system

Abstract

We provide the system. [Solution] An information processing means that analyzes document files and generates visual improvement suggestions, An information processing means that analyzes the presentation script and proposes an optimized method of expression, A practice support method that provides real-time feedback to the user, A system that includes this.

Description

Technical Field

[0004] , , ,

[0005] , , , ,

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

Means for Solving the Problems

[0005] This invention solves the above problems by providing an information processing system that analyzes presentation materials and generates visual improvement suggestions. Furthermore, it supports the user's ability to clearly convey what they want to communicate through an information processing means that analyzes the presentation script and suggests effective expression methods. In addition, by providing a practice support means that provides real-time feedback during presentation execution, it enables the user to quickly identify areas for improvement and improve their skills.

[0006] A "document file" is a digital file used as presentation material, and includes, for example, slides and documents.

[0007] "Visual improvement suggestions" are specific advice on how to make the design and layout of presentation materials more effective, and include adjustments to color, fonts, and layout.

[0008] "Information processing means" refers to systems or programs that have the function of analyzing digital data and generating output according to a specific purpose.

[0009] A "presentation script" refers to the manuscript or script used by the speaker during a presentation, and is intended to organize the oral explanation.

[0010] "Optimized presentation methods" refer to techniques proposed to convey information more clearly and effectively in a presentation, and include adjustments to improve conciseness and clarity.

[0011] A "practice support tool" is a tool or system that has the function of providing feedback to help users improve their presentation skills.

[0012] "Real-time feedback" refers to evaluations and suggestions for improvement that are provided instantly while the user is giving a presentation. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0014] An example of an embodiment of the system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0019] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] This invention relates to an information processing system for engineers to efficiently improve the design and content of presentation materials and optimize the effective expression of presentation scripts. This system takes user-created presentation material files and scripts as input, analyzes them on the server side, generates improvement suggestions, and provides them to the user.

[0035] First, the user uploads presentation materials and a presentation script to the system using their device. The materials refer to digital files, such as slides or documents. These files are then sent to the server.

[0036] Next, the server analyzes the document files. The analysis process evaluates factors such as slide layout, font and color palette consistency, and the amount of text information. This analysis generates specific suggestions for improving the visual impression of the document.

[0037] Simultaneously, the server analyzes the presentation script. This analysis uses natural language processing techniques to evaluate grammar, clarity, and tone. Suggestions for sentence simplification and keyword emphasis are generated as needed.

[0038] The server sends suggestions for improving the generated materials and optimizations to the terminal, providing feedback to the user. The user can then revise the materials and script based on this feedback. Furthermore, the user can practice their presentation while receiving real-time feedback on their terminal. This practice support feature allows the user to receive immediate evaluations of their speaking style, speed, and intonation during the presentation.

[0039] In this way, the present invention enables users to improve their skills in effectively communicating specialized knowledge to others. It contributes to the efficiency and quality improvement of presentation preparation.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The user uses a terminal to upload presentation materials and presentation scripts to the system. The terminal temporarily stores these files as input data.

[0043] Step 2:

[0044] The terminal sends the saved data files to the server. The server receives the data files and begins analyzing the content.

[0045] Step 3:

[0046] The server analyzes the structure of the document files and extracts the slide layout, fonts, and colors used. Based on this information, it generates visual improvement suggestions, such as adjustments to the color scheme or font size.

[0047] Step 4:

[0048] The terminal sends the saved presentation script to the server. The server receives the script and uses NLP (Natural Language Processing) technology to analyze the grammar and the effectiveness of the expressions.

[0049] Step 5:

[0050] Based on the script analysis results, the server generates script optimization suggestions, such as clarifying sentences and highlighting key points. For example, it may suggest simplifying complex sentences and emphasizing important keywords.

[0051] Step 6:

[0052] The server sends back suggestions for improving the generated materials and optimization suggestions for the script to the terminal. The terminal then displays this feedback to the user.

[0053] Step 7:

[0054] Users can review the feedback presented through their devices and revise their materials and scripts. This allows users to improve the quality of their presentations.

[0055] Step 8:

[0056] The user practices their presentation using a device. During this practice, the device evaluates the user's speaking style, speed, and intonation in real time and provides feedback.

[0057] Step 9:

[0058] Users can receive real-time feedback to further refine their presentation skills.

[0059] (Example 1)

[0060] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0061] Conventional presentation creation support systems require significant time and expertise to design and optimize the content of materials, and optimizing the effective expression of scripts is particularly difficult. This makes it challenging for users to receive immediate feedback and prepare effectively. Furthermore, there is a lack of concrete suggestions for improving presentation effectiveness, limiting users' means of obtaining specific guidance for self-improvement.

[0062] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0063] In this invention, the server includes information processing means for analyzing data and generating visual improvement suggestions, information processing means for analyzing presentation scripts and suggesting optimized expressions, exercise support means for providing immediate feedback to the user, and means for utilizing a generative model to enhance the effectiveness of the presentation. This enables users to efficiently create high-quality presentation materials, optimize the expression of their presentation scripts, and improve their presentation skills through real-time feedback, even without specialized knowledge.

[0064] "Document data" refers to digital files containing information in the form of slides or documents used in presentations.

[0065] "Information processing means" refers to technical processes and devices used to analyze data and perform improvements or optimizations in accordance with specific purposes.

[0066] A "presentation script" is a document containing spoken language used during a presentation, and is a script used to effectively convey the content of the presentation.

[0067] "Practice support tools" are features that provide real-time feedback to users when they practice their presentations, and support their preparation.

[0068] A "generative model" is an algorithm or system that automatically generates suggestions for improvements or optimizations tailored to a specific purpose.

[0069] A "visual improvement suggestion" refers to proposed changes to presentation materials to achieve a more effective and appealing appearance.

[0070] "Natural language processing tools" are automated processing technologies used to analyze documents such as presentation scripts and evaluate their grammar and clarity of content.

[0071] This invention is an information processing system for efficiently optimizing a user's presentation materials and presentation scripts. The user uploads presentation material files and presentation scripts to the system using a terminal. The material files are digital data in slide or document format and are transmitted to the server.

[0072] The server uses specialized software to analyze the received document data. At this stage, a design analysis engine evaluates the consistency of the slide layout, fonts, and color palette. Image recognition technology is also used to determine the balance of visual elements. For example, if the placement of images and text is not effective, it generates suggestions for improvement.

[0073] Next, the server analyzes the presentation script using natural language processing (NLTK) techniques. This analysis utilizes open-source NLTK libraries (e.g., spaCy or NLTK). It evaluates grammar, tone, and clarity, and generates suggestions to shorten sentences or emphasize keywords as needed.

[0074] Users can receive feedback from the server on their devices and revise their materials and scripts. They can also practice presentations in an environment that provides real-time feedback. This allows them to receive instant evaluations of their speaking style, speed, intonation, and other aspects, enabling them to improve their skills.

[0075] As a concrete example, here are some prompt statements that can be passed to a generative AI model: "Please suggest improvements to the design of the presentation materials. The current slides lack consistency." "Please tell me about grammatical improvements to the presentation script and ways to express it more effectively." This allows the user to obtain specific guidance for improvement.

[0076] In this way, the system helps users efficiently prepare for presentations and deliver high-quality presentations.

[0077] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0078] Step 1:

[0079] Users use a terminal to upload presentation materials and presentation scripts to the system. Input files include slide files such as Microsoft® PowerPoint and script files in Word format. These files are sent to the server in digital format.

[0080] Step 2:

[0081] The server begins design analysis on the received document data. The input is the document file uploaded in Step 1. The server uses its analysis engine to verify the slide layout, fonts, and consistent color palette. As part of the data processing, it analyzes the element position and style of each slide and extracts visually appealing improvement suggestions. As output, a list of improvement suggestions is generated.

[0082] Step 3:

[0083] The server analyzes the presentation script. The input is the script file uploaded in Step 1. Natural language processing techniques are used to evaluate grammar, tone, and clarity. Data calculations use open-source libraries to simplify sentences and extract important keywords. The output is a list of script improvement suggestions and optimization proposals.

[0084] Step 4:

[0085] The server sends suggestions for improving the document and optimizing the script to the terminal. The input is the list of suggestions generated in steps 2 and 3. As output, this feedback is provided on the terminal. The terminal immediately displays it to the user, allowing the user to modify the document or script.

[0086] Step 5:

[0087] Users operate a device and practice their presentations while receiving real-time feedback. The input is feedback from a server. The device analyzes the user's voice, speaking pace, intonation, etc., and provides immediate feedback. Based on this feedback, users can adjust and improve their presentation skills.

[0088] (Application Example 1)

[0089] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0090] When giving a presentation, it is necessary to immediately improve the visual design of the materials and the expression of the script, and to flexibly change the content of the materials in response to the audience's reactions. However, with the current system, it is difficult to perform these tasks effectively and quickly, so reducing the burden on the speaker and improving the quality of the presentation are challenges.

[0091] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0092] In this invention, the server includes means for analyzing document files and generating visual improvement suggestions, means for analyzing presentation scripts and suggesting optimized presentation methods, and means for dynamically modifying the document content based on observer reactions. This allows the design and content of the document to be optimized in real time during the presentation, enabling the speaker to deliver a flexible presentation in response to observer reactions.

[0093] "Information processing means for analyzing document files and generating visual improvement suggestions" refers to a device that evaluates the layout, font, consistency, etc., of input documents and generates specific suggestions for achieving visually superior presentations.

[0094] "Information processing means for analyzing presentation scripts and proposing optimized expression methods" refers to a device that analyzes presentation scripts using natural language processing technology and generates suggestions for improving grammar, clarity, and tone.

[0095] A "practice support device that provides real-time feedback to users" is a device that provides immediate evaluation of a user's speaking style, speed, and intonation while they are giving a presentation, and points out areas for improvement.

[0096] "Means for dynamically modifying the content of materials based on observer reactions" refers to a device that acquires data on the observer's facial expressions and reactions, and then changes the order and design of the presentation content based on that data.

[0097] The system implementing this invention consists of a server that performs analysis using document files and presentation scripts as input. The server first receives the document files and scripts in digital format from the user. The document files are in slide or document format, and the system analyzes them to generate visual improvement suggestions.

[0098] The server employs existing presentation tools and custom-developed algorithms to evaluate the layout, fonts, consistency, and information density of the materials. Next, the server analyzes the presentation script using natural language processing software to provide suggestions for grammar, clarity, and tone improvement. Typical software for this includes open-source natural language processing libraries.

[0099] On the user's device, a real-time feedback function is available to practice presentations. This feedback includes evaluations of speaking style, speed, and intonation, allowing the user to adjust their speaking style accordingly.

[0100] Furthermore, the server uses software to analyze observer reactions, collecting data such as observer facial expressions and dynamically modifying the content of the materials. This allows for flexible changes to the order and design of materials during the presentation, keeping the observer engaged.

[0101] For example, when giving a presentation at a large academic conference, even if it's difficult to gauge the audience's reactions, this system allows for real-time feedback and flexible adjustments to the presentation materials. Therefore, effective presentations are possible even in situations requiring immediate responses.

[0102] An example of a prompt using a generative AI model is: "Suggest a method to evaluate the visual design and script content of a presentation and generate improvement suggestions in real time. Refine the suggestions using audience reaction data." Using this prompt makes it possible to provide more specific feedback.

[0103] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0104] Step 1:

[0105] Users upload presentation materials and presentation scripts to the system using their terminals. The input consists of digital materials and scripts, which are sent to the server. The server receives and stores these files.

[0106] Step 2:

[0107] The server analyzes the received document files. The input is the document files, and the output is visual improvement suggestions. The server analyzes the slide layout, fonts, consistency, and amount of text information, and generates visual design improvement suggestions based on this analysis. In doing so, it uses presentation tool APIs and proprietary algorithms.

[0108] Step 3:

[0109] The server analyzes the presentation script. The input is the script, and the output is suggestions for improving the presentation. The server uses natural language processing techniques to evaluate grammar, clarity, and tone, and generates optimization suggestions. Specifically, it uses a natural language processing library to analyze the script and suggests sentence simplification and keyword emphasis.

[0110] Step 4:

[0111] The server sends the generated improvement suggestions to the terminal. The terminal displays them and provides feedback to the user. This allows the user to modify the documents or scripts. The input is the improvement suggestions, and the output is the feedback displayed on the user's screen.

[0112] Step 5:

[0113] Users practice their presentations while receiving real-time feedback on the device. Input is the user's presentation voice and speed, while output is immediate evaluation. The device uses a microphone to collect audio and provides feedback on speaking style, speed, and intonation. Voice analysis software is used in this process.

