CN111833672B - Teaching video display method, device and system - Google Patents
Teaching video display method, device and system Download PDFInfo
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- CN111833672B CN111833672B CN202010776202.0A CN202010776202A CN111833672B CN 111833672 B CN111833672 B CN 111833672B CN 202010776202 A CN202010776202 A CN 202010776202A CN 111833672 B CN111833672 B CN 111833672B
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- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B5/00—Electrically-operated educational appliances
- G09B5/06—Electrically-operated educational appliances with both visual and audible presentation of the material to be studied
- G09B5/065—Combinations of audio and video presentations, e.g. videotapes, videodiscs, television systems
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- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B7/00—Electrically-operated teaching apparatus or devices working with questions and answers
- G09B7/02—Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by a student
Abstract
A teaching video display method, device and system are provided, the method comprises: collecting teaching video and voice of a teacher in a classroom to form teaching image data and audio data; identifying the teacher teaching voice content, the student question-asking voice content and the teacher answering voice content in the voice content, and separating to form independent multi-track teaching audio data; obtaining teaching audio-visual data; generating a teaching display video, and uploading the teaching display video to a teaching platform; the students communicate with the platform through the student terminals, and select a teaching display video to play so as to realize classroom reappearance. The invention provides a perfect teaching video learning method, combines an internet teaching platform, exerts the advantages of internet teaching, integrates the advantages of off-line learning and on-line learning, and is beneficial to obviously improving the student score.
Description
Technical Field
The invention relates to the technical field of internet, in particular to a teaching video display method, device and system.
Background
With the rapid development of information technology, the traditional learning mode of people is also greatly changed. The traditional classroom teaching mode inherently has a lot of advantages, but under the background of the current information era, the traditional classroom teaching mode is limited by time, place, teacher and resource and other aspects, so that the number of people who can really receive the teaching of excellent teachers is greatly limited, and meanwhile, due to the individual difference of students and the limitation of teacher knowledge, one-to-one targeted learning and assistance cannot be performed, so that the learning efficiency is not high.
The development of the internet technology brings huge changes to education, and the distance in space is continuously reduced by the network technology, so that teaching resources are shared more conveniently. On-site audio and video contents of classroom teaching, lectures, conferences and the like, even contents of integrated demonstration are manufactured into multimedia texts which are stored on a teaching server connected with the Internet, and users can online or review the teaching contents through the Internet at any time and any place by means of on-demand and live broadcasting technologies. With the help of the increasingly popular network, especially the mobile internet, users can conveniently develop online teaching, remote teaching, live classroom broadcast and the like through various internet. The system for live broadcasting and recording on the internet not only needs to record videos and audios of teaching, lectures and meetings, but also needs to be integrated with the content of demonstration, and needs relatively complex equipment and interactive cooperation.
The online learning fully utilizes the advantages of convenience and rapidness brought by information technology, breaks through the limitation of time, place and teacher resource, and provides a flexible and effective learning mode for students at any time and place. However, it should be noted that while students enjoy the convenience and rapidness of online learning, they also face some problems: students and teachers are connected through a network, and the teachers and the students are not in direct contact with each other and cannot deeply know each other; the flexibility of time arrangement causes some problems of real-time online interaction between teachers and students, and particularly the real-time property of teacher answering questions cannot be ensured; the flexibility of the study time of students is easy to disturb the rest time of teachers; due to the unfamiliarity between teachers and students, the inefficiency of communication and coaching between the two parties is easily caused.
The key point of the prior art lies in the realization of the network teaching process, including on-line live broadcast of a classroom, curriculum recording and the like, and for recorded and broadcast contents, no matter stored in a video form or a classified data stream form, the method aims to provide a way for students to review and consolidate the curriculum, emphasizes the possibility of autonomous learning, does not further process the recorded classroom teaching, does not pay attention to how to really realize the effect of the recorded curriculum, and does not pay attention to the actual effect of the recorded classroom teaching for review and consolidation of the curriculum.
Disclosure of Invention
The invention provides a teaching video display method, a device and a system, which change the traditional teaching mode and really bring the function and effect of a recorded classroom into play.
The invention provides a teaching video display method in a first aspect, which comprises the following steps:
step 1, collecting teaching videos of teachers in a classroom to form teaching image data; collecting classroom voices to form teaching audio data;
step 2, aiming at the teaching audio data, identifying the teacher teaching voice content, the student question-asking voice content and the teacher answer voice content in the teaching audio data, and separating to form independent multi-track teaching audio data;
Step 3, obtaining teaching audio-visual data based on the teaching image data and the multi-track teaching audio data;
step 4, generating a teaching display video according to the teaching audio-visual data, and uploading the teaching display video to a teaching platform;
step 5, the students communicate with the platform through the student end, and a teaching display video is selected for playing to realize classroom reappearance;
step 6, in the playing process of the teaching display video, the students select a digital note mode according to the requirements and record notes;
step 7, answering in class, and providing questions for students, wherein the platform provides answers for the students;
step 8, the students finish the online homework, and the platform gives out scores; for the test questions which are wrongly made, playing a teaching display video paragraph corresponding to the test questions by searching a test question association database; and the test question arrangement sequence of the online operation is consistent with the time sequence of the teaching key points in the teaching display video from shallow to deep.
