CN115240485A - Teaching live broadcast method based on artificial intelligence - Google Patents
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Abstract
The invention discloses a teaching live broadcast method based on artificial intelligence, which comprises the following steps: processing the teaching courseware based on an artificial intelligence technology to form a voice format file of the teaching courseware; in the teaching live broadcast process, recording a teaching site in a camera shooting mode to form a live broadcast video; setting a teaching field area and a teaching courseware area on a teaching live broadcast picture displayed by a teaching live broadcast receiving end; the live broadcast video is displayed in the teaching field area, and the teaching courseware is displayed in the teaching courseware area; in the teaching live broadcast process, the live broadcast video and the teaching courseware are synchronized based on the artificial intelligence technology and the voice format file of the teaching courseware.
Description
Technical Field
The invention relates to a teaching live broadcast method, in particular to a teaching live broadcast method based on artificial intelligence.
Background
With the rapid development of information technology, especially from the internet to the mobile internet, cross-space life, work and learning modes are created, and the mode of acquiring knowledge is fundamentally changed. The teaching and learning can be free from the limitation of time, space and place conditions, and the knowledge acquisition channel is flexible and diversified.
Distance education is an education form that students and teachers, students and education organizations mainly adopt various media ways to carry out system teaching and communication connection, and is education for delivering courses to one or more students outside a campus. Modern distance education refers to education in which courses are delivered outside the campus via audio, video (live or video) and computer technologies including real-time and non-real-time. Modern distance education is a new education mode generated along with the development of modern information technology. The development of computer technology, multimedia technology and communication technology, especially the rapid development of the Internet, makes the means of remote education have qualitative leap and become remote education under the condition of high and new technology. Modern distance education is mainly based on modern distance education means, and is compatible with traditional teaching forms such as face teaching, letter teaching and self-learning, and an education mode of optimized combination of various media. The current common mode is a direct teaching broadcast mode.
However, the existing teaching live broadcast has the problem that the teaching courseware and the live broadcast content can not be automatically synchronized.
Disclosure of Invention
The invention provides a teaching live broadcast method based on artificial intelligence, which aims to solve the problems in the prior art.
The invention provides a teaching live broadcast method based on artificial intelligence, which comprises the following steps:
s100, processing the teaching courseware based on an artificial intelligence technology to form a voice format file of the teaching courseware;
s200, in the teaching live broadcast process, recording a teaching site in a shooting mode to form a live broadcast video;
s300, setting a teaching field area and a teaching courseware area on a teaching live broadcast picture displayed by a teaching live broadcast receiving end; the live broadcast video is displayed in the teaching field area, and the teaching courseware is displayed in the teaching courseware area;
s400, in the teaching live broadcast process, the live broadcast video and the teaching courseware are synchronized based on the artificial intelligence technology and the voice format file of the teaching courseware.
Preferably, the S100 includes:
s101, making teaching courseware, wherein each page of the teaching courseware is provided with marking information, and the standard information comprises: labeling the subject name, a plurality of keywords and chapter information of the corresponding page, or labeling the page number of the corresponding page;
s102, forming a voice format file corresponding to the teaching courseware based on a character-to-audio artificial intelligence synthesis method; the voice format file comprises audio information corresponding to the marking information on each page.
Preferably, the S400 includes:
s401, collecting the on-site sound of a teacher in a live video in real time in the live video process;
s402, setting the audio information including the label information as the opposite side;
s403, judging whether the collected field voice information is matched with the labeled information in the audio information or not by adopting an artificial intelligence comparison method, if so, executing a step S404, and if not, executing a step S405;
s404, turning pages of the teaching courseware to corresponding pages marked with information in an artificial intelligence control mode;
s405, the teaching courseware is not processed, and the teaching courseware is in the current state; or turning the teaching courseware to the standby page.
Preferably, the S404 includes:
s4041, constructing an index relation between the labeling information and the page number on each page of the teaching courseware in an index database;
s4042, quickly retrieving the page number of the corresponding teaching courseware in the index database by adopting an artificial intelligence control mode according to the standard information in the field voice information;
s4043, controlling the teaching courseware to turn pages to corresponding pages according to the searched pages of the teaching courseware.
Preferably, the S404 further includes:
s4044, turning the teaching courseware page by page backwards or forwards in an artificial intelligent control mode;
s4045, the teaching courseware is turned backwards or forwards in a page skipping mode in an artificial intelligent control mode.