[0114] Step 6:

[0115] The server dynamically modifies the content of the materials based on the observer's reactions. The input is the observer's facial expressions and other reaction data, and the output is the modified material suggestion. The server uses visual data analysis software to analyze the observer's reactions and generate suggestions for adjusting the materials.

[0116] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0117] This invention relates to an information processing system that analyzes and improves presentation materials and presentation scripts, and further combines them with an emotion engine that recognizes user emotions. This system takes user-provided material files and presentation scripts as input, collects data for emotion recognition, and generates and provides improvement suggestions to the user based on this information.

[0118] First, the user uploads presentation materials, a presentation script, and facial image and audio data for emotion recognition to the system using their device. The device temporarily stores this data and prepares to send it to the server.

[0119] Next, the server analyzes the document files. This analysis process evaluates the consistency of the slide layout, design elements, fonts, and color palette, and generates visual improvement suggestions.

[0120] The server further analyzes the presentation script using natural language processing techniques. It evaluates grammar, clarity, and tone, and generates suggestions for script optimization, such as sentence simplification and keyword emphasis, as needed.

[0121] In addition, the emotion engine installed on the server recognizes the user's emotions in real time. It extracts features from facial imagery and identifies emotional states such as intonation and tension from audio data. Based on this information, it understands the user's psychological state during presentations and provides feedback and support appropriate to that emotional state.

[0122] The server sends back suggestions for improving the generated materials, optimization suggestions for the scripts, and feedback based on sentiment recognition to the terminal. The terminal presents this information to the user, encouraging them to revise the materials and scripts.

[0123] Users practice their presentations based on feedback provided on their devices. During these practice sessions, real-time feedback provides personalized advice tailored to the user's emotional changes, enabling efficient skill improvement based on their own emotional state.

[0124] This invention enables users to improve both the technical and psychological aspects of their presentations, thereby achieving more effective communication.

[0125] The following describes the processing flow.

[0126] Step 1:

[0127] Users upload presentation files, presentation scripts, facial expression images, and audio data to the system using their devices. This provides the necessary data for analysis.

[0128] Step 2:

[0129] The terminal temporarily stores the user's input data and prepares to send it to the server.

[0130] Step 3:

[0131] The terminal sends data files, scripts, facial expression images, and audio data to the server. The server then assigns this data to the respective analysis modules.

[0132] Step 4:

[0133] The server analyzes the document files. This analysis checks the slide structure, fonts, and consistency of the color palette, among other things. Based on this, the server generates visual improvement suggestions.

[0134] Step 5:

[0135] The server analyzes the presentation script. Using natural language processing technology, it evaluates grammatical errors and sentence clarity, and generates suggestions for effective script improvements.

[0136] Step 6:

[0137] The server processes facial image data and audio data. It identifies emotions from facial image data and analyzes intonation and tone of voice from audio data to determine the user's emotional state.

[0138] Step 7:

[0139] The server integrates the analysis results and generates suggestions for improving materials, optimizing scripts, and providing feedback based on the user's emotional state. For example, if the user is feeling stressed, it will generate advice to help them relax.

[0140] Step 8:

[0141] The server sends the generated feedback and suggestions back to the terminal. The terminal presents this to the user and supports the user in modifying the materials and scripts.

[0142] Step 9:

[0143] The user practices their presentation using feedback displayed on the device. The device monitors the user's progress in real time and provides feedback that responds to changes in their emotions.

[0144] Step 10:

[0145] Users incorporate feedback from the system to improve materials and scripts, and comprehensively enhance their presentation skills and emotional state.

[0146] (Example 2)

[0147] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0148] In modern presentations, in addition to visual design and script clarity, the presenter's emotions and psychological state are also crucial elements. However, there is no integrated system that efficiently improves these elements and enhances the overall quality of a presentation. This invention aims to provide a system that comprehensively supports these elements, enabling users to more effectively improve their presentation skills.

[0149] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0150] In this invention, the server includes information processing means for analyzing data files and generating visual improvement suggestions, information processing means for analyzing presentation scripts and suggesting optimized presentation methods, and emotion recognition means for recognizing a person's emotions and providing feedback based on those emotions. This enables improvement in the quality of presentations and self-improvement by the presenter.

[0151] A "document file" refers to digital data that includes slides and their design elements used in a presentation.

[0152] "Information processing means" refers to a function consisting of hardware and software devices for analyzing data provided by the user and generating suggestions based on the results.

[0153] A "presentation script" is text data that describes the content to be spoken in a presentation.

[0154] "Visual improvement suggestions" are specific recommendations for improving the consistency of the design and layout of document files.

[0155] "Optimized expression methods" are proposals for achieving grammatically correct and clear expression in presentation scripts.

[0156] "Emotion recognition means" refers to techniques and methods for analyzing a person's emotional state, which involves recognition using facial expression and voice data.

[0157] A "practice support tool that provides real-time feedback" is a system function that provides users with immediate advice and suggestions for improvement while they are practicing their presentations.

[0158] This invention relates to an information processing system for improving the quality of presentation materials and scripts. This system uses material files provided by the user, presentation scripts, facial expression images necessary for emotion recognition, and audio data.

[0159] The user uploads this data to the system using a terminal. The terminal temporarily stores the data and prepares it for transmission to the server. This process ensures that the data is sent to the server in the correct format.

[0160] The server utilizes algorithms to evaluate visual elements in order to analyze the document files. Specifically, it checks for consistency in design and layout and generates suggestions for improvements to fonts and color palettes. This involves using software for evaluating slide design.

[0161] Furthermore, the server analyzes the presentation script using natural language processing technology. This technology is essential to ensure grammatical accuracy and clarity, and enables script optimization. The natural language processing engine then suggests the most appropriate expression for the user.

[0162] Furthermore, the emotion recognition engine on the server analyzes facial image and audio data to understand the user's emotional state. This allows for real-time feedback based on the user's psychological state during presentations. Specifically, it integrates deep learning and audio analysis software to identify the user's emotions and generate appropriate advice.

[0163] The device receives feedback from the server and presents it to the user. This allows the user to learn specific areas for improvement in their materials and scripts, and effectively improve their presentation skills through practice.

[0164] For example, if a user preparing a new product launch uses this system, the consistency of the document design will be evaluated, and improvements to font size will be suggested. Furthermore, for complex technical explanations in the script, more concise language will be recommended. In addition, the user's level of tension will be detected through emotion recognition, and advice on relaxation techniques will be provided.

[0165] An example of a prompt would be: "Here are my presentation materials and script. Please give me suggestions for improving the visual design, clarifying the script, and advice tailored to my emotional state."

[0166] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0167] Step 1:

[0168] The user uploads presentation files, presentation scripts, facial expression images, and audio data using the device. The input data consists of these files, which the device formats appropriately and temporarily stores. Specifically, the user selects the necessary files from the device's file selection screen and clicks the upload button.

[0169] Step 2:

[0170] The terminal prepares to send the uploaded data to the server. The data is temporarily stored and converted to a format that the server can process. Specifically, this involves actions such as compressing image and audio data and formatting filenames. The output of this step is data ready to be transferred to the server.

[0171] Step 3:

[0172] The server analyzes presentation files received from the terminal and generates visual improvement suggestions. The input is the presentation file, and the algorithm evaluates the slide layout and design elements. Specifically, design evaluation software is used to check for consistency in font size and color palette, and to list areas for improvement. The output of this step is a detailed list of visual improvement suggestions.

[0173] Step 4:

[0174] The server analyzes the presentation script using natural language processing techniques and proposes an optimized presentation method. The input is the presentation script, which is then analyzed for grammatical structure and clarity. Specifically, the natural language processing engine detects grammatical errors and simplifies the text. The output of this step is the optimized script proposal.

[0175] Step 5:

[0176] The server uses an emotion recognition engine to recognize the user's emotions in real time from facial image and audio data. The input consists of facial image and audio data, and deep learning and speech analysis software identify the emotional state. Specifically, it extracts facial feature points and generates emotion labels based on them. The output is detailed information about the user's emotional state.

[0177] Step 6:

[0178] Based on the analysis results described above, the server compiles suggestions for improving the materials, optimizing the scripts, and providing feedback based on sentiment recognition into a single report. The input consists of the individual analysis results, which are then integrated to generate a report ready for the user. Specifically, the report generation flow clearly summarizes each piece of information. The output is a feedback report.

[0179] Step 7:

[0180] The terminal displays feedback reports received from the server to the user. The input is the feedback report, which is displayed in a way that is easy for the user to understand. Specifically, the terminal displays the report on its screen and provides the user with ways to use it to improve materials and scripts. The output of this step is useful feedback information for the user.

[0181] (Application Example 2)

[0182] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0183] In situations where the goal is to improve the quality of customer service, it is essential for staff to accurately understand customer emotions and provide the most appropriate response in each situation. However, there is a lack of suitable means to analyze customer emotions in real time and make improvement suggestions accordingly, making it difficult for staff to efficiently meet customer needs. Technical support is needed to solve this problem.

[0184] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0185] In this invention, the server includes means for analyzing information data and generating visual improvement suggestions, means for analyzing data scripts and suggesting optimized representation methods, and emotion recognition means for analyzing emotion data and providing individualized advice. This enables store employees to understand customer emotions in real time and provide more effective customer service.

[0186] "Information data" refers to all forms of data collected from users, including text, images, and audio.

[0187] "Visual improvement suggestions" refer to providing specific suggestions for improvements to the layout, design, and color scheme of a document.

[0188] A "data script" refers to document data containing the content of text used in presentations or explanations.

[0189] "Optimized representation methods" refer to proposed improvements to grammar and expression to make data script representations more efficient and effective.

[0190] "Emotional data" refers to information about a user's emotional state obtained by analyzing their facial expressions and tone of voice.

[0191] "Emotion recognition means" refers to technical methods or devices for analyzing collected emotion data and identifying the user's emotions.

[0192] "Individualized advice" refers to providing appropriate guidance and feedback to specific users based on the information collected.

[0193] The system for implementing this invention mainly consists of a terminal and a server. The user uploads information data using the terminal, and the server collects the data necessary for analysis.

[0194] First, the device uses its camera and microphone to acquire information data. This information data includes image data capturing the customer's facial expressions and audio data recording their voice tone. This data is temporarily stored on the device, but is then sent to a server.

[0195] The server performs several information processing steps to analyze the received data. Image data is analyzed based on visual metrics to generate visual improvement suggestions. Next, the data script is analyzed using natural language processing techniques. Here, grammatical appropriateness and clarity of expression are evaluated, and improvement suggestions for more effective communication are generated.

[0196] Furthermore, the server includes emotion recognition capabilities to analyze emotional data. For voice analysis, it uses tools such as "IBM Watson® Tone Analyzer," and for facial expression analysis, it uses tools such as "Microsoft Azure® Face API." Based on these results, personalized advice tailored to the user's psychological state is generated and sent back to the terminal.

[0197] A concrete example of this system is customer service support in retail stores. When a store employee interacts with a customer, they can receive service improvement suggestions based on the customer's facial expressions and tone of voice through information displayed on smart glasses. In this way, employees can respond flexibly to customers in real time, leading to improved service quality.

[0198] Using a generative AI model, the server dynamically generates suggested customer service dialogue using the following example prompt: "Suggest improvements to the customer service dialogue to provide when a customer looks anxious."

[0199] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0200] Step 1:

[0201] The device uses its camera and microphone to collect user information data. This data includes image data capturing the customer's facial expressions and audio data recording their voice tone. The collected data is temporarily stored on the device. This image and audio data, as input, is then used to prepare for the next analysis step.

[0202] Step 2:

[0203] Information data is sent from the terminal to the server. Image data is analyzed using tools such as "Microsoft Azure Face API" to recognize emotions from facial expressions. Audio data is analyzed using tools such as "IBM Watson Tone Analyzer" to identify voice tone and emotion. By analyzing the input image and audio data, metadata indicating the user's emotions is output.

[0204] Step 3:

[0205] The server evaluates the user's emotional state based on the analysis results of image and audio data, and generates personalized advice tailored to the user's psychological state and emotional changes. Using a generative AI model, it generates responses based on prompt sentences. For example, it takes a prompt sentence such as "Suggest improvements to the customer service dialogue to provide when a customer looks anxious" as input and outputs specific improvement suggestions.

[0206] Step 4:

[0207] The advice and improvement suggestions generated by the server are sent back to the terminal. The store staff receive this information in real time through the smart glasses display. The suggestions aim to improve service based on customer emotions, providing guidance, for example, on how to conduct conversations that make customers feel at ease. This step visually displays the analysis results and suggested data.

[0208] Step 5:

[0209] Based on the improvement suggestions received, users adjust their customer service methods in real time to provide more effective service to customers. They observe customer feedback and operate the terminal as needed to receive further suggestions. In this process, they receive feedback as input and prepare to smoothly proceed to the next step.