The second aspect of the present invention provides a teaching video display system, including:
the acquisition unit is used for acquiring teaching videos of teachers in a classroom to form teaching image data; collecting classroom voices to form teaching audio data;
The recognition unit is used for recognizing the teacher teaching voice content, the student question-asking voice content and the teacher answering voice content in the teaching audio data and separating to form independent multi-track teaching audio data;
the integration unit is used for obtaining teaching audio-visual data based on the teaching image data and the multi-track teaching audio data;
the generating unit is used for generating a teaching display video according to the teaching audio-visual data and uploading the teaching display video to a teaching platform;
the playing unit is used for enabling students to communicate with the platform through the student end and selecting one teaching display video to play so as to realize classroom reproduction;
the note unit is used for recording notes by a student selecting a digital note mode according to requirements in the playing process of the teaching display video;
the answering unit is used for answering in class, the students put forward questions and the platform provides answers for the students;
the testing unit is used for the students to complete online homework, and the platform gives scores; for the test questions which are wrongly made, playing a teaching display video paragraph corresponding to the test questions by searching a test question association database; and the test question arrangement sequence of the online operation is consistent with the time sequence of the teaching key points in the teaching display video from shallow to deep.
The third aspect of the present invention provides a teaching video display system, including:
a storage unit for storing a computer-executable program;
and the processing unit is used for reading the computer executable program in the storage unit so as to execute the teaching video display method.
Compared with the prior art, the invention can realize the following beneficial effects:
firstly, the invention provides a perfect teaching video learning method, combines an internet teaching platform, exerts the advantages of internet teaching, especially integrates the advantages of offline and online learning through active learning in the stage of autonomous learning after class, and is beneficial to obviously improving the achievement of students.
Secondly, the invention not only can provide a complete teaching video, but also can lead students to mark and capture pictures according to the needs of the students, thereby facilitating the study of the students and the network teaching.
Thirdly, the problems are classified into corresponding categories through cluster analysis, keyword analysis, feature extraction, feature matching and problem classification, the problems proposed by students can be accurately matched with the teaching video paragraphs, relevant questioning videos can be played for the students more accurately or excellent teachers in relevant fields can be selected for answering questions on line, and the learning efficiency of the students is improved.
In addition, the invention gives students sufficient selection right, can not only select to accept the existing problematic questions and answers, but also meet the rapid requirement; the teacher can be required to provide one-to-one questions and answers, and diversified requirements are met;
finally, the invention focuses on course recording, associates the classroom explanation focus with the segmentation of the recorded data when the course is studied, and can also quickly display the teaching display video paragraph associated with the wrong test question, thereby carrying out targeted review.
Drawings
In order to make the technical problems solved by the present invention, the technical means adopted and the technical effects obtained more clear, the following will describe in detail the embodiments of the present invention with reference to the accompanying drawings. It should be noted, however, that the drawings described below are only illustrations of exemplary embodiments of the invention, from which other embodiments can be derived by those skilled in the art without inventive step.
Fig. 1 is a flowchart of a teaching video display method according to the present invention.
Fig. 2 is a schematic structural diagram of a teaching video display system according to the present invention.
Fig. 3 is a schematic structural diagram of a teaching video display device according to the present invention.
Fig. 4 is a schematic diagram of an application architecture of a teaching video display system according to the present invention.
Detailed Description
Exemplary embodiments of the present invention will now be described more fully hereinafter with reference to the accompanying drawings, in which exemplary embodiments of the invention may be embodied in many specific forms, and should not be construed as limited to the embodiments set forth herein. Rather, these exemplary embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the invention to those skilled in the art.
The structures, properties, effects or other characteristics described in a certain embodiment may be combined in any suitable manner in one or more other embodiments, while still complying with the technical idea of the invention.
In describing particular embodiments, specific details of structures, properties, effects, or other features are set forth in order to provide a thorough understanding of the embodiments by one skilled in the art. However, it is not excluded that a person skilled in the art may implement the invention in a specific case without the above-described structures, performances, effects or other features.
The flow chart in the drawings is only an exemplary flow demonstration, and does not represent that all the contents, operations and steps in the flow chart are necessarily included in the scheme of the invention, nor does it represent that the execution is necessarily performed in the order shown in the drawings. For example, some operations/steps in the flowcharts may be divided, some operations/steps may be combined or partially combined, and the like, and the execution order shown in the flowcharts may be changed according to actual situations without departing from the gist of the present invention.
