CN109889918B - Self-adaptive adjustment method for teaching video playing speed - Google Patents
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Abstract
The invention discloses a self-adaptive adjustment method for the playing speed of a teaching video, which comprises the following steps: constructing a general pheromone matrix, a classification pheromone matrix and a speed migration parameter matrix of the video by utilizing T time periods of the video and preset m playing speeds; collecting preview feedback of the viewer to categorize the viewer; calculating an initial playing speed according to the type of the viewer; calculating the probability that the playing speed is changed into each speed of m speeds when the current viewer watches the next time slot according to the speed migration parameter matrix, the playing speed of the current time slot, and the general pheromone matrix and the classification pheromone matrix which are updated after the previous viewer watches the next time slot in the watching process; adjusting the playing speed of the current viewer in the next time period according to the probability; generating a playing speed path of the current viewer for watching the video after playing; and collecting the post-class feedback of the viewers and updating the general pheromone matrix and the classified pheromone matrix according to the post-class feedback and the playing speed path.
Description
Technical Field
The invention relates to a self-adaptive adjustment method for a teaching video playing speed, and belongs to the field of computer application.
Background
In the process of online learning by watching videos, the speed of a lecturer influences the comprehension of the video viewers on the materials and the enthusiasm of learning. However, viewers with different knowledge bases and habits often have different requirements on the speed of a lecturer. Moreover, the optimal speed of teaching is also closely related to the curriculum theme, the type of the teaching content and the difficulty of the content in the corresponding section.
Most of the existing video speed adjusting methods need a viewer to actively adjust the playing speed in the learning process. However, in order to keep the speed of speech for teaching in the parts with different difficulty in content in a proper interval, the speed is often adjusted many times, which tends to distract the viewer from learning. In addition, some methods identify and monitor the speed of the lecturer, so as to automatically adjust the playing speed according to the speed of the lecturer, but the method neglects the difficulty of course content and the personalized requirements of video viewers.
The above background disclosure is only for the purpose of assisting understanding of the inventive concept and technical solutions of the present invention, and does not necessarily belong to the prior art of the present patent application, and should not be used for evaluating the novelty and inventive step of the present application in the case that there is no clear evidence that the above content is disclosed before the filing date of the present patent application.
Disclosure of Invention
The invention mainly aims to provide a self-adaptive adjustment method of the playing speed of a teaching video based on an ant colony algorithm, which is characterized in that after video viewers are classified, corresponding playing speed paths are formed for each type of viewers, so that the viewers dynamically adjust the video playing speed according to the corresponding playing speed paths in the process of watching the teaching video, and the self-adaptive adjustment of the playing speed is realized, so that the problems that the learning effect is influenced by the fact that the viewers need to self-adjust the playing speed when watching the online teaching video in the prior art and the existing scheme for automatically adjusting the playing speed according to the language speed of a lecturer cannot adapt to the requirements of different viewers are solved.
The invention provides a technical scheme for achieving the aim as follows:
a self-adaptive adjusting method for teaching video playing speed comprises the following steps:
s1, dividing the video into T time periods, and presetting m possible playing speeds v for each time period1,v2,v3,…,vm；
S2, constructing a general pheromone matrix M ═ (τ) of the video by using the T time slots and the M playing speeds of each time slott,j(n-1))T×mSorting a matrix of pheromones
And a velocity migration parameter matrix MSpeedChange＝(μij)m×mN-1 indicates that there are n-1 views of the videoThe viewer has viewed that initially n is 1, style is 1,2,3, …, k represents a preset type of viewer, i, j e (v)1,v2,v3,…,vm) (ii) a Wherein: tau ist,j(n-1) indicating that the video has n-1 general pheromone concentrations with the playing speed j in the t time period after the video is watched by the viewers;
the classified pheromone concentration of the playing speed j in the t time period after n-1 viewers finish watching the video is represented; mu.sijA probability factor representing a transition of a playing speed of the video from i to j;
s3, defining the nth viewer as the current viewer, collecting preview feedback information of the current viewer after watching the pre-generated preview video, and classifying the current viewer according to the preview feedback information, wherein the type of the current viewer is style (n);
s4, according to the type style (n) of the current viewer, calculating the playing speed of the current viewer watching the video in the 1 st time period
And speed the current viewer
Starting to watch the video;
s5, in the watching process, calculating the probability that the playing speed is changed into each speed in the m playing speeds when the current watcher watches the video in the next time period according to the speed migration parameter matrix, the playing speed in the current time period, and the updated general pheromone matrix and the classification pheromone matrix after the last watcher watches the video;
s6, adjusting the video playing speed of the current viewer in the next time period according to the probability;
s7, looping steps S5 and S6, and generating a playing speed path for the current viewer to watch the video after the playing is finished
Wherein
For the playing speed when the current viewer watches the T-th time slot, T is 1,2,3, …, T;
s8, collecting the feedback information after class of the current viewer, updating the general pheromone matrix and the classified pheromone matrix according to the feedback information after class and the playing speed path V (n), and repeating the steps S3-S8 for the next viewer.