[0210] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0211] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0212] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0213] [Second Embodiment]

[0214] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0215] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0216] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0217] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0218] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0219] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0220] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0221] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0222] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0223] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0224] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0225] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0226] This invention relates to an information processing system for engineers to efficiently improve the design and content of presentation materials and optimize the effective expression of presentation scripts. This system takes user-created presentation material files and scripts as input, analyzes them on the server side, generates improvement suggestions, and provides them to the user.

[0227] First, the user uploads presentation materials and a presentation script to the system using their device. The materials refer to digital files, such as slides or documents. These files are then sent to the server.

[0228] Next, the server analyzes the document files. The analysis process evaluates factors such as slide layout, font and color palette consistency, and the amount of text information. This analysis generates specific suggestions for improving the visual impression of the document.

[0229] Simultaneously, the server analyzes the presentation script. This analysis uses natural language processing techniques to evaluate grammar, clarity, and tone. Suggestions for sentence simplification and keyword emphasis are generated as needed.

[0230] The server sends suggestions for improving the generated materials and optimizations to the terminal, providing feedback to the user. The user can then revise the materials and script based on this feedback. Furthermore, the user can practice their presentation while receiving real-time feedback on their terminal. This practice support feature allows the user to receive immediate evaluations of their speaking style, speed, and intonation during the presentation.

[0231] In this way, the present invention enables users to improve their skills in effectively communicating specialized knowledge to others. It contributes to the efficiency and quality improvement of presentation preparation.

[0232] The following describes the processing flow.

[0233] Step 1:

[0234] The user uses a terminal to upload presentation materials and presentation scripts to the system. The terminal temporarily stores these files as input data.

[0235] Step 2:

[0236] The terminal sends the saved data files to the server. The server receives the data files and begins analyzing the content.

[0237] Step 3:

[0238] The server analyzes the structure of the document files and extracts the slide layout, fonts, and colors used. Based on this information, it generates visual improvement suggestions, such as adjustments to the color scheme or font size.

[0239] Step 4:

[0240] The terminal sends the saved presentation script to the server. The server receives the script and uses NLP (Natural Language Processing) technology to analyze the grammar and the effectiveness of the expressions.

[0241] Step 5:

[0242] Based on the script analysis results, the server generates script optimization suggestions, such as clarifying sentences and highlighting key points. For example, it may suggest simplifying complex sentences and emphasizing important keywords.

[0243] Step 6:

[0244] The server sends back suggestions for improving the generated materials and optimization suggestions for the script to the terminal. The terminal then displays this feedback to the user.

[0245] Step 7:

[0246] Users can review the feedback presented through their devices and revise their materials and scripts. This allows users to improve the quality of their presentations.

[0247] Step 8:

[0248] The user practices their presentation using a device. During this practice, the device evaluates the user's speaking style, speed, and intonation in real time and provides feedback.

[0249] Step 9:

[0250] Users can receive real-time feedback to further refine their presentation skills.

[0251] (Example 1)

[0252] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0253] Conventional presentation creation support systems require significant time and expertise to design and optimize the content of materials, and optimizing the effective expression of scripts is particularly difficult. This makes it challenging for users to receive immediate feedback and prepare effectively. Furthermore, there is a lack of concrete suggestions for improving presentation effectiveness, limiting users' means of obtaining specific guidance for self-improvement.

[0254] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0255] In this invention, the server includes information processing means for analyzing data and generating visual improvement suggestions, information processing means for analyzing presentation scripts and suggesting optimized expressions, exercise support means for providing immediate feedback to the user, and means for utilizing a generative model to enhance the effectiveness of the presentation. This enables users to efficiently create high-quality presentation materials, optimize the expression of their presentation scripts, and improve their presentation skills through real-time feedback, even without specialized knowledge.

[0256] "Document data" refers to digital files containing information in the form of slides or documents used in presentations.

[0257] "Information processing means" refers to technical processes and devices used to analyze data and perform improvements or optimizations in accordance with specific purposes.

[0258] A "presentation script" is a document containing spoken language used during a presentation, and is a script used to effectively convey the content of the presentation.

[0259] "Practice support tools" are features that provide real-time feedback to users when they practice their presentations, and support their preparation.

[0260] A "generative model" is an algorithm or system that automatically generates suggestions for improvements or optimizations tailored to a specific purpose.

[0261] A "visual improvement suggestion" refers to proposed changes to presentation materials to achieve a more effective and appealing appearance.

[0262] "Natural language processing tools" are automated processing technologies used to analyze documents such as presentation scripts and evaluate their grammar and clarity of content.

[0263] This invention is an information processing system for efficiently optimizing a user's presentation materials and presentation scripts. The user uploads presentation material files and presentation scripts to the system using a terminal. The material files are digital data in slide or document format and are transmitted to the server.

[0264] The server uses specialized software to analyze the received document data. At this stage, a design analysis engine evaluates the consistency of the slide layout, fonts, and color palette. Image recognition technology is also used to determine the balance of visual elements. For example, if the placement of images and text is not effective, it generates suggestions for improvement.

[0265] Next, the server analyzes the presentation script using natural language processing (NLTK) techniques. This analysis utilizes open-source NLTK libraries (e.g., spaCy or NLTK). It evaluates grammar, tone, and clarity, and generates suggestions to shorten sentences or emphasize keywords as needed.

[0266] Users can receive feedback from the server on their devices and revise their materials and scripts. They can also practice presentations in an environment that provides real-time feedback. This allows them to receive instant evaluations of their speaking style, speed, intonation, and other aspects, enabling them to improve their skills.

[0267] As a concrete example, here are some prompt statements that can be passed to a generative AI model: "Please suggest improvements to the design of the presentation materials. The current slides lack consistency." "Please tell me about grammatical improvements to the presentation script and ways to express it more effectively." This allows the user to obtain specific guidance for improvement.

[0268] In this way, the system helps users efficiently prepare for presentations and deliver high-quality presentations.

[0269] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0270] Step 1:

[0271] Users use a terminal to upload presentation materials and presentation scripts to the system. Input files include slide files such as Microsoft PowerPoint and script files in Word format. These files are sent to the server in digital format.

[0272] Step 2:

[0273] The server begins design analysis on the received document data. The input is the document file uploaded in Step 1. The server uses its analysis engine to verify the slide layout, fonts, and consistent color palette. As part of the data processing, it analyzes the element position and style of each slide and extracts visually appealing improvement suggestions. As output, a list of improvement suggestions is generated.

[0274] Step 3:

[0275] The server analyzes the presentation script. The input is the script file uploaded in Step 1. Natural language processing techniques are used to evaluate grammar, tone, and clarity. Data calculations use open-source libraries to simplify sentences and extract important keywords. The output is a list of script improvement suggestions and optimization proposals.

[0276] Step 4:

[0277] The server sends suggestions for improving the document and optimizing the script to the terminal. The input is the list of suggestions generated in steps 2 and 3. As output, this feedback is provided on the terminal. The terminal immediately displays it to the user, allowing the user to modify the document or script.

[0278] Step 5:

[0279] The user operates the terminal and practices the presentation while receiving real-time feedback. The input is the feedback from the server. The terminal analyzes the user's voice, speech pace, intonation, etc., and provides immediate feedback. Based on this feedback, the user can adjust and improve their presentation skills.

[0280] (Application Example 1)

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

[0282] When giving a presentation, it is required to immediately improve the visual design of the materials and the expression of the script, and further flexibly change the content of the materials according to the reactions of the observers. However, in the current system, it is difficult to perform these tasks effectively and quickly, so reducing the burden on the speaker and improving the quality of the presentation are issues. [[ID=...]]

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

[0284] In this invention, the server includes means for analyzing the material file and generating visual improvement proposals, means for analyzing the presentation script and proposing an optimized expression method, and means for dynamically modifying the content of the materials based on the reactions of the observers. As a result, the design and content of the materials are optimized in real time during the presentation, and the speaker can make a flexible presentation according to the reactions of the observers.

[0285] The "information processing means for analyzing the material file and generating visual improvement proposals" is a device that evaluates the layout, font, consistency, etc. of the input materials and generates specific proposals for realizing a visually excellent presentation.

[0286] The "information processing means for analyzing a presentation script and proposing an optimized expression method" is a device that analyzes a presentation script using natural language processing technology and generates proposals for improving grammar, clarity, and the effect of intonation.

[0287] The "drill support means for providing real-time feedback to the user" is a device that immediately provides an evaluation regarding speaking style, speed, and intonation and points out areas for improvement while the user is giving a presentation.

[0288] The "means for dynamically modifying the content of materials based on the reactions of observers" is a device that acquires the expressions and reactions of observers as data and changes the order and design of the presentation content based on that data.

[0289] The system for implementing this invention is composed of a server that performs analysis with a materials file and a presentation script as inputs. The server first receives a digital-form materials file and a script from the user. The materials file is in slide format or document format, and this is analyzed to generate proposals for visual improvement.

[0290] The server employs existing presentation tools or independently developed algorithms to evaluate the layout, font, consistency, and information volume of the materials. Next, the server analyzes the presentation script using natural language processing software and provides proposals for improving grammar, clarity, and intonation. As representative software, open-source natural language processing libraries can be considered.

[0291] On the user terminal, it is possible to practice giving a presentation using the real-time feedback function. This feedback includes evaluations regarding speaking style, speed, and intonation, and based on this, the user can adjust their speaking style.

[0292] Furthermore, the server uses software to analyze observer reactions, collecting data such as observer facial expressions and dynamically modifying the content of the materials. This allows for flexible changes to the order and design of materials during the presentation, keeping the observer engaged.

[0293] For example, when giving a presentation at a large academic conference, even if it's difficult to gauge the audience's reactions, this system allows for real-time feedback and flexible adjustments to the presentation materials. Therefore, effective presentations are possible even in situations requiring immediate responses.

[0294] An example of a prompt using a generative AI model is: "Suggest a method to evaluate the visual design and script content of a presentation and generate improvement suggestions in real time. Refine the suggestions using audience reaction data." Using this prompt makes it possible to provide more specific feedback.

[0295] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0296] Step 1:

[0297] Users upload presentation materials and presentation scripts to the system using their terminals. The input consists of digital materials and scripts, which are sent to the server. The server receives and stores these files.

[0298] Step 2:

[0299] The server analyzes the received document files. The input is the document files, and the output is visual improvement suggestions. The server analyzes the slide layout, fonts, consistency, and amount of text information, and generates visual design improvement suggestions based on this analysis. In doing so, it uses presentation tool APIs and proprietary algorithms.

[0300] Step 3:

[0301] The server analyzes the presentation script. The input is the script, and the output is a proposal for improving the expression. The server uses natural language processing technology to evaluate grammar, clarity, and tone, and generates an optimization plan. Specifically, it uses a natural language processing library to analyze the script and propose simplifying sentences and highlighting keywords.

[0302] Step 4:

[0303] <用 The server sends the generated improvement proposal to the terminal. The terminal displays it and provides feedback to the user. This enables the user to modify the materials and script. The input is the improvement proposal, and the output is the feedback display on the user's screen.

[0304] Step 5:

[0305] The user practices the presentation while receiving real-time feedback on the terminal. The input is the user's presentation voice and speed, and the output is an immediate evaluation. The terminal uses a microphone to collect the voice and provides feedback on speaking style, speed, and intonation. At this time, voice analysis software is used.

[0306] Step 6:

[0307] The server dynamically modifies the material content based on the reactions of the observers. The input is the observers' expressions and other reaction data, and the output is a proposed modified material. The server uses visual data analysis software to analyze the observers' reactions and generates a proposal to adjust the material.

[0308] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion recognition model 59 and perform specific processing using the user's emotion.

[0309] It should be noted that there seems to be a misspelling in line 13 where "用0000956" is likely incorrect. It's left as is in the translation according to the instruction.This invention relates to an information processing system that analyzes and improves presentation materials and presentation scripts, and further combines them with an emotion engine that recognizes user emotions. This system takes user-provided material files and presentation scripts as input, collects data for emotion recognition, and generates and provides improvement suggestions to the user based on this information.

[0310] First, the user uploads presentation materials, a presentation script, and facial image and audio data for emotion recognition to the system using their device. The device temporarily stores this data and prepares to send it to the server.

[0311] Next, the server analyzes the document files. This analysis process evaluates the consistency of the slide layout, design elements, fonts, and color palette, and generates visual improvement suggestions.

[0312] The server further analyzes the presentation script using natural language processing techniques. It evaluates grammar, clarity, and tone, and generates suggestions for script optimization, such as sentence simplification and keyword emphasis, as needed.

[0313] In addition, the emotion engine installed on the server recognizes the user's emotions in real time. It extracts features from facial imagery and identifies emotional states such as intonation and tension from audio data. Based on this information, it understands the user's psychological state during presentations and provides feedback and support appropriate to that emotional state.

