Calligraphy digital teaching system and method based on artificial intelligence

Abstract

The invention relates to the technical field of artificial intelligence, and discloses a calligraphy digital teaching system and method based on artificial intelligence, and the system comprises a user input module, an image processing module, an artificial intelligence evaluation module, a feedback and guidance module, a learning progress tracking module, a cloud data storage and analysis module, and a virtual calligraphy teacher module. According to the invention, the system can automatically adjust the teaching content and provide customized practice plans and suggestions according to the progress and weakness of the students by analyzing the writing conditions of the students in real time, so that each student can learn under the rhythm which is most suitable for the student, and the system can improve the learning efficiency through intelligent evaluation and feedback. Errors can be immediately indicated and correction suggestions can be provided when students write, the situation that the students frequently practice repeatedly in wrong habits in traditional calligraphy teaching is avoided, and the students are helped to improve efficiently.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular, to a digital calligraphy teaching system and method based on artificial intelligence. Background Art

[0002] With the rapid development of artificial intelligence technology, digital education has been widely applied in various fields, and calligraphy teaching has gradually entered a new era of intelligence and personalization. Although traditional calligraphy teaching has a profound cultural heritage, due to limited teacher resources and relatively fixed teaching content and methods, many students feel confused or progress slowly during the learning process. Especially in improving calligraphy skills, apprentices often need to go through long-term imitation and repeated practice, and it is difficult to obtain immediate feedback and precise guidance.

[0003] To overcome these deficiencies, a digital calligraphy teaching system based on artificial intelligence has emerged. Through image recognition technology, the system can analyze each stroke written by the learner in real time and compare it with a standard calligraphy template to provide feedback in a timely manner. With the help of machine learning and deep learning algorithms, the system can not only accurately identify glyphs and strokes, but also continuously optimize teaching content through the learning data of users and generate personalized learning paths. In addition, the system can simulate the writing styles of traditional calligraphy masters and provide dynamic writing demonstrations to help learners better understand and master calligraphy skills.

[0004] This intelligent calligraphy teaching mode not only improves learning efficiency, solves the bottleneck problems in traditional teaching methods, but also enables calligraphy art to be popularized on a wider scale, allowing more people to have the opportunity to come into contact with this traditional art form. By combining modern technology with traditional culture, the inheritance and innovation of calligraphy are further promoted. In addition, with the continuous update and upgrade of the system technology, it will provide more personalized feedback and customized learning plans for learners, promote the continuous progress of calligraphy art, further enhance cultural confidence, and make it glow with new vitality globally.

[0005] Therefore, we propose a digital calligraphy teaching system and method based on artificial intelligence. Summary of the Invention

[0006] The present invention mainly solves the technical problems existing in the above-mentioned prior art, and provides a digital calligraphy teaching system and method based on artificial intelligence.

[0007] To achieve the above object, the present invention adopts the following technical solutions. A digital calligraphy teaching system based on artificial intelligence includes a user input module, an image processing module, an artificial intelligence evaluation module, a feedback and guidance module, a learning progress tracking module, a cloud data storage and analysis module, and a virtual calligraphy teacher module.

[0008] Preferably, the user input module is used to receive the user's calligraphy input and supports multiple input methods, including a graphics tablet, a touch screen, speech recognition, etc.

[0009] Preferably, the image processing module includes image denoising, stroke extraction, glyph recognition, etc.

[0010] Preferably, the artificial intelligence evaluation module comprehensively evaluates the user's calligraphy based on deep learning and machine learning models. The evaluation metrics include stroke order, stroke shape, stroke strength, glyph structure, etc.

[0011] Preferably, the feedback and guidance module includes real-time feedback, dynamic demonstration, and voice and text guidance.

[0012] Preferably, the learning progress tracking module is responsible for recording the user's learning progress and tracking the user's practice frequency, improvement of calligraphy level, etc.

[0013] Preferably, the cloud data storage and analysis module stores the user's learning data in the cloud, and the system will conduct trend analysis on the user's calligraphy learning through big data analysis.

