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Multi-device integrated calligraphy teaching system

A teaching system and multi-equipment technology, applied in the direction of electronically operated teaching aids, teaching aids, educational appliances, etc., can solve the problems of single evaluation standard, inability to intuitively find, and copying methods detached.

Inactive Publication Date: 2022-07-22
盖新宇
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] Aiming at the deficiencies of the prior art, the present invention provides a multi-device fusion calligraphy teaching system, which solves the problems of the single evaluation standard and the inability to intuitively discover the writing process when using the traditional APP for auxiliary calligraphy practice. The problem that makes the copying method deviate from the traditional calligraphy writing method when using it

Method used

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  • Multi-device integrated calligraphy teaching system

Examples

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Effect test

Embodiment 1

[0032] A calligraphy teaching system integrating multiple devices, a calligraphy teaching system integrating multiple devices, comprising a calligraphy practice module, a surface electromyographic signal acquisition, a practice evaluation module and a calligraphy tutorial module, characterized in that: the calligraphy practice module is composed of writing The posture correction function, the writing strength correction function and the word cutting function are composed. The surface EMG signal acquisition is composed of the feature extraction of the surface EMG signal, the classification of the surface EMG signal, the muscle strength estimation of the surface EMG signal and the posture recognition of the image. The exercise evaluation module consists of offline handwritten Chinese character recognition and handwritten Chinese character image comparison. The electromyographic signal (EMG) is a series of motor unit action potentials generated in the process of muscle excitation ...

Embodiment 2

[0033]Embodiment 2: The difference between this embodiment and Embodiment 1 is that the feature extraction of the surface EMG signal adopts PCA-based multi-channel EMG information fusion. During the muscle exertion process, the contact loosening and relative displacement between the array surface electrodes and the skin will introduce corresponding noise, resulting in pseudo-muscle activation and abnormal overall activation intensity during the resting period. Using the preprocessing method of PCA, the signal denoising and enhancement of the channel which is seriously polluted by noise can be well achieved. The classification of the surface EMG signals was performed using LSTM. The sampling frequency of the EMG signal is 1000Hz, and the writing process may be as long as tens of seconds, which leads to a long sequence of EMG signals. In order to solve the problem of gradient disappearance and gradient explosion in the long sequence training process, LSTML is used. Perform clas...

Embodiment 3

[0034] Embodiment 3: The difference between this implementation and Embodiment 1 is that the offline handwritten Chinese character recognition adopts the DBN+CNN technology. Offline handwritten Chinese characters have many near-character shapes, and it is difficult to extract features and easy to identify inaccurately. And in the project application scenario, it is necessary to recognize Chinese characters of various writing levels. A fusion model of convolutional neural network CNN and deep belief network DBN is now used. Using CNN to automatically extract image features and DBN's advantages of continuously weakening the errors and secondary information of each layer of network, a fusion comparison strategy is adopted to extract a classification result as much as possible to improve the recognition ability. The choice of the handwritten Chinese character image comparison technique is to use a twin neural network. The Siamese neural network has two inputs, and the two inputs...

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Abstract

The invention discloses a multi-device fusion calligraphy teaching system, and relates to the technical field of calligraphy teaching. The multi-device fused calligraphy teaching system solves the problems that when a traditional APP for assisting calligraphy practice is used, the evaluation standard is single, the problem in the writing process cannot be visually found, and meanwhile when the APP is used, a copying mode is separated from a traditional calligraphy writing mode.

Description

technical field [0001] The invention relates to the technical field of calligraphy teaching, in particular to a calligraphy teaching system integrating multiple devices. Background technique [0002] At present, the existing APPs to assist calligraphy practice are generally not targeted, and their usage is very limited. The specific manifestations are as follows: [0003] (1) The copying method is separated from the traditional calligraphy writing method. Users use capacitive pens and fingers to practice calligraphy instead of traditional pen, ink, paper and inkstone. In this way, the user cannot feel the real details of the calligraphy and brush strokes, which is not conducive to the user's calligraphy progress. [0004] (2) Problems in the writing process cannot be found intuitively. Users only know that the writing "result" is wrong, but they don't know whether the writing "process" is wrong, and it is difficult to know the strength and posture errors in the writi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G09B11/00G09B5/06G06K9/00G06K9/62G06N3/04G06N3/08G06V40/20
CPCG09B11/00G09B5/065G06N3/08G06N3/044G06N3/045G06F2218/00G06F18/241
Inventor 王春鹏盖新宇刘丰睿张岩石翔慧江楠周芸帆单佳豪
Owner 盖新宇
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