[0314] The server sends back suggestions for improving the generated materials, optimization suggestions for the scripts, and feedback based on sentiment recognition to the terminal. The terminal presents this information to the user, encouraging them to revise the materials and scripts.

[0315] Users practice their presentations based on feedback provided on their devices. During these practice sessions, real-time feedback provides personalized advice tailored to the user's emotional changes, enabling efficient skill improvement based on their own emotional state.

[0316] This invention enables users to improve both the technical and psychological aspects of their presentations, thereby achieving more effective communication.

[0317] The following describes the processing flow.

[0318] Step 1:

[0319] Users upload presentation files, presentation scripts, facial expression images, and audio data to the system using their devices. This provides the necessary data for analysis.

[0320] Step 2:

[0321] The terminal temporarily stores the user's input data and prepares to send it to the server.

[0322] Step 3:

[0323] The terminal sends data files, scripts, facial expression images, and audio data to the server. The server then assigns this data to the respective analysis modules.

[0324] Step 4:

[0325] The server analyzes the document files. This analysis checks the slide structure, fonts, and consistency of the color palette, among other things. Based on this, the server generates visual improvement suggestions.

[0326] Step 5:

[0327] The server analyzes the presentation script. Using natural language processing technology, it evaluates grammatical errors and sentence clarity, and generates suggestions for effective script improvements.

[0328] Step 6:

[0329] The server processes facial image data and audio data. It identifies emotions from facial image data and analyzes intonation and tone of voice from audio data to determine the user's emotional state.

[0330] Step 7:

[0331] The server integrates the analysis results and generates suggestions for improving materials, optimizing scripts, and providing feedback based on the user's emotional state. For example, if the user is feeling stressed, it will generate advice to help them relax.

[0332] Step 8:

[0333] The server sends the generated feedback and suggestions back to the terminal. The terminal presents this to the user and supports the user in modifying the materials and scripts.

[0334] Step 9:

[0335] The user practices their presentation using feedback displayed on the device. The device monitors the user's progress in real time and provides feedback that responds to changes in their emotions.

[0336] Step 10:

[0337] Users incorporate feedback from the system to improve materials and scripts, and comprehensively enhance their presentation skills and emotional state.

[0338] (Example 2)

[0339] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0340] In modern presentations, in addition to visual design and script clarity, the presenter's emotions and psychological state are also crucial elements. However, there is no integrated system that efficiently improves these elements and enhances the overall quality of a presentation. This invention aims to provide a system that comprehensively supports these elements, enabling users to more effectively improve their presentation skills.

[0341] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0342] In this invention, the server includes information processing means for analyzing data files and generating visual improvement suggestions, information processing means for analyzing presentation scripts and suggesting optimized presentation methods, and emotion recognition means for recognizing a person's emotions and providing feedback based on those emotions. This enables improvement in the quality of presentations and self-improvement by the presenter.

[0343] A "document file" refers to digital data that includes slides and their design elements used in a presentation.

[0344] "Information processing means" refers to a function consisting of hardware and software devices for analyzing data provided by the user and generating suggestions based on the results.

[0345] A "presentation script" is text data that describes the content to be spoken in a presentation.

[0346] "Visual improvement suggestions" are specific recommendations for improving the consistency of the design and layout of document files.

[0347] "Optimized expression methods" are proposals for achieving grammatically correct and clear expression in presentation scripts.

[0348] "Emotion recognition means" refers to techniques and methods for analyzing a person's emotional state, which involves recognition using facial expression and voice data.

[0349] A "practice support tool that provides real-time feedback" is a system function that provides users with immediate advice and suggestions for improvement while they are practicing their presentations.

[0350] This invention relates to an information processing system for improving the quality of presentation materials and scripts. This system uses material files provided by the user, presentation scripts, facial expression images necessary for emotion recognition, and audio data.

[0351] The user uploads this data to the system using a terminal. The terminal temporarily stores the data and prepares it for transmission to the server. This process ensures that the data is sent to the server in the correct format.

[0352] The server utilizes algorithms to evaluate visual elements in order to analyze the document files. Specifically, it checks for consistency in design and layout and generates suggestions for improvements to fonts and color palettes. This involves using software for evaluating slide design.

[0353] Furthermore, the server analyzes the presentation script using natural language processing technology. This technology is essential to ensure grammatical accuracy and clarity, and enables script optimization. The natural language processing engine then suggests the most appropriate expression for the user.

[0354] Furthermore, the emotion recognition engine on the server analyzes facial image and audio data to understand the user's emotional state. This allows for real-time feedback based on the user's psychological state during presentations. Specifically, it integrates deep learning and audio analysis software to identify the user's emotions and generate appropriate advice.

[0355] The device receives feedback from the server and presents it to the user. This allows the user to learn specific areas for improvement in their materials and scripts, and effectively improve their presentation skills through practice.

[0356] For example, if a user preparing a new product launch uses this system, the consistency of the document design will be evaluated, and improvements to font size will be suggested. Furthermore, for complex technical explanations in the script, more concise language will be recommended. In addition, the user's level of tension will be detected through emotion recognition, and advice on relaxation techniques will be provided.

[0357] An example of a prompt would be: "Here are my presentation materials and script. Please give me suggestions for improving the visual design, clarifying the script, and advice tailored to my emotional state."

[0358] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0359] Step 1:

[0360] The user uploads presentation files, presentation scripts, facial expression images, and audio data using the device. The input data consists of these files, which the device formats appropriately and temporarily stores. Specifically, the user selects the necessary files from the device's file selection screen and clicks the upload button.

[0361] Step 2:

[0362] The terminal prepares to send the uploaded data to the server. The data is temporarily stored and converted to a format that the server can process. Specifically, this involves actions such as compressing image and audio data and formatting filenames. The output of this step is data ready to be transferred to the server.

[0363] Step 3:

[0364] The server analyzes presentation files received from the terminal and generates visual improvement suggestions. The input is the presentation file, and the algorithm evaluates the slide layout and design elements. Specifically, design evaluation software is used to check for consistency in font size and color palette, and to list areas for improvement. The output of this step is a detailed list of visual improvement suggestions.

[0365] Step 4:

[0366] The server analyzes the presentation script using natural language processing techniques and proposes an optimized presentation method. The input is the presentation script, which is then analyzed for grammatical structure and clarity. Specifically, the natural language processing engine detects grammatical errors and simplifies the text. The output of this step is the optimized script proposal.

[0367] Step 5:

[0368] The server uses an emotion recognition engine to recognize the user's emotions in real time from facial image and audio data. The input consists of facial image and audio data, and deep learning and speech analysis software identify the emotional state. Specifically, it extracts facial feature points and generates emotion labels based on them. The output is detailed information about the user's emotional state.

[0369] Step 6:

[0370] Based on the analysis results described above, the server compiles suggestions for improving the materials, optimizing the scripts, and providing feedback based on sentiment recognition into a single report. The input consists of the individual analysis results, which are then integrated to generate a report ready for the user. Specifically, the report generation flow clearly summarizes each piece of information. The output is a feedback report.

[0371] Step 7:

[0372] The terminal displays feedback reports received from the server to the user. The input is the feedback report, which is displayed in a way that is easy for the user to understand. Specifically, the terminal displays the report on its screen and provides the user with ways to use it to improve materials and scripts. The output of this step is useful feedback information for the user.

[0373] (Application Example 2)

[0374] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0375] In situations where the goal is to improve the quality of customer service, it is essential for staff to accurately understand customer emotions and provide the most appropriate response in each situation. However, there is a lack of suitable means to analyze customer emotions in real time and make improvement suggestions accordingly, making it difficult for staff to efficiently meet customer needs. Technical support is needed to solve this problem.

[0376] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0377] In this invention, the server includes means for analyzing information data and generating visual improvement suggestions, means for analyzing data scripts and suggesting optimized representation methods, and emotion recognition means for analyzing emotion data and providing individualized advice. This enables store employees to understand customer emotions in real time and provide more effective customer service.

[0378] "Information data" refers to all forms of data collected from users, including text, images, and audio.

[0379] "Visual improvement suggestions" refer to providing specific suggestions for improvements to the layout, design, and color scheme of a document.

[0380] A "data script" refers to document data containing the content of text used in presentations or explanations.

[0381] "Optimized representation methods" refer to proposed improvements to grammar and expression to make data script representations more efficient and effective.

[0382] "Emotional data" refers to information about a user's emotional state obtained by analyzing their facial expressions and tone of voice.

[0383] "Emotion recognition means" refers to technical methods or devices for analyzing collected emotion data and identifying the user's emotions.

[0384] "Individualized advice" refers to providing appropriate guidance and feedback to specific users based on the information collected.

[0385] The system for implementing this invention mainly consists of a terminal and a server. The user uploads information data using the terminal, and the server collects the data necessary for analysis.

[0386] First, the device uses its camera and microphone to acquire information data. This information data includes image data capturing the customer's facial expressions and audio data recording their voice tone. This data is temporarily stored on the device, but is then sent to a server.

[0387] The server performs several information processing steps to analyze the received data. Image data is analyzed based on visual metrics to generate visual improvement suggestions. Next, the data script is analyzed using natural language processing techniques. Here, grammatical appropriateness and clarity of expression are evaluated, and improvement suggestions for more effective communication are generated.

[0388] Furthermore, the server includes emotion recognition capabilities to analyze emotional data. For voice analysis, it uses tools such as "IBM Watson Tone Analyzer," and for facial expression analysis, it can use tools such as "Microsoft Azure Face API." Based on these results, personalized advice tailored to the user's psychological state is generated and sent back to the terminal.

[0389] A concrete example of this system is customer service support in retail stores. When a store employee interacts with a customer, they can receive service improvement suggestions based on the customer's facial expressions and tone of voice through information displayed on smart glasses. In this way, employees can respond flexibly to customers in real time, leading to improved service quality.

[0390] Using a generative AI model, the server dynamically generates suggested customer service dialogue using the following example prompt: "Suggest improvements to the customer service dialogue to provide when a customer looks anxious."

[0391] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0392] Step 1:

[0393] The device uses its camera and microphone to collect user information data. This data includes image data capturing the customer's facial expressions and audio data recording their voice tone. The collected data is temporarily stored on the device. This image and audio data, as input, is then used to prepare for the next analysis step.

[0394] Step 2:

[0395] Information data is sent from the terminal to the server. Image data is analyzed using tools such as "Microsoft Azure Face API" to recognize emotions from facial expressions. Audio data is analyzed using tools such as "IBM Watson Tone Analyzer" to identify voice tone and emotion. By analyzing the input image and audio data, metadata indicating the user's emotions is output.

[0396] Step 3:

[0397] The server evaluates the user's emotional state based on the analysis results of image and audio data, and generates personalized advice tailored to the user's psychological state and emotional changes. Using a generative AI model, it generates responses based on prompt sentences. For example, it takes a prompt sentence such as "Suggest improvements to the customer service dialogue to provide when a customer looks anxious" as input and outputs specific improvement suggestions.

[0398] Step 4:

[0399] The advice and improvement suggestions generated by the server are sent back to the terminal. The store staff receive this information in real time through the smart glasses display. The suggestions aim to improve service based on customer emotions, providing guidance, for example, on how to conduct conversations that make customers feel at ease. This step visually displays the analysis results and suggested data.

[0400] Step 5:

[0401] Based on the improvement suggestions received, users adjust their customer service methods in real time to provide more effective service to customers. They observe customer feedback and operate the terminal as needed to receive further suggestions. In this process, they receive feedback as input and prepare to smoothly proceed to the next step.

[0402] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0403] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0404] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0405] [Third Embodiment]

[0406] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0407] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0408] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0409] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0410] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0411] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0412] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0413] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0414] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0415] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0416] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0417] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0418] This invention relates to an information processing system for engineers to efficiently improve the design and content of presentation materials and optimize the effective expression of presentation scripts. This system takes user-created presentation material files and scripts as input, analyzes them on the server side, generates improvement suggestions, and provides them to the user.

[0419] First, the user uploads presentation materials and a presentation script to the system using their device. The materials refer to digital files, such as slides or documents. These files are then sent to the server.

[0420] Next, the server analyzes the document files. The analysis process evaluates factors such as slide layout, font and color palette consistency, and the amount of text information. This analysis generates specific suggestions for improving the visual impression of the document.

[0421] Simultaneously, the server analyzes the presentation script. This analysis uses natural language processing techniques to evaluate grammar, clarity, and tone. Suggestions for sentence simplification and keyword emphasis are generated as needed.

[0422] The server sends suggestions for improving the generated materials and optimizations to the terminal, providing feedback to the user. The user can then revise the materials and script based on this feedback. Furthermore, the user can practice their presentation while receiving real-time feedback on their terminal. This practice support feature allows the user to receive immediate evaluations of their speaking style, speed, and intonation during the presentation.