As shown in fig. 1, the method for displaying a teaching video provided by the present invention includes:
step 1, collecting teaching videos of teachers in a classroom to form teaching image data; collecting classroom voices to form teaching audio data;
step 2, aiming at the teaching audio data, identifying the teacher teaching voice content, the student question-asking voice content and the teacher answer voice content in the teaching audio data, and separating to form independent multi-track teaching audio data;
step 3, obtaining teaching audio-visual data based on the teaching image data and the multi-track teaching audio data;
step 4, generating a teaching display video according to the teaching audio-visual data, and uploading the teaching display video to a teaching platform;
step 5, the students communicate with the platform through the student end, and a teaching display video is selected for playing to realize classroom reappearance;
step 6, in the playing process of the teaching display video, the students select a digital note mode according to the requirements and record notes;
step 7, answering in a classroom, providing questions for students, and providing answers for the students by the platform;
8, completing the online work of the students, and giving scores by the platform; for the test questions which are wrongly made, playing a teaching display video paragraph corresponding to the test questions by searching a test question association database; and the test question arrangement sequence of the online operation is consistent with the time sequence of the teaching key points in the teaching display video from shallow to deep.
Preferably, in step 4, the generating a teaching display video according to the teaching audiovisual data specifically includes:
cutting and marking the teaching audio-visual data according to the time sequence of the teaching key points in the teaching audio-visual data to form segmented marked audio-visual data corresponding to the teaching key points;
carrying out association processing on the segmented marked audio-visual data and the test questions to establish a test question association database;
carrying out voice recognition on the multi-track teaching audio data, and converting a voice recognition result into characters;
and establishing a time axis for the characters, embedding the time axis as a subtitle into the segmented marked audio-visual data, and generating a teaching display video.
Preferably, in the step 6, in the playing process of the teaching display video, the student selects a digital note mode according to the requirement and records the note;
the digital note modes include: a screenshot mode, a screen recording mode and a character mode;
when the screenshot mode is selected, the student end performs screenshot on the teaching display video according to a screenshot instruction sent by the student to generate a teaching screenshot note;
when the screen recording mode is selected, the student end starts to record the screen according to a video recording instruction sent by the student and stops recording the screen according to a stopping instruction sent by the student to generate a teaching screen recording note;
When the character mode is selected, the student end pops up a text recording box according to a character instruction sent by the student, synchronously displays the text recording box and the teaching display video, and is used for the student to record notes, simultaneously marks the current frame image of the teaching display video, and associates the marked frame image with the character record.
Preferably, in step 7, the classroom answers the questions, the students ask questions, and the platform provides answers for the students, specifically including:
step 7-1, performing keyword analysis based on the questions provided by the students, performing feature extraction and feature matching on the questions, and classifying the questions into corresponding topics;
7-2, searching student question voice contents and teacher answer voice contents containing the same or similar subjects in the teaching display video;
7-3, generating a first answering order based on the searched student question voice content and the found teacher answering voice content, and returning to the student;
7-4, waiting for the student to reply; if the student accepts the first answer order, then step 7-8 is entered; if the student refuses, entering step 7-5;
7-5, finding out a teacher with the highest association degree with the problem theme proposed by the student according to the association degree calculation method;
7-6, generating a second answer order containing the question based on the question, and pushing the second answer order to the students and the teachers;
7-7, establishing network communication between a student end and a teacher end after the answer order is determined to be effective so that the teacher can answer questions to the students;
and 7-8, after the completion of the answering order is determined, mutually scoring the students and the teachers, and updating the scores to the associated information to be used as a basis for calculating the association degree.
Preferably, in the step 7-1, keyword analysis is performed on the questions posed by the students, feature extraction and feature matching are performed on the questions, and the questions are classified into corresponding topics, which specifically includes:
step 7-1-1, obtaining the text recognition results of the student questioning voice content and the teacher answering voice content in the voice recognition of the multi-track teaching audio data;
7-1-2, extracting keywords from the characters, performing clustering analysis, and classifying question voices and question answering voices into a plurality of subjects;
preferably, in one embodiment, the words are segmented from the word recognition result data of the student question voice content and the teacher answer voice content, and the keywords are extracted from the word recognition result after the word segmentation processing and are converted into the vector. And carrying out clustering analysis on the vectors to form a plurality of problem subjects. For example, a method for calculating the volume of a cylinder, a method for calculating the area of a cylinder side, a method for calculating the volume of a cone, a method for calculating the area of a cone side, a method for calculating the volume of a circular truncated cone, and a method for calculating the area of a circular truncated cone of a problem which is presented by a student in a video classify the problem subjects through cluster analysis.
Vectorization of keywords, i.e., the use of numerical features to represent text, because computers cannot directly understand human-created languages and words. In order to make a computer understand text, the text information needs to be mapped into a numerical semantic space, which we can refer to as a word vector space. There are many algorithms for converting text into vectors, such as TF-IDF, BOW, One-Hot, word2vec, etc. In the embodiment, the vectorization of the text adopts a word2vec algorithm, the word2vec model is an unsupervised learning model, and the mapping of the text information to the semantic space can be realized by using the training of an unmarked corpus. Teachers accumulate a large amount of historical teaching text data in long-term teaching activities, and the historical teaching text data can be used as corpora for word2vec model training.
