A method, device, medium and electronic device for retrieving recorded video

Abstract

The present disclosure provides a method, device, medium and electronic device for retrieving recorded and broadcasted videos, the method comprising: obtaining a keyword group in a sentence input by a lecturer or a student; performing hierarchical classification based on the keywords in the keyword group to obtain a first-level keyword group and a second-level keyword group; performing a search based on the first-level keyword group in a search courseware information set including a plurality of first-level keyword groups to obtain an image segment identifier corresponding to a first-level keyword group matching the first-level keyword group; performing a search based on the second-level keyword group in an image information set including a plurality of second-level keyword groups indicated by the image segment identifier to obtain a matching key time point corresponding to a second-level keyword group matching the second-level keyword group; and starting to play the image video and / or the courseware video based on the matching key time point.

Description

Technical Field

[0001] The present disclosure relates to the field of search technology, and in particular to a method, device, medium and electronic device for retrieving recorded and broadcasted videos. Background Art

[0002] With the development of computer technology, live teaching based on the Internet has begun to emerge, and a panoramic smart blackboard combined with multimedia technology has also emerged with live teaching.

[0003] The panoramic smart blackboard is usually placed in the classroom, and students watch the teaching content in the panoramic smart blackboard through remote live broadcast. The desktop of the panoramic smart blackboard usually includes two fixed display areas, namely the area for displaying the full-body image of the lecturer and the area for displaying the teaching text (such as the display area of ​​the presentation). During the live broadcast, two cameras are usually used to shoot the full-body image area and the teaching text area respectively, and the two videos are made into a composite video in real time so that they can be played repeatedly in subsequent teaching.

[0004] However, this type of recorded and broadcasted synthetic video seriously affects teaching interaction. Students cannot get answers to questions directly from the recorded and broadcasted synthetic video, but need to watch it repeatedly to find the corresponding knowledge in the video, or need to arrange another teacher to answer the questions. This teaching method is extremely unfriendly in practice.

[0005] Therefore, the present disclosure provides a method for retrieving recorded videos to solve one of the above technical problems. Summary of the invention

[0006] The purpose of the present disclosure is to provide a method, device, medium and electronic device for retrieving recorded and broadcasted videos, which can solve at least one of the technical problems mentioned above. The specific solution is as follows:

[0007] According to a specific implementation of the present disclosure, in a first aspect, the present disclosure provides a method for retrieving a recorded video, comprising:

[0008] Obtaining key words in the sentences input by the lecturer or the students;

[0009] Performing level division based on the keywords in the keyword group to obtain a first-level keyword group and a second-level keyword group;

[0010] Based on the first-level keyword group, a search is performed in a search courseware information set including a plurality of first-category keyword groups, and an image segment identifier corresponding to a first-category keyword group matching the first-level keyword group is obtained, wherein the first-category keyword group is a keyword group obtained from a courseware segment, and the courseware segment is a video segment obtained by dividing a courseware video into units of courseware pages in the courseware video;

[0011] Based on the second-level keyword group, a search is performed in the image information set including a plurality of second-category keyword groups indicated by the image segment identifier to obtain a matching key time point corresponding to the second-category keyword group that matches the second-level keyword group, wherein the second-category keyword group is a keyword group obtained based on an audio segment in the image segment, and the image segment is a video segment obtained by dividing the image video based on the time period corresponding to the courseware segment;

[0012] The image video and / or the courseware video starts playing based on the matching key time point.

[0013] According to a specific embodiment of the present disclosure, in a second aspect, the present disclosure provides a retrieval device for recorded and broadcasted videos, comprising:

[0014] An acquisition unit, used for acquiring a key word group in a sentence input by a lecturer or a student;

[0015] A grading unit, configured to perform grading based on the keywords in the keyword group to obtain a first-level keyword group and a second-level keyword group;

[0016] A primary search unit, configured to perform a search based on the first-level keyword group in a search courseware information set including a plurality of first-category keyword groups, and obtain an image segment identifier corresponding to a first-category keyword group matching the first-level keyword group, wherein the first-category keyword group is a keyword group obtained from a courseware segment, and the courseware segment is a video segment obtained by dividing a courseware video into units of courseware pages in the courseware video;

[0017] A secondary retrieval unit is used to perform a search in an image information set including a plurality of second-category keyword groups indicated by the image segment identifier based on the second-level keyword group, and obtain a matching key time point corresponding to a second-category keyword group that matches the second-level keyword group, wherein the second-category keyword group is a keyword group obtained based on an audio segment in an image segment, and the image segment is a video segment obtained by dividing an image video based on a time period corresponding to the courseware segment;

[0018] A playback unit is used to start playing the image video and / or the courseware video based on the matching key time point.