[0423] In this way, the present invention enables users to improve their skills in effectively communicating specialized knowledge to others. It contributes to the efficiency and quality improvement of presentation preparation.

[0424] The following describes the processing flow.

[0425] Step 1:

[0426] The user uses a terminal to upload presentation materials and presentation scripts to the system. The terminal temporarily stores these files as input data.

[0427] Step 2:

[0428] The terminal sends the saved data files to the server. The server receives the data files and begins analyzing the content.

[0429] Step 3:

[0430] The server analyzes the structure of the document files and extracts the slide layout, fonts, and colors used. Based on this information, it generates visual improvement suggestions, such as adjustments to the color scheme or font size.

[0431] Step 4:

[0432] The terminal sends the saved presentation script to the server. The server receives the script and uses NLP (Natural Language Processing) technology to analyze the grammar and the effectiveness of the expressions.

[0433] Step 5:

[0434] Based on the script analysis results, the server generates script optimization suggestions, such as clarifying sentences and highlighting key points. For example, it may suggest simplifying complex sentences and emphasizing important keywords.

[0435] Step 6:

[0436] The server sends back suggestions for improving the generated materials and optimization suggestions for the script to the terminal. The terminal then displays this feedback to the user.

[0437] Step 7:

[0438] Users can review the feedback presented through their devices and revise their materials and scripts. This allows users to improve the quality of their presentations.

[0439] Step 8:

[0440] The user practices their presentation using a device. During this practice, the device evaluates the user's speaking style, speed, and intonation in real time and provides feedback.

[0441] Step 9:

[0442] Users can receive real-time feedback to further refine their presentation skills.

[0443] (Example 1)

[0444] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0445] Conventional presentation creation support systems require significant time and expertise to design and optimize the content of materials, and optimizing the effective expression of scripts is particularly difficult. This makes it challenging for users to receive immediate feedback and prepare effectively. Furthermore, there is a lack of concrete suggestions for improving presentation effectiveness, limiting users' means of obtaining specific guidance for self-improvement.

[0446] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0447] In this invention, the server includes information processing means for analyzing data and generating visual improvement suggestions, information processing means for analyzing presentation scripts and suggesting optimized expressions, exercise support means for providing immediate feedback to the user, and means for utilizing a generative model to enhance the effectiveness of the presentation. This enables users to efficiently create high-quality presentation materials, optimize the expression of their presentation scripts, and improve their presentation skills through real-time feedback, even without specialized knowledge.

[0448] "Document data" refers to digital files containing information in the form of slides or documents used in presentations.

[0449] "Information processing means" refers to technical processes and devices used to analyze data and perform improvements or optimizations in accordance with specific purposes.

[0450] A "presentation script" is a document containing spoken language used during a presentation, and is a script used to effectively convey the content of the presentation.

[0451] "Practice support tools" are features that provide real-time feedback to users when they practice their presentations, and support their preparation.

[0452] A "generative model" is an algorithm or system that automatically generates suggestions for improvements or optimizations tailored to a specific purpose.

[0453] A "visual improvement suggestion" refers to proposed changes to presentation materials to achieve a more effective and appealing appearance.

[0454] "Natural language processing tools" are automated processing technologies used to analyze documents such as presentation scripts and evaluate their grammar and clarity of content.

[0455] This invention is an information processing system for efficiently optimizing a user's presentation materials and presentation scripts. The user uploads presentation material files and presentation scripts to the system using a terminal. The material files are digital data in slide or document format and are transmitted to the server.

[0456] The server uses specialized software to analyze the received document data. At this stage, a design analysis engine evaluates the consistency of the slide layout, fonts, and color palette. Image recognition technology is also used to determine the balance of visual elements. For example, if the placement of images and text is not effective, it generates suggestions for improvement.

[0457] Next, the server analyzes the presentation script using natural language processing (NLTK) techniques. This analysis utilizes open-source NLTK libraries (e.g., spaCy or NLTK). It evaluates grammar, tone, and clarity, and generates suggestions to shorten sentences or emphasize keywords as needed.

[0458] Users can receive feedback from the server on their devices and revise their materials and scripts. They can also practice presentations in an environment that provides real-time feedback. This allows them to receive instant evaluations of their speaking style, speed, intonation, and other aspects, enabling them to improve their skills.

[0459] As a concrete example, here are some prompt statements that can be passed to a generative AI model: "Please suggest improvements to the design of the presentation materials. The current slides lack consistency." "Please tell me about grammatical improvements to the presentation script and ways to express it more effectively." This allows the user to obtain specific guidance for improvement.

[0460] In this way, the system helps users efficiently prepare for presentations and deliver high-quality presentations.

[0461] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0462] Step 1:

[0463] Users use a terminal to upload presentation materials and presentation scripts to the system. Input files include slide files such as Microsoft PowerPoint and script files in Word format. These files are sent to the server in digital format.

[0464] Step 2:

[0465] The server begins design analysis on the received document data. The input is the document file uploaded in Step 1. The server uses its analysis engine to verify the slide layout, fonts, and consistent color palette. As part of the data processing, it analyzes the element position and style of each slide and extracts visually appealing improvement suggestions. As output, a list of improvement suggestions is generated.

[0466] Step 3:

[0467] The server analyzes the presentation script. The input is the script file uploaded in Step 1. Natural language processing techniques are used to evaluate grammar, tone, and clarity. Data calculations use open-source libraries to simplify sentences and extract important keywords. The output is a list of script improvement suggestions and optimization proposals.

[0468] Step 4:

[0469] The server sends suggestions for improving the document and optimizing the script to the terminal. The input is the list of suggestions generated in steps 2 and 3. As output, this feedback is provided on the terminal. The terminal immediately displays it to the user, allowing the user to modify the document or script.

[0470] Step 5:

[0471] Users operate a device and practice their presentations while receiving real-time feedback. The input is feedback from a server. The device analyzes the user's voice, speaking pace, intonation, etc., and provides immediate feedback. Based on this feedback, users can adjust and improve their presentation skills.

[0472] (Application Example 1)

[0473] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0474] When giving a presentation, it is necessary to immediately improve the visual design of the materials and the expression of the script, and to flexibly change the content of the materials in response to the audience's reactions. However, with the current system, it is difficult to perform these tasks effectively and quickly, so reducing the burden on the speaker and improving the quality of the presentation are challenges.

[0475] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0476] In this invention, the server includes means for analyzing document files and generating visual improvement suggestions, means for analyzing presentation scripts and suggesting optimized presentation methods, and means for dynamically modifying the document content based on observer reactions. This allows the design and content of the document to be optimized in real time during the presentation, enabling the speaker to deliver a flexible presentation in response to observer reactions.

[0477] "Information processing means for analyzing document files and generating visual improvement suggestions" refers to a device that evaluates the layout, font, consistency, etc., of input documents and generates specific suggestions for achieving visually superior presentations.

[0478] "Information processing means for analyzing presentation scripts and proposing optimized expression methods" refers to a device that analyzes presentation scripts using natural language processing technology and generates suggestions for improving grammar, clarity, and tone.

[0479] A "practice support device that provides real-time feedback to users" is a device that provides immediate evaluation of a user's speaking style, speed, and intonation while they are giving a presentation, and points out areas for improvement.

[0480] "Means for dynamically modifying the content of materials based on observer reactions" refers to a device that acquires data on the observer's facial expressions and reactions, and then changes the order and design of the presentation content based on that data.

[0481] The system implementing this invention consists of a server that performs analysis using document files and presentation scripts as input. The server first receives the document files and scripts in digital format from the user. The document files are in slide or document format, and the system analyzes them to generate visual improvement suggestions.

[0482] The server employs existing presentation tools and custom-developed algorithms to evaluate the layout, fonts, consistency, and information density of the materials. Next, the server analyzes the presentation script using natural language processing software to provide suggestions for grammar, clarity, and tone improvement. Typical software for this includes open-source natural language processing libraries.

[0483] On the user's device, a real-time feedback function is available to practice presentations. This feedback includes evaluations of speaking style, speed, and intonation, allowing the user to adjust their speaking style accordingly.

[0484] Furthermore, the server uses software to analyze observer reactions, collecting data such as observer facial expressions and dynamically modifying the content of the materials. This allows for flexible changes to the order and design of materials during the presentation, keeping the observer engaged.

[0485] For example, when giving a presentation at a large academic conference, even if it's difficult to gauge the audience's reactions, this system allows for real-time feedback and flexible adjustments to the presentation materials. Therefore, effective presentations are possible even in situations requiring immediate responses.

[0486] An example of a prompt using a generative AI model is: "Suggest a method to evaluate the visual design and script content of a presentation and generate improvement suggestions in real time. Refine the suggestions using audience reaction data." Using this prompt makes it possible to provide more specific feedback.

[0487] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0488] Step 1:

[0489] Users upload presentation materials and presentation scripts to the system using their terminals. The input consists of digital materials and scripts, which are sent to the server. The server receives and stores these files.

[0490] Step 2:

[0491] The server analyzes the received document files. The input is the document files, and the output is visual improvement suggestions. The server analyzes the slide layout, fonts, consistency, and amount of text information, and generates visual design improvement suggestions based on this analysis. In doing so, it uses presentation tool APIs and proprietary algorithms.

[0492] Step 3:

[0493] The server analyzes the presentation script. The input is the script, and the output is suggestions for improving the presentation. The server uses natural language processing techniques to evaluate grammar, clarity, and tone, and generates optimization suggestions. Specifically, it uses a natural language processing library to analyze the script and suggests sentence simplification and keyword emphasis.

[0494] Step 4:

[0495] The server sends the generated improvement suggestions to the terminal. The terminal displays them and provides feedback to the user. This allows the user to modify the documents or scripts. The input is the improvement suggestions, and the output is the feedback displayed on the user's screen.

[0496] Step 5:

[0497] Users practice their presentations while receiving real-time feedback on the device. Input is the user's presentation voice and speed, while output is immediate evaluation. The device uses a microphone to collect audio and provides feedback on speaking style, speed, and intonation. Voice analysis software is used in this process.

[0498] Step 6:

[0499] The server dynamically modifies the content of the materials based on the observer's reactions. The input is the observer's facial expressions and other reaction data, and the output is the modified material suggestion. The server uses visual data analysis software to analyze the observer's reactions and generate suggestions for adjusting the materials.

[0500] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0501] This invention relates to an information processing system that analyzes and improves presentation materials and presentation scripts, and further combines them with an emotion engine that recognizes user emotions. This system takes user-provided material files and presentation scripts as input, collects data for emotion recognition, and generates and provides improvement suggestions to the user based on this information.

[0502] First, the user uploads presentation materials, a presentation script, and facial image and audio data for emotion recognition to the system using their device. The device temporarily stores this data and prepares to send it to the server.

[0503] Next, the server analyzes the document files. This analysis process evaluates the consistency of the slide layout, design elements, fonts, and color palette, and generates visual improvement suggestions.

[0504] The server further analyzes the presentation script using natural language processing techniques. It evaluates grammar, clarity, and tone, and generates suggestions for script optimization, such as sentence simplification and keyword emphasis, as needed.

[0505] In addition, the emotion engine installed on the server recognizes the user's emotions in real time. It extracts features from facial imagery and identifies emotional states such as intonation and tension from audio data. Based on this information, it understands the user's psychological state during presentations and provides feedback and support appropriate to that emotional state.

[0506] The server sends back suggestions for improving the generated materials, optimization suggestions for the scripts, and feedback based on sentiment recognition to the terminal. The terminal presents this information to the user, encouraging them to revise the materials and scripts.

[0507] Users practice their presentations based on feedback provided on their devices. During these practice sessions, real-time feedback provides personalized advice tailored to the user's emotional changes, enabling efficient skill improvement based on their own emotional state.

[0508] This invention enables users to improve both the technical and psychological aspects of their presentations, thereby achieving more effective communication.

[0509] The following describes the processing flow.

[0510] Step 1:

[0511] Users upload presentation files, presentation scripts, facial expression images, and audio data to the system using their devices. This provides the necessary data for analysis.

[0512] Step 2:

[0513] The terminal temporarily stores the user's input data and prepares to send it to the server.

[0514] Step 3:

[0515] The terminal sends data files, scripts, facial expression images, and audio data to the server. The server then assigns this data to the respective analysis modules.

[0516] Step 4:

[0517] The server analyzes the document files. This analysis checks the slide structure, fonts, and consistency of the color palette, among other things. Based on this, the server generates visual improvement suggestions.

[0518] Step 5:

[0519] The server analyzes the presentation script. Using natural language processing technology, it evaluates grammatical errors and sentence clarity, and generates suggestions for effective script improvements.

