Emotion attention method for AI online education

Abstract

The invention discloses an emotion attention method for AI online education, which is applied among student ends, a teacher end and a server, and the server sends a live video stream of the teacher end to each student end for playing. According to the emotion attention method for AI online education, the average understanding degree value is calculated according to the learning expressions of the students, the understanding and attention degree of the students to the current course listening are evaluated, the playing speed of each student terminal is dynamically and intelligently adjusted, personalized learning experience is provided for each student, and therefore the learning efficiency is improved; the reminding information of the overall understanding condition of the students is sent to the teacher end, so that the teacher can better interact with the students and adjust the teaching method and content in time; according to the embodiment of the invention, the student end starting the camera sends the speed regulation state information to all other student ends and the server, the server does not need to carry out message interaction with each student end, the processing pressure of the server can be reduced, and the server adjusts the code stream of the live video stream by calculating each playing proportion.

Description

Technical Field

[0001] The present invention belongs to the technical field of online education, and particularly relates to an emotion attention method for AI online education. Background Art

[0002] Online learning refers to learning carried out in an electronic environment composed of communication technology, microcomputer technology, computer technology, artificial intelligence, network technology, multimedia technology, etc., which is technology-based learning. It is a way of network teaching and learning through the computer Internet or through the mobile phone wireless network in a network virtual classroom. Interactive learning refers to a new learning method that uses multimedia computer technology and network technology to enable communication and interaction between teachers and learners and among learner groups. This learning method is easier to achieve one-on-one communication between learning and teaching, fully respects the individuality of learning, stimulates the motivation of learning, and is not restricted by time, place, and space, and can achieve the same interaction as in reality.

[0003] In the existing online learning, by default, students passively watch course videos and generally cannot adjust the playback speed of live courses. Even if a small part of the online education system supports the real-time playback function, students need to manually perform playback or adjust the playback speed, and it is impossible to achieve adaptive adjustment of the course playback speed according to the situation of each student. Even if the manual adjustment method is adopted, the operation is not convenient; and if students do not actively feedback their respective understanding levels to the teacher, it is impossible to obtain the understanding information of students, resulting in low educational efficiency. Summary of the Invention

[0004] The purpose of the present invention is to propose an emotion attention method for AI online education in view of solving the problems raised in the background art.

[0005] To achieve the above purpose, the technical solutions adopted by the present invention are as follows: An emotion attention method for AI online education proposed by the present invention, the method is applied among the student terminal, the teacher terminal and the server, and the server sends the live video stream of the teacher terminal to each student terminal for playback, wherein: For the student terminals with the camera turned on, collect a preset number of face images, and perform facial expression recognition on the collected face images through a trained deep learning model to obtain the learning expressions corresponding to the respective face images; According to the mapping relationship between the preset learning expressions and the understanding degree values, each student terminal with the camera turned on calculates the average understanding degree value of the corresponding student; Compare each average understanding degree value with the acceleration playback threshold and / or the deceleration playback threshold, and adjust the playback speed of each student terminal according to the comparison result; Each student terminal with a camera enabled uses a broadcast mechanism to send speed adjustment status information to all other student terminals and the server. Each student terminal determines whether the first preset condition is met based on the current playback time point of the video stream, the speed adjustment status information, and the total number of student terminals, and the server determines whether the second preset condition is met based on the current playback time point of the live video stream, the speed adjustment status information, and the total number of student terminals. For each student terminal, when the first preset condition is met, the current student terminal calculates the first normal playback ratio, the first decelerated playback ratio, and the first accelerated playback ratio based on the respective speed adjustment status information, and the current student terminal adjusts its own playback speed according to the magnitudes of these three ratios. When the second preset condition is met, the server calculates the second normal playback ratio, the second decelerated playback ratio, and the second accelerated playback ratio based on the respective speed adjustment status information, and the server sends a reminder message about the overall understanding situation of the students to the teacher terminal according to the magnitudes of these three ratios.

[0006] Preferably, data caching is performed while the live video stream is being played on the student terminal, and the data caching speed is greater than the playback speed.

[0007] Preferably, the categories of the learning expressions include understanding and concentrating, understanding but distracted, confused but not giving up, confused and giving up, and not in the state.

