Online education system and device based on AI algorithm

Abstract

The invention provides an online education system and device based on an AI algorithm, and the system comprises the steps: collecting the voice and teaching information pictures of a teacher through a voice collection device and a camera device, collecting the face pictures and learning information pictures of students, employing an AI-based analysis mode, and carrying out the collection of the face pictures and learning information pictures of the students, and teaching and learning progresses of teachers and students are obtained. The beneficial effects of the invention are that the voice of the teacher is used as the real-time learning progress, the teaching information and the learning information are synchronized, and the concentration degree of the student in each time period and each class is evaluated according to the synchronization condition, the emotion of the student and the like, so that the teacher can obtain the learning progress of the student in time, and the learning efficiency is improved. A teacher does not need to check a camera and work in real time, and the online teaching efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of computer and educational technology, and in particular to an online education system and device based on AI algorithm. Background Art

[0002] With the influence of unstable factors, the demand for online education systems has become urgent.

[0003] However, existing online education can only continuously monitor students' performance in class through cameras and other means, which makes it impossible for teachers to effectively monitor students' learning progress. At the same time, due to geographical issues, teachers and students use different teaching methods, which makes the learning efficiency of remote online education low and unable to effectively track students' learning progress. Summary of the invention

[0004] The main purpose of the embodiment of the present invention is to propose an online education system based on AI algorithm, which solves the problem of synchronization of classroom learning between teachers and students, and at the same time evaluates the learning progress of students, so that teachers can understand the learning progress of students in real time.

[0005] One aspect of the present invention provides an online education system based on an AI algorithm, characterized in that it includes: A first acquisition module, used to acquire first image and sound data of a first target area of ​​a first user, where the first user is used to represent a teaching leader; A first recognition module is used to recognize the sound data using a sound detection model to obtain a sound recognition result, and is used to detect the first image using a first recognition model to obtain a first image recognition result, wherein the first image recognition result is used to represent a text image recognition result; A second acquisition module is used to obtain a second image of a second target area of ​​a second user, and to obtain a third image of a third target area of ​​the second user, wherein the second user is used to represent a teaching object, and the second image is used to represent a face image; a second recognition module, configured to detect the second image using a second recognition model to obtain a second image recognition result, and to detect the third image using a third recognition model to obtain a third image recognition result, wherein the second image recognition result is used to represent a face recognition result, and the third image recognition result is used to represent a text image recognition result; A teaching synchronization module, which determines the teaching progress according to the first image recognition result and the sound recognition result, and synchronizes the teaching progress of the teaching object according to the teaching progress and the third image recognition result; A teaching evaluation module is used to determine a first concentration of the teaching object according to the face recognition result, and to determine a second concentration of the teaching object according to the second image recognition result and the third image recognition result, and to determine a teaching evaluation result of the teaching object according to the first concentration and the second concentration.

[0006] According to the online education system based on AI algorithm, the first acquisition module includes: A first detection unit is used to identify a teaching mode of the first user, where the teaching mode of the first user includes one of online classroom teaching and online e-learning; a sound collection unit, configured to collect the sound of the first user to obtain the sound data; The first image acquisition unit is used to perform a process of text image calling and text image acquisition according to the teaching mode of the first user to obtain a first image, the text image calling includes obtaining a screenshot of the first target area through a calling interface, and the text image acquisition includes determining the first target area and acquiring the first image.

[0007] According to the online education system based on AI algorithm, the first recognition module includes: A first identity recognition unit, configured to detect the sound data using a voiceprint recognition model, and compare the sound data with a preset voiceprint preset by the first user to determine the identity of the first user; A sound recognition unit, configured to recognize the sound data by using the sound detection model trained by using one of a deep convolutional neural network and a Gaussian mixture model to obtain the sound recognition result; The first image recognition unit is used to recognize the first image by using an optical character detection model to obtain the first image recognition result.

[0008] According to the online education system based on AI algorithm, the first recognition module further includes: The sound image matching unit is used to obtain the sound recognition result, determine the sound time period, match the first image recognition result with the sound recognition result according to the sound time period, and perform prompts or adjust the position of the first target area according to the matching results.

