Claim 3)

[1812] 10. The system of claim 1, further comprising means for the server to generate a final checklist and notes for the presentation and provide it to the user. [Explanation of symbols]

[1813] 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. A means for a user to input presentation materials; a means for a user to record a presentation practice video; A means for the server to analyze the presentation materials and the presentation practice video; A means for the server to identify specific areas for improvement based on the analysis results; A means for the server to generate a feedback video based on the improvements; The system includes a means for the server to provide the feedback video to the user.

2. A means for users to practice their presentation again based on the feedback video; 10. The system of claim 1, further comprising means for uploading the re-recorded presentation practice video to a server.

3. 2. The system of claim 1, further comprising means for the server to generate a final checklist and notes for the presentation and provide it to the user.

Images