Preferably, the turning the teaching courseware to the standby page in S405 includes:
s4051, jumping the teaching courseware to a general catalog page;
s4052, jumping the teaching courseware to a chapter catalog page where the current page is located;
s4053, when the teacher observes that the teaching page jumps to the general directory page or the chapter directory page through the live broadcast feedback screen, the teacher can read the chapter or page number of the course in the voice mode, and then step S403 is executed, and whether the acquired chapter or page number of the course read by the teacher is matched with the label information in the audio information or not is judged by adopting an artificial intelligence comparison method.
Preferably, after S400, the method further includes:
s500, adopting an artificial intelligence statistical technology to screen out the most questions from the messages;
s600, feeding back the screened problems to a teaching live broadcast end used by a teacher, and enabling the teacher to realize interaction with students through answering the problems.
Preferably, the S4041 includes:
s4041-1, establishing an index table according to the index relation constructed in the index data;
s4041-2, in a first range preset by the index table, judging whether the index data in the index table meets a merging condition, if so, executing the step S4041-3, and if not, executing the step S4041-4;
s4041-3, merging the index data meeting the conditions on a row basis, or merging the index data meeting the conditions on a column basis;
s4041-4, in a second range outside the first range of the index table, judging whether the index data in the index table meets the merging condition, if so, merging rows or columns, traversing all data of the index table in sequence, and stopping until the merging condition is not met.
Preferably, before S100, the method includes:
s700, collecting morphological characteristics, mouth shape characteristics and language use habit characteristics of a teacher in a teaching live broadcast process through an artificial intelligence simulation learning system;
s800, extracting main features of the acquired morphological features, mouth shape features and language use habit features of the teacher in a live teaching process based on the deep bible network model, and constructing a teaching simulation model of the teacher in a feature vector mode;
correspondingly, S100 specifically includes: restoring the teaching habits of the teacher based on the teaching simulation model, and combining the teaching habits in a text-to-audio mode to form an audio file attached to the teacher, wherein the audio file is a voice format file of teaching courseware;
the method for extracting the main features according to the mouth shape features comprises the following steps:
establishing an HMM model for each word or phrase in the database through the sample sequence, wherein the HMM model comprises an initial parameter and a final parameter, and the initial parameter comprises: the method comprises the following steps that (1) an initial state probability pi, a transition matrix A between hidden states, a mixing matrix B, the number N of the hidden states and the number M of observation values corresponding to each hidden state are obtained; after initializing the initialization parameters, updating the initial parameters based on the forward probability and the backward probability, and determining the final parameters through iterative computation;
extracting features of a video to be identified through lip region detection, and calculating and determining feature vectors;
calculating each HMM model by using a Viterbi algorithm to obtain the probability of the feature vector to be identified, and comparing to obtain the maximum probability;
the character or word corresponding to the model with the maximum probability is a corresponding recognition result;
updating the initial parameters based on the forward probability and the backward probability, and determining the final parameters through iterative calculation, wherein the iterative calculation comprises the following steps:
calculating forward probability and backward probability, calculating the increment of the forward probability and the backward probability respectively, calculating the ratio of the forward probability increment to the forward probability, and calculating the ratio of the backward probability increment to the backward probability, stopping iteration when the absolute value of the ratio is less than a preset iteration limit value, determining a final parameter, and continuing to calculate the forward probability and the backward probability if the absolute value of the ratio is more than the preset iteration limit value.
In the process of extracting and identifying the mouth shape features by the method, different parameters of the HMM model are obtained by constructing reasonable initial parameters, and the parameters of the HMM model determine the mouth shape feature extraction and identification rate.
Preferably, the feature extraction by lip region detection includes:
selecting a face area of the whole lip, performing lip color enhancement by using an optimal Fisher classification vector, calculating a threshold value according to experience, performing lip color and skin color segmentation, binarizing the lip, performing edge extraction, finally selecting a lip edge sample point, and performing curve fitting on the sample point;
wherein the empirically calculated threshold value formula is as follows:
wherein, y k Denotes a threshold value, m 1 Representing the lip color sample point vector mean vector, m 2 Representing the vector mean vector of skin color sample points, n 1 Number of lip color samples, n 2 Representing the number of skin color samples, W representing the optimal Fisher classification vector, m 1 T Is m 1 Transposed vector of (c), m 2 T Is m 2 The transposed vector of (1).