[0009] According to the online education system based on AI algorithm, the second acquisition module includes: a second detection unit, configured to identify a teaching mode of the second user, wherein the teaching mode includes one of online classroom teaching and online electronic teaching; A second image acquisition unit, configured to acquire a facial image of the second user of the user to obtain the second image; The third image acquisition unit is used to execute a process of text image calling and text image acquisition according to the teaching mode to obtain a second image, wherein the text image calling includes obtaining a screenshot of the third target area through a calling interface, and the text image acquisition includes determining the third target area and acquiring a third image.

[0010] According to the online education system based on AI algorithm, the second recognition module includes: A second identity recognition unit, configured to detect the second image and preset facial features using a facial recognition model to determine the identity of the second user; A second image recognition unit, configured to classify and recognize the second image using a face recognition model to obtain a second image recognition result, wherein the second image recognition result includes a facial expression and a facial orientation; The third image recognition unit is used to recognize the third image by using an optical character detection model to obtain the third image recognition result.

[0011] According to the online education system based on AI algorithm, the teaching synchronization module also includes: A first synchronization unit is used to obtain keywords in the sound recognition result, perform a matching query from the first image recognition result, and if the match is successful, generate the teaching progress; otherwise, perform one of voice prompts and automatic jumps, wherein the automatic jump is an automatic setting; The second synchronization unit is used to perform a matching query with the third image recognition result according to the teaching progress to obtain learning progress synchronization information, wherein the learning progress synchronization information is used to characterize the immediacy of learning. If the match fails, a voice prompt and an automatic jump are performed, wherein the automatic jump is an automatic setting.

[0012] According to the online education system based on AI algorithm, the teaching evaluation module includes: The first concentration unit is used to determine the emotion of the first user according to the facial expression in a first preset time period, determine the learning seriousness of the first user according to the angle of the face facing the third target area, and obtain the first concentration according to the emotion and the learning seriousness.

[0013] a second concentration unit, configured to determine the second concentration of the first user according to the learning progress synchronization information in a first preset time period; The evaluation unit obtains the total scores of the first focus unit and the second focus unit in a second preset time period, and performs dynamic and customized query and display on the total scores.

[0014] According to the online education system based on the AI ​​algorithm, it also includes an online education resource module for dynamically and synchronously switching the online education resources between the first target area and the third target area.

[0015] Another aspect of the present invention also includes an online education device based on an AI algorithm, comprising: A sound collection device, used to obtain sound data of a first user, where the first user is used to represent a teaching leader; A first camera device, used to obtain a first image of a first target area of ​​a first user, where the first user is used to represent a teaching leader; A first client is used to recognize the sound data using a sound detection model to obtain a sound recognition result, and is used to detect the first image using a first recognition model to obtain a first image recognition result, wherein the first image recognition result is used to represent a text image recognition result; A second camera device is used to obtain a second image of a second target area of ​​a second user, the second user is used to represent the teaching object, and the second image is used to represent the face image; A third camera device, used to obtain a third image of a third target area of ​​the second user; The second client is used to detect the second image using a second recognition model to obtain a second image recognition result, and to detect the third image using a third recognition model to obtain a third image recognition result, wherein the second image recognition result is used to represent a face recognition result, and the third image recognition result is used to represent a text image recognition result; The server is used to determine the teaching progress according to the first image recognition result and the voice recognition result, synchronize the teaching progress of the teaching object according to the teaching progress and the third image recognition result, and determine the first concentration of the teaching object according to the face recognition result, and determine the second concentration of the teaching object according to the second image recognition result and the third image recognition result, and determine the teaching evaluation result of the teaching object according to the first concentration and the second concentration.

[0016] The beneficial effects of the present invention are as follows: the voice acquisition device and the camera device are used to acquire the teacher's voice and teaching information pictures, as well as the student's facial pictures and learning information pictures, and an AI-based analysis method is used to obtain the teaching and learning progress of the teacher and the student. The teacher's voice is used as the real-time learning progress, and the teaching information and the learning information are synchronized. At the same time, the student's concentration in each time period (such as 10 minutes) and each class (such as 45 minutes) is evaluated according to the synchronization status and the student's emotions, so that the teacher can obtain the student's learning progress in time, without the teacher having to check the camera and homework in real time, thereby improving the efficiency of online teaching. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which: Figure 1 It is a schematic diagram of an online education device based on AI algorithm according to an embodiment of the present invention.

[0018] Figure 2 It is a schematic diagram of an online education system based on AI algorithm according to an embodiment of the present invention.