[0008] Preferably, each student terminal with a camera enabled calculates the average understanding degree value of the corresponding student The formula is as follows: ; Wherein, represents the number of face images collected by each student terminal, represents the understanding degree value corresponding to the learning expression of the th face image collected, represents the weight corresponding to the understanding degree value of the th face image collected.

[0009] Preferably, comparing the respective average understanding degree values with the accelerated playback threshold and / or the decelerated playback threshold, and adjusting the playback speed of each student terminal according to the comparison result includes: Each student terminal with a camera enabled compares its own current playback time point of the video stream with the current playback time point of the live video stream. When the difference between the two is within the preset range, the current student terminal with a camera enabled is watching the live broadcast, otherwise the current student terminal with a camera enabled is watching a non-live broadcast. For the student terminals that are watching the live broadcast and have cameras enabled, compare the average understanding degree values of the respective students with the decelerated playback threshold: If the average comprehension degree value is less than or equal to the slow - down playback threshold, the playback speed adjustment state of the student side of the corresponding activated camera is to slow down the playback at the first preset speed; If the average comprehension degree value is greater than the slow - down playback threshold, the playback speed adjustment state of the student side of the corresponding activated camera is to play normally at the second preset speed; For the student side that watches non - live videos and has the camera activated, the average comprehension degree values of the corresponding students are respectively compared with the slow - down playback threshold and the speed - up playback threshold: If the average comprehension degree value is less than or equal to the slow - down playback threshold, the playback speed adjustment state of the student side of the corresponding activated camera is to slow down the playback at the first preset speed; If the average comprehension degree value is greater than or equal to the speed - up playback threshold, the playback speed adjustment state of the student side of the corresponding activated camera is to speed up the playback at the third preset speed; If the average comprehension degree value is greater than the slow - down playback threshold and less than the speed - up playback threshold, the playback speed adjustment state of the student side of the corresponding activated camera is to play normally at the second preset speed.

[0010] Preferably, the speed - adjustment state information includes the student ID, the current playback video stream time point T1 when each student side with the camera activated sends the speed - adjustment state information, and the playback speed adjustment state, where the playback speed adjustment state is normal playback, slow - down playback, or speed - up playback.

[0011] Preferably, each student side determines whether the first preset condition is met according to the current playback video stream time point, the speed - adjustment state information, and the total number of student sides, and the server determines whether the second preset condition is met according to the current playback time point of the live video stream, the speed - adjustment state information, and the total number of student sides, including: After each student side receives the speed - adjustment state information, it respectively calculates the first difference between the current playback video stream time point T2 of the student side itself and T1 in each speed - adjustment state information, and counts the number A of the first differences less than the first threshold; Judge whether the ratio of the number A to the total number of student sides is greater than the second threshold. If it is greater than the second threshold, the first preset condition is met; After the server receives each speed - adjustment state information, it respectively calculates the second difference between the current playback time point T3 of the live video stream and T1 in each speed - adjustment state information, and counts the number B of the second differences less than the first threshold; Judge whether the ratio of the number B to the total number of student sides is greater than the second threshold. If it is greater than the second threshold, the second preset condition is met.

[0012] Preferably, for each student terminal, when the first preset condition is satisfied, the current student terminal calculates the first normal playback ratio, the first slow-down playback ratio, and the first speed-up playback ratio respectively according to each speed regulation state information, and the current student terminal adjusts its own playback speed according to the magnitudes of these three ratios, including: The first normal playback ratio is the ratio of the number of normal playback in all received speed regulation state information to the quantity A, the first slow-down playback ratio is the ratio of the number of slow-down playback in all received speed regulation state information to the quantity A, and the first speed-up playback ratio is the ratio of the number of speed-up playback in all received speed regulation state information to the quantity A; For each student terminal, among the first normal playback ratio, the first slow-down playback ratio, and the first speed-up playback ratio, if one of the ratios reaches the third threshold, the current student terminal plays at the playback speed in the speed regulation state information corresponding to this ratio. If none of the three ratios reaches the third threshold, the current student terminal continues to play at its current speed.