After the vectorization of the text is completed, the vectors need to be subjected to cluster analysis, and there are many kinds of algorithm models for performing cluster analysis, such as: LDA, LSI, SVM, Chameleon algorithm model. In the present embodiment, a TextCNN model based on deep learning is used. The TextCNN model includes an input layer, a convolutional layer, a pooling layer, and a fully-connected layer. Clustering analysis work is completed through the textCNN model based on deep learning, and a teacher does not need to classify question or teaching text data, so that the work of the teacher is reduced, and the working pressure of the teacher is relieved.
7-1-3, setting a plurality of keywords which embody the characteristics of each type of theme, and establishing an index table of the keywords;
and 7-1-4, extracting keywords of the problem proposed by the current student, searching and traversing an index table of each problem topic, counting the number of keyword matches, finding out the topic with the most keyword matches, and classifying the problem into the corresponding topics.
In another embodiment, on the basis of the above technical solution, the step 7-1-4 may also implement matching between the question and the corresponding topic by using a topic matching model. The theme matching model comprises a coding layer and a matching layer, wherein the coding layer is used for converting input characters into sentence vectors, and the matching layer is used for matching calculation among the sentence vectors. The input interfaces of the coding layer are multiple, wherein one interface is used for inputting students' questions, and the other interfaces are used for inputting determined question topics.
In the above embodiment, preferably, the coding layer adopts a bidirectional long and short term memory network model. The bidirectional long-short term memory network model is one of the cyclic neural networks, and can better consider words before and after a sentence, such as 'I do not feel the good look of clothes', wherein 'not' is to limit the good look of clothes at the back and shows the negation of the good look of clothes, the dependence relationship of a longer distance can be better captured by adopting the bidirectional long-short term memory network model, and the bidirectional long-short term memory network model can also consider the limitation of the words at the back to words at the front, such as 'the cup is beautiful and not going', wherein 'not going' is the modification and limitation of 'beautiful'. In the present embodiment, the bidirectional long-term and short-term memory network model is trained by using a history dialogue record as training data in a supervised learning manner.
In the above embodiment, preferably, the number of the input interfaces of the coding layer is four, the first of the four input interfaces is a question input by a student, and the last three input interfaces are standard question sentences selected from the question topics obtained by the cluster analysis. Through the operation of the bidirectional long-term and short-term memory network model, the coding layer outputs sentence vectors corresponding to the four question sentences. In other embodiments, more input interfaces may be provided, or a traversal manner may be adopted to traverse the standard question sentences in the standard question sentence set to match the closest standard question sentence.
In the above embodiment, preferably, the matching layer calculates the matching degree between the sentence vectors of the student question sentences and the sentence vectors of the standard question sentences by using a cosine algorithm. The problem provided by the student is calculated to be closest to the calculation method of the circular truncated cone side area, so that the content which the student wants to learn is determined to be the calculation method of the circular truncated cone side area.
As shown in fig. 2, the present invention provides a teaching video display system, which includes:
the acquisition unit is used for acquiring teaching videos of teachers in a classroom to form teaching image data; collecting classroom voices to form teaching audio data;
the recognition unit is used for recognizing the teacher teaching voice content, the student question-asking voice content and the teacher answering voice content in the teaching audio data and separating to form independent multi-track teaching audio data;
The integration unit is used for obtaining teaching audio-visual data based on the teaching image data and the multi-track teaching audio data;
the generating unit is used for generating a teaching display video according to the teaching audio-visual data and uploading the teaching display video to a teaching platform;
the playing unit is used for enabling students to communicate with the platform through the student end and selecting one teaching display video to play so as to realize classroom reproduction;
the note unit is used for enabling students to select a digital note mode according to requirements and record notes in the playing process of the teaching display video;
the answering unit is used for answering in class, the students put forward questions and the platform provides answers for the students;
the testing unit is used for the students to complete online homework, and the platform gives scores; for the test questions which are wrongly made, playing a teaching display video paragraph corresponding to the test questions by searching a test question association database; and the test question arrangement sequence of the online operation is consistent with the time sequence of the teaching key points in the teaching display video from shallow to deep.
Preferably, the generating unit is configured to generate a teaching display video according to the teaching audiovisual data, and specifically includes:
The cutting unit is used for cutting and marking the teaching audio-visual data according to the time sequence of the teaching key points in the teaching audio-visual data to form segmented marked audio-visual data corresponding to the teaching key points;
the association unit is used for associating the sectional marked audio-visual data with the test questions and establishing a test question association database;
the voice unit is used for carrying out voice recognition on the multi-track teaching audio data and converting a voice recognition result into characters;
and the caption unit is used for establishing a time axis for the characters, embedding the time axis as a caption into the segmented marked audio-visual data and generating a teaching display video.
Preferably, the note unit is used for recording notes in a manner that students select digital notes according to requirements in the playing process of teaching display videos;
the digital note modes include: a screenshot mode, a screen recording mode and a character mode;
the note unit specifically comprises:
the screenshot unit is used for carrying out screenshot on the teaching display video by the student end according to a screenshot instruction sent by the student when the screenshot mode is selected, and a teaching screenshot note is generated;
the screen recording unit is used for starting screen recording according to a video recording instruction sent by a student and stopping screen recording according to a stopping instruction sent by the student to generate a teaching screen recording note when the screen recording mode is selected;
And the text unit is used for popping up a text recording box according to a text instruction sent by a student when a text mode is selected, synchronously displaying the text recording box with the teaching display video, recording notes by the student, marking the current frame image of the teaching display video, and associating the marked frame image with the text recording.