[0019] Figure 3 It is a schematic diagram of a first acquisition module according to an embodiment of the present invention.

[0020] Figure 4 2 is a schematic diagram of a first identification module according to an embodiment of the present invention.

[0021] Figure 5 It is a schematic diagram of a second acquisition module according to an embodiment of the present invention.

[0022] Figure 6 2 is a schematic diagram of a second identification module according to an embodiment of the present invention.

[0023] Figure 7 Schematic diagram of a teaching synchronization module according to an embodiment of the present invention.

[0024] Figure 8 Schematic diagram of a teaching evaluation module according to an embodiment of the present invention.

[0025] Fig. 9 It is a schematic diagram of an online education system with an online education resource module added according to an embodiment of the present invention. DETAILED DESCRIPTION

[0026] The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions. In the subsequent description, the use of suffixes such as "module", "component" or "unit" used to represent elements is only for the purpose of facilitating the description of the present invention, and has no specific meaning in itself. Therefore, "module", "component" or "unit" can be used in a mixed manner. "First", "second" and the like are only used for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features or implicitly indicating the order of the indicated technical features. In this subsequent description, the continuous numbering of the method steps is for the convenience of review and understanding. In combination with the overall technical solution of the present invention and the logical relationship between the various steps, adjusting the implementation order between the steps will not affect the technical effect achieved by the technical solution of the present invention. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0027] Reference Figure 1 , Figure 1Schematic diagram of an online education device based on an AI algorithm according to an embodiment of the present invention, which includes a first client 100, a second client 200, and a server 300, wherein the client 100 is connected to a sound collection device 110 and a first camera device 120, and the server 300 is connected to the first client 100 and the second client 200 by remote communication, wherein the second client is connected to a second camera device 210 and a third camera device 230. Among them, the sound collection device 110 is used to obtain the sound data of the first user, and the first user is used to characterize the teaching leader; the first camera device 120 is used to obtain the first image of the first target area of ​​the first user, and the first user is used to characterize the teaching leader; the first client 100 is used to recognize the sound data using a sound detection model to obtain a sound recognition result, and is used to detect the first image using a first recognition model to obtain a first image recognition result, and the first image recognition result is used to characterize the text image recognition result; the second camera device 210 is used to obtain a second image of the second target area of ​​the second user, and the second user is used to characterize the teaching object, and the second image is used to characterize the face image; the third camera device 220 is used to obtain a third image of the third target area of ​​the second user; the first The client 200 is used to detect the second image using the second recognition model to obtain the second image recognition result, and to detect the third image using the third recognition model to obtain the third image recognition result. The second image recognition result is used to represent the face recognition result, and the third image recognition result is used for the text image recognition result. The server 300 is used to determine the teaching progress according to the first image recognition result and the sound recognition result, synchronize the teaching progress of the teaching object according to the teaching progress and the third image recognition result, and determine the first concentration of the teaching object according to the face recognition result, and determine the second concentration of the teaching object according to the second image recognition result and the third image recognition result, and determine the teaching evaluation result of the teaching object according to the first concentration and the second concentration.

[0028] In some embodiments, the teaching leader and the teaching object are teachers and students respectively.

[0029] In some embodiments, the first client and the second client are devices with camera and audio recording functions, such as a PC, a tablet computer, or a smart phone.

[0030] In some embodiments, the first recognition model, the second recognition model and the third recognition model are trained through corresponding data sets according to the collected data types.

[0031] In some embodiments, the shooting positions corresponding to the first camera device, the second camera device and the third camera device are the first target area, the second target area and the third target area respectively. For example, the first target area is the teacher's teaching area or textbook, the second target area is the user's face area, and the third target area is the student's learning area, such as a mobile phone screen or a book learning area.