[0520] Step 6:

[0521] The server processes facial image data and audio data. It identifies emotions from facial image data and analyzes intonation and tone of voice from audio data to determine the user's emotional state.

[0522] Step 7:

[0523] The server integrates the analysis results and generates suggestions for improving materials, optimizing scripts, and providing feedback based on the user's emotional state. For example, if the user is feeling stressed, it will generate advice to help them relax.

[0524] Step 8:

[0525] The server sends the generated feedback and suggestions back to the terminal. The terminal presents this to the user and supports the user in modifying the materials and scripts.

[0526] Step 9:

[0527] The user practices their presentation using feedback displayed on the device. The device monitors the user's progress in real time and provides feedback that responds to changes in their emotions.

[0528] Step 10:

[0529] Users incorporate feedback from the system to improve materials and scripts, and comprehensively enhance their presentation skills and emotional state.

[0530] (Example 2)

[0531] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0532] In modern presentations, in addition to visual design and script clarity, the presenter's emotions and psychological state are also crucial elements. However, there is no integrated system that efficiently improves these elements and enhances the overall quality of a presentation. This invention aims to provide a system that comprehensively supports these elements, enabling users to more effectively improve their presentation skills.

[0533] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0534] In this invention, the server includes information processing means for analyzing data files and generating visual improvement suggestions, information processing means for analyzing presentation scripts and suggesting optimized presentation methods, and emotion recognition means for recognizing a person's emotions and providing feedback based on those emotions. This enables improvement in the quality of presentations and self-improvement by the presenter.

[0535] A "document file" refers to digital data that includes slides and their design elements used in a presentation.

[0536] "Information processing means" refers to a function consisting of hardware and software devices for analyzing data provided by the user and generating suggestions based on the results.

[0537] A "presentation script" is text data that describes the content to be spoken in a presentation.

[0538] "Visual improvement suggestions" are specific recommendations for improving the consistency of the design and layout of document files.

[0539] "Optimized expression methods" are proposals for achieving grammatically correct and clear expression in presentation scripts.

[0540] "Emotion recognition means" refers to techniques and methods for analyzing a person's emotional state, which involves recognition using facial expression and voice data.

[0541] A "practice support tool that provides real-time feedback" is a system function that provides users with immediate advice and suggestions for improvement while they are practicing their presentations.

[0542] This invention relates to an information processing system for improving the quality of presentation materials and scripts. This system uses material files provided by the user, presentation scripts, facial expression images necessary for emotion recognition, and audio data.

[0543] The user uploads this data to the system using a terminal. The terminal temporarily stores the data and prepares it for transmission to the server. This process ensures that the data is sent to the server in the correct format.

[0544] The server utilizes algorithms to evaluate visual elements in order to analyze the document files. Specifically, it checks for consistency in design and layout and generates suggestions for improvements to fonts and color palettes. This involves using software for evaluating slide design.

[0545] Furthermore, the server analyzes the presentation script using natural language processing technology. This technology is essential to ensure grammatical accuracy and clarity, and enables script optimization. The natural language processing engine then suggests the most appropriate expression for the user.

[0546] Furthermore, the emotion recognition engine on the server analyzes facial image and audio data to understand the user's emotional state. This allows for real-time feedback based on the user's psychological state during presentations. Specifically, it integrates deep learning and audio analysis software to identify the user's emotions and generate appropriate advice.

[0547] The device receives feedback from the server and presents it to the user. This allows the user to learn specific areas for improvement in their materials and scripts, and effectively improve their presentation skills through practice.

[0548] For example, if a user preparing a new product launch uses this system, the consistency of the document design will be evaluated, and improvements to font size will be suggested. Furthermore, for complex technical explanations in the script, more concise language will be recommended. In addition, the user's level of tension will be detected through emotion recognition, and advice on relaxation techniques will be provided.

[0549] An example of a prompt would be: "Here are my presentation materials and script. Please give me suggestions for improving the visual design, clarifying the script, and advice tailored to my emotional state."

[0550] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0551] Step 1:

[0552] The user uploads presentation files, presentation scripts, facial expression images, and audio data using the device. The input data consists of these files, which the device formats appropriately and temporarily stores. Specifically, the user selects the necessary files from the device's file selection screen and clicks the upload button.

[0553] Step 2:

[0554] The terminal prepares to send the uploaded data to the server. The data is temporarily stored and converted to a format that the server can process. Specifically, this involves actions such as compressing image and audio data and formatting filenames. The output of this step is data ready to be transferred to the server.

[0555] Step 3:

[0556] The server analyzes presentation files received from the terminal and generates visual improvement suggestions. The input is the presentation file, and the algorithm evaluates the slide layout and design elements. Specifically, design evaluation software is used to check for consistency in font size and color palette, and to list areas for improvement. The output of this step is a detailed list of visual improvement suggestions.

[0557] Step 4:

[0558] The server analyzes the presentation script using natural language processing techniques and proposes an optimized presentation method. The input is the presentation script, which is then analyzed for grammatical structure and clarity. Specifically, the natural language processing engine detects grammatical errors and simplifies the text. The output of this step is the optimized script proposal.

[0559] Step 5:

[0560] The server uses an emotion recognition engine to recognize the user's emotions in real time from facial image and audio data. The input consists of facial image and audio data, and deep learning and speech analysis software identify the emotional state. Specifically, it extracts facial feature points and generates emotion labels based on them. The output is detailed information about the user's emotional state.

[0561] Step 6:

[0562] Based on the analysis results described above, the server compiles suggestions for improving the materials, optimizing the scripts, and providing feedback based on sentiment recognition into a single report. The input consists of the individual analysis results, which are then integrated to generate a report ready for the user. Specifically, the report generation flow clearly summarizes each piece of information. The output is a feedback report.

[0563] Step 7:

[0564] The terminal displays feedback reports received from the server to the user. The input is the feedback report, which is displayed in a way that is easy for the user to understand. Specifically, the terminal displays the report on its screen and provides the user with ways to use it to improve materials and scripts. The output of this step is useful feedback information for the user.

[0565] (Application Example 2)

[0566] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0567] In situations where the goal is to improve the quality of customer service, it is essential for staff to accurately understand customer emotions and provide the most appropriate response in each situation. However, there is a lack of suitable means to analyze customer emotions in real time and make improvement suggestions accordingly, making it difficult for staff to efficiently meet customer needs. Technical support is needed to solve this problem.

[0568] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0569] In this invention, the server includes means for analyzing information data and generating visual improvement suggestions, means for analyzing data scripts and suggesting optimized representation methods, and emotion recognition means for analyzing emotion data and providing individualized advice. This enables store employees to understand customer emotions in real time and provide more effective customer service.

[0570] "Information data" refers to all forms of data collected from users, including text, images, and audio.

[0571] "Visual improvement suggestions" refer to providing specific suggestions for improvements to the layout, design, and color scheme of a document.

[0572] A "data script" refers to document data containing the content of text used in presentations or explanations.

[0573] "Optimized representation methods" refer to proposed improvements to grammar and expression to make data script representations more efficient and effective.

[0574] "Emotional data" refers to information about a user's emotional state obtained by analyzing their facial expressions and tone of voice.

[0575] "Emotion recognition means" refers to technical methods or devices for analyzing collected emotion data and identifying the user's emotions.

[0576] "Individualized advice" refers to providing appropriate guidance and feedback to specific users based on the information collected.

[0577] The system for implementing this invention mainly consists of a terminal and a server. The user uploads information data using the terminal, and the server collects the data necessary for analysis.

[0578] First, the device uses its camera and microphone to acquire information data. This information data includes image data capturing the customer's facial expressions and audio data recording their voice tone. This data is temporarily stored on the device, but is then sent to a server.

[0579] The server performs several information processing steps to analyze the received data. Image data is analyzed based on visual metrics to generate visual improvement suggestions. Next, the data script is analyzed using natural language processing techniques. Here, grammatical appropriateness and clarity of expression are evaluated, and improvement suggestions for more effective communication are generated.

[0580] Furthermore, the server includes emotion recognition capabilities to analyze emotional data. For voice analysis, it uses tools such as "IBM Watson Tone Analyzer," and for facial expression analysis, it can use tools such as "Microsoft Azure Face API." Based on these results, personalized advice tailored to the user's psychological state is generated and sent back to the terminal.

[0581] A concrete example of this system is customer service support in retail stores. When a store employee interacts with a customer, they can receive service improvement suggestions based on the customer's facial expressions and tone of voice through information displayed on smart glasses. In this way, employees can respond flexibly to customers in real time, leading to improved service quality.

[0582] Using a generative AI model, the server dynamically generates suggested customer service dialogue using the following example prompt: "Suggest improvements to the customer service dialogue to provide when a customer looks anxious."

[0583] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0584] Step 1:

[0585] The device uses its camera and microphone to collect user information data. This data includes image data capturing the customer's facial expressions and audio data recording their voice tone. The collected data is temporarily stored on the device. This image and audio data, as input, is then used to prepare for the next analysis step.

[0586] Step 2:

[0587] Information data is sent from the terminal to the server. Image data is analyzed using tools such as "Microsoft Azure Face API" to recognize emotions from facial expressions. Audio data is analyzed using tools such as "IBM Watson Tone Analyzer" to identify voice tone and emotion. By analyzing the input image and audio data, metadata indicating the user's emotions is output.

[0588] Step 3:

[0589] The server evaluates the user's emotional state based on the analysis results of image and audio data, and generates personalized advice tailored to the user's psychological state and emotional changes. Using a generative AI model, it generates responses based on prompt sentences. For example, it takes a prompt sentence such as "Suggest improvements to the customer service dialogue to provide when a customer looks anxious" as input and outputs specific improvement suggestions.

[0590] Step 4:

[0591] The advice and improvement suggestions generated by the server are sent back to the terminal. The store staff receive this information in real time through the smart glasses display. The suggestions aim to improve service based on customer emotions, providing guidance, for example, on how to conduct conversations that make customers feel at ease. This step visually displays the analysis results and suggested data.

[0592] Step 5:

[0593] Based on the improvement suggestions received, users adjust their customer service methods in real time to provide more effective service to customers. They observe customer feedback and operate the terminal as needed to receive further suggestions. In this process, they receive feedback as input and prepare to smoothly proceed to the next step.

[0594] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0595] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0596] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0597] [Fourth Embodiment]

[0598] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0599] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0600] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0601] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0602] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0603] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0604] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0605] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0606] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0607] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0608] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0609] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0610] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0611] This invention relates to an information processing system for engineers to efficiently improve the design and content of presentation materials and optimize the effective expression of presentation scripts. This system takes user-created presentation material files and scripts as input, analyzes them on the server side, generates improvement suggestions, and provides them to the user.

[0612] First, the user uploads presentation materials and a presentation script to the system using their device. The materials refer to digital files, such as slides or documents. These files are then sent to the server.

[0613] Next, the server analyzes the document files. The analysis process evaluates factors such as slide layout, font and color palette consistency, and the amount of text information. This analysis generates specific suggestions for improving the visual impression of the document.

[0614] Simultaneously, the server analyzes the presentation script. This analysis uses natural language processing techniques to evaluate grammar, clarity, and tone. Suggestions for sentence simplification and keyword emphasis are generated as needed.

[0615] The server sends suggestions for improving the generated materials and optimizations to the terminal, providing feedback to the user. The user can then revise the materials and script based on this feedback. Furthermore, the user can practice their presentation while receiving real-time feedback on their terminal. This practice support feature allows the user to receive immediate evaluations of their speaking style, speed, and intonation during the presentation.

[0616] In this way, the present invention enables users to improve their skills in effectively communicating specialized knowledge to others. It contributes to the efficiency and quality improvement of presentation preparation.

[0617] The following describes the processing flow.

[0618] Step 1:

[0619] The user uses a terminal to upload presentation materials and presentation scripts to the system. The terminal temporarily stores these files as input data.

[0620] Step 2:

[0621] The terminal sends the saved data files to the server. The server receives the data files and begins analyzing the content.

[0622] Step 3:

[0623] The server analyzes the structure of the document files and extracts the slide layout, fonts, and colors used. Based on this information, it generates visual improvement suggestions, such as adjustments to the color scheme or font size.

[0624] Step 4:

[0625] The terminal sends the saved presentation script to the server. The server receives the script and uses NLP (Natural Language Processing) technology to analyze the grammar and the effectiveness of the expressions.

[0626] Step 5:

[0627] Based on the script analysis results, the server generates script optimization suggestions, such as clarifying sentences and highlighting key points. For example, it may suggest simplifying complex sentences and emphasizing important keywords.

[0628] Step 6:

[0629] The server sends back suggestions for improving the generated materials and optimization suggestions for the script to the terminal. The terminal then displays this feedback to the user.