[0019] According to a specific implementation of the present disclosure, in a third aspect, the present disclosure provides a computer-readable storage medium having a computer program stored thereon, wherein when the program is executed by a processor, the method for retrieving the recorded video as described in any one of the above items is implemented.

[0020] According to the specific implementation of the present disclosure, in a fourth aspect, the present disclosure provides an electronic device, including: one or more processors; a storage device for storing one or more programs, when the one or more programs are executed by the one or more processors, the one or more processors implement the retrieval method for the recorded video as described in any one of the above items.

[0021] Compared with the prior art, the above solution of the embodiment of the present disclosure has at least the following beneficial effects:

[0022] The present disclosure provides a method, device, medium and electronic device for retrieving recorded videos. The present disclosure divides the keyword groups in the sentences input by the lecturer or the students into first-level keyword groups and second-level keyword groups according to the level, and then respectively retrieves the corresponding two-level information sets through the first-level keyword groups and the second-level keyword groups, from rough positioning to detailed positioning, so as to find the playback time point related to the input sentence in the recorded video. The accuracy and consistency of the recorded video retrieval are guaranteed, and the interaction between the lecturer and the students and the recorded video is realized. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 A flowchart of a method for retrieving recorded and broadcasted videos according to an embodiment of the present disclosure is shown;

[0024] Figure 2 A flow chart showing a method for generating a courseware information set according to an embodiment of the present disclosure is shown;

[0025] Figure 3 A flowchart of a method for generating an image information set according to an embodiment of the present disclosure is shown;

[0026] Figure 4 A flowchart of a method for generating data in a graded data set according to an embodiment of the present disclosure is shown;

[0027] Figure 5 A unit block diagram of a device for retrieving recorded and broadcasted videos according to an embodiment of the present disclosure is shown;

[0028] Figure 6 A schematic diagram of a connection structure of an electronic device provided according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0029] In order to make the purpose, technical solutions and advantages of the present disclosure clearer, the present disclosure will be further described in detail below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0030] The terms used in the embodiments of the present disclosure are only for the purpose of describing specific embodiments, and are not intended to limit the present disclosure. The singular forms "a", "said" and "the" used in the embodiments of the present disclosure and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings, and "multiple" generally includes at least two.

[0031] It should be understood that the term "and / or" used in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0032] It should be understood that although the terms first, second, third, etc. may be used to describe in the disclosed embodiments, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, without departing from the scope of the disclosed embodiments, the first may also be referred to as the second, and similarly, the second may also be referred to as the first.

[0033] As used herein, the words "if" and "if" may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0034] It should also be noted that the term "includes", "comprising" or any other variation thereof is intended to cover non-exclusive inclusion, so that a commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprising a ..." do not exclude the existence of other identical elements in the commodity or device including the elements.

[0035] The optional embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

[0036] Example 1

[0037] The embodiment provided by the present disclosure is an embodiment of a method for retrieving recorded and broadcasted videos.

[0038] Combine the following Figure 1 The embodiments of the present disclosure are described in detail.

[0039] When recording and broadcasting videos, the disclosed embodiment provides two cameras, one camera is used to capture the image video of the teacher teaching in the panoramic smart blackboard, and the other camera is used to capture the courseware video of the lecture in the panoramic smart blackboard.

[0040] The image video and the courseware video are collected synchronously. The image video and the courseware video collected synchronously can be understood as the video collected separately after the image video and the courseware video are synchronized based on the same clock. For example, at time point T1, the panoramic intelligent blackboard plays the video image A1 of the image video and the video image B1 of the courseware video; the camera N1 is used to collect the image video, and the camera N2 is used to collect the courseware video; when the camera N1 and the camera N2 are synchronized based on the same clock, the camera N1 collects the video image A2 at time point T1, and the timestamp marked at the video image A2 is TT1, and the camera N2 collects the video image B2 at time point T1, and the timestamp marked at the video image B2 is the same as TT1. At this time, the video image A2 is consistent with the video image A1, and the video image B2 is consistent with the video image B1. That is, the time points of the video images collected synchronously at the same time point are kept consistent. To avoid abnormal retrieval due to the time misalignment of the multi-video mark when retrieving multi-video information, the synchronous collection of videos ensures the accuracy of the retrieved information.

[0041] The most widely used courseware includes electronic presentations (PowerPoint, PPT for short). PPT can present pre-made teaching content page by page by playing slides.

[0042] In a courseware video, each page of the courseware is called a courseware page. Each time a courseware page is displayed, the content of the courseware page remains unchanged until the page is turned. Therefore, in the disclosed embodiment, a video segment showing the content of the same page in a courseware video is called a courseware segment. The video image in the courseware segment is called a courseware segment image. The display content of all courseware segment images in a courseware segment is the same.