[0032] Reference Figure 2 , Figure 2 It is a schematic diagram of an online education system based on an AI algorithm according to an embodiment of the present invention. It includes: a first acquisition module, which is used to obtain a first image and sound data of a first target area of ​​a first user, and the first user is used to characterize the teaching leader; a first recognition module, which is used to recognize the sound data using a sound detection model to obtain a sound recognition result, and is used to detect the first image using a first recognition model to obtain a first image recognition result, and the first image recognition result is used to characterize the text image recognition result; a second acquisition module, which is used to obtain a second image of a second target area of ​​a second user, and a third image of a third target area of ​​a second user, and the second user is used to characterize the teaching object, and the second image is used to characterize the face image; a second recognition module, which is used to detect the second image using a second recognition model , obtain a second image recognition result, and, be used to detect the third image using a third recognition model to obtain a third image recognition result, the second image recognition result is used to characterize the face recognition result, and the third image recognition result is used for the text image recognition result; a teaching synchronization module, according to the first image recognition result and the sound recognition result, determines the teaching progress, and synchronizes the teaching progress of the teaching object according to the teaching progress and the third image recognition result; a teaching evaluation module, for determining the first concentration of the teaching object according to the face recognition result, and, for determining the second concentration of the teaching object according to the second image recognition result and the third image recognition result, and determining the teaching evaluation result of the teaching object according to the first concentration and the second concentration.

[0033] In some embodiments, Figure 3 : is a schematic diagram of the first acquisition module. It includes: a first detection unit, used to identify the teaching mode of the first user, the teaching mode of the first user includes one of online classroom teaching and online e-learning; a sound acquisition unit, used to collect the voice of the first user to obtain sound data; a first image acquisition unit, used to perform one of text image call and text image acquisition according to the teaching mode of the first user to obtain a first image, the text image call includes obtaining a screenshot of the first target area through a calling interface, and the text image acquisition includes determining the first target area and acquiring the first image.

[0034] In some embodiments, the online classroom teaching of the teaching mode is a live real-time teaching method, such as the teacher teaching directly in the classroom or a similar location, and the first acquisition module collects pictures of the teacher's blackboard or textbook. It can be understood that the online electronic teaching is conducted through an interactive interface.

[0035] In some embodiments, it can be understood that the text image call is to take a screenshot of the teaching area of ​​the interactive interface by calling the device interface, and the text image acquisition is directly obtained by shooting with a camera.

[0036] In some embodiments, wherein Figure 4 It is a schematic diagram of a first recognition module, which includes: a first identity recognition unit, used to detect sound data using a voiceprint recognition model, and compare it with a preset voiceprint preset by the first user to determine the identity of the first user; a sound recognition unit, used to recognize the sound data using a sound detection model trained by a deep convolutional neural network and a Gaussian mixture model to obtain a sound recognition result; a first image recognition unit, used to recognize the first image using an optical character detection model to obtain a first image recognition result.

[0037] In some embodiments, the first recognition module also includes a sound image matching unit, which is used to obtain sound recognition results, determine the sound time period, match the first image recognition results and the sound recognition results according to the sound time period, and perform prompts or adjust the position of the first target area according to the matching results.

[0038] In some embodiments, wherein Figure 5 Schematic diagram of the second acquisition module. It includes: a second detection unit, used to identify the teaching mode of the second user, the teaching mode includes one of online classroom teaching and online e-learning; a second image acquisition unit, used to acquire the facial image of the second user of the user to obtain a second image; a third image acquisition unit, used to perform one of text image call and text image acquisition according to the teaching mode to obtain the second image, the text image call includes obtaining a screenshot of the third target area through the calling interface, and the text image acquisition includes determining the third target area and acquiring the third image.

[0039] In some embodiments, wherein Figure 6Schematic diagram of the second recognition module. It includes: a second identity recognition unit, which is used to detect the second image and preset facial features using a face recognition model to determine the identity of the second user; a second image recognition unit, which is used to classify and recognize the second image using a face recognition model to obtain a second image recognition result, and the second image recognition result includes facial expression and face orientation; a third image recognition unit, which is used to recognize the third image using an optical character detection model to obtain a third image recognition result.

[0040] In some embodiments, wherein Figure 7 Schematic diagram of teaching synchronization module. It includes: a first synchronization unit, which is used to obtain keywords in the sound recognition result, perform matching query from the first image recognition result, and generate teaching progress if the match is successful, otherwise, perform one of voice prompts and automatic jumps, where the automatic jump is automatically set; a second synchronization unit, which is used to perform matching query with the third image recognition result according to the teaching progress, obtain learning progress synchronization information, and the learning progress synchronization information is used to represent the immediacy of learning, and if the match fails, perform one of voice prompts and automatic jumps, where the automatic jump is automatically set.