[0013] Preferably, when the second preset condition is satisfied, the server calculates the second normal playback ratio, the second slow-down playback ratio, and the second speed-up playback ratio respectively according to each speed regulation state information, and the server sends a reminder message about the overall understanding situation of the students to the teacher terminal according to the magnitudes of these three ratios, including: The second normal playback ratio is the ratio of the number of normal playback in all received speed regulation state information to the quantity B, the second slow-down playback ratio is the ratio of the number of slow-down playback in all received speed regulation state information to the quantity B, and the second speed-up playback ratio is the ratio of the number of speed-up playback in all received speed regulation state information to the quantity B; Among the second normal playback ratio, the second slow-down playback ratio, and the second speed-up playback ratio, if the second slow-down playback ratio reaches the fourth threshold, the server sends a reminder message that the students have overall difficulty in understanding to the teacher terminal. If the second normal playback ratio or the second speed-up playback ratio reaches the fourth threshold, the server sends a reminder message that the students have normal overall understanding to the teacher terminal.

[0014] Preferably, when the server sends a reminder message that the students have overall difficulty in understanding to the teacher terminal, the server also reduces the bitrate of the live video stream of each student terminal; When the server sends a reminder message that the students have normal overall understanding to the teacher terminal, the server also restores the bitrate of the live video stream of each student terminal to the original bitrate; Wherein, the original bitrate is the bitrate at which the server sends the live video stream of the teacher terminal to each student terminal for playback.

[0015] Compared with the prior art, the beneficial effects of the present invention are: The emotion attention method for this AI online education calculates the average comprehension degree value based on the learning expressions of students to evaluate the understanding and attention of students to the current course lecture, and dynamically and intelligently adjusts the playback speed of each student terminal to provide a personalized learning experience for each student, thereby improving learning efficiency; and sends reminder information about the overall comprehension of students to the teacher terminal, enabling teachers to better interact with students and timely adjust teaching methods and content; In this method, the student terminals with the camera turned on send speed adjustment status information to all other student terminals and the server. There is no need for the server to interact with each student terminal, which can reduce the server processing pressure. And the server adjusts the bitrate of the live video stream by calculating each playback ratio to prevent the video cache of the student terminal from being overloaded, so as to optimize the user experience and performance. Brief Description of the Drawings

[0016] Figure 1 It is a flowchart of the emotion attention method for the AI online education of the present invention. Detailed Embodiment

[0017] In order to make the purpose, technical solution and advantages of this application clearer, the following further details this application in combination with the drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain this application and are not used to limit this application.

[0018] In one embodiment, as Figure 1 shown, an emotion attention method for AI online education is provided. This method is applied among student terminals, teacher terminals and the server. The server sends the live video stream of the teacher terminal to each student terminal for playback (the teacher starts live teaching through educational software (such as APP, small program, etc.) on a smart terminal (such as a computer, PAD, mobile phone, etc.). The educational software is called the teacher terminal. The live teaching content of the teacher terminal is sent in the form of a video stream and in a multicast manner through the server. Multiple students join the multicast group through the educational software client of the smart terminal (called the student terminal) to watch the live teaching content. While the live video stream is being played on the student terminal, data caching is performed, and the data caching speed is greater than the playback speed, where: Step 1: For the student terminal with the camera turned on, collect a preset number of face images, and perform expression recognition on the collected face images through a trained deep learning model to obtain the learning expressions corresponding to their respective face images; It should be noted that for the student terminal with the camera turned on, the camera samples face images periodically (such as once every five minutes), and in order to reduce random errors, multiple face images are collected each time, such as three; if the deep learning model is a convolutional neural network model, the process of how to train the deep learning model and how to perform expression recognition belongs to the prior art, and this solution will not be elaborated in detail.

[0019] Among them, in this embodiment, the categories of learning expressions include understanding and concentrating, understanding but being distracted, being confused but not giving up, being confused and giving up, and being out of state.

[0020] Step 2: According to the pre-set mapping relationship between learning expressions and understanding degree values, each student terminal with the camera turned on calculates the average understanding degree value of the corresponding student. In this embodiment, the pre-set mapping relationship between learning expressions and understanding degree values is as follows: the understanding degree value corresponding to understanding and concentrating is 1, the understanding degree value corresponding to understanding but being distracted is 0.7, the understanding degree value corresponding to being confused but not giving up is 0.3, the understanding degree value corresponding to being confused and giving up is 0, and the understanding degree value corresponding to being out of state is 0.5. Among them, each student terminal with the camera turned on calculates the average understanding degree value of the corresponding student using the following formula (calculated by the weighted average method): ; Among them, represents the number of face images collected by each student terminal (in this embodiment is 3), represents the understanding degree value corresponding to the learning expression of the th face image collected, represents the weight corresponding to the understanding degree value of the th face image collected.