Preferably, the answering unit is used for answering in class, the student proposes the question, and the platform provides the answer for the student, specifically includes:
the classification unit is used for carrying out keyword analysis based on the questions provided by the students, carrying out feature extraction and feature matching on the questions and classifying the questions into corresponding topics;
the searching unit is used for searching student question-asking voice contents and teacher question-answering voice contents containing the same or similar subjects in the teaching display video;
the first order unit is used for generating a first answer order based on the found student question-asking voice content and the found teacher answer voice content and returning the first answer order to the student;
the judging unit is used for waiting for the student to reply; executing a scoring unit if the student accepts the first answer order; if the student refuses, executing an association calculation unit;
The association calculation unit is used for finding out a teacher with the highest association degree with the problem theme proposed by the student according to the association degree calculation method;
the second order unit is used for generating a second answer order containing the question based on the question and pushing the second answer order to the students and the teachers;
the communication unit is used for establishing network communication between the student end and the teacher end after the answering order is confirmed to take effect so that the teacher can answer questions to the students conveniently;
and the scoring unit is used for determining that the students and the teachers score each other after the answering orders are finished, and updating the scores to the associated information to be used as a basis for calculating the association degree.
Preferably, the classifying unit is configured to perform keyword analysis on a question posed by a student, perform feature extraction and feature matching on the question, and classify the question into a corresponding topic, and specifically includes:
the character acquisition unit is used for acquiring character recognition results of the student question voice content and the teacher question answering voice content in the voice recognition of the multi-track teaching audio data;
the question classification unit is used for extracting keywords from the characters, carrying out clustering analysis and classifying question voices and question answering voices into a plurality of subjects;
Preferably, in one embodiment, the words are segmented from the word recognition result data of the student question voice content and the teacher answer voice content, and the keywords are extracted from the word recognition result after the word segmentation processing and are converted into the vector. And carrying out clustering analysis on the vectors to form a plurality of problem subjects. For example, a method for calculating the volume of a cylinder, a method for calculating the area of a cylinder side, a method for calculating the volume of a cone, a method for calculating the area of a cone side, a method for calculating the volume of a circular truncated cone, and a method for calculating the area of a circular truncated cone of a problem which is presented by a student in a video classify the problem subjects through cluster analysis.
Vectorization of keywords, i.e., representing text using numerical features, because computers cannot directly understand human-created languages and words. In order to make a computer understand text, the text information needs to be mapped into a numerical semantic space, which we can refer to as a word vector space. There are many algorithms for converting text into vectors, such as TF-IDF, BOW, One-Hot, word2vec, etc. In the embodiment, the vectorization of the text adopts a word2vec algorithm, the word2vec model is an unsupervised learning model, and the mapping of the text information to the semantic space can be realized by using the training of an unmarked corpus. Teachers accumulate a large amount of historical teaching text data in long-term teaching activities, and the historical teaching text data can be used as corpora for word2vec model training.
After the vectorization of the text is completed, the vectors need to be subjected to cluster analysis, and there are many kinds of algorithm models for performing cluster analysis, such as: LDA, LSI, SVM, Chameleon algorithm model. In the present embodiment, a TextCNN model based on deep learning is used. The TextCNN model includes an input layer, a convolutional layer, a pooling layer, and a fully-connected layer. The clustering analysis work is completed through the textCNN model based on deep learning, and a teacher does not need to classify questions or teaching text data, so that the work of the teacher is reduced, and the working pressure of the teacher is relieved.
The index establishing unit is used for setting a plurality of keywords which embody the characteristics of each type of theme and establishing an index table of the keywords;
the searching and matching unit is used for extracting keywords of the problems proposed by the current students, searching and traversing an index table of each problem topic, counting the number of keyword matches, finding out the topic with the most keyword matches, and classifying the problems into the corresponding topics.
In another embodiment, on the basis of the above technical solution, the searching matching unit may also use a topic matching model to implement matching between the question and the corresponding topic. The theme matching model comprises a coding layer and a matching layer, wherein the coding layer is used for converting input characters into sentence vectors, and the matching layer is used for matching calculation among the sentence vectors. The input interfaces of the coding layer are multiple, one of the input interfaces is used for inputting the student questions, and the other input interfaces are used for inputting the determined question topics.
In the above embodiment, preferably, the coding layer adopts a bidirectional long and short term memory network model. The bidirectional long-short term memory network model is one of the cyclic neural networks, and can better consider words before and after a sentence, such as 'I do not feel the good look of clothes', wherein 'not' is to limit the good look of clothes at the back and shows the negation of the good look of clothes, the dependence relationship of a longer distance can be better captured by adopting the bidirectional long-short term memory network model, and the bidirectional long-short term memory network model can also consider the limitation of the words at the back to words at the front, such as 'the cup is beautiful and not going', wherein 'not going' is the modification and limitation of 'beautiful'. In the present embodiment, the bidirectional long-term and short-term memory network model is trained by using a history dialogue record as training data in a supervised learning manner.