[0041] In some embodiments, wherein Figure 8 Schematic diagram of teaching evaluation module. It includes: a first focus unit, which is used to determine the emotion of the first user according to the facial expression in the first preset time period, determine the learning seriousness of the first user according to the angle of the face facing the third target area, and obtain the first focus according to the emotion and learning seriousness; a second focus unit, which is used to determine the second focus of the first user according to the learning progress synchronization information in the first preset time period; an evaluation unit, which obtains the total score of the first focus unit and the second focus unit in the second preset time period, and performs dynamic and custom query display on the total score.

[0042] In some embodiments, wherein Fig. 9 A schematic diagram of an online education system with an online education resource module added, which is used to dynamically and synchronously switch online education resources between the first target area and the third target area.

[0043] In some selectable embodiments, the function / operation mentioned in the block diagram may not occur in the order mentioned in the operation diagram. For example, depending on the function / operation involved, the two boxes shown in succession can actually be executed substantially simultaneously or the boxes can sometimes be executed in reverse order. In addition, the embodiment presented and described in the flow chart of the present invention is provided by way of example, for the purpose of providing a more comprehensive understanding of technology. The disclosed method is not limited to the operation and logic flow presented herein. Selectable embodiments are expected, wherein the order of various operations is changed and the sub-operation of a part for which is described as a larger operation is performed independently.

[0044] The embodiment of the present invention also discloses a computer program product or a computer program, which includes a computer instruction stored in a computer-readable storage medium. The processor of the computer device can read the computer instruction from the computer-readable storage medium, and the processor executes the computer instruction, so that the computer device executes the aforementioned online education system based on the AI ​​algorithm.

[0045] In addition, although the present invention is described in the context of functional modules, it should be understood that, unless otherwise specified, one or more of the functions and / or features described may be integrated into a single physical device and / or software module, or one or more functions and / or features may be implemented in separate physical devices or software modules. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the present invention. More specifically, in view of the properties, functions, and internal relationships of the various functional modules in the device disclosed herein, the actual implementation of the module will be understood within the conventional skills of the engineer. Therefore, those skilled in the art can implement the present invention set forth in the claims without excessive experimentation using ordinary techniques. It is also understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present invention, which is determined by the full scope of the appended claims and their equivalents.

[0046] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0047] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0048] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0049] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0050] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0051] Although the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the claims and their equivalents.

[0052] The above is a specific description of the preferred implementation of the present invention, but the present invention is not limited to the described embodiments. Those skilled in the art may make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of this application.

Claims

1. An online education system based on AI algorithm, characterized in that: include: A first acquisition module, used to acquire first image and sound data of a first target area of ​​a first user, where the first user is used to represent a teaching leader; A first recognition module is used to recognize the sound data using a sound detection model to obtain a sound recognition result, and is used to detect the first image using a first recognition model to obtain a first image recognition result, wherein the first image recognition result is used to represent a text image recognition result; A second acquisition module is used to obtain a second image of a second target area of ​​a second user, and to obtain a third image of a third target area of ​​the second user, wherein the second user is used to represent a teaching object, and the second image is used to represent a face image; a second recognition module, configured to detect the second image using a second recognition model to obtain a second image recognition result, and to detect the third image using a third recognition model to obtain a third image recognition result, wherein the second image recognition result is used to represent a face recognition result, and the third image recognition result is used to represent a text image recognition result; A teaching synchronization module, which determines the teaching progress according to the first image recognition result and the sound recognition result, and synchronizes the teaching progress of the teaching object according to the teaching progress and the third image recognition result; A teaching evaluation module is used to determine a first concentration of the teaching object according to the face recognition result, and to determine a second concentration of the teaching object according to the second image recognition result and the third image recognition result, and to determine a teaching evaluation result of the teaching object according to the first concentration and the second concentration.

2. The online education system based on AI algorithm according to claim 1, characterized in that: The first acquisition module includes: A first detection unit is used to identify a teaching mode of the first user, where the teaching mode of the first user includes one of online classroom teaching and online e-learning; a sound collection unit, configured to collect the sound of the first user to obtain the sound data; The first image acquisition unit is used to perform a process of text image calling and text image acquisition according to the teaching mode of the first user to obtain a first image, the text image calling includes obtaining a screenshot of the first target area through a calling interface, and the text image acquisition includes determining the first target area and acquiring the first image.