[0021] In this embodiment, the weight of being out of state is 1, and the weights of understanding and concentrating, understanding but being distracted, being confused but not giving up, and being confused and giving up are all 3, so as to reduce the influence degree of being out of state (possibly understanding, possibly not understanding) on the average understanding degree value. The understanding and attention degree of students' listening to the current course is evaluated through the average understanding degree value .

[0022] Step 3: Compare each average understanding degree value with the fast-forward play threshold and / or the slow-down play threshold, and adjust the play speed of each student terminal according to the comparison result, including: Each student terminal with the camera turned on compares the current play time point of its own video stream with the current play time point of the live video stream. When the difference between the two is within the preset range (such as within 1 minute), the current student terminal with the camera turned on is watching the live broadcast, otherwise the current student terminal with the camera turned on is watching a non-live broadcast; For the student terminals that are watching the live broadcast and have the camera turned on, compare the average understanding degree values of the corresponding students with the slow-down play threshold (in this embodiment, the slow-down play threshold is 0.3): If the average comprehension degree value is less than or equal to the speed - down playback threshold, the playback speed adjustment status of the student side of the corresponding turned - on camera is to play at a reduced speed according to the first preset speed (for example, play at a reduced speed of 0.8 times the original speed); If the average comprehension degree value is greater than the speed - down playback threshold, the playback speed adjustment status of the student side of the corresponding turned - on camera is to play normally according to the second preset speed (that is, play normally at 1.0 times the original speed); For the student side of the non - live video with the camera turned on, the average comprehension degree values of the corresponding students are respectively compared with the speed - down playback threshold and the speed - up playback threshold (in this embodiment, the speed - up playback threshold is 0.7): If the average comprehension degree value is less than or equal to the speed - down playback threshold, the playback speed adjustment status of the student side of the corresponding turned - on camera is to play at a reduced speed according to the first preset speed (for example, play at a reduced speed of 0.8 times the original speed); If the average comprehension degree value is greater than or equal to the speed - up playback threshold, the playback speed adjustment status of the student side of the corresponding turned - on camera is to play at an increased speed according to the third preset speed (for example, play at an increased speed of 1.2 times the original speed); If the average comprehension degree value is greater than the speed - down playback threshold and less than the speed - up playback threshold, the playback speed adjustment status of the student side of the corresponding turned - on camera is to play normally according to the second preset speed (that is, play normally at 1.0 times the original speed).

[0023] Step 4: Each student side with the camera turned on uses the broadcast mechanism to send the speed - adjustment status information to all other student sides (including the server) (where the broadcast mechanism means that the student side with the camera turned on sends the speed - adjustment status information to all other students (including the student side with the camera turned on and the student side without the camera turned on) and the server); Among them, the speed - adjustment status information includes the student ID, the current playback video stream time point T1 when each student side with the camera turned on sends the speed - adjustment status information (that is, T1 is the current playback video timestamp when the student side with the camera turned on sends the speed - adjustment status information), and the playback speed adjustment status, where the playback speed adjustment status is normal playback, reduced - speed playback, or increased - speed playback.

[0024] Step 5: Each student side determines whether it meets the first preset condition according to the current playback video stream time point, the speed - adjustment status information, and the total number of student sides, and the server determines whether it meets the second preset condition according to the current playback time point of the live video stream, the speed - adjustment status information, and the total number of student sides, including: For determining whether the first preset condition is satisfied: After each student terminal receives the speed adjustment status information, it calculates the first difference between the current playback video stream time point T2 of the student terminal itself (i.e., T2 is the current playback video stream time point of the student terminal that receives the speed adjustment status information) and T1 in each speed adjustment status information respectively, and counts the number A of the first differences less than the first threshold (such as the first threshold is 30 seconds); Judge whether the ratio of the number A to the total number of student terminals is greater than the second threshold (such as the second threshold is 30%. By comparing with the second threshold, if it is greater than the second threshold, it means there is certain reference value). If it is greater than the second threshold, the first preset condition is satisfied (otherwise it is not satisfied); For determining whether the second preset condition is satisfied: After the server receives each speed adjustment status information, it calculates the second difference between the current playback time point T3 of the live video stream and T1 in each speed adjustment status information respectively, and counts the number B of the second differences less than the first threshold; Judge whether the ratio of the number B to the total number of student terminals is greater than the second threshold. If it is greater than the second threshold, the second preset condition is satisfied (otherwise it is not satisfied).