The self-adaptive adjustment method for the video playing speed of the teaching provided by the technical scheme of the invention can automatically select a proper playing speed path for a video viewer, and takes the characteristics and requirements of different types of viewers into consideration; in addition, the problem that the speed of speech of the teaching in part of teaching videos is not designed is solved to a certain extent, and the method has practical application value.
Drawings
FIG. 1 is a flow chart of a method for adaptively adjusting the playback speed of a teaching video according to an embodiment of the present invention;
fig. 2 is a visual play speed path diagram according to an embodiment of the invention.
Detailed Description
The invention is further described with reference to the following figures and detailed description of embodiments.
The specific implementation manner of the present invention provides a self-adaptive adjustment method for the playing speed of a teaching video, referring to fig. 1, the method includes the following steps:
step S1, dividing the video into T time periods, and presetting m possible playing speeds v for each time period1,v2,v3,…,vm. In the T time periods, the first T-1 time periods are divided equally, and the time lengths are all TspaceSuppose the total duration of the video is ttotalThen, there are: t ═ Ttotal/tspace]+1；[·]Indicating rounding of the numbers in parentheses. V is preset for each time segment1,v2,v3,…,vmE.g. possible play-out speed per time periodThe degrees are {0.75,0.8,0.85, … …,1.3,1.35,1.4,1.45,1.5}, in which example m is 16. It should be understood that one skilled in the art can set t differently according to specific scenarios and requirementsspaceValues corresponding to different tspaceThe value, the optimal interval setting between different speeds in the set of play speeds is also different.
Step S2, constructing a general pheromone matrix M ═ (τ) of the video using the T time slots and M playback speeds for each time slott,j(n-1))T×mSorting a matrix of pheromones
And a velocity migration parameter matrix MSpeedChange＝(μij)m×mN-1 indicates that n-1 viewers have watched the video, initially n is 1, style is 1,2,3, …, k indicates a preset type of viewer, i, j e (v)1,v2,v3,…,vm) (ii) a Wherein: tau ist,j(n-1) indicating that the video has n-1 general pheromone concentrations with the playing speed j in the t time period after the video is watched by the viewers;
the classified pheromone concentration of the playing speed j in the t time period after n-1 viewers finish watching the video is represented; mu.sijRepresenting a probability factor for the play speed of the video to migrate from i to j. Step S2 is a step of initializing the general pheromone matrix and the classification pheromone matrix, and in the initialization step S2, no one has viewed the video, that is, n is 1, and τ is given to any of t, j, and stylet,j(0)＝1，
In addition, the velocity migration parameter matrix satisfies:
The invention provides the improved ant colony algorithm based on the concept principle of the ant colony algorithm, converts the speed adjustment into the path optimization problem, and constructs a general pheromone matrix M ═ (tau) for calculating the speed transformation probabilityt,j(n-1))T×mSorting a matrix of pheromones
And a velocity migration parameter matrix MSpeedChange＝(μij)m×m。
Step S3, defining the nth viewer as the current viewer, collecting preview feedback information of the current viewer after viewing the pre-generated preview video, and classifying the current viewer according to the preview feedback information, wherein the obtained type is style (n). For an online teaching video, the invention generates a short preview video for the video in advance, and a viewer can only watch the preview video at a default speed, aiming at obtaining a preliminary feedback of the viewer on the speed of the video so as to classify the viewer. The preview feedback includes play speed feedback, language difficulty feedback, and content difficulty feedback. In one specific example, the play speed feedback SR is-1, 0,1 (corresponding to "slower", "medium", and "faster", respectively); language difficulty DL ═ 1,0,1 (corresponding to "simple", "medium", and "difficult", respectively); the content difficulty DC is-1, 0,1 (corresponding to "simple", "medium", and "difficult", respectively). With this feedback, the genre of the video viewer can be defined as shown in table 1 below:
TABLE 1 exemplary viewer types and their classification conditions
| Viewer type style | Condition |
| 1 (very slow speed is required)) | SR＝1&DC+DL>0 |
| 2 (need slower speed) | SR＝1&DC+DL≤0,or SR＝0&DC+DL＝2 |
| 3 (need moderate speed) | SR＝0&-2<DC+DL<2 |
| 4 (need faster speed) | SR＝-1&DC+DL≧0,or SR＝0&DC+DL＝-2 |
| 5 (need to be fast) | SR＝-1&DC+DL<0 |
Thus, the above example gives the five types of definitions of viewers and their classification conditions, and for a viewer, the viewer can be classified as long as he submits preview feedback after viewing the preview video. It should be understood that the viewer types and numbers are not limited to those listed in table 1 above, and preview feedback for other dimensions may be integrated to give different types than those in table 1 above.