3. The online education system based on AI algorithm according to claim 1, characterized in that: The first identification module comprises: A first identity recognition unit, configured to detect the sound data using a voiceprint recognition model, and compare the sound data with a preset voiceprint preset by the first user to determine the identity of the first user; A sound recognition unit, configured to recognize the sound data by using the sound detection model trained by using one of a deep convolutional neural network and a Gaussian mixture model to obtain the sound recognition result; The first image recognition unit is used to recognize the first image by using an optical character detection model to obtain the first image recognition result.

4. The online education system based on AI algorithm according to claim 3 is characterized in that: The first identification module also includes: The sound image matching unit is used to obtain the sound recognition result, determine the sound time period, match the first image recognition result with the sound recognition result according to the sound time period, and perform prompts or adjust the position of the first target area according to the matching results.

5. The online education system based on AI algorithm according to claim 1, characterized in that: The second acquisition module includes: a second detection unit, configured to identify a teaching mode of the second user, wherein the teaching mode includes one of online classroom teaching and online electronic teaching; A second image acquisition unit, configured to acquire a facial image of the second user of the user to obtain the second image; The third image acquisition unit is used to execute a process of text image calling and text image acquisition according to the teaching mode to obtain a second image. The text image calling includes obtaining a screenshot of the third target area through a calling interface, and the text image acquisition includes determining the third target area and acquiring a third image.

6. The online education system based on AI algorithm according to claim 1, characterized in that: The second identification module comprises: A second identity recognition unit, configured to detect the second image and preset facial features using a facial recognition model to determine the identity of the second user; A second image recognition unit is used to classify and recognize the second image using a face recognition model to obtain a second image recognition result, wherein the second image recognition result includes a facial expression and a facial orientation; The third image recognition unit is used to recognize the third image by using an optical character detection model to obtain the third image recognition result.

7. The online education system based on AI algorithm according to claim 6, characterized in that: The teaching synchronization module also includes: A first synchronization unit is used to obtain keywords in the sound recognition result, perform a matching query from the first image recognition result, and if the match is successful, generate the teaching progress; otherwise, perform one of voice prompts and automatic jumps, wherein the automatic jump is an automatic setting; The second synchronization unit is used to perform a matching query with the third image recognition result according to the teaching progress to obtain learning progress synchronization information, wherein the learning progress synchronization information is used to characterize the immediacy of learning. If the match fails, a voice prompt and an automatic jump are performed, wherein the automatic jump is an automatic setting.

8. The online education system based on AI algorithm according to claim 7, characterized in that: The teaching evaluation module includes: The first concentration unit is used to determine the emotion of the first user according to the facial expression in a first preset time period, determine the learning seriousness of the first user according to the angle of the face facing the third target area, and obtain the first concentration according to the emotion and the learning seriousness.

9. A second concentration unit, configured to determine the second concentration of the first user according to the learning progress synchronization information in a first preset time period; The evaluation unit obtains the total scores of the first focus unit and the second focus unit in a second preset time period, and performs dynamic and customized query and display on the total scores.

10. The online education system based on AI algorithm according to claim 1, characterized in that: It also includes an online education resource module for dynamically and synchronously switching online education resources between the first target area and the third target area.

11. An online education device based on AI algorithm, characterized in that: include: A sound collection device, used to obtain sound data of a first user, where the first user is used to represent a teaching leader; A first camera device, used to obtain a first image of a first target area of ​​a first user, where the first user is used to represent a teaching leader; A first client is used to recognize the sound data using a sound detection model to obtain a sound recognition result, and is used to detect the first image using a first recognition model to obtain a first image recognition result, wherein the first image recognition result is used to represent a text image recognition result; A second camera device is used to obtain a second image of a second target area of ​​a second user, the second user is used to represent the teaching object, and the second image is used to represent the face image; A third camera device, used to obtain a third image of a third target area of ​​the second user; The second client is used to detect the second image using a second recognition model to obtain a second image recognition result, and to detect the third image using a third recognition model to obtain a third image recognition result, wherein the second image recognition result is used to represent a face recognition result, and the third image recognition result is used to represent a text image recognition result; The server is used to determine the teaching progress according to the first image recognition result and the voice recognition result, synchronize the teaching progress of the teaching object according to the teaching progress and the third image recognition result, and determine the first concentration of the teaching object according to the face recognition result, and determine the second concentration of the teaching object according to the second image recognition result and the third image recognition result, and determine the teaching evaluation result of the teaching object according to the first concentration and the second concentration.

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