[0630] Step 7:

[0631] Users can review the feedback presented through their devices and revise their materials and scripts. This allows users to improve the quality of their presentations.

[0632] Step 8:

[0633] The user practices their presentation using a device. During this practice, the device evaluates the user's speaking style, speed, and intonation in real time and provides feedback.

[0634] Step 9:

[0635] Users can receive real-time feedback to further refine their presentation skills.

[0636] (Example 1)

[0637] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0638] Conventional presentation creation support systems require significant time and expertise to design and optimize the content of materials, and optimizing the effective expression of scripts is particularly difficult. This makes it challenging for users to receive immediate feedback and prepare effectively. Furthermore, there is a lack of concrete suggestions for improving presentation effectiveness, limiting users' means of obtaining specific guidance for self-improvement.

[0639] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0640] In this invention, the server includes information processing means for analyzing data and generating visual improvement suggestions, information processing means for analyzing presentation scripts and suggesting optimized expressions, exercise support means for providing immediate feedback to the user, and means for utilizing a generative model to enhance the effectiveness of the presentation. This enables users to efficiently create high-quality presentation materials, optimize the expression of their presentation scripts, and improve their presentation skills through real-time feedback, even without specialized knowledge.

[0641] "Document data" refers to digital files containing information in the form of slides or documents used in presentations.

[0642] "Information processing means" refers to technical processes and devices used to analyze data and perform improvements or optimizations in accordance with specific purposes.

[0643] A "presentation script" is a document containing spoken language used during a presentation, and is a script used to effectively convey the content of the presentation.

[0644] "Practice support tools" are features that provide real-time feedback to users when they practice their presentations, and support their preparation.

[0645] A "generative model" is an algorithm or system that automatically generates suggestions for improvements or optimizations tailored to a specific purpose.

[0646] A "visual improvement suggestion" refers to proposed changes to presentation materials to achieve a more effective and appealing appearance.

[0647] "Natural language processing tools" are automated processing technologies used to analyze documents such as presentation scripts and evaluate their grammar and clarity of content.

[0648] This invention is an information processing system for efficiently optimizing a user's presentation materials and presentation scripts. The user uploads presentation material files and presentation scripts to the system using a terminal. The material files are digital data in slide or document format and are transmitted to the server.

[0649] The server uses specialized software to analyze the received document data. At this stage, a design analysis engine evaluates the consistency of the slide layout, fonts, and color palette. Image recognition technology is also used to determine the balance of visual elements. For example, if the placement of images and text is not effective, it generates suggestions for improvement.

[0650] Next, the server analyzes the presentation script using natural language processing (NLTK) techniques. This analysis utilizes open-source NLTK libraries (e.g., spaCy or NLTK). It evaluates grammar, tone, and clarity, and generates suggestions to shorten sentences or emphasize keywords as needed.

[0651] Users can receive feedback from the server on their devices and revise their materials and scripts. They can also practice presentations in an environment that provides real-time feedback. This allows them to receive instant evaluations of their speaking style, speed, intonation, and other aspects, enabling them to improve their skills.

[0652] As a concrete example, here are some prompt statements that can be passed to a generative AI model: "Please suggest improvements to the design of the presentation materials. The current slides lack consistency." "Please tell me about grammatical improvements to the presentation script and ways to express it more effectively." This allows the user to obtain specific guidance for improvement.

[0653] In this way, the system helps users efficiently prepare for presentations and deliver high-quality presentations.

[0654] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0655] Step 1:

[0656] Users use a terminal to upload presentation materials and presentation scripts to the system. Input files include slide files such as Microsoft PowerPoint and script files in Word format. These files are sent to the server in digital format.

[0657] Step 2:

[0658] The server begins design analysis on the received document data. The input is the document file uploaded in Step 1. The server uses its analysis engine to verify the slide layout, fonts, and consistent color palette. As part of the data processing, it analyzes the element position and style of each slide and extracts visually appealing improvement suggestions. As output, a list of improvement suggestions is generated.

[0659] Step 3:

[0660] The server analyzes the presentation script. The input is the script file uploaded in Step 1. Natural language processing techniques are used to evaluate grammar, tone, and clarity. Data calculations use open-source libraries to simplify sentences and extract important keywords. The output is a list of script improvement suggestions and optimization proposals.

[0661] Step 4:

[0662] The server sends suggestions for improving the document and optimizing the script to the terminal. The input is the list of suggestions generated in steps 2 and 3. As output, this feedback is provided on the terminal. The terminal immediately displays it to the user, allowing the user to modify the document or script.

[0663] Step 5:

[0664] Users operate a device and practice their presentations while receiving real-time feedback. The input is feedback from a server. The device analyzes the user's voice, speaking pace, intonation, etc., and provides immediate feedback. Based on this feedback, users can adjust and improve their presentation skills.

[0665] (Application Example 1)

[0666] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0667] When giving a presentation, it is necessary to immediately improve the visual design of the materials and the expression of the script, and to flexibly change the content of the materials in response to the audience's reactions. However, with the current system, it is difficult to perform these tasks effectively and quickly, so reducing the burden on the speaker and improving the quality of the presentation are challenges.

[0668] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0669] In this invention, the server includes means for analyzing document files and generating visual improvement suggestions, means for analyzing presentation scripts and suggesting optimized presentation methods, and means for dynamically modifying the document content based on observer reactions. This allows the design and content of the document to be optimized in real time during the presentation, enabling the speaker to deliver a flexible presentation in response to observer reactions.

[0670] "Information processing means for analyzing document files and generating visual improvement suggestions" refers to a device that evaluates the layout, font, consistency, etc., of input documents and generates specific suggestions for achieving visually superior presentations.

[0671] "Information processing means for analyzing presentation scripts and proposing optimized expression methods" refers to a device that analyzes presentation scripts using natural language processing technology and generates suggestions for improving grammar, clarity, and tone.

[0672] A "practice support device that provides real-time feedback to users" is a device that provides immediate evaluation of a user's speaking style, speed, and intonation while they are giving a presentation, and points out areas for improvement.

[0673] "Means for dynamically modifying the content of materials based on observer reactions" refers to a device that acquires data on the observer's facial expressions and reactions, and then changes the order and design of the presentation content based on that data.

[0674] The system implementing this invention consists of a server that performs analysis using document files and presentation scripts as input. The server first receives the document files and scripts in digital format from the user. The document files are in slide or document format, and the system analyzes them to generate visual improvement suggestions.

[0675] The server employs existing presentation tools and custom-developed algorithms to evaluate the layout, fonts, consistency, and information density of the materials. Next, the server analyzes the presentation script using natural language processing software to provide suggestions for grammar, clarity, and tone improvement. Typical software for this includes open-source natural language processing libraries.

[0676] On the user's device, a real-time feedback function is available to practice presentations. This feedback includes evaluations of speaking style, speed, and intonation, allowing the user to adjust their speaking style accordingly.

[0677] Furthermore, the server uses software to analyze observer reactions, collecting data such as observer facial expressions and dynamically modifying the content of the materials. This allows for flexible changes to the order and design of materials during the presentation, keeping the observer engaged.

[0678] For example, when giving a presentation at a large academic conference, even if it's difficult to gauge the audience's reactions, this system allows for real-time feedback and flexible adjustments to the presentation materials. Therefore, effective presentations are possible even in situations requiring immediate responses.

[0679] An example of a prompt using a generative AI model is: "Suggest a method to evaluate the visual design and script content of a presentation and generate improvement suggestions in real time. Refine the suggestions using audience reaction data." Using this prompt makes it possible to provide more specific feedback.

[0680] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0681] Step 1:

[0682] Users upload presentation materials and presentation scripts to the system using their terminals. The input consists of digital materials and scripts, which are sent to the server. The server receives and stores these files.

[0683] Step 2:

[0684] The server analyzes the received document files. The input is the document files, and the output is visual improvement suggestions. The server analyzes the slide layout, fonts, consistency, and amount of text information, and generates visual design improvement suggestions based on this analysis. In doing so, it uses presentation tool APIs and proprietary algorithms.

[0685] Step 3:

[0686] The server analyzes the presentation script. The input is the script, and the output is suggestions for improving the presentation. The server uses natural language processing techniques to evaluate grammar, clarity, and tone, and generates optimization suggestions. Specifically, it uses a natural language processing library to analyze the script and suggests sentence simplification and keyword emphasis.

[0687] Step 4:

[0688] The server sends the generated improvement suggestions to the terminal. The terminal displays them and provides feedback to the user. This allows the user to modify the documents or scripts. The input is the improvement suggestions, and the output is the feedback displayed on the user's screen.

[0689] Step 5:

[0690] Users practice their presentations while receiving real-time feedback on the device. Input is the user's presentation voice and speed, while output is immediate evaluation. The device uses a microphone to collect audio and provides feedback on speaking style, speed, and intonation. Voice analysis software is used in this process.

[0691] Step 6:

[0692] The server dynamically modifies the content of the materials based on the observer's reactions. The input is the observer's facial expressions and other reaction data, and the output is the modified material suggestion. The server uses visual data analysis software to analyze the observer's reactions and generate suggestions for adjusting the materials.

[0693] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0694] This invention relates to an information processing system that analyzes and improves presentation materials and presentation scripts, and further combines them with an emotion engine that recognizes user emotions. This system takes user-provided material files and presentation scripts as input, collects data for emotion recognition, and generates and provides improvement suggestions to the user based on this information.

[0695] First, the user uploads presentation materials, a presentation script, and facial image and audio data for emotion recognition to the system using their device. The device temporarily stores this data and prepares to send it to the server.

[0696] Next, the server analyzes the document files. This analysis process evaluates the consistency of the slide layout, design elements, fonts, and color palette, and generates visual improvement suggestions.

[0697] The server further analyzes the presentation script using natural language processing techniques. It evaluates grammar, clarity, and tone, and generates suggestions for script optimization, such as sentence simplification and keyword emphasis, as needed.

[0698] In addition, the emotion engine installed on the server recognizes the user's emotions in real time. It extracts features from facial imagery and identifies emotional states such as intonation and tension from audio data. Based on this information, it understands the user's psychological state during presentations and provides feedback and support appropriate to that emotional state.

[0699] The server sends back suggestions for improving the generated materials, optimization suggestions for the scripts, and feedback based on sentiment recognition to the terminal. The terminal presents this information to the user, encouraging them to revise the materials and scripts.

[0700] Users practice their presentations based on feedback provided on their devices. During these practice sessions, real-time feedback provides personalized advice tailored to the user's emotional changes, enabling efficient skill improvement based on their own emotional state.

[0701] This invention enables users to improve both the technical and psychological aspects of their presentations, thereby achieving more effective communication.

[0702] The following describes the processing flow.

[0703] Step 1:

[0704] Users upload presentation files, presentation scripts, facial expression images, and audio data to the system using their devices. This provides the necessary data for analysis.

[0705] Step 2:

[0706] The terminal temporarily stores the user's input data and prepares to send it to the server.

[0707] Step 3:

[0708] The terminal sends data files, scripts, facial expression images, and audio data to the server. The server then assigns this data to the respective analysis modules.

[0709] Step 4:

[0710] The server analyzes the document files. This analysis checks the slide structure, fonts, and consistency of the color palette, among other things. Based on this, the server generates visual improvement suggestions.

[0711] Step 5:

[0712] The server analyzes the presentation script. Using natural language processing technology, it evaluates grammatical errors and sentence clarity, and generates suggestions for effective script improvements.

[0713] Step 6:

[0714] The server processes facial image data and audio data. It identifies emotions from facial image data and analyzes intonation and tone of voice from audio data to determine the user's emotional state.

[0715] Step 7:

[0716] The server integrates the analysis results and generates suggestions for improving materials, optimizing scripts, and providing feedback based on the user's emotional state. For example, if the user is feeling stressed, it will generate advice to help them relax.

[0717] Step 8:

[0718] The server sends the generated feedback and suggestions back to the terminal. The terminal presents this to the user and supports the user in modifying the materials and scripts.

[0719] Step 9:

[0720] The user practices their presentation using feedback displayed on the device. The device monitors the user's progress in real time and provides feedback that responds to changes in their emotions.

[0721] Step 10:

[0722] Users incorporate feedback from the system to improve materials and scripts, and comprehensively enhance their presentation skills and emotional state.

[0723] (Example 2)

[0724] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0725] In modern presentations, in addition to visual design and script clarity, the presenter's emotions and psychological state are also crucial elements. However, there is no integrated system that efficiently improves these elements and enhances the overall quality of a presentation. This invention aims to provide a system that comprehensively supports these elements, enabling users to more effectively improve their presentation skills.