[0025] Step 6. For each student terminal, when the first preset condition is satisfied (if the first preset condition is not satisfied, the current student terminal does not need to adjust its own playback speed and continues to play at its current speed), then the current student terminal calculates the first normal playback ratio, the first deceleration playback ratio and the first acceleration playback ratio according to each speed adjustment status information respectively, and the current student terminal adjusts its own playback speed according to the magnitudes of these three ratios, including: The first normal playback ratio is the ratio of the number of normal playback in all received speed adjustment status information to the number A, the first deceleration playback ratio is the ratio of the number of deceleration playback in all received speed adjustment status information to the number A, and the first acceleration playback ratio is the ratio of the number of acceleration playback in all received speed adjustment status information to the number A; For each student terminal, among the first normal playback ratio, the first deceleration playback ratio and the first acceleration playback ratio, if one of the ratios reaches the third threshold (i.e., greater than or equal to the third threshold, such as the third threshold is 60%), then the current student terminal plays at the playback speed in the speed adjustment status information corresponding to this ratio (i.e., the playback speed corresponding to the first normal playback ratio is normal playback, the playback speed corresponding to the first deceleration playback ratio is deceleration playback, and the playback speed corresponding to the first acceleration playback ratio is acceleration playback). If none of the three ratios reaches the third threshold, the current student terminal continues to play at its current speed; that is, steps 4 - 6 realize global speed adjustment judgment through the broadcast mechanism of the student terminals with the camera turned on.

[0026] Step 7: When the second preset condition is met (if the second preset condition is not met, the server does not need to send a reminder message to the teacher terminal, nor does it need to adjust the bitrate of the live video stream of each student terminal, and continues with the current bitrate), the server calculates the second normal playback ratio, the second slow-down playback ratio, and the second speed-up playback ratio based on each speed adjustment state information respectively. And the server sends a reminder message about the overall understanding situation of the students to the teacher terminal according to the magnitudes of these three ratios, including: The second normal playback ratio is the ratio of the number of normal playback in all received speed adjustment state information to the quantity B. The second slow-down playback ratio is the ratio of the number of slow-down playback in all received speed adjustment state information to the quantity B. The second speed-up playback ratio is the ratio of the number of speed-up playback in all received speed adjustment state information to the quantity B; Among the second normal playback ratio, the second slow-down playback ratio, and the second speed-up playback ratio, if the second slow-down playback ratio reaches the fourth threshold (i.e., is greater than or equal to the fourth threshold, such as the fourth threshold is 60%), the server sends a reminder message that the students have overall difficulty in understanding to the teacher terminal. If the second normal playback ratio or the second speed-up playback ratio reaches the fourth threshold, the server sends a reminder message that the students have normal overall understanding to the teacher terminal. The teacher terminal reminds the teacher of the reminder message, and the teacher adjusts the teaching content, speed, or method according to the reminder message.

[0027] Among them, when the server sends a reminder message that the students have overall difficulty in understanding to the teacher terminal, the server also reduces the bitrate of the live video stream of each student terminal (specifically, how much to reduce can be set according to actual needs. By adjusting the bitrate, it is possible to prevent the video buffer of the student terminal from overloading); When the server sends a reminder message that the students have normal overall understanding to the teacher terminal, the server also restores the bitrate of the live video stream of each student terminal to the original bitrate; Among them, the original bitrate is the bitrate at which the server sends the live video stream of the teacher terminal to each student terminal for playback.

[0028] Then return to Step 1 to continue continuous detection.

[0029] In another embodiment, the present application further includes an emotion attention device for AI online education, including a processor and a memory storing a number of computer instructions. When the computer instructions are executed by the processor, the steps of the method described in Steps 1 - 7 are implemented.