Based on the above formula, m 1 T W represents the product of lip color mean and the optimal Fisher classification vector, m 2 T W represents the product of the skin color mean value and the optimal Fisher classification vector, and the calculation mode can be better adoptedThe lip face region is segmented. Moreover, by adopting the calculation formula, multiple times of circular calculation are not needed, and the calculation efficiency is improved.
Preferably, after S400, the method further includes:
s900, forming a first audio file from a voice format file of a teaching courseware, forming a video file from a live video of a teacher in a live broadcasting process, extracting a second audio file from the video file, extracting information related to the teaching courseware from the second audio file by adopting an artificial intelligence technology, setting the information as a useful audio file, sequencing the useful audio files according to the sequence of the teaching courseware to form a pure teaching audio file, constructing an index relation among the teaching courseware, the first audio file and the pure teaching audio file, and forming a recorded broadcast video, wherein when the teaching courseware is opened, the recorded broadcast video firstly plays the content of the first audio file of a current display page, and then plays the content of the pure teaching audio file.
Compared with the prior art, the invention has the following advantages:
the invention provides a teaching live broadcast method based on artificial intelligence, which processes teaching courseware based on artificial intelligence technology to form a voice format file of the teaching courseware; in the teaching live broadcast process, recording a teaching site in a shooting mode to form a live broadcast video; setting a teaching field area and a teaching courseware area on a teaching live broadcast picture displayed by a teaching live broadcast receiving end; the live broadcast video is displayed in the teaching field area, and the teaching courseware is displayed in the teaching courseware area; in the teaching live broadcast process, live broadcast video and teaching courseware are synchronized based on an artificial intelligence technology and combined with a voice format file of the teaching courseware.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a flowchart of a teaching live broadcast method based on artificial intelligence in an embodiment of the present invention;
FIG. 2 is a flow chart of a method for synchronizing live video and the courseware in an embodiment of the present invention;
FIG. 3 is a flowchart of a method for turning pages of a courseware by using an artificial intelligence control mode in the embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it should be understood that they are presented herein only to illustrate and explain the present invention and not to limit the present invention.
The embodiment of the invention provides a teaching live broadcast method based on artificial intelligence, which comprises the following steps as shown in figures 1-3:
s100, processing the teaching courseware based on an artificial intelligence technology to form a voice format file of the teaching courseware;
s200, in the teaching live broadcast process, recording a teaching site in a shooting mode to form a live broadcast video;
s300, setting a teaching field area and a teaching courseware area on a teaching live broadcast picture displayed by a teaching live broadcast receiving end; the live broadcast video is displayed in the teaching field area, and the teaching courseware is displayed in the teaching courseware area;
s400, in the teaching live broadcast process, the live broadcast video and the teaching courseware are synchronized based on the artificial intelligence technology and the voice format file of the teaching courseware.
The working principle of the technical scheme is as follows: the scheme adopted by the embodiment is that the teaching courseware is processed based on an artificial intelligence technology to form a voice format file of the teaching courseware; in the teaching live broadcast process, recording a teaching site in a shooting mode to form a live broadcast video; setting a teaching field area and a teaching courseware area on a teaching live broadcast picture displayed by a teaching live broadcast receiving end; the live broadcast video is displayed in the teaching field area, and the teaching courseware is displayed in the teaching courseware area; in the teaching live broadcast process, live broadcast video and teaching courseware are synchronized based on an artificial intelligence technology and combined with a voice format file of the teaching courseware.
The beneficial effects of the above technical scheme are: the scheme provided by the embodiment is adopted to process the teaching courseware based on the artificial intelligence technology to form a voice format file of the teaching courseware; in the teaching live broadcast process, recording a teaching site in a shooting mode to form a live broadcast video; setting a teaching field area and a teaching courseware area on a teaching live broadcast picture displayed by a teaching live broadcast receiving end; the live broadcast video is displayed in the teaching field area, and the teaching courseware is displayed in the teaching courseware area; in the teaching live broadcast process, the live broadcast video and the teaching courseware are synchronized based on the artificial intelligence technology and the voice format file of the teaching courseware.
In another embodiment, the S100 includes:
s101, making teaching courseware, wherein each page of the teaching courseware is provided with marking information, and the standard information comprises: marking the subject name, a plurality of key words and chapter information of the corresponding page, or marking the page number of the corresponding page;
s102, forming a voice format file corresponding to the teaching courseware based on a character-to-audio artificial intelligence synthesis method; the voice format file comprises audio information corresponding to the marking information on each page.