[0043] If a courseware segment is located in a courseware video for a time period Ta, then the video segment in the synchronously acquired image video within the time period Ta is called an image segment, and the audio segment in the image segment is called an audio segment.

[0044] The disclosed embodiment provides a retrieval method based on the recorded video so that the teacher or the students can interact with the recorded video.

[0045] Step S101, obtaining a keyword group in a sentence input by a lecturer or a student.

[0046] A sentence may be a string of text inputted through an input method, or a voice inputted through a microphone. It should be understood by those skilled in the art that any feasible method may be used for input.

[0047] For example, the course is to explain Newton's second law of motion, and the students in the class enter a string of text through the input method: "Newton's second law of motion formula".

[0048] The keyword group includes multiple keywords. The keywords refer to multiple core words in a sentence, and the core semantics of the sentence can be represented by the multiple core words.

[0049] For example, continuing the above example, the keywords are: "Newton", "second", "motion", "law" and "formula", which constitute the keyword group.

[0050] Step S102, performing level division based on the keywords in the keyword group to obtain a first-level keyword group and a second-level keyword group.

[0051] According to the characteristics of the recorded video, the disclosed embodiment divides the search into two-level search, so as to accurately find the video location required by the lecturer or the student. In order to cooperate with the two-level search, the keyword group is divided into the first-level keyword group and the second-level keyword group before the search.

[0052] In some specific embodiments, the step of performing level division based on the keywords in the keyword group to obtain the first-level keyword group and the second-level keyword group includes the following steps:

[0053] Step S102-1, performing a search in a level data set based on the keywords in the keyword group to obtain the level tags of the keywords.

[0054] The level data set includes the correspondence between keywords and level tags.

[0055] The grade mark includes a primary mark or a secondary mark.

[0056] The step of performing a search in the level data set based on the keywords in the keyword group to obtain the level tags of the keywords can be understood as obtaining each keyword from the keyword group, searching the keywords in the level data set for each keyword, and obtaining the level tags corresponding to the matching keywords. For example, the keyword group is: "Newton", "second", "motion", "law" and "formula"; the records in the level data set are as follows:

[0057] Keywords Level Mark Newton 1 second 1 sports 1 law 1 formula 2

[0058] Among them, the level mark is 1, which means the first-level mark; the level mark is 2, which means the second-level mark.

[0059] Step S102-2: Combining keywords with first-level tags to form a first-level keyword group, and combining keywords with second-level tags to form a second-level keyword group.

[0060] For example, continuing the above example, the first-level keyword group generated by combination is: "Newton", "second", "motion" and "law"; the second-level keyword group generated by combination is "formula".

[0061] Step S103: performing a search in a search courseware information set including a plurality of first-category keyword groups based on the first-level keyword group, and obtaining an image segment identifier corresponding to the first-category keyword group matching the first-level keyword group.

[0062] The first type of keyword group is a keyword group obtained from a courseware segment, and the courseware segment is a video segment obtained by dividing the courseware page in the courseware video as a unit.

[0063] In the courseware video, each page of the courseware is called a courseware page. Each time a courseware page is displayed, the content of the courseware page remains unchanged until the page is turned. The video image in the courseware segment is called a courseware segment image. It can be understood that all courseware segment images in the courseware segment are the same.

[0064] The courseware information set includes a correspondence between a first category of keyword groups and image segment identifiers.

[0065] The purpose of this step is to find the first type of keyword group whose matching degree meets the preset matching degree condition from the courseware information set, so as to obtain the image segment identifier corresponding to the first type of keyword group in the courseware information set.

[0066] In the disclosed embodiment, each image segment has a corresponding image information set. The image segment identifier is used to indicate the image information set. For example, the image segment identifier is the name of the image information set, PAGE_1_TABLE, PAGE_2_TABLE.

[0067] Since the courseware segments are mainly used to display the key content and knowledge structure of the teaching, the first type of keyword group includes the summary information of the teaching content. This step realizes the rough positioning of the summary information of the teaching content based on the question.

[0068] The first-level keyword group obtains the image segment identifier by matching with the first-class keyword group in the courseware information set, which improves the adaptability of the retrieval and ensures the effectiveness of the retrieval.

[0069] In some specific embodiments, performing a search based on the first-level keyword group in a search courseware information set including a plurality of first-category keyword groups to obtain an image segment identifier corresponding to a first-category keyword group matching the first-level keyword group includes the following steps:

[0070] Step S103-1, matching the first-level keyword group with the first-category keyword group in the courseware information set, and obtaining a first matching result for each first-category keyword group.

[0071] In the disclosed embodiment, the first matching result includes a first matching degree.