In the above embodiment, preferably, the number of the input interfaces of the coding layer is four, the first of the four input interfaces is a question input by a student, and the last three input interfaces are standard question sentences selected from the question topics obtained by the cluster analysis. Through the operation of the bidirectional long-term and short-term memory network model, the coding layer outputs sentence vectors corresponding to the four question sentences. In other embodiments, more input interfaces may be provided, or a traversal manner may be adopted to traverse the standard question sentences in the standard question sentence set to match the closest standard question sentence.
In the above embodiment, preferably, the matching layer calculates the matching degree between the sentence vectors of the student question sentences and the sentence vectors of the standard question sentences by using a cosine algorithm. The problem provided by the student is calculated to be closest to the calculation method of the circular truncated cone side area, so that the content which the student wants to learn is determined to be the calculation method of the circular truncated cone side area.
As shown in fig. 3, the present invention provides a display device for teaching videos, which includes:
a storage unit for storing a computer-executable program;
and the processing unit is used for reading the computer executable program in the storage unit so as to execute the teaching video display method.
In one embodiment, the apparatus for presenting instructional video further comprises a bus 330 connecting the various system components (including the memory unit 320 and the processing unit 310), a display unit 340, and the like.
The storage unit 320 stores a computer readable program, which may be a code of a source program or a read-only program. The program may be executed by the processing unit 310 such that the processing unit 310 performs the steps of various embodiments of the present invention. For example, the processing unit 310 may perform the steps shown in fig. 1.
The storage unit 320 may include readable media in the form of volatile storage units, such as a random access memory unit (RAM)3201 and/or a cache storage unit 3202, and may further include a read only memory unit (ROM) 3203. The storage unit 320 may also include a program/utility 3204 having a set (at least one) of program modules 3205, such program modules 3205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.
The network environment based learning aid 300 may also communicate with one or more external devices 370 (e.g., keyboard, display, network device, bluetooth device, etc.) such that a user may interact with the processing unit 310 via input/output (I/O) interfaces 350 via these external devices 370, and may also communicate with one or more networks (e.g., Local Area Network (LAN), Wide Area Network (WAN), and/or a public network, such as the internet, via network adapter 360. The network adapter 360 may communicate with other modules of the network environment based learning aid 300 via a bus. It should be appreciated that, although not shown in the figures, other hardware and/or software modules may be used in the network environment based learning aid 300, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
As shown in fig. 4, the application framework of the teaching video display system provided by the present invention includes: teacher end, student end, keeper end, platform end, educational administration end. Users with different identities log in by using the personal side to realize different operation functions.
Therefore, compared with the prior art, the invention can realize the following beneficial effects:
firstly, the invention provides a perfect teaching video learning method, combines an internet teaching platform, exerts the advantages of internet teaching, especially integrates the advantages of offline and online learning by active learning in the stage of autonomous learning after class, and is beneficial to obviously improving the achievement of students.
Secondly, the invention not only can provide a complete teaching video, but also can lead students to mark and capture pictures according to the needs of the students, thereby facilitating the study of the students and the network teaching.
Thirdly, the problems are classified into corresponding categories through cluster analysis, keyword analysis, feature extraction, feature matching and problem classification, the problems proposed by students can be accurately matched with the teaching video paragraphs, relevant questioning videos can be played for the students more accurately or excellent teachers in relevant fields can be selected for answering questions on line, and the learning efficiency of the students is improved.
In addition, the invention gives students sufficient selection right, can not only select to accept the existing problematic questions and answers, but also meet the rapid requirement; the teacher can be required to provide one-to-one questions and answers, and diversified requirements are met;
finally, the invention focuses on course recording, associates the classroom explanation focus with the segmentation of the recorded data when the course is studied, and can also quickly display the teaching display video paragraph associated with the wrong test question, thereby carrying out targeted review.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments of the present invention described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiment of the present invention can be embodied in the form of a software product, which can be stored in a computer-readable storage medium (which can be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to make a data processing device (which can be a personal computer, a server, or a network device, etc.) execute the above-mentioned method according to the present invention.
The invention may be implemented as a method, apparatus, electronic device, or computer-readable medium executing a computer program. Some or all of the functions of the present invention may be implemented in practice using a general-purpose data processing device such as a micro processing unit or a digital signal processing unit (DSP).
While the foregoing embodiments have described the objects, aspects and advantages of the present invention in further detail, it should be understood that the present invention is not inherently related to any particular computer, virtual machine or electronic device, and various general-purpose machines may be used to implement the present invention. The invention is not to be considered as limited to the specific embodiments thereof, but is to be understood as being modified in all respects, all changes and equivalents that come within the spirit and scope of the invention.