[0014] Preferably, the virtual calligraphy teacher module simulates a virtual calligraphy teacher through artificial intelligence algorithms, can interact with the user in real time, and provide personalized guidance.

[0015] A digital calligraphy teaching method based on artificial intelligence includes the following steps: S1: preliminary recognition and scoring; S2: intelligent feedback and correction; S3: personalized practice; S4: progress evaluation and optimization.

[0016] Preferably, preliminary recognition and scoring: including glyph recognition at the start of writing, stroke analysis and error marking, and dimensional scoring and comprehensive evaluation; intelligent feedback and correction: including detailed intelligent feedback, correction suggestions and demonstration presentations, and interactive correction and real-time demonstrations; personalized practice: including data-driven personalized adjustment, personalized practice for strengthening weak links, and formulation of an adaptive practice plan; progress evaluation and optimization: including periodic progress reports, data-based dynamic optimization, and maximization of learning effects.

[0017] The present invention provides a digital calligraphy teaching system and method based on artificial intelligence, having the following beneficial effects:

[0018] 1. For the digital calligraphy teaching system and method based on artificial intelligence, by analyzing the writing situation of students in real time, the system can automatically adjust the teaching content according to the progress and weaknesses of the students, provide customized practice plans and suggestions, so that each student can learn at the most suitable rhythm for themselves.

[0019] 2. The digital calligraphy teaching system and method based on artificial intelligence can, through intelligent evaluation and feedback, immediately point out mistakes and provide correction suggestions when students are writing, avoiding the situation in traditional calligraphy teaching where students often repeatedly practice with wrong habits and helping students improve efficiently.

[0020] 3. The digital calligraphy teaching system and method based on artificial intelligence can, by means of deep learning and machine vision technologies, accurately evaluate and annotate calligraphy strokes, glyphs, etc., reducing the time waste caused by lagging feedback in traditional teaching methods and enabling students to master calligraphy skills faster.

[0021] 4. The digital calligraphy teaching system and method based on artificial intelligence records and analyzes students' learning data, provides detailed learning reports and progress tracking for students, helps students clearly understand their progress in calligraphy learning, and can also provide valuable teaching references for teachers to optimize teaching strategies.

[0022] 5. The digital calligraphy teaching system and method based on artificial intelligence, through virtual calligraphy teachers and calligraphy demonstrations, not only provides modern technology assistance for students, but also can simulate the writing styles of traditional calligraphy masters, enhancing the cultural inheritance and innovation of calligraphy art and promoting the revival and popularization of this traditional art form in modern society. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only exemplary, and for those of ordinary skill in the art, without creative efforts, other implementation drawings can also be obtained based on the provided drawings.

[0024] The structures, ratios, sizes, etc. shown in this specification are only used to cooperate with the content disclosed in the specification for those familiar with this technology to understand and read, and are not used to limit the limiting conditions under which the present invention can be implemented. Therefore, they do not have technical substantive meanings. Any modification of the structure, change of the ratio relationship, or adjustment of the size, without affecting the effects that the present invention can produce and the purposes that can be achieved, should still fall within the scope covered by the technical content disclosed in the present invention.

[0025] Figure 1 It is a system block diagram of a digital calligraphy teaching system based on artificial intelligence;

[0026] Figure 2 It is a flowchart of a digital calligraphy teaching method based on artificial intelligence. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0027] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0028] Embodiment: An artificial intelligence-based digital calligraphy teaching system, as Figure 1 shown, includes a user input module, an image processing module, an artificial intelligence evaluation module, a feedback and guidance module, a learning progress tracking module, a cloud data storage and analysis module, and a virtual calligraphy teacher module;