[0030] The emotional attention method for this AI online education calculates the average comprehension degree value based on the learning expressions of students to evaluate the understanding and attention of students to the current course lecture, and dynamically and intelligently adjusts the playback speed of each student terminal to provide a personalized learning experience for each student, thereby improving learning efficiency; and sends reminder information about the overall understanding of students to the teacher terminal, enabling teachers to better interact with students and timely adjust teaching methods and content; in this method, the student terminal with the camera turned on sends speed adjustment status information to all other student terminals and the server, without the need for the server to interact with each student terminal, which can reduce the server processing pressure, and the server adjusts the bitrate of the live video stream by calculating each playback ratio to prevent the video cache of the student terminal from overloading, so as to optimize the user experience and performance.

[0031] It should be understood that although Figure 1 the steps in the flowchart of Figure 1 are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, there is no strict order limit for the execution of these steps, and these steps can be executed in other orders. Moreover,

[0032] The above-described embodiments only represent several implementation manners of the present application, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the invention patent. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

Claims

1. A method for emotional attention in AI online education, characterized in that: The method is applied among the student side, the teacher side and the server. The server sends the live video stream of the teacher side to each student side for playing, where: For the student side with the camera turned on, a preset number of face images are collected, and the collected face images are subjected to expression recognition through a trained deep learning model to obtain the learning expressions corresponding to their respective face images; According to the mapping relationship between the preset learning expressions and the understanding degree values, each student side with the camera turned on calculates the average understanding degree value of the corresponding student; Compare each average understanding degree value with the acceleration playback threshold and / or the deceleration playback threshold, and adjust the playback speed of each student side according to the comparison result; Each student side with the camera turned on uses the broadcast mechanism to send the speed adjustment status information to all other student sides and the server; Each student side judges whether the first preset condition is met according to the current playback time point of the video stream, the speed adjustment status information and the total number of student sides, and the server judges whether the second preset condition is met according to the current playback time point of the live video stream, the speed adjustment status information and the total number of student sides; For each student side, when the first preset condition is met, the current student side calculates the first normal playback ratio, the first deceleration playback ratio and the first acceleration playback ratio respectively according to the speed adjustment status information, and the current student side adjusts its own playback speed according to the magnitudes of these three ratios; When the second preset condition is met, the server calculates the second normal playback ratio, the second deceleration playback ratio and the second acceleration playback ratio respectively according to the speed adjustment status information, and the server sends a reminder message about the overall understanding situation of the students to the teacher side according to the magnitudes of these three ratios.

2. The method for emotional attention in AI online education according to claim 1, characterized in that: Data caching is performed while the live video stream is being played on the student side, and the data caching speed is greater than the playback speed.

3. The method for emotional attention in AI online education according to claim 1, characterized in that: The categories of the learning expressions include understanding and concentrating, understanding but being distracted, being confused but not giving up, being confused and giving up, and being out of state.

4. The method for emotional attention in AI online education according to claim 1, characterized in that: Each student terminal that turns on the camera calculates the average comprehension degree value of the corresponding student The formula is as follows: ； Among them, represents the number of face images collected by each student terminal, represents the understanding degree value corresponding to the learning expression of the th face image collected, and represents the weight corresponding to the understanding degree value of the th face image collected.

5. The method for emotional attention in AI online education according to claim 1, characterized in that: The comparing each average understanding degree value with the acceleration playback threshold and / or the deceleration playback threshold, and adjusting the playback speed of each student side according to the comparison result includes: Each student side with the camera turned on compares its own current playback time point of the video stream with the current playback time point of the live video stream. When the difference between the two is within the preset range, the currently camera - turned - on student side is watching the live broadcast, otherwise the currently camera - turned - on student side is watching non - live broadcast; For the student side watching the live broadcast and with the camera turned on, compare the average understanding degree value of each corresponding student with the deceleration playback threshold: If the average understanding degree value is less than or equal to the deceleration playback threshold, the corresponding student side with the camera turned on adjusts the playback speed state to decelerate playback at the first preset speed; If the average understanding degree value is greater than the deceleration playback threshold, the corresponding student side with the camera turned on adjusts the playback speed state to normal playback at the second preset speed; For the student side watching non - live broadcast and with the camera turned on, compare the average understanding degree value of each corresponding student with the deceleration playback threshold and the acceleration playback threshold respectively: If the average comprehension degree value is less than or equal to the slow-down playback threshold, the playback speed adjustment state of the student side of the corresponding turned-on camera is to slow down the playback at the first preset speed; If the average comprehension degree value is greater than or equal to the speed-up playback threshold, the playback speed adjustment state of the student side of the corresponding turned-on camera is to speed up the playback at the third preset speed; If the average comprehension degree value is greater than the slow-down playback threshold and less than the speed-up playback threshold, the playback speed adjustment state of the student side of the corresponding turned-on camera is to play normally at the second preset speed.