[0072] The first matching degree refers to the ratio of the first matching number to the number of first-category keywords in the first-category keyword group.

[0073] The first matching number refers to the number of identical words between the first-level keywords in the first-level keyword group and the first-category keywords in the first-category keyword group.

[0074] For example, the first-level keyword group is: "Newton", "second", "motion" and "law", and the first-category keyword group A in the courseware information set is: "Newton", "second", "motion" and "law"; since the first-category keywords in the first-category keyword group A are the same as the first-level keywords in the first-level keyword group, the first matching number is 4, and the number of first-category keywords in the first-category keyword group A is also 4, then the first matching degree is 100%.

[0075] Step S103 - 2 , determining that the first category keyword group whose first matching result satisfies a preset first matching condition is the first category keyword group matching the first level keyword group.

[0076] For example, the first matching condition is preset as follows: the first matching result is greater than or equal to 80%; continuing the above example, the first category keyword group A is determined to be the matched first category keyword group.

[0077] Step S103 - 3 , searching the courseware information set based on the first category keyword group matching the first level keyword group to obtain a corresponding video clip identifier.

[0078] Since the courseware information set includes the correspondence between the first-class keyword group and the image segment identifier, the corresponding image segment identifier can be retrieved from the courseware information set through the first-class keyword group that matches the first-level keyword group. For example, continuing the above example, in the courseware information set, the first-class keyword group A that matches the first-level keyword group has a correspondence with the image segment identifier PAGE_1_TABLE.

[0079] Those skilled in the art should understand that the method of step 103 may be implemented in any feasible manner.

[0080] Step S104: performing a search in the image information set indicated by the image segment identifier and including a plurality of second-category keyword groups based on the second-level keyword group, and obtaining a matching key time point corresponding to the second-category keyword group matching the second-level keyword group.

[0081] Among them, the second type of keyword group is a keyword group obtained based on the audio segment in the image segment, and the image segment is a video segment obtained by dividing the image video based on the time period corresponding to the courseware segment.

[0082] The audio in the image clip is called an audio clip.

[0083] The time period corresponding to the courseware segment refers to the time period from the start time point to the end time point of the courseware segment. If the time period of a courseware segment in the courseware video is Ta, then the video segment in the time period Ta in the synchronously collected image video is called an image segment. It can be understood that the synchronously collected courseware segment and the image segment have the same recording time, and the information generated thereby has an associated relationship.

[0084] The image information set includes the correspondence between the second category keyword groups and key time points.

[0085] The key time point refers to the starting time point of the sentence audio including the second category keywords in the second category keyword group.

[0086] Optionally, the second type of keyword group is a keyword group obtained based on the key sentence audio of the audio segment in the image segment. The key time point is the starting time point of the key sentence audio.

[0087] The key sentence audio includes sentence audio related to the teaching focus in the audio clip.

[0088] Since the video clip mainly explains the teaching content displayed in the courseware clip image in detail, the second type of keywords includes detailed information of the teaching content. This step realizes the precise positioning of the detailed information of the teaching content based on the question.

[0089] The second-level keyword group obtains the key time point for playing the recorded video by matching with the second-type keyword group in the image information set, thereby improving the adaptability of the retrieval and ensuring the effectiveness of the retrieval.

[0090] In some specific embodiments, performing a search in the image information set including a plurality of second-category keyword groups indicated by the image segment identifier based on the second-level keyword group to obtain a matching key time point corresponding to the second-category keyword group matching the second-level keyword group includes the following steps:

[0091] Step S104 - 1 , matching the second-level keyword group with the second-category keyword group in the image information set, and obtaining a second matching result for each second-category keyword group.

[0092] In the disclosed embodiment, the second matching result includes a second matching degree.

[0093] The second matching degree refers to the ratio of the second matching number to the number of second-category keywords in the second-category keyword group.

[0094] The second matching number refers to the number of identical words between the second-level keywords in the second-level keyword group and the second-category keywords in the second-category keyword group.

[0095] For example, the second-level keyword group is "formula", and there is a second-category keyword group B in the courseware information set: "formula"; since the second-category keywords in the second-category keyword group B are the same as the second-level keywords in the second-level keyword group, the second matching number is 1, and the number of second-category keywords in the second-category keyword group B is also 1, then the second matching degree is 100%.

[0096] Step S104-2: Determine that the first-category keyword group whose second matching result meets the preset second matching condition is a second-category keyword group that matches the second-level keyword group.

[0097] For example, the preset second matching condition is: the second matching result is greater than or equal to 80%; continuing the above example, the second category keyword group B is determined to be the second category keyword group that matches the second level keyword group.

[0098] Step S104 - 3 , searching the image information set based on the second category keyword group that matches the second level keyword group, and obtaining the corresponding matching key time point.