The working principle of the technical scheme is as follows: the scheme that this embodiment adopted is the preparation teaching courseware be provided with label information on each page of teaching courseware, standard information includes: labeling the subject name, a plurality of keywords and chapter information of the corresponding page, or labeling the page number of the corresponding page; forming a voice format file corresponding to the teaching courseware based on a character-to-audio artificial intelligent synthesis method; the voice format file comprises audio information corresponding to the marking information on each page.
The beneficial effects of the above technical scheme are: the scheme that this embodiment of adoption provided is the preparation teaching courseware be provided with mark information on every page of teaching courseware, standard information includes: marking the subject name, a plurality of key words and chapter information of the corresponding page, or marking the page number of the corresponding page; forming a voice format file corresponding to the teaching courseware based on a character-to-audio artificial intelligent synthesis method; the voice format file comprises audio information corresponding to the marking information on each page.
In another embodiment, as shown in fig. 2, the S400 includes:
s401, collecting the on-site sound of a teacher in a live video in real time in the live video process;
s402, setting the audio information including the label information as the comparison party;
s403, judging whether the collected field voice information is matched with the labeled information in the audio information or not by adopting an artificial intelligence comparison method, if so, executing a step S404, and if not, executing a step S405;
s404, turning pages of the teaching courseware to corresponding pages marked with information in an artificial intelligence control mode;
s405, the teaching courseware is not processed and is in a current state; or turning the teaching courseware to the standby page.
The working principle of the technical scheme is as follows: the scheme adopted by the embodiment is that in the live broadcasting process, the on-site sound of a teacher in a live video is collected in real time; setting the audio information including the label information as a comparison party; judging whether the collected field voice information is matched with the labeled information in the audio information or not by adopting an artificial intelligence comparison method, if so, executing the step of turning the teaching courseware to a page of the corresponding labeled information by adopting an artificial intelligence control mode; if not, the step is executed to not process the teaching courseware, and the teaching courseware is in the current state; or turning the teaching courseware to the standby page.
The beneficial effects of the above technical scheme are: the scheme provided by the embodiment is adopted to collect the live sound of a teacher in a live video in real time in the live broadcasting process; setting the audio information including the label information as a comparison party; judging whether the collected field voice information is matched with the labeled information in the audio information or not by adopting an artificial intelligence comparison method, if so, executing the step of turning the teaching courseware to the page of the corresponding labeled information by adopting an artificial intelligence control mode; if not, the step is executed to not process the teaching courseware, and the teaching courseware is in the current state; or turning the teaching courseware to the standby page.
In another embodiment, as shown in fig. 3, the S404 includes:
s4041, constructing an index relation between the labeling information and the page number on each page of the teaching courseware in an index database;
s4042, quickly retrieving the page number of the corresponding teaching courseware in the index database by adopting an artificial intelligence control mode according to the standard information in the field voice information;
s4043, controlling the teaching courseware to turn pages to corresponding pages according to the searched pages of the teaching courseware.
The working principle of the technical scheme is as follows: the scheme adopted by the embodiment is that the index relation is built in the index database by the marking information and the page number on each page of the teaching courseware; rapidly searching out the page number of the corresponding teaching courseware in the index database by adopting an artificial intelligence control mode according to the standard information in the field voice information; and controlling the teaching courseware to turn to the corresponding page number according to the retrieved page number of the teaching courseware.
The beneficial effects of the above technical scheme are: the scheme provided by the embodiment is that the index relation is constructed by the marking information and the page number on each page of the teaching courseware in the index database; rapidly searching out the page number of the corresponding teaching courseware in the index database by adopting an artificial intelligence control mode according to the standard information in the field voice information; and controlling the teaching courseware to turn pages to corresponding pages according to the searched page number of the teaching courseware.
In another embodiment, the S404 further includes:
s4044, turning the pages of the teaching courseware backward or forward page by page in an artificial intelligent control mode;
s4045, the teaching courseware is turned backwards or forwards in a page skipping mode in an artificial intelligent control mode.
The working principle of the technical scheme is as follows: the scheme adopted by the embodiment is that an artificial intelligent control mode is adopted to turn the pages of the teaching courseware page by page backwards or forwards; and adopting an artificial intelligent control mode to page the teaching courseware in a backward or forward page skipping mode.
The beneficial effects of the above technical scheme are: the scheme provided by the embodiment is that the teaching courseware is turned backwards or forwards page by page in an artificial intelligent control mode; and adopting an artificial intelligent control mode to page the teaching courseware in a backward or forward page skipping mode.