[0029] Among them, the user input module is used to receive the user's calligraphy input and supports multiple input methods, including a writing tablet, a touch screen, voice recognition, etc. The specific operation process is as follows: Handwriting input: The user can input calligraphy content through a calligraphy-specific touch screen or an electronic pen tablet, and the strokes of each calligraphy character are recorded through pressure sensing or touch sensing; Voice input: The user can input text through the voice recognition function, and the system converts the voice into text and performs subsequent processing; Gesture recognition: Through the interaction between the user's gestures and the screen, the system can recognize the user's actions and record them in the database; Through these input methods, the user's calligraphy content can be accurately input into the system, providing data support for subsequent image processing and evaluation;

[0030] The image processing module is mainly responsible for image processing of the user's writing content, including image denoising, stroke extraction, glyph recognition, etc.; The specific steps are as follows: Image preprocessing: After the system receives the user's writing content, it first performs preprocessing of the image, including removing noise, enhancing contrast, adjusting brightness, etc., to facilitate subsequent recognition; Stroke extraction: The system uses image recognition algorithms, such as edge detection, Hough transform, etc., to extract each stroke in the writing content, and the stroke information includes the starting point, ending point, curvature, thickness, etc. of the stroke; Glyph matching: The system compares the extracted glyphs with the standard glyphs to determine the accuracy and standardization of the glyphs. If the glyphs are not standardized, the system will mark them for subsequent evaluation and feedback; Through efficient image processing, the system can accurately identify the user's writing situation and provide data support for the subsequent intelligent evaluation module;

[0031] The artificial intelligence evaluation module comprehensively evaluates the user's calligraphy based on deep learning and machine learning models. The evaluation metrics include stroke order, stroke shape, stroke strength, and glyph structure, etc. The specific process is as follows: Deep learning model training: The system is trained through a large number of calligraphy datasets, and deep learning algorithms such as convolutional neural networks (CNNs) are used to extract the features of calligraphy. These features include the rise, fall, turn, and connection of strokes, and the structure of glyphs. Evaluation criteria: The system scores each character according to the user's writing content. The scoring criteria mainly include the following aspects: Stroke order: Whether the strokes are written in the correct order. Stroke shape: Whether each stroke is standardized and matches the standard calligraphy font. Stroke strength: Whether the thickness and darkness of the strokes meet the specifications. Glyph structure: Whether the size and proportion of the glyphs are coordinated. During the evaluation process, the system will give the user a detailed score (for example, a full score of 100 points) based on real-time data and mark the non-standard parts;

[0032] The feedback and guidance module, based on the results of the artificial intelligence evaluation module, will immediately provide feedback to the user and give corresponding corrective suggestions. The specific steps are as follows: Real-time feedback: The evaluation results of each character written by the user will be displayed in real time. For example, the system will give prompts such as "incorrect stroke order" or "irregular glyph". Dynamic demonstration: When the user's glyph is not standardized, the system will show the correct writing process through dynamic demonstration. The user can improve their calligraphy by imitating the demonstration. Voice and text guidance: The virtual calligraphy teacher will provide detailed guidance to the user in the form of voice or text according to the evaluation results. For example, "The second stroke of this character should be a horizontal fold and hook. You can try to increase the strength in this part;

[0033] The learning progress tracking module is responsible for recording the user's learning progress and tracking the user's practice frequency, improvement of calligraphy level, etc. The specific steps are as follows: Learning time record: The system will record the time of each user practice and calculate the learning duration per week and per month. Progress analysis: The system evaluates the user's calligraphy progress through data analysis. According to the change of the scores evaluated by the system, the user can clearly see their progress trend. Personalized report: The system generates a learning report every once in a while. The report includes the user's score changes, progress, practice frequency, etc., to help the user better plan their learning;

[0034] The cloud data storage and analysis module saves the user's learning data in the cloud. The system will conduct trend analysis on the user's calligraphy learning through big data analysis. The specific process is as follows: Data storage: Information such as the user's calligraphy works, scoring data, and progress reports will be uploaded to the cloud server to ensure data security and accessibility; Data analysis: Based on the historical data stored in the cloud, the system will regularly provide personalized learning reports for the user. For example, "You have performed outstandingly in the 'cursive script' section, but your progress in the 'regular script' section is slow. We suggest that you increase the time for regular script practice."