[0099] Since the image information set includes the correspondence between the second-class keyword group and the key time point, the corresponding key time point (i.e., the matching key time point) can be retrieved from the image information set by the second-class keyword group that matches the second-level keyword group. For example, continuing the above example, in the image information set, the second-class keyword group B that matches the second-level keyword group has a correspondence with the key time point "6 minutes and 30 seconds".

[0100] Those skilled in the art should understand that the method of step 104 may be implemented in any feasible manner.

[0101] Step S105: start playing the image video and / or the courseware video based on the matching key time point.

[0102] The disclosed embodiment divides the keyword groups in the sentences input by the lecturer or the students into first-level keyword groups and second-level keyword groups according to the level, and then retrieves the corresponding two-level information sets through the first-level keyword groups and the second-level keyword groups respectively, from rough positioning to detailed positioning, so as to find the playback time point related to the input sentence in the recorded video. The accuracy and consistency of the recorded video retrieval are guaranteed, and the interaction between the lecturer and the students and the recorded video is realized.

[0103] Example 2

[0104] Since the embodiments of the present disclosure are further optimized based on the above embodiments, the explanations based on the same method composition and the same name meanings are the same as those of the above embodiments and will not be repeated here.

[0105] The present disclosure provides a method for generating a courseware information set. Figure 2 As shown, the method further comprises the following steps:

[0106] Step S201, obtaining each courseware segment in the courseware video.

[0107] In the disclosed embodiment, a video segment in a courseware video that displays the content of the same courseware page is referred to as a courseware segment.

[0108] Step S202: Generate an image segment identifier indicating the image information set according to the courseware segment.

[0109] In the disclosed embodiment, each image segment has a corresponding image information set. The image segment identifier is used to indicate the image information set. For example, the image segment identifier is the name of the image information set, PAGE_1_TABLE, PAGE_2_TABLE.

[0110] Step S203, obtaining the corresponding first-category keyword group based on each courseware segment.

[0111] Since all the courseware segment images in the courseware segment are the same, the obtaining of the corresponding first category keyword group based on each courseware segment can be understood as obtaining the corresponding first category keyword group based on any courseware segment image in the courseware segment.

[0112] Based on the text semantic analysis model, text semantic analysis is performed on the courseware segment image in each courseware segment to obtain the corresponding first category keyword group.

[0113] The text semantic analysis model is an analysis model generated after the text in the history courseware fragment image is trained with the history courseware fragment image as a training sample. The text semantic analysis model can analyze the text in the courseware fragment image and extract the first category of keywords from the text in the courseware fragment image according to the semantics of the text to form the first category of keyword groups.

[0114] The text semantic analysis model is used to perform text semantic analysis on the courseware fragment images, which improves the accuracy of the text semantic analysis in the image.

[0115] Step S204: generating the courseware information set based on each first-category keyword group and the image segment identifier corresponding to the first-category keyword group.

[0116] Since the first-category keyword groups and the image segment identifiers in the courseware information set have a corresponding relationship, all the first-category keyword groups obtained in the courseware video and the image segment identifiers corresponding to the first-category keyword groups are saved to generate the courseware information set.

[0117] Example 3

[0118] Since the embodiments of the present disclosure are further optimized based on the above embodiments, the explanations based on the same method composition and the same name meanings are the same as those of the above embodiments and will not be repeated here.

[0119] The present disclosure provides a method for generating an image information set. Figure 3 As shown, the method further comprises the following steps:

[0120] Step S301, in the image video, obtain the image segment corresponding to the courseware segment based on each time period.

[0121] The time period refers to the time period from the start time point to the end time point of the courseware segment.

[0122] Step S302: Acquire multiple key sentence audios based on the audio segments in each image segment.

[0123] The key sentence audio includes sentence audio related to the teaching focus in the audio clip.

[0124] Step S303, obtaining the original keyword group and the key time point at which the key sentence audio appears based on each key sentence audio.

[0125] Based on the audio semantic analysis model, audio semantic analysis is performed on the key sentence audio to obtain the original keyword group.

[0126] The audio semantic analysis model uses the historical key sentence audio as a training sample and performs semantic recognition training on the speaker's sentence audio in the historical key sentence audio to generate an analysis model. The audio semantic analysis model can analyze the key sentence audio in the audio clip and extract the original keywords, that is, the original keyword group, from the key sentence audio.

[0127] The disclosed embodiment performs audio semantic analysis on key sentence audio through an audio semantic analysis model, thereby improving the accuracy of the audio semantic analysis.

[0128] Step S304, removing the first category of keywords in the first category of keyword groups corresponding to the courseware segment from the original keyword groups of each key sentence audio, to obtain the second category of keyword groups.