In another embodiment, the turning the teaching courseware to the standby page in S405 includes:
s4051, jumping the teaching courseware to a general catalog page;
s4052, jumping the teaching courseware to a chapter catalog page where the current page is located;
s4053, when the teacher observes that the teaching page jumps to the general catalog page or the chapter catalog page through the live broadcast feedback screen, the teacher reads the chapter or page number of the taught course in a voice mode, and then step S403 is executed, and whether the collected chapter or page number of the taught course read by the teacher has a matching relation with the label information in the audio information is judged by adopting an artificial intelligence comparison method.
The working principle of the technical scheme is as follows: the scheme adopted by the embodiment is to turn the teaching courseware to a standby page, and the method comprises the following steps: jumping the teaching courseware to a general catalog page; jumping the teaching courseware to a chapter catalog page where the current page is located; and when the teacher observes that the teaching page jumps to the general directory page or the chapter directory page through the live broadcast feedback screen, the teacher can read the chapter or page number of the course in a voice mode, and the execution step adopts an artificial intelligence comparison method to judge whether the collected chapter or page number of the course read by the teacher is matched with the label information in the audio information.
The beneficial effects of the above technical scheme are: the scheme that this embodiment of adoption provided is to turning over the page teaching courseware to spare page on, include: jumping the teaching courseware to a general catalog page; jumping the teaching courseware to a chapter catalog page where the current page is located; and when the teacher observes that the teaching page jumps to the general directory page or the chapter directory page through the live broadcast feedback screen, the teacher can read the chapter or page number of the course in a voice mode, and the execution step adopts an artificial intelligence comparison method to judge whether the collected chapter or page number of the course read by the teacher is matched with the label information in the audio information.
In another embodiment, after S400, the method includes:
s500, adopting an artificial intelligence statistical technology to screen out the most questions from the messages;
s600, feeding the screened problems back to a live teaching end used by the teacher, and enabling the teacher to interact with students through answering the problems.
The working principle of the technical scheme is as follows: the scheme adopted by the embodiment is that the artificial intelligence statistical technology is adopted, and the problems with the most questions are screened out from the messages; the problem that will select is fed back to the teaching live broadcast end that the teacher used, and the teacher realizes with student's interaction through the solution to the problem.
The beneficial effects of the above technical scheme are: the scheme provided by the embodiment is that the artificial intelligence statistical technology is adopted, and the problems with the most questions are screened out from the messages; the problem that will select is fed back to the teaching live broadcast end that the teacher used, and the teacher realizes with student's interaction through the solution to the problem.
In another embodiment, the S4041 includes:
s4041-1, establishing an index table according to the index relation constructed in the index data;
s4041-2, in a first range preset by the index table, judging whether the index data in the index table meets a merging condition, if so, executing the step S4041-3, and if not, executing the step S4041-4;
s4041-3, merging the index data meeting the conditions in a row basis, or merging the index data meeting the conditions in a column basis;
s4041-4, in a second range outside the first range of the index table, judging whether the index data in the index table meets the merging condition, if so, merging rows or columns, traversing all data of the index table in sequence, and stopping until the merging condition is not met.
The working principle of the technical scheme is as follows: the scheme adopted by the embodiment is that an index table is established according to an index relation constructed in index data; judging whether index data in the index table meet a merging condition or not within a preset first range of the index table, if so, executing the step of merging the index data meeting the condition with a row standard, or merging the index data meeting the condition with a column standard, if not, executing the step within a second range outside the first range of the index table, judging whether the index data in the index table meet the merging condition or not, if so, merging rows or columns, traversing all data of the index table in sequence, and stopping the operation until the merging condition is not met.
The beneficial effects of the above technical scheme are: the scheme provided by the embodiment is that an index table is established according to the index relation constructed in the index data; judging whether index data in the index table meet a merging condition or not within a preset first range of the index table, if so, executing the step of merging the index data meeting the condition with a row standard, or merging the index data meeting the condition with a column standard, if not, executing the step within a second range outside the first range of the index table, judging whether the index data in the index table meet the merging condition or not, if so, merging rows or columns, traversing all data of the index table in sequence, and stopping the operation until the merging condition is not met.