6. The method for emotional attention in AI online education according to claim 5, characterized in that: The speed adjustment state information includes the student ID, the current playback video stream time point T1 when each student side with the turned-on camera sends the speed adjustment state information, and the playback speed adjustment state, where the playback speed adjustment state is normal playback, slow-down playback or speed-up playback.

7. The method for emotional attention in AI online education according to claim 6, characterized in that: Each student side determines whether the first preset condition is met based on the current playback video stream time point, the speed adjustment state information, and the total number of student sides, and the server determines whether the second preset condition is met based on the current playback time point of the live video stream, the speed adjustment state information, and the total number of student sides, including: After each student side receives the speed adjustment state information, it calculates the first difference between its own current playback video stream time point T2 and T1 in each speed adjustment state information respectively, and counts the number A of the first differences less than the first threshold; Judge whether the ratio of the number A to the total number of student sides is greater than the second threshold. If it is greater than the second threshold, the first preset condition is met; After the server receives each speed adjustment state information, it calculates the second difference between the current playback time point T3 of the live video stream and T1 in each speed adjustment state information respectively, and counts the number B of the second differences less than the first threshold; Judge whether the ratio of the number B to the total number of student sides is greater than the second threshold. If it is greater than the second threshold, the second preset condition is met.

8. The method for emotional attention in AI online education according to claim 7, characterized in that: For each student side, when the first preset condition is met, the current student side calculates the first normal playback ratio, the first slow-down playback ratio, and the first speed-up playback ratio respectively according to each speed adjustment state information, and the current student side adjusts its own playback speed according to the magnitudes of these three ratios, including: The first normal playback ratio is the ratio of the number of normal playback in all received speed adjustment state information to the number A, the first slow-down playback ratio is the ratio of the number of slow-down playback in all received speed adjustment state information to the number A, and the first speed-up playback ratio is the ratio of the number of speed-up playback in all received speed adjustment state information to the number A; For each student side, among the first normal playback ratio, the first slow-down playback ratio, and the first speed-up playback ratio, if one of the ratios reaches the third threshold, the current student side plays at the playback speed in the speed adjustment state information corresponding to this ratio. If none of the three ratios reaches the third threshold, the current student side continues to play at its own current speed.

9. The emotional attention method for AI online education according to claim 7, characterized in that: When the second preset condition is satisfied, the server calculates the second normal playback ratio, the second slow-down playback ratio, and the second speed-up playback ratio according to each speed adjustment state information respectively, and the server sends a reminder message about the overall understanding situation of the students to the teacher side according to the magnitudes of these three ratios, including: The second normal playback ratio is the ratio of the number of normal playback in all received speed adjustment state information to the quantity B, the second slow-down playback ratio is the ratio of the number of slow-down playback in all received speed adjustment state information to the quantity B, and the second speed-up playback ratio is the ratio of the number of speed-up playback in all received speed adjustment state information to the quantity B; Among the second normal playback ratio, the second slow-down playback ratio, and the second speed-up playback ratio, if the second slow-down playback ratio reaches the fourth threshold, the server sends a reminder message that the students have overall difficulty in understanding to the teacher side, and if the second normal playback ratio or the second speed-up playback ratio reaches the fourth threshold, the server sends a reminder message that the students have normal overall understanding to the teacher side.

10. The emotional attention method for AI online education according to claim 9, characterized in that: When the server sends a reminder message that the students have overall difficulty in understanding to the teacher side, the server also reduces the bitrate of the live video stream of each student side; When the server sends a reminder message that the students have normal overall understanding to the teacher side, the server also restores the bitrate of the live video stream of each student side to the original bitrate; Wherein, the original bitrate is the bitrate at which the server sends the live video stream of the teacher side to each student side for playback.

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