[0129] The original keyword group belonging to the same key sentence audio is obtained, and the first category of keywords in the original keyword group corresponding to the courseware segment is deleted, thereby reducing the repeated information of the secondary search and improving the search efficiency.

[0130] Step S305 : generating an image information set corresponding to the image segment based on each second-category keyword group of each image segment and the key time point corresponding to the second-category keyword group.

[0131] Since the second-category keyword groups in the image information set have a corresponding relationship with the key time points, all the second-category keyword groups and the key time points corresponding to the second-category keyword groups obtained in the image video are saved according to the corresponding image information set to generate the image information set of the corresponding image segment. That is, each image segment has a corresponding image information set.

[0132] Example 4

[0133] Since the embodiments of the present disclosure are further optimized based on the above embodiments, the explanations based on the same method composition and the same name meanings are the same as those of the above embodiments and will not be repeated here.

[0134] The present disclosure provides a method for generating a level data set. Figure 4 As shown, the specific method also includes the following steps:

[0135] Step S401a, obtaining the first category of keywords in the first category of keyword groups based on the courseware information set.

[0136] Based on the above embodiments, the embodiment of the present disclosure acquires the first category of keywords from the courseware information set.

[0137] Step S402a: storing the first category of keywords into the level data set, and using the first level mark as the level mark of the first category of keywords.

[0138] For example, if the first-category keywords are obtained in the courseware information set: "Newton", "second", "motion" and "law", the records stored in the level data set are as follows:

[0139] Keywords Level Mark Newton 1 second 1 sports 1 law 1

[0140] Among them, the level mark is 1, which means the first-level mark.

[0141] The specific method also includes the following steps:

[0142] Step S401b: obtaining the second category keywords in the second category keyword group based on the image information set.

[0143] Based on the above embodiments, the embodiment of the present disclosure acquires the second category of keywords from the image information set.

[0144] Step S402b: storing the second-category keywords into the level data set, and using the second-level mark as the level mark of the second-category keywords.

[0145] For example, if the second-category keyword "formula" is obtained in the image information set, the following records are stored in the level data set:

[0146] Keywords Level Mark formula 2

[0147] Among them, the level mark is 2, which means the secondary mark.

[0148] Example 5

[0149] The present disclosure also provides an apparatus embodiment that is consistent with the above-mentioned embodiment, and is used to implement the method steps described in the above-mentioned embodiment. The explanation based on the same name meaning is the same as that of the above-mentioned embodiment, and has the same technical effect as that of the above-mentioned embodiment, and will not be repeated here.

[0150] like Figure 5 As shown, the present disclosure provides a retrieval device 500 for recorded and broadcasted videos, comprising:

[0151] An acquisition unit 501 is used to acquire a keyword group in a sentence input by a lecturer or a student;

[0152] A grading unit 502, configured to perform grading based on the keywords in the keyword group to obtain a first-level keyword group and a second-level keyword group;

[0153] A primary search unit 503 is used to perform a search in a search courseware information set including a plurality of first-category keyword groups based on the first-level keyword group, and obtain an image segment identifier corresponding to a first-category keyword group matching the first-level keyword group, wherein the first-category keyword group is a keyword group obtained from a courseware segment, and the courseware segment is a video segment obtained by dividing a courseware video into units of courseware pages in the courseware video;

[0154] A secondary retrieval unit 504 is used to perform a search in the image information set including a plurality of second-category keyword groups indicated by the image segment identifier based on the second-level keyword group, and obtain a matching key time point corresponding to the second-category keyword group matching the second-level keyword group, wherein the second-category keyword group is a keyword group obtained based on an audio segment in the image segment, and the image segment is a video segment obtained by dividing the image video based on the time period corresponding to the courseware segment;

[0155] The playing unit 505 is used to start playing the image video and / or the courseware video based on the matching key time point.

[0156] Optionally, the primary retrieval unit 503 includes:

[0157] A first matching subunit, used for matching the first-level keyword group with the first-category keyword group in the courseware information set, and obtaining a first matching result for each first-category keyword group;

[0158] A first determining subunit, configured to determine that the first category of keyword groups that satisfy a preset first matching condition in the first matching result is a first category of keyword groups that matches the first level keyword groups;

[0159] The first search subunit is used to search the courseware information set based on the first category keyword group matching the first level keyword group to obtain the corresponding image segment identifier.

[0160] Optionally, the secondary retrieval unit 504 includes:

[0161] A second matching subunit is used to match the second-level keyword group with the second-category keyword group in the image information set to obtain a second matching result for each second-category keyword group;

[0162] A second determining subunit, configured to determine that the first category of keyword group that satisfies the preset second matching condition in the second matching result is a second category of keyword group that matches the second level keyword group;

[0163] The second retrieval subunit is used to retrieve the image information set based on the second category keyword group matching the second level keyword group to obtain the corresponding matching key time point.