In another embodiment, said S100 is preceded by:
s700, collecting morphological characteristics, mouth shape characteristics and language use habit characteristics of a teacher in a teaching live broadcast process through an artificial intelligent simulation learning system;
s800, extracting main features of the acquired morphological features, mouth shape features and language use habit features of the teacher in a live teaching process based on the deep bible network model, and constructing a teaching simulation model of the teacher in a feature vector mode;
correspondingly, S100 specifically includes: restoring the teaching habits of the teacher based on the teaching simulation model, and combining the teaching habits in a text-to-audio mode to form an audio file attached to the teacher, wherein the audio file is a voice format file of a teaching courseware;
the method for extracting the main features according to the mouth shape features comprises the following steps:
establishing an HMM model for each word or phrase in the database through the sample sequence, wherein the HMM model comprises an initial parameter and a final parameter, and the initial parameter comprises: the method comprises the following steps of (1) obtaining initial state probability, a transition matrix between hidden states, a mixing matrix, the number of the hidden states and the number of observed values corresponding to each hidden state; the final parameters are obtained by initializing the initialization parameters, updating the initial parameters based on the forward probability and the backward probability, and determining the final parameters through iterative computation;
extracting features of a video to be identified through lip region detection, and calculating and determining feature vectors;
calculating each HMM model by using a Viterbi algorithm to obtain the probability of the feature vector to be identified, and comparing to obtain the maximum probability;
the word or the word corresponding to the model with the maximum probability is the corresponding recognition result.
In the process of extracting and identifying the mouth shape features by the method, different parameters of the HMM model are obtained by constructing reasonable final parameters, and the parameters of the HMM model determine the mouth shape feature extraction and identification rate;
updating the initial parameters based on the forward probability and the backward probability, and determining the final parameters through iterative calculation, wherein the iterative calculation comprises the following steps:
calculating forward probability and backward probability, calculating the increment of the forward probability and the backward probability respectively, calculating the ratio of the forward probability increment to the forward probability, and calculating the ratio of the backward probability increment to the backward probability, stopping iteration when the absolute value of the ratio is less than a preset iteration limit value, determining a final parameter, and continuing to calculate the forward probability and the backward probability if the absolute value of the ratio is more than the preset iteration limit value.
The extracting features through lip region detection includes:
selecting a face area of the whole lip, performing lip color enhancement by using an optimal Fisher classification vector, calculating a threshold value according to experience, performing lip color and skin color segmentation, binarizing the lip, performing edge extraction, finally selecting a lip edge sample point, and performing curve fitting on the sample point;
wherein the empirically calculated threshold value formula is as follows:
wherein, y k Denotes a threshold value, m 1 Represents the lip color sample point vector mean vector, m 2 Representing the vector mean vector of skin color sample points, n 1 Number of lip color samples, n 2 Representing the number of skin color samples, W representing the optimal Fisher classification vector, m 1 T Is m 1 Transposed vector of (1), m 2 T Is m 2 The transposed vector of (1).
Based on the above formula, m 1 T W represents the product of the lip color mean and the optimal Fisher classification vector, m 2 T W represents the product of the skin color mean and the optimal Fisher classification vector, and the lip face area can be better segmented by adopting the calculation mode. Moreover, by adopting the calculation formula, repeated cyclic calculation is not needed, and the calculation efficiency is improved.
The working principle of the technical scheme is as follows: the scheme adopted by the embodiment is that through an artificial intelligence simulation learning system, morphological characteristics, mouth shape characteristics and language use habit characteristics of a teacher in the teaching live broadcast process are collected; performing main feature extraction on morphological features, mouth shape features and language use habit features of the acquired instructor in the teaching live broadcast process based on the deep bible network model, and constructing a teaching simulation model of the instructor by adopting a feature vector mode; correspondingly, the teaching habits of the teacher are restored based on the teaching simulation model, and an audio file which is a voice format file of the teaching courseware is formed by combining the teaching habits in a text-to-audio mode.
The beneficial effects of the above technical scheme are: the scheme provided by the embodiment is that the morphological characteristics, the mouth shape characteristics and the language use habit characteristics of a teacher in the teaching live broadcast process are collected through an artificial intelligence simulation learning system; performing main feature extraction on morphological features, mouth shape features and language use habit features of the acquired instructor in the teaching live broadcast process based on the deep bible network model, and constructing a teaching simulation model of the instructor by adopting a feature vector mode; correspondingly, the teaching habits of the teacher are restored based on the teaching simulation model, and an audio file which is a voice format file of the teaching courseware is formed by combining the teaching habits in a text-to-audio mode.