After determining the style (n) of the current viewer according to the manner of step S3, step S4 may calculate the playing speed of the current viewer watching the video in the 1 st time period according to the style (n)
I.e. initial viewing speed, and let the current viewer speed
The video starts to be viewed. Taking the above Table 1 as an example, the initial viewing speed of the current viewer with style (n) as the type
Here, the initial speed calculation formula is not limited to this, and may be set separately according to specific situations, or may directly specify the initial viewing speed of each type (style) of viewer.
Step S5, during the viewing process (usually, when a certain time period of the video is about to be viewed), calculating the probability of playing at each speed of m playing speeds in the next time period according to the speed transition parameter matrix, the playing speed of the current time period, and the general pheromone matrix and the classification pheromone matrix updated after the previous viewer viewed the video. The calculation formula is as follows:
wherein, alpha and beta are weight parameters; q ∈ (v)1,v2,v3,…,vm)；
I.e. the probability that the next time period (t +1 th time period) is played at speed q; playing speed of current time period t
And step S6, adjusting the video playing speed of the current viewer in the next time period according to the probability obtained by the previous calculation, namely, randomly transforming the video playing speed of the current viewer in the next time period according to the probability.
Step S7, looping steps S5 and S6, and generating a playing speed path for the current viewer to watch the video after the playing is finished
Wherein
For the current viewingThe player watches the playing speed at the T-th time slot, T being 1,2,3, …, T.
And S8, after the viewer watches the whole video, collecting the post-class feedback information of the current viewer, updating the general pheromone matrix and the classified pheromone matrix according to the post-class feedback information and the playing speed path V (n) thereof, and repeating the steps S3-S8 for the next viewer. The specific updating method is as follows:
firstly, obtaining the comprehensive Score (n) of the current viewer to the whole-course playing speed of the video, and respectively calculating the average Score of all the viewers up to the current timeaveAnd average score of all viewers of the same type
And then using ScoreaveAnd
calculating update parameters (n) andstyle(n)(n)：
then, the general pheromone matrix and the classification pheromone matrix are updated by using the updating parameters, and the updating formula is as follows:
wherein:
wherein, c0、c1Update constants for the general pheromone matrix and the classified pheromone matrix, respectively; rho0、ρ1The decay rates of the general pheromone matrix and the classified pheromone matrix, respectively. That is, each time a viewer finishes viewing the video, an iteration is completed, and each iteration updates the general pheromone matrix and the classified pheromone matrix of the video.
As the number of viewers of the video increases, each type of playback speed path converges, and at this time, the playback speed paths corresponding to the various types can be visualized, specifically, taking the five types shown in table 1 as an example, an exemplary visualized playback speed path is shown in fig. 2. The subsequent lecturer of the video can adjust the speed migration parameter matrix, the m possible playing speeds, the speed migration threshold value and the like according to the visual playing speed path, the feedback after class of the viewer and the like.
The foregoing is a more detailed description of the invention in connection with specific preferred embodiments and it is not intended that the invention be limited to these specific details. For those skilled in the art to which the invention pertains, several equivalent substitutions or obvious modifications can be made without departing from the spirit of the invention, and all the properties or uses are considered to be within the scope of the invention.