[0164] Optionally, the classification unit 502 includes:

[0165] A third retrieval subunit, configured to perform a search in the level data set based on the keywords in the keyword group to obtain the level tags of the keywords;

[0166] The combining subunit is used to combine keywords with first-level tags to form a first-level keyword group, and to combine keywords with second-level tags to form a second-level keyword group.

[0167] Optionally, the device further comprises a level classification unit;

[0168] The level classification unit comprises:

[0169] A first acquisition subunit, configured to acquire first-category keywords in a first-category keyword group based on the courseware information set;

[0170] A first storing subunit, used for storing the first category of keywords into the grade data set, and using the first level mark as the grade mark of the first category of keywords;

[0171] and / or,

[0172] A second acquisition subunit, configured to acquire second-category keywords in a second-category keyword group based on the image information set;

[0173] The second storing subunit is used to store the second category keywords into the level data set and use the second level mark as the level mark of the second category keywords.

[0174] Optionally, the device further includes a first generating unit;

[0175] The first generating unit comprises:

[0176] A courseware segment acquisition subunit is used to acquire each courseware segment in the courseware video;

[0177] An identification generating subunit, used for generating an image segment identification indicating the image information set according to the courseware segment;

[0178] A first obtaining subunit is used to obtain a corresponding first-category keyword group based on each courseware segment;

[0179] The first generating subunit is used to generate the courseware information set based on each first-category keyword group and the image segment identifier corresponding to the first-category keyword group.

[0180] Optionally, the device further includes a second generating unit;

[0181] The second generating unit comprises:

[0182] An image segment acquisition subunit is used to acquire image segments corresponding to the courseware segments in the image video based on each time period;

[0183] An audio acquisition subunit, used for acquiring a plurality of key sentence audios based on the audio segments in each image segment;

[0184] An original information acquisition subunit, used to obtain an original keyword group and a key time point at which the key sentence audio appears based on each key sentence audio;

[0185] The second obtaining subunit is used to remove the first category of keywords in the first category of keyword groups corresponding to the courseware segment from the original keyword groups of each key sentence audio to obtain the second category of keyword groups;

[0186] The second generating subunit is used to generate an image information set corresponding to the image segment based on each second-category keyword group of each image segment and a key time point corresponding to the second-category keyword group.

[0187] The disclosed embodiment divides the keyword groups in the sentences input by the lecturer or the students into first-level keyword groups and second-level keyword groups according to the level, and then retrieves the corresponding two-level information sets through the first-level keyword groups and the second-level keyword groups respectively, from rough positioning to detailed positioning, so as to find the playback time point related to the input sentence in the recorded video. The accuracy and consistency of the recorded video retrieval are guaranteed, and the interaction between the lecturer and the students and the recorded video is realized.

[0188] Example 6

[0189] like Figure 6 As shown, this embodiment provides an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method steps described in the above embodiment.

[0190] Example 7

[0191] An embodiment of the present disclosure provides a non-volatile computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions can execute the method steps described in the above embodiment.

[0192] Example 8

[0193] Reference below Figure 6, which shows a schematic diagram of the structure of an electronic device suitable for implementing the embodiments of the present disclosure. The terminal device in the embodiments of the present disclosure may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 6 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0194] like Figure 6 As shown, the electronic device may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage device 608 into a random access memory (RAM) 603. In RAM 603, various programs and data required for the operation of the electronic device are also stored. The processing device 601, ROM 602, and RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0195] Typically, the following devices may be connected to the I / O interface 605: an input device 606 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 607 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 608 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 609. The communication device 609 may allow the electronic device to communicate with other devices wirelessly or by wire to exchange data. Although Figure 6 An electronic device having various devices is shown, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead.

[0196] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device 609, or installed from a storage device 608, or installed from a ROM 602. When the computer program is executed by the processing device 601, the above-mentioned functions defined in the method of the embodiment of the present disclosure are executed.

[0197] It should be noted that the computer-readable medium disclosed above may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device. In the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0198] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0199] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0200] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0201] The units involved in the embodiments described in the present disclosure may be implemented by software or hardware, wherein the name of a unit does not, in some cases, limit the unit itself.