In another embodiment, after S400, the method further includes:
s900, forming a first audio file from a voice format file of a teaching courseware, forming a video file from a live video of a teacher in a live broadcasting process, extracting a second audio file from the video file, extracting information related to the teaching courseware from the second audio file by adopting an artificial intelligence technology, setting the information as a useful audio file, sequencing the useful audio files according to the sequence of the teaching courseware to form a pure teaching audio file, constructing an index relation among the teaching courseware, the first audio file and the pure teaching audio file, and forming a recorded broadcast video, wherein when the teaching courseware is opened, the recorded broadcast video firstly plays the content of the first audio file of a current display page, and then plays the content of the pure teaching audio file.
The working principle of the technical scheme is as follows: the method comprises the steps of forming a voice format file of a teaching courseware into a first audio file, forming a live video of a teacher in a live broadcasting process into a video file, extracting a second audio file from the video file, extracting information related to the teaching courseware from the second audio file by adopting an artificial intelligence technology, setting the information as a useful audio file, sequencing the useful audio files according to the sequence of the teaching courseware to form a pure teaching audio file, constructing an index relationship among the teaching courseware, the first audio file and the pure teaching audio file, and forming a recorded broadcast video, wherein when the teaching courseware is opened, the recorded broadcast video firstly plays the content of the first audio file of a current display page, and then plays the content of the pure teaching audio file.
The beneficial effects of the above technical scheme are: the method comprises the steps of forming a first audio file from a voice format file of a teaching courseware, forming a video file from a live video of a teacher in a live broadcasting process, extracting a second audio file from the video file, extracting information related to the teaching courseware from the second audio file by adopting an artificial intelligence technology, setting the information as a useful audio file, sequencing the useful audio files according to the sequence of the teaching courseware to form a pure teaching audio file, constructing an index relation among the teaching courseware, the first audio file and the pure teaching audio file, and forming a recorded broadcast video, wherein when the teaching courseware is opened, the recorded broadcast video firstly plays the content of the first audio file of a current display page, and then plays the content of the pure teaching audio file.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. A teaching live broadcast method based on artificial intelligence is characterized by comprising the following steps:
s100, processing the courseware based on an artificial intelligence technology to form a voice format file of the courseware;
s200, in the teaching live broadcast process, recording a teaching site in a shooting mode to form a live broadcast video;
s300, setting a teaching field area and a teaching courseware area on a teaching live broadcast picture displayed by a teaching live broadcast receiving end; the live broadcast video is displayed in the teaching field area, and the teaching courseware is displayed in the teaching courseware area;
s400, in the teaching live broadcast process, the live broadcast video and the teaching courseware are synchronized based on the artificial intelligence technology and the voice format file of the teaching courseware.
2. The artificial intelligence based teaching live broadcast method according to claim 1, wherein the S100 includes:
s101, making teaching courseware, wherein each page of the teaching courseware is provided with marking information, and the standard information comprises: marking the subject name, a plurality of key words and chapter information of the corresponding page, or marking the page number of the corresponding page;
s102, forming a voice format file corresponding to the teaching courseware based on a character-to-audio artificial intelligence synthesis method; the voice format file comprises audio information corresponding to the marking information on each page.
3. The artificial intelligence based teaching live broadcast method according to claim 2, wherein the S400 comprises:
s401, collecting the on-site sound of a teacher in a live video in real time in the live video process;
s402, setting the audio information including the label information as the comparison party;
s403, judging whether the collected field voice information is matched with the labeled information in the audio information or not by adopting an artificial intelligence comparison method, if so, executing a step S404, and if not, executing a step S405;
s404, turning pages of the teaching courseware to corresponding pages marked with information in an artificial intelligence control mode;
s405, the teaching courseware is not processed, and the teaching courseware is in the current state; or turning the teaching courseware to the standby page.
4. The artificial intelligence based teaching live broadcast method according to claim 1, wherein the S404 comprises:
s4041, constructing an index relation between the labeling information and the page number on each page of the teaching courseware in an index database;
s4042, quickly retrieving the page number of the corresponding teaching courseware in the index database by adopting an artificial intelligence control mode according to the standard information in the field voice information;
s4043, according to the searched page number of the teaching courseware, controlling the teaching courseware to turn to the corresponding page number.
5. The artificial intelligence based teaching live broadcast method according to claim 3, wherein the S404 further comprises:
s4044, turning the pages of the teaching courseware backward or forward page by page in an artificial intelligent control mode;
s4045, the teaching courseware is turned backwards or forwards in a page jumping mode in an artificial intelligence control mode.
