Handwriting learning system

Abstract

This invention provides a character learning system to address the shortcomings of traditional character learning methods. The system includes: a database module storing the first path sequence, first path coordinates, and first path pressure values ​​of individual character strokes; a display module displaying one character; a writing module allowing the user to write a character, generating pressure trajectory data; a writing analysis module analyzing the pressure trajectory data to obtain the second path sequence, second path coordinates, and second path pressure values ​​of the character strokes; and a writing evaluation module comparing the second path sequence, second path coordinates, and second path pressure values ​​with the first path sequence, first path coordinates, and first path pressure values ​​to generate a writing evaluation. This invention can improve the accuracy of character learning.

Claims

1. A character learning system, comprising: a database module (1) for storing at least one character dataset, each character dataset having multiple character data, each character data including a first path timing, a first path coordinate and a first path pressure value representing at least one stroke of a character; a display module (2) coupled to the database module (1) and used to play a character represented by one of the character data; a writing module (3) including a pressure sensing panel for a user to write a character to generate pressure trajectory data; optionally, the writing module (3) is coupled to the display module (2) to display an image of the character written by the user through the display module (2); A writing analysis module (4), coupled to the writing module (3), is used to analyze the pressure trajectory data to obtain a second path timing, a second path coordinate, and a second path pressure value relative to at least one stroke of the character; and a writing evaluation module (5), coupled to the database module (1) and the writing analysis module (4), and including a pre-trained analysis model (M), is used to compare the second path timing, the second path coordinate, and the second path pressure value with the first path timing, the first path coordinate, and the first path pressure value of the single character displayed on the display module (2) to generate a writing evaluation.

2. The character learning system as described in claim 1, wherein, The first path sequence and the first path coordinate system are associated with the first stroke order and the first stroke trajectory direction of the character, and the second path sequence and the second path coordinate system are associated with the second stroke order and the second stroke trajectory direction of the character. The analysis model (M) determines whether there is a sequence difference between the first stroke order and the second stroke order, or whether there is a directional difference between the first stroke trajectory direction and the second stroke trajectory direction, based on the first path sequence, the first path coordinate system, the second path sequence, and the second path coordinate system. When the sequence difference or directional difference is determined, the writing evaluation module controls the display module to play a stroke order error indication or a stroke direction error indication, respectively, as part of the writing evaluation.

3. The character learning system as described in claim 1, wherein, The first path coordinate system is associated with the outline size of the first stroke of the character, and the second path coordinate system is associated with the outline size of the second stroke of the character. The analysis model (M) determines whether the difference in the outline size ratio between the first stroke outline size and the second stroke outline size exceeds a preset outline size ratio after standardizing the first path coordinate system and the second path coordinate system. When it is determined that the difference in the outline size ratio exceeds the preset outline size ratio, the writing evaluation module controls the display module to play an outline size ratio error indication as part of the writing evaluation.

4. The character learning system as described in claim 1, wherein, The first path pressure value and the first path coordinate system are associated with the pressure distribution of a first stroke of the character, and the second path pressure value and the second path coordinate system are associated with the pressure distribution of a second stroke of the character. The analysis model (M) determines whether a pressure difference between the first stroke pressure distribution and the second stroke pressure distribution exceeds a preset pressure threshold based on the first path pressure value, the first path coordinate system, the second path pressure value, and the second path coordinate system. When it is determined that the pressure difference exceeds the preset pressure threshold, the writing evaluation module controls the display module to play a stroke pressure error indication as part of the writing evaluation.

5. The character learning system as described in Request 1, wherein, The first path timing and the first path coordinate system are associated with the trajectory direction of the first stroke of the character. The analysis model (M) generates a writing reminder for the current stroke or the next stroke of the character on the display module based on the current stroke of the character written by the user and the trajectory direction of the first stroke of the character to be learned. The writing reminder includes at least one of the position, length, direction or force of the stroke.

6. The character learning system as described in claim 5 further includes a voice module (6) coupled to the handwriting evaluation module (5), the handwriting evaluation module (5) controlling the voice module (6) to generate a reminder voice relative to the handwriting evaluation.

7. The character learning system as described in any one of claims 1 to 6 further includes an input module (7) coupled to the database module (1) and used to allow a user to select a single character from the at least one character dataset for writing.

8. The character learning system as described in any one of claims 1 to 6 further includes a writing playback module (8) coupled to the writing analysis module (4) and the display module (2), wherein when the writing playback module (8) is triggered, the display module (2) generates and displays a dynamic image of character writing based on the second path timing, second path coordinates and second path pressure value of at least one stroke of the character.

9. The character learning system as described in any one of claims 1 to 6 further includes a single character playback module (9) coupled to the database module (1) and the display module (2), wherein when the single character playback module (9) is triggered, the display module (2) generates and displays a single character writing dynamic image based on the first path timing, first path coordinates and first path pressure value of at least one stroke of the single character.

10. A character learning system, comprising: a database module (1) for storing at least one character dataset, each character dataset having multiple single character data, each single character data including a first path timing, a first path coordinate and a first path pressure value representing at least one stroke of a single character; a writing module (3) including a pressure sensing panel for a user to write a character to generate pressure trajectory data; and a display module (2) coupled to the writing module (3) for displaying an image of the character written by the user. A writing analysis module (4), coupled to the writing module (3), is used to analyze the pressure trajectory data to obtain a second path timing, a second path coordinate, and a second path pressure value relative to at least one stroke of the character; and a writing evaluation module (5), coupled to the database module and the writing analysis module, and having a pre-trained analysis model (M), is used to compare the second path timing, the second path coordinate, and the second path pressure value with the first path timing, the first path coordinate, and the first path pressure value of each character in the at least one character dataset stored in the database module (1) to find the most similar character and generate a writing evaluation.

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