Claims

1. A method for retrieving recorded videos, characterized in that: include: Obtaining key words in the sentences input by the lecturer or the students; Performing level division based on the keywords in the keyword group to obtain a first-level keyword group and a second-level keyword group; Based on the first-level keyword group, a search is performed in a search courseware information set including a plurality of first-category keyword groups, and an image segment identifier corresponding to a first-category keyword group matching the first-level keyword group is obtained, wherein the first-category keyword group is a keyword group obtained from a courseware segment, and the courseware segment is a video segment obtained by dividing a courseware video into units of courseware pages in the courseware video; Based on the second-level keyword group, a search is performed in the image information set including a plurality of second-category keyword groups indicated by the image segment identifier to obtain a matching key time point corresponding to the second-category keyword group that matches the second-level keyword group, wherein the second-category keyword group is a keyword group obtained based on an audio segment in the image segment, and the image segment is a video segment obtained by dividing the image video based on the time period corresponding to the courseware segment; The image video and / or the courseware video starts playing based on the matching key time point.

2. The method according to claim 1, characterized in that The step of performing a search in a search courseware information set including a plurality of first-category keyword groups based on the first-level keyword group to obtain an image segment identifier corresponding to the first-category keyword group matching the first-level keyword group includes: Matching the first-level keyword group with the first-category keyword group in the courseware information set to obtain a first matching result for each first-category keyword group; Determine that the first category keyword group that satisfies the preset first matching condition in the first matching result is the first category keyword group that matches the first level keyword group; The courseware information set is retrieved based on the first category keyword group that matches the first level keyword group to obtain a corresponding image segment identifier.

3. The method according to claim 1, characterized in that: The step of performing a search in the image information set including a plurality of second-category keyword groups indicated by the image segment identifier based on the second-level keyword group to obtain a matching key time point corresponding to the second-category keyword group matching the second-level keyword group includes: Matching the second-level keyword group with the second-category keyword group in the image information set to obtain a second matching result for each second-category keyword group; Determine that the first category keyword group that the second matching result satisfies the preset second matching condition is a second category keyword group that matches the second level keyword group; The image information set is retrieved based on the second category keyword group that matches the second level keyword group to obtain the corresponding matching key time point.

4. The method according to claim 1, characterized in that: The step of performing level division based on the keywords in the keyword group to obtain the first-level keyword group and the second-level keyword group includes: Performing a search in a grade data set based on the keywords in the keyword group to obtain grade tags of the keywords; Keywords with first-level tags are combined to form a first-level keyword group, and keywords with second-level tags are combined to form a second-level keyword group.

5. The method according to claim 4, further comprising: Acquire the first category of keywords in the first category of keyword groups based on the courseware information set; storing the first category of keywords in the grade data set, and using the first level mark as the grade mark of the first category of keywords; and / or, Acquire the second category of keywords in the second category of keyword groups based on the image information set; The second-category keywords are stored in the level data set, and the second-level tags are used as level tags for the second-category keywords.

6. The method according to claim 1, characterized in that The method further comprises: In the courseware video, obtain each courseware segment; Generating an image segment identifier indicating the image information set according to the courseware segment; Obtaining a corresponding first-category keyword group based on each courseware segment; The courseware information set is generated based on each first-category keyword group and the image segment identifier corresponding to the first-category keyword group.

7. The method according to claim 1, characterized in that The method further comprises: In the image video, an image segment corresponding to a courseware segment is obtained based on each time period; Acquire multiple key sentence audios based on the audio clips in each image clip; Based on each key sentence audio, obtain the original key word group and the key time point at which the key sentence audio appears; In the original keyword group of each key sentence audio, the first category of keywords in the first category of keyword group corresponding to the courseware segment are removed to obtain the second category of keyword group; An image information set corresponding to the image segment is generated based on each second-category keyword group of each image segment and a key time point corresponding to the second-category keyword group.

8. A retrieval device for recorded and broadcasted videos, characterized in that: include: An acquisition unit, used for acquiring a key word group in a sentence input by a lecturer or a student; A grading unit, configured to perform grading based on the keywords in the keyword group to obtain a first-level keyword group and a second-level keyword group; A primary search unit, configured to perform a search based on the first-level keyword group in a search courseware information set including a plurality of first-category keyword groups, and obtain an image segment identifier corresponding to a first-category keyword group matching the first-level keyword group, wherein the first-category keyword group is a keyword group obtained from a courseware segment, and the courseware segment is a video segment obtained by dividing a courseware video into units of courseware pages in the courseware video; A secondary retrieval unit is used to perform a search in an image information set including a plurality of second-category keyword groups indicated by the image segment identifier based on the second-level keyword group, and obtain a matching key time point corresponding to a second-category keyword group that matches the second-level keyword group, wherein the second-category keyword group is a keyword group obtained based on an audio segment in an image segment, and the image segment is a video segment obtained by dividing an image video based on a time period corresponding to the courseware segment; A playback unit is used to start playing the image video and / or the courseware video based on the matching key time point.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

10. An electronic device, characterized in that: include: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method as claimed in any one of claims 1 to 7.

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