6. The artificial intelligence based teaching live broadcast method according to claim 3, wherein the turning the teaching courseware to the standby page in S405 includes:
s4051, jumping the teaching courseware to a general catalog page;
s4052, jumping the teaching courseware to a chapter catalog page where the current page is located;
s4053, when the teacher observes that the teaching page jumps to the general catalog page or the chapter catalog page through the live broadcast feedback screen, the teacher reads the chapter or page number of the taught course in a voice mode, and then step S403 is executed, and whether the collected chapter or page number of the taught course read by the teacher has a matching relation with the label information in the audio information is judged by adopting an artificial intelligence comparison method.
7. The artificial intelligence-based teaching live broadcast method according to claim 1, wherein after S400, the method comprises:
s500, screening out the most questions from the messages by adopting an artificial intelligence statistical technology;
s600, feeding the screened problems back to a live teaching end used by the teacher, and enabling the teacher to interact with students through answering the problems.
8. The artificial intelligence based teaching live broadcast method according to claim 4, wherein the S4041 includes:
s4041-1, establishing an index table according to the index relation constructed in the index data;
s4041-2, in a first range preset by the index table, judging whether the index data in the index table meets a merging condition, if so, executing the step S4041-3, and if not, executing the step S4041-4;
s4041-3, merging the index data meeting the conditions on a row basis, or merging the index data meeting the conditions on a column basis;
s4041-4, in a second range outside the first range of the index table, judging whether the index data in the index table meets the merging condition, if so, merging rows or columns, traversing all data of the index table in sequence, and stopping after the merging condition is not met.
9. The artificial intelligence based teaching live broadcast method according to claim 1, wherein before S100, the method comprises:
s700, collecting morphological characteristics, mouth shape characteristics and language use habit characteristics of a teacher in a teaching live broadcast process through an artificial intelligent simulation learning system;
s800, extracting main features of the acquired morphological features, mouth shape features and language use habit features of the teacher in a live teaching process based on the deep bible network model, and constructing a teaching simulation model of the teacher in a feature vector mode;
correspondingly, S100 specifically includes: restoring the teaching habits of the teacher based on the teaching simulation model, and combining the teaching habits in a text-to-audio mode to form an audio file attached to the teacher, wherein the audio file is a voice format file of a teaching courseware;
the method for extracting the main features according to the mouth shape features comprises the following steps:
establishing an HMM model for each word or word in the database through the sample sequence, wherein the HMM model comprises an initial parameter and a final parameter, and the initial parameter comprises: the method comprises the following steps that (1) an initial state probability pi, a transition matrix A between hidden states, a mixing matrix B, the number N of the hidden states and the number M of observation values corresponding to each hidden state are obtained; after initializing the initialization parameters, updating the initial parameters based on the forward probability and the backward probability, and determining the final parameters through iterative computation;
extracting features of a video to be identified through lip region detection, and calculating and determining feature vectors;
calculating each HMM model by using a Viterbi algorithm to obtain the probability of the feature vector to be identified, and comparing to obtain the maximum probability;
the character or word corresponding to the model with the maximum probability is the corresponding recognition result;
updating the initial parameters based on the forward probability and the backward probability, and determining the final parameters through iterative calculation, wherein the iterative calculation comprises the following steps:
calculating forward probability and backward probability, calculating the increment of the forward probability and the backward probability respectively, calculating the ratio of the forward probability increment to the forward probability, and calculating the ratio of the backward probability increment to the backward probability, stopping iteration when the absolute value of the ratio is less than a preset iteration limit value, determining a final parameter, and continuing to calculate the forward probability and the backward probability if the absolute value of the ratio is more than the preset iteration limit value.
10. The artificial intelligence based teaching live broadcast method according to claim 1, further comprising after S400:
s900, forming a first audio file from a voice format file of a teaching courseware, forming a video file from a live video of a teacher in a live broadcasting process, extracting a second audio file from the video file, extracting information related to the teaching courseware from the second audio file by adopting an artificial intelligence technology, setting the information as a useful audio file, sequencing the useful audio files according to the sequence of the teaching courseware to form a pure teaching audio file, constructing an index relation among the teaching courseware, the first audio file and the pure teaching audio file, and forming a recorded broadcast video, wherein when the teaching courseware is opened, the recorded broadcast video firstly plays the content of the first audio file of a current display page, and then plays the content of the pure teaching audio file.
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