Claims (7)
1. A teaching video display method is characterized by comprising the following steps:
step 1, collecting teaching videos of teachers in a classroom to form teaching image data; collecting classroom voices to form teaching audio data;
step 2, aiming at the teaching audio data, identifying teacher teaching voice content, student question-asking voice content and teacher answer voice content in the teaching audio data, and performing voice separation to form independent multi-track teaching audio data;
step 3, obtaining teaching audio-visual data based on the teaching image data and the multi-track teaching audio data;
step 4, generating a teaching display video according to the teaching audio-visual data, and uploading the teaching display video to a teaching platform;
Step 5, the students communicate with the platform through the student end, and a teaching display video is selected for playing to realize classroom reappearance;
step 6, in the playing process of the teaching display video, the students select a digital note mode according to the requirements and record notes;
step 7, answering in a classroom, submitting a question for a student, and providing the answer for the student by the platform;
8, completing the online work of the students, and giving scores by the platform; for the test questions which are wrongly made, playing a teaching display video paragraph corresponding to the test questions by searching a test question association database; the test question arrangement sequence of the online operation is consistent with the time sequence of the teaching key points in the teaching display video;
wherein, step 7, the classroom is answered the question, and the student proposes the problem, and the platform provides the answer for the student, specifically includes:
step 7-1, performing keyword analysis based on the questions provided by the students, performing feature extraction and feature matching on the questions, and classifying the questions into corresponding topics;
7-2, searching student question voice contents and teacher answer voice contents containing the same or similar subjects in the teaching display video;
7-3, generating a first answering order based on the searched student question voice content and the found teacher answering voice content, and returning to the student;
Step 7-4, waiting for the student to reply; if the student accepts the first answer order, then step 7-8 is entered; if the student refuses, entering step 7-5;
7-5, finding out a teacher with the highest association degree with the problem theme proposed by the student according to the association degree calculation method;
7-6, generating a second answer order containing the question based on the question, and pushing the second answer order to the students and the teachers; 7-7, establishing network communication between a student end and a teacher end after the answer order is determined to be effective so that the teacher can answer questions to the students;
7-8, after the completion of the answering order is determined, mutually scoring the students and the teachers, and updating the scores to association information to be used as a basis for calculating the association degree;
step 7-1, keyword analysis is performed based on the questions posed by the students, feature extraction and feature matching are performed on the questions, and the questions are classified into corresponding topics, which specifically includes:
step 7-1-1, obtaining the text recognition results of the student questioning voice content and the teacher answering voice content in the voice recognition of the multi-track teaching audio data;
7-1-2, extracting keywords from the characters, performing clustering analysis, and classifying question voices and question answering voices into a plurality of subjects;
7-1-3, setting a plurality of keywords for embodying the characteristics of each type of theme, and establishing an index table of the keywords;
and 7-1-4, extracting keywords of the problems proposed by the current students, searching and traversing an index table of each problem topic, counting the number of keyword matches, finding out the topic with the most keyword matches, and classifying the problems to the corresponding topics.
2. The method according to claim 1, wherein said step 4 of generating an instructional presentation video based on said instructional audiovisual data specifically comprises:
cutting and marking the teaching audio-visual data according to the time sequence of the teaching key points in the teaching audio-visual data to form segmented marked audio-visual data corresponding to the teaching key points;
performing association processing on the segmented marked audio-visual data and test questions to establish a test question association database;
carrying out voice recognition on the multi-track teaching audio data, and converting a voice recognition result into characters;
and establishing a time axis for the characters, embedding the time axis as a subtitle into the segmented marked audio-visual data, and generating a teaching display video.
3. The method according to claim 1, wherein in the step 6, in the playing process of the teaching demonstration video, students select a digital note mode according to requirements and record notes;
The digital note modes include: a screenshot mode, a screen recording mode and a character mode;
when the screenshot mode is selected, the student end performs screenshot on the teaching display video according to a screenshot instruction sent by the student to generate a teaching screenshot note;
when the screen recording mode is selected, the student end starts to record the screen according to a video recording instruction sent by the student and stops recording the screen according to a stopping instruction sent by the student to generate a teaching screen recording note;
when the character mode is selected, the student end pops up a text recording box according to a character instruction sent by the student, synchronously displays the text recording box and the teaching display video, and is used for the student to record notes, simultaneously marks the current frame image of the teaching display video, and associates the marked frame image with the character record.