[0726] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0727] In this invention, the server includes information processing means for analyzing data files and generating visual improvement suggestions, information processing means for analyzing presentation scripts and suggesting optimized presentation methods, and emotion recognition means for recognizing a person's emotions and providing feedback based on those emotions. This enables improvement in the quality of presentations and self-improvement by the presenter.

[0728] A "document file" refers to digital data that includes slides and their design elements used in a presentation.

[0729] "Information processing means" refers to a function consisting of hardware and software devices for analyzing data provided by the user and generating suggestions based on the results.

[0730] A "presentation script" is text data that describes the content to be spoken in a presentation.

[0731] "Visual improvement suggestions" are specific recommendations for improving the consistency of the design and layout of document files.

[0732] "Optimized expression methods" are proposals for achieving grammatically correct and clear expression in presentation scripts.

[0733] "Emotion recognition means" refers to techniques and methods for analyzing a person's emotional state, which involves recognition using facial expression and voice data.

[0734] A "practice support tool that provides real-time feedback" is a system function that provides users with immediate advice and suggestions for improvement while they are practicing their presentations.

[0735] This invention relates to an information processing system for improving the quality of presentation materials and scripts. This system uses material files provided by the user, presentation scripts, facial expression images necessary for emotion recognition, and audio data.

[0736] The user uploads this data to the system using a terminal. The terminal temporarily stores the data and prepares it for transmission to the server. This process ensures that the data is sent to the server in the correct format.

[0737] The server utilizes algorithms to evaluate visual elements in order to analyze the document files. Specifically, it checks for consistency in design and layout and generates suggestions for improvements to fonts and color palettes. This involves using software for evaluating slide design.

[0738] Furthermore, the server analyzes the presentation script using natural language processing technology. This technology is essential to ensure grammatical accuracy and clarity, and enables script optimization. The natural language processing engine then suggests the most appropriate expression for the user.

[0739] Furthermore, the emotion recognition engine on the server analyzes facial image and audio data to understand the user's emotional state. This allows for real-time feedback based on the user's psychological state during presentations. Specifically, it integrates deep learning and audio analysis software to identify the user's emotions and generate appropriate advice.

[0740] The device receives feedback from the server and presents it to the user. This allows the user to learn specific areas for improvement in their materials and scripts, and effectively improve their presentation skills through practice.

[0741] For example, if a user preparing a new product launch uses this system, the consistency of the document design will be evaluated, and improvements to font size will be suggested. Furthermore, for complex technical explanations in the script, more concise language will be recommended. In addition, the user's level of tension will be detected through emotion recognition, and advice on relaxation techniques will be provided.

[0742] An example of a prompt would be: "Here are my presentation materials and script. Please give me suggestions for improving the visual design, clarifying the script, and advice tailored to my emotional state."

[0743] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0744] Step 1:

[0745] The user uploads presentation files, presentation scripts, facial expression images, and audio data using the device. The input data consists of these files, which the device formats appropriately and temporarily stores. Specifically, the user selects the necessary files from the device's file selection screen and clicks the upload button.

[0746] Step 2:

[0747] The terminal prepares to send the uploaded data to the server. The data is temporarily stored and converted to a format that the server can process. Specifically, this involves actions such as compressing image and audio data and formatting filenames. The output of this step is data ready to be transferred to the server.

[0748] Step 3:

[0749] The server analyzes presentation files received from the terminal and generates visual improvement suggestions. The input is the presentation file, and the algorithm evaluates the slide layout and design elements. Specifically, design evaluation software is used to check for consistency in font size and color palette, and to list areas for improvement. The output of this step is a detailed list of visual improvement suggestions.

[0750] Step 4:

[0751] The server analyzes the presentation script using natural language processing techniques and proposes an optimized presentation method. The input is the presentation script, which is then analyzed for grammatical structure and clarity. Specifically, the natural language processing engine detects grammatical errors and simplifies the text. The output of this step is the optimized script proposal.

[0752] Step 5:

[0753] The server uses an emotion recognition engine to recognize the user's emotions in real time from facial image and audio data. The input consists of facial image and audio data, and deep learning and speech analysis software identify the emotional state. Specifically, it extracts facial feature points and generates emotion labels based on them. The output is detailed information about the user's emotional state.

[0754] Step 6:

[0755] Based on the analysis results described above, the server compiles suggestions for improving the materials, optimizing the scripts, and providing feedback based on sentiment recognition into a single report. The input consists of the individual analysis results, which are then integrated to generate a report ready for the user. Specifically, the report generation flow clearly summarizes each piece of information. The output is a feedback report.

[0756] Step 7:

[0757] The terminal displays feedback reports received from the server to the user. The input is the feedback report, which is displayed in a way that is easy for the user to understand. Specifically, the terminal displays the report on its screen and provides the user with ways to use it to improve materials and scripts. The output of this step is useful feedback information for the user.

[0758] (Application Example 2)

[0759] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0760] In situations where the goal is to improve the quality of customer service, it is essential for staff to accurately understand customer emotions and provide the most appropriate response in each situation. However, there is a lack of suitable means to analyze customer emotions in real time and make improvement suggestions accordingly, making it difficult for staff to efficiently meet customer needs. Technical support is needed to solve this problem.

[0761] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0762] In this invention, the server includes means for analyzing information data and generating visual improvement suggestions, means for analyzing data scripts and suggesting optimized representation methods, and emotion recognition means for analyzing emotion data and providing individualized advice. This enables store employees to understand customer emotions in real time and provide more effective customer service.

[0763] "Information data" refers to all forms of data collected from users, including text, images, and audio.

[0764] "Visual improvement suggestions" refer to providing specific suggestions for improvements to the layout, design, and color scheme of a document.

[0765] A "data script" refers to document data containing the content of text used in presentations or explanations.

[0766] "Optimized representation methods" refer to proposed improvements to grammar and expression to make data script representations more efficient and effective.

[0767] "Emotional data" refers to information about a user's emotional state obtained by analyzing their facial expressions and tone of voice.

[0768] "Emotion recognition means" refers to technical methods or devices for analyzing collected emotion data and identifying the user's emotions.

[0769] "Individualized advice" refers to providing appropriate guidance and feedback to specific users based on the information collected.

[0770] The system for implementing this invention mainly consists of a terminal and a server. The user uploads information data using the terminal, and the server collects the data necessary for analysis.

[0771] First, the device uses its camera and microphone to acquire information data. This information data includes image data capturing the customer's facial expressions and audio data recording their voice tone. This data is temporarily stored on the device, but is then sent to a server.

[0772] The server performs several information processing steps to analyze the received data. Image data is analyzed based on visual metrics to generate visual improvement suggestions. Next, the data script is analyzed using natural language processing techniques. Here, grammatical appropriateness and clarity of expression are evaluated, and improvement suggestions for more effective communication are generated.

[0773] Furthermore, the server includes emotion recognition capabilities to analyze emotional data. For voice analysis, it uses tools such as "IBM Watson Tone Analyzer," and for facial expression analysis, it can use tools such as "Microsoft Azure Face API." Based on these results, personalized advice tailored to the user's psychological state is generated and sent back to the terminal.

[0774] A concrete example of this system is customer service support in retail stores. When a store employee interacts with a customer, they can receive service improvement suggestions based on the customer's facial expressions and tone of voice through information displayed on smart glasses. In this way, employees can respond flexibly to customers in real time, leading to improved service quality.

[0775] Using a generative AI model, the server dynamically generates suggested customer service dialogue using the following example prompt: "Suggest improvements to the customer service dialogue to provide when a customer looks anxious."

[0776] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0777] Step 1:

[0778] The device uses its camera and microphone to collect user information data. This data includes image data capturing the customer's facial expressions and audio data recording their voice tone. The collected data is temporarily stored on the device. This image and audio data, as input, is then used to prepare for the next analysis step.

[0779] Step 2:

[0780] Information data is sent from the terminal to the server. Image data is analyzed using tools such as "Microsoft Azure Face API" to recognize emotions from facial expressions. Audio data is analyzed using tools such as "IBM Watson Tone Analyzer" to identify voice tone and emotion. By analyzing the input image and audio data, metadata indicating the user's emotions is output.

[0781] Step 3:

[0782] The server evaluates the user's emotional state based on the analysis results of image and audio data, and generates personalized advice tailored to the user's psychological state and emotional changes. Using a generative AI model, it generates responses based on prompt sentences. For example, it takes a prompt sentence such as "Suggest improvements to the customer service dialogue to provide when a customer looks anxious" as input and outputs specific improvement suggestions.

[0783] Step 4:

[0784] The advice and improvement suggestions generated by the server are sent back to the terminal. The store staff receive this information in real time through the smart glasses display. The suggestions aim to improve service based on customer emotions, providing guidance, for example, on how to conduct conversations that make customers feel at ease. This step visually displays the analysis results and suggested data.

[0785] Step 5:

[0786] Based on the improvement suggestions received, users adjust their customer service methods in real time to provide more effective service to customers. They observe customer feedback and operate the terminal as needed to receive further suggestions. In this process, they receive feedback as input and prepare to smoothly proceed to the next step.

[0787] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0788] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0789] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0790] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0791] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0792] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0793] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0794] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0795] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0796] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0797] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0798] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0799] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0800] 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.

[0801] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0802] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0803] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0804] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0805] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0806] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0807] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0808] The following is further disclosed regarding the embodiments described above.

[0809] (Claim 1)

[0810] An information processing means that analyzes document files and generates visual improvement suggestions,

[0811] An information processing means that analyzes the presentation script and proposes an optimized method of expression,

[0812] A practice support method that provides real-time feedback to the user,

[0813] A system that includes this.

[0814] (Claim 2)

[0815] The system according to claim 1, comprising information processing means for extracting and evaluating the structure and design of a data file.

[0816] (Claim 3)

[0817] The system according to claim 1, comprising a natural language processing means for evaluating the grammar and clarity of a presentation script.

[0818] "Example 1"

[0819] (Claim 1)

[0820] An information processing means that analyzes data and generates visual improvement suggestions,

[0821] An information processing means that analyzes a presentation script and proposes an optimized expression,

[0822] A training support tool that provides immediate feedback to users,

[0823] A system that includes means of utilizing generative models to enhance the effectiveness of presentations.

[0824] (Claim 2)

[0825] The system according to claim 1, comprising information processing means for extracting and evaluating the structure and design of data.

[0826] (Claim 3)

[0827] The system according to claim 1, comprising a natural language processing means for evaluating the grammar and clarity of a presentation script.

[0828] "Application Example 1"

[0829] (Claim 1)

[0830] An information processing means that analyzes document files and generates visual improvement suggestions,

[0831] An information processing means that analyzes the presentation script and proposes an optimized method of expression,

[0832] A training support system that provides real-time feedback to users,

[0833] A means of dynamically modifying the content of the materials based on the observer's reactions,

[0834] A system that includes this.

[0835] (Claim 2)

[0836] The system according to claim 1, comprising information processing means for extracting and evaluating the structure and design of a data file.

[0837] (Claim 3)

[0838] The system according to claim 1, comprising a natural language processing means for evaluating the grammar and clarity of a presentation script.

[0839] "Example 2 of combining an emotion engine"

[0840] (Claim 1)

[0841] An information processing means that analyzes document files and generates visual improvement suggestions,

[0842] An information processing means that analyzes the presentation script and proposes an optimized method of expression,

[0843] An emotion recognition means that recognizes a person's emotions and provides feedback based on that state,

[0844] A practice support method that provides real-time feedback to the user,

[0845] A system that includes this.

[0846] (Claim 2)

[0847] The system according to claim 1, comprising information processing means for extracting and evaluating the structure and design of a data file.

[0848] (Claim 3)

[0849] The system according to claim 1, comprising a natural language processing means for evaluating the grammar and clarity of a presentation script.

[0850] "Application example 2 when combining with an emotional engine"

[0851] (Claim 1)

[0852] An information processing means that analyzes information data and generates visual improvement suggestions,

[0853] An information processing means that analyzes data scripts and proposes an optimized representation method,

[0854] A practice support method that provides real-time feedback to the user,

[0855] An emotion recognition tool that analyzes emotional data and provides personalized advice,

[0856] A system that includes this.

[0857] (Claim 2)

[0858] The system according to claim 1, comprising information processing means for extracting and evaluating the structure and format of information data.

[0859] (Claim 3)

[0860] The system according to claim 1, comprising a language analysis means for evaluating the grammar and clarity of a data script. [Explanation of Symbols]

[0861] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. An information processing means that analyzes document files and generates visual improvement suggestions, An information processing means that analyzes the presentation script and proposes an optimized method of expression, A practice support method that provides real-time feedback to the user, A system that includes this.

2. The system according to claim 1, comprising information processing means for extracting and evaluating the structure and design of a data file.

3. The system according to claim 1, comprising a natural language processing means for evaluating the grammar and clarity of a presentation script.

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