Claims (9)
1. A self-adaptive adjusting method for teaching video playing speed is characterized by comprising the following steps:
s1, dividing the video into T time periods, and presetting m possible playing speeds v for each time period1,v2,v3,…,vm；
S2, constructing a general pheromone matrix M ═ (τ) of the video by using the T time slots and the M playing speeds of each time slott,j(n-1))T×mSorting a matrix of pheromones
And a velocity migration parameter matrix MSpeedChange＝(μij)m×mN-1 indicates that n-1 viewers have watched the video, initially n is 1, style is 1,2,3, …, k indicates a preset type of viewer, i, j e (v)1,v2,v3,…,vm) (ii) a Wherein: tau ist,j(n-1) indicating that the video has n-1 general pheromone concentrations with the playing speed j in the t time period after the video is watched by the viewers;
the classified pheromone concentration of the playing speed j in the t time period after n-1 viewers finish watching the video is represented; mu.sijA probability factor representing a transition of a playing speed of the video from i to j;
s3, defining the nth viewer as the current viewer, collecting preview feedback information of the current viewer after watching the pre-generated preview video, and classifying the current viewer according to the preview feedback information, wherein the type of the current viewer is style (n);
s4, according to the type style (n) of the current viewer, calculating the playing speed of the current viewer watching the video in the 1 st time period
And speed the current viewer
Starting to watch the video;
s5, in the viewing process, calculating the probability that the playing speed of the current viewer changes to each of the m playing speeds when the current viewer views the video in the next time period according to the speed transition parameter matrix, the playing speed of the current time period, and the general pheromone matrix and the classification pheromone matrix updated after the previous viewer views the video, which specifically includes:
if the playing speed of the current time period t
The playing speed of the current viewer watching the video in the next time period
Probability for each of the m playback speeds
Comprises the following steps:
wherein, alpha and beta are weight parameters; q ∈ (v)1,v2,v3,…,vm)；
S6, adjusting the video playing speed of the current viewer in the next time period according to the probability;
s7, looping steps S5 and S6, and generating a playing speed path for the current viewer to watch the video after the playing is finished
Wherein
For the playing speed when the current viewer watches the T-th time slot, T is 1,2,3, …, T;
s8, collecting the feedback information after class of the current viewer, updating the general pheromone matrix and the classified pheromone matrix according to the feedback information after class and the playing speed path V (n), and repeating the steps S3-S8 for the next viewer.
2. The adaptive adjusting method for teaching video playing speed according to claim 1, wherein the step S1 specifically includes:obtaining the total duration t of the videototalAnd dividing the time interval into T time intervals, wherein the time length of each time interval of the first T-1 time intervals is Tspace；
Wherein, ttotal、T、tspaceThe relationship between the three is T ═ Ttotal/tspace]+1。
3. The adaptive adjustment method for video playing speed in education as claimed in claim 1, wherein at the initialization of step S2, for any t, j, style, τt,j(0)＝1，
4. The adaptive adjustment method for the video playing speed of teaching according to claim 1, wherein the speed migration parameter matrix satisfies:
5. The adaptive adjusting method for teaching video playing speed according to claim 1, wherein the step S3 specifically includes:
s31, generating a preview video of the video;
s32, collecting preview feedback information after a current viewer watches the preview video at a default speed, wherein the preview feedback information comprises play speed feedback, language difficulty feedback and content difficulty feedback;
and S33, classifying the current viewer according to the playing speed feedback, the language difficulty feedback and the content difficulty feedback.
6. The adaptive adjusting method for teaching video playing speed according to claim 1, wherein step S8 includes:
s81, acquiring the current viewer positionThe overall Score (n) of the full play speed of the video is calculated, and the average Score scores of all viewers up to the present are calculated respectivelyaveAnd average score of all viewers of the same type
S82 use of ScoreaveAnd
calculating update parameters (n) andstyle(n)(n)：
s83, using the updated parameters (n) andstyle(n)(n) updating the general pheromone matrix and the classified pheromone matrix by the following formula:
τt,j(n)＝ρ0·τt,j(n-1)+Δτt,j(n)，
wherein:
7. The adaptive adjustment method for the video playback speed in teaching according to claim 1, further comprising the steps of:
and S9, visualizing the playing speed paths when the playing speed paths corresponding to each type converge with the increase of the viewers to obtain the playing speed path curve graphs of the different types of viewers of the video.
8. The adaptive adjustment method for video playback speed in teaching according to claim 4, further comprising the step of adjusting by the lecturer: and the video lecturer adjusts the speed migration parameter matrix, the m possible playing speeds and the speed migration threshold value by comparing the post-session feedback of the viewer and the playing speed path.
9. The adaptive adjusting method for teaching video playing speed according to claim 1, wherein the step S6 specifically includes: and randomly transforming the video playing speed of the current viewer in the next time period according to the probability.
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| CN113012506B (en) * | 2021-03-01 | 2022-10-11 | 安徽壹芯科技股份有限公司 | Interactive teaching system based on big data |
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