4. A display system for teaching video, comprising:
the acquisition unit is used for acquiring teaching videos of teachers in a classroom to form teaching image data; collecting classroom voices to form teaching audio data;
the recognition unit is used for recognizing the teacher teaching voice content, the student question-asking voice content and the teacher answering voice content in the teaching audio data, and voice separation is carried out to form independent multi-track teaching audio data;
The integration unit is used for obtaining teaching audio-visual data based on the teaching image data and the multi-track teaching audio data;
the generating unit is used for generating a teaching display video according to the teaching audio-visual data and uploading the teaching display video to a teaching platform;
the playing unit is used for enabling students to communicate with the platform through the student end and selecting one teaching display video to play so as to realize classroom reproduction; the note unit is used for recording notes by a student selecting a digital note mode according to requirements in the playing process of the teaching display video; the answering unit is used for answering in class and submitting questions for students, and the platform provides answers for the students;
the testing unit is used for the students to complete online homework, and the platform gives scores; for the test questions which are wrongly made, playing a teaching display video paragraph corresponding to the test questions by searching a test question association database; the test question arrangement sequence of the online operation is consistent with the time sequence of the teaching key points in the teaching display video;
wherein, the unit of answering for the classroom is answered in the doubt, and the student proposes the problem, and the platform specifically includes for the student provides the answer:
the classification unit is used for carrying out keyword analysis on the problems provided by students, carrying out feature extraction and feature matching on the problems and classifying the problems into corresponding subjects;
The searching unit is used for searching student question-asking voice contents and teacher answer voice contents containing the same or similar subjects in the teaching display video;
the first order unit is used for generating a first answer order based on the searched student question voice content and the found teacher answer voice content and returning the first answer order to the student;
the judging unit is used for waiting for the student to reply; executing a scoring unit if the student accepts the first answer order; if the student refuses, executing an association calculation unit;
the association calculation unit is used for finding out a teacher with the highest association degree with the problem theme proposed by the student according to the association degree calculation method;
the second order unit is used for generating a second answer order containing the question based on the question and pushing the second answer order to the students and the teachers;
the communication unit is used for establishing network communication between the student end and the teacher end after the answering order is confirmed to take effect so that the teacher can answer questions to the students conveniently;
the scoring unit is used for determining that the students and the teachers score each other after the answering orders are finished, and updating the scores to the associated information to be used as a basis for calculating the association degree;
The classification unit is used for performing keyword analysis on the questions provided by the students, performing feature extraction and feature matching on the questions, and classifying the questions into corresponding topics, and specifically comprises the following steps:
the character acquisition unit is used for acquiring character recognition results of the student question voice content and the teacher answer voice content in the voice recognition of the multi-track teaching audio data;
the question classification unit is used for extracting keywords from the characters, carrying out clustering analysis and classifying question voices and question answering voices into a plurality of subjects;
the index establishing unit is used for setting a plurality of keywords which embody the characteristics of each type of theme and establishing an index table of the keywords; the searching and matching unit is used for extracting keywords of the problems proposed by the current students, searching and traversing an index table of each problem topic, counting the number of keyword matches, finding out the topic with the most keyword matches, and classifying the problems into the corresponding topics.
5. The system according to claim 4, wherein the generating unit is configured to generate an instructional presentation video according to the instructional audiovisual data, and specifically includes:
the cutting unit is used for cutting and marking the teaching audio-visual data according to the time sequence of the teaching key points in the teaching audio-visual data to form segmented marked audio-visual data corresponding to the teaching key points;
The association unit is used for associating the segmented marked audio-visual data with the test questions to establish a test question association database;
the voice unit is used for carrying out voice recognition on the multi-track teaching audio data and converting a voice recognition result into characters;
and the caption unit is used for establishing a time axis for the characters, embedding the time axis as a caption into the segmented marked audio-visual data and generating a teaching display video.
6. The system of claim 5, wherein the note unit is configured to record a note by selecting a digital note manner according to a requirement by a student during playing of the teaching demonstration video;
the digital note modes include: a screenshot mode, a screen recording mode and a character mode; the note unit specifically comprises: the screenshot unit is used for carrying out screenshot on the teaching display video by the student end according to a screenshot instruction sent by the student when the screenshot mode is selected, and a teaching screenshot note is generated;
the screen recording unit is used for starting screen recording according to a video recording instruction sent by a student and stopping screen recording according to a stopping instruction sent by the student to generate a teaching screen recording note when the screen recording mode is selected;
and the text unit is used for popping up a text recording box according to a text instruction sent by a student when a text mode is selected, synchronously displaying the text recording box with the teaching display video, recording notes by the student, marking the current frame image of the teaching display video, and associating the marked frame image with the text recording.
7. A display system for teaching video, comprising:
a storage unit for storing a computer executable program;
a processing unit for reading the computer executable program in the storage unit to execute the teaching video display method of any one of claims 1 to 3.
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| CN113099256B (en) * | 2021-04-01 | 2022-11-08 | 读书郎教育科技有限公司 | Method and system for playing back videos and adding voice notes in smart class |
| CN113301369B (en) * | 2021-05-20 | 2022-11-25 | 读书郎教育科技有限公司 | Interaction system and method for recorded and broadcast videos in intelligent classroom |
| CN114077707A (en) * | 2021-11-19 | 2022-02-22 | 北京伟开赛德科技发展有限公司 | Network education system for realizing personalized teaching mode and operation method thereof |
| CN113936512B (en) * | 2021-12-17 | 2022-03-01 | 正方软件股份有限公司 | Remote teaching method and system for colleges and universities |
| CN114444982B (en) * | 2022-04-07 | 2022-07-01 | 牛剑教育科技(深圳)有限公司 | Teaching quality monitoring system based on internet education |
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