[0035] The virtual calligraphy teacher module simulates a virtual calligraphy teacher through artificial intelligence algorithms and can interact with the user in real time to provide personalized guidance. The specific operations are as follows: Gesture recognition and speech recognition: The virtual calligraphy teacher uses gesture recognition technology to identify the user's writing problems and provides immediate corrective suggestions. Through speech recognition, the system can adjust the teaching content according to the user's feedback; Personalized guidance: The virtual calligraphy teacher will customize a personalized teaching plan based on the user's progress and learning needs. For difficult parts of learning, the system will repeatedly give prompts and demonstrations to help the user gradually improve.

[0036] A calligraphy digital teaching method based on artificial intelligence, as Figure 2 shown, includes the following steps:

[0037] S1: Preliminary recognition and scoring: including the glyph recognition at the start of writing, stroke analysis and error marking, and dimension scoring and comprehensive evaluation; The glyph recognition at the start of writing uses machine vision technology to real-time recognize the user's glyphs, compares the glyphs written by the user with the standard calligraphy glyphs, and automatically generates a preliminary score. The scoring dimensions include: Stroke standardization: Whether the writing meets the requirements of the standard strokes, Glyph symmetry: Whether the glyph is balanced and symmetrical, Line smoothness: Whether the line is smooth and natural; The stroke analysis and error marking analyze each stroke of each character one by one, identify the form, order, angle, etc. of the starting, running, and ending of each stroke. The standardization of each stroke will be marked separately, and combined with the standard glyph, the non-standard parts will be pointed out. The system visualizes the error parts, and the user can clearly see the improvement points. The scoring range is from 0 to 100 points, and a comprehensive score is given according to the actual performance of each dimension; The dimension scoring and comprehensive evaluation system comprehensively scores the three major dimensions of stroke standardization (40%), glyph symmetry (30%), and line smoothness (30%), and finally gives a total score. The scoring basis includes but is not limited to the symmetry of the glyph, the smoothness of the strokes, the thickness of the lines, the starting and ending of the strokes, etc., to ensure the comprehensiveness and objectivity of the scoring;

[0038] S2: Intelligent Feedback and Correction: including detailed intelligent feedback, correction suggestions and demonstration, and interactive correction and real-time demonstration; After analyzing the written content, the detailed intelligent feedback system provides detailed intelligent feedback. For example, the system will clearly point out that "the connection between the second and third strokes is not tight" or "the curvature of the stroke is too large". The feedback content is based on the details of the writing and specifically points out the errors of each stroke; The correction suggestion and demonstration system provides specific correction suggestions according to the type of error. For example, when the "stroke is too thin", it is recommended to thicken the stroke. The system will also provide a dynamic demonstration of the correct writing method. Users can observe the correct writing method in real time. Through animations and the trajectory demonstration of virtual pens, it helps users understand the gap between errors and correctness; The interactive correction and real-time demonstration system will adjust the demonstration method according to the user's feedback. If the user corrects, the system will automatically give positive feedback and prompt for continuous improvement. The response time of real-time correction demonstration and feedback is generally 3-5 seconds to ensure efficient interaction during the learning process;

[0039] S3: Personalized Practice: including data-driven personalized adjustment, personalized practice for strengthening weak links, and formulation of adaptive practice plans. Based on the historical data and scores of the user's writing, the data-driven personalized adjustment system will automatically adjust the difficulty of the practice to strengthen the user's weak links. If the user scores low in "glyph symmetry", the system will automatically recommend relevant symmetry practices, such as "left-right symmetry practice" or "symmetry practice of radicals"; The personalized practice system for strengthening weak links will recommend specific practice sets according to the dimensions where the user scores low (such as stroke standardization, glyph symmetry, etc.). For example, if the glyph fluency is poor, the system will arrange practices to increase coherence for the user. It is recommended to practice at least 5 times a week, and each practice time is about 30 minutes to ensure continuous progress; The adaptive practice plan formulation system adjusts the practice plan according to the user's learning progress and feedback, gradually increasing the difficulty and challenge of the practice. Users can arrange their weekly learning tasks according to the plan. The system will remind users to complete tasks on time and adjust the practice for the next stage according to the learning progress;

[0040] S4: Progress Evaluation and Optimization: This includes periodic progress reports, data-based dynamic optimization, and maximizing learning effects. The periodic progress report system automatically generates detailed progress reports, which contain detailed grade changes, room for improvement, learning suggestions, and specific improvement directions. Users can view their learning progress through an intuitive score curve graph to identify progress trends and problem areas. Data-based dynamic optimization adjusts the learning plan dynamically according to each user's learning data. For example, if it is found that the progress of improving a certain skill is slow, the system will increase the practice frequency or depth of this part, and vice versa, it will appropriately reduce the challenge difficulty. The system for maximizing learning effects regularly adjusts the practice suggestions in the progress report to ensure that the user's weak points are strengthened and not over-trained. For example, for users with relatively weak glyph symmetry, the system will continuously recommend practicing this skill, while for users with relatively strong stroke standardization, more attention will be paid to improvements in other dimensions.

[0041] The above has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art of this industry should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification only illustrates the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. An artificial intelligence-based digital calligraphy teaching system, characterized in that: It includes a user input module, an image processing module, an artificial intelligence evaluation module, a feedback and guidance module, a learning progress tracking module, a cloud data storage and analysis module, and a virtual calligraphy teacher module.

2. The digital calligraphy teaching system based on artificial intelligence according to claim 1, wherein: The user input module is used to receive the user's calligraphy input and supports multiple input methods, including a graphics tablet, a touch screen, voice recognition, etc.

3. The digital calligraphy teaching system based on artificial intelligence according to claim 1, characterized in that: The image processing module includes image denoising, stroke extraction, glyph recognition, etc.

4. The digital calligraphy teaching system based on artificial intelligence according to claim 1, characterized in that: The artificial intelligence evaluation module is based on deep learning and machine learning models to comprehensively evaluate the user's calligraphy. The evaluation indicators include stroke order, stroke shape, stroke strength, glyph structure, etc.

5. The digital calligraphy teaching system based on artificial intelligence according to claim 1, characterized in that: The feedback and guidance module includes real-time feedback, dynamic demonstration, and voice and text guidance.

6. The digital calligraphy teaching system based on artificial intelligence according to claim 1, characterized in that: The learning progress tracking module is responsible for recording the user's learning progress and tracking the user's practice frequency, improvement of calligraphy level, etc.

7. The digital calligraphy teaching system based on artificial intelligence according to claim 1, wherein: The cloud data storage and analysis module saves the user's learning data in the cloud, and the system will conduct trend analysis on the user's calligraphy learning through big data analysis.

8. The digital calligraphy teaching system based on artificial intelligence according to claim 1, characterized in that: The virtual calligraphy teacher module simulates a virtual calligraphy teacher through artificial intelligence algorithms, can interact with the user in real time, and provide personalized guidance.

9. A digital calligraphy teaching method based on artificial intelligence, characterized in that, It includes a calligraphy digital teaching system based on artificial intelligence according to any one of claims 1-8. It includes the following steps: S1: Preliminary recognition and scoring; S2: Intelligent feedback and correction; S3: Personalized practice; S4: Progress evaluation and optimization.

10. The method for digital calligraphy teaching based on artificial intelligence according to claim 9, characterized in that: The preliminary recognition and scoring: includes glyph recognition at the start of writing, stroke analysis and error marking, and dimensional scoring and comprehensive evaluation; Intelligent feedback and correction: includes detailed intelligent feedback, correction suggestions and demonstration presentations, and interactive correction and real-time demonstrations; Personalized practice: includes data-driven personalized adjustment, personalized practice for strengthening weak links, and formulation of an adaptive practice plan; Progress evaluation and optimization: includes periodic progress reports, data-based dynamic optimization, and maximization of learning effects.

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