CN115134666A - Live broadcast card pause detection method, system, equipment and storage medium - Google Patents
Live broadcast card pause detection method, system, equipment and storage medium Download PDFInfo
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- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
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- H04N21/442—Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed, the storage space available from the internal hard disk
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Abstract
The application discloses a live broadcast card pause detection method, a live broadcast card pause detection system, live broadcast card pause detection equipment and a storage medium. The method comprises the following steps: acquiring a speech message of a live audience; filtering the speaking message according to preset pause keywords to obtain pause content messages with different weight types; carrying out de-duplication processing on the stuck content message to obtain stuck user quantities with different weight types; calculating the stuck value according to the stuck user quantities with different weight types; and when the stuck value is larger than the threshold value, pushing a stuck alarm prompt. The click-through analysis is carried out based on the interactive chat content of the audience and the anchor in the live broadcast, the interactive chat content analysis data volume is small, the analysis flow is short, the speed of generating the click-through warning message is high, the click-through warning delay is small, and better audio-visual experience is provided for users.
Description
Technical Field
The present application relates to the field of data processing, and in particular, to a live tone stuck detection method, system, device, and storage medium.
Background
With the development of the internet, the live broadcast mode is applied to various aspects of people's daily life. In the process of live broadcast, the live broadcast end can generate a phenomenon of playing pause, so that the live broadcast quality of the application of the live broadcast end needs to be evaluated to optimize the application of the broadcast end.
The current detection method for the direct broadcast playing stuck is to count the number of video frames received by a player at a direct broadcast playing end per second, calculate the frame loss rate according to the total count per second, the number of rendered video frames and the number of live broadcast source frames in each minute, generate the situation of the whole network stuck per minute, compare alarm thresholds and generate a stuck alarm message.
However, the data processing amount for generating the full network stuck condition per minute is large, the time delay is high, and the stuck alarm prompt message has a minute-level lag.
Disclosure of Invention
Based on the above problems, the present application provides a live broadcast stuck detection method, system, device and storage medium, which can perform stuck analysis based on the interactive speech between the audience and the anchor in live broadcast, and have a small calculation amount, so that the stuck alarm delay is small, and better audio-visual experience is provided for users.
The application discloses the following technical scheme:
the application provides a live broadcast stuck detection method in a first aspect, including:
acquiring a speech message of a live audience;
filtering the speaking message according to preset pause keywords to obtain pause content messages with different weight types;
carrying out de-duplication processing on the stuck content message to obtain stuck user quantities with different weight types;
calculating the stuck value according to the stuck user quantities with different weight types;
and when the stuck value is larger than the threshold value, pushing a stuck alarm prompt.
In one possible implementation, the calculating the stuck value according to the stuck user quantities of different weight types includes:
and calculating the stuck value according to the stuck user amount, the weight value and the number of the online live audiences of different weight types.
In one possible implementation, the specific way of calculating the stuck value is as follows:
calculating the product of the amount of the katton user of each weight type and the corresponding weight value to obtain a first result;
cumulatively summing the first results of different types to obtain a second result;
and calculating the second result to be divided by the number of the online live audiences to obtain a pause value.
In a possible implementation manner, the performing deduplication processing on the morton content message to obtain a morton user amount includes:
and in a preset time, the pause content message of each user is de-duplicated, so that only one pause content message of each user with different weight types is reserved, and the pause user amount with different weight types is obtained according to the number of the pause content messages with different weight types after the duplication removal.
This application second aspect provides a live card dune detecting system, includes: a chat room server and a katton analysis server;
the chat room server is used for receiving the speaking message of the live audience;
the morton analysis server is used for acquiring a speech message of a live audience; filtering the speaking message according to preset pause keywords to obtain pause content messages with different weight types; carrying out de-duplication processing on the stuck content message to obtain stuck user quantities with different weight types; calculating the stuck value according to the stuck user quantities with different weight types; and when the stuck value is larger than the threshold value, pushing a stuck alarm prompt.
In one possible implementation manner, the katton analysis server is specifically configured to calculate a katton value according to the amounts of the katton users with different weight types, the weight values and the number of online live viewers.
In one possible implementation manner, the katton analysis server is specifically configured to calculate a product of a katton user amount of each weight type and a corresponding weight value, and obtain a first result; cumulatively summing the first results of different types to obtain a second result; and calculating the second result to be divided by the number of the online live audiences to obtain a pause value.
In a possible implementation manner, the morton analysis server is specifically configured to remove the weight of the morton content message of each user within a preset time, so that only one morton content message of each user with different weight types is reserved, and the amount of the morton users with different weight types is obtained according to the number of the morton content messages with different weight types after the weight removal.
This application third aspect provides a live card pause check out test set, includes: a processor, a memory, a system bus;
the processor and the memory are connected through the system bus;
the memory is configured to store one or more programs, the one or more programs comprising instructions, which when executed by the processor, cause the processor to perform the live morton detection method of any one of the first aspects of the present application.
A fourth aspect of the present application provides a computer-readable storage medium, where instructions are stored, and when the instructions are executed on a terminal device, the terminal device is caused to execute a live morton detection method according to any one of the first aspect of the present application.
Compared with the prior art, the method has the following beneficial effects:
the application provides a live broadcast stuck detection method, which comprises the following steps: acquiring a speech message of a live audience; filtering the speaking message according to preset pause keywords to obtain pause content messages with different weight types; carrying out de-weight processing on the stuck content message to obtain stuck user quantities with different weight types; calculating the stuck value according to the stuck user quantities with different weight types; and when the stuck value is larger than the threshold value, pushing a stuck alarm prompt. The click-through analysis is carried out based on the interactive chat content of the audience and the anchor in the live broadcast, the interactive chat content analysis data volume is small, the analysis flow is short, the speed of generating the click-through warning message is high, the click-through warning delay is small, and better audio-visual experience is provided for users.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.
Fig. 1 is a schematic diagram of an example scenario provided in an embodiment of the present application;
fig. 2 is a flowchart of a live morton detection method according to an embodiment of the present disclosure;
fig. 3 is a structural diagram of a live morton detection system according to an embodiment of the present disclosure;
fig. 4 is a schematic diagram of a detection process performed by a live morton detection system according to an embodiment of the present application;
fig. 5 is a structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, embodiments accompanying the drawings are described in detail below.
As described above, in the live broadcast process, the live broadcast end may have a pause phenomenon in the broadcast, so that it is necessary to evaluate the live broadcast quality of the live broadcast end application to optimize the broadcast end application. At present, a method for detecting a blocking of a live broadcast player counts the number of video frames received by a player at a live broadcast player per second, calculates a frame loss rate according to the total count per second, the number of rendered video frames, and the number of live source frames in each minute, generates a full-network blocking condition per minute, compares an alarm threshold, and generates a blocking alarm message. However, the data processing amount for generating the full network stuck condition per minute is large, the time delay is high, and the stuck alarm prompt message has a minute-level lag.
Based on this, the embodiment of the application provides a live broadcast stuck detection method, a live broadcast stuck detection system, live broadcast stuck detection equipment and a storage medium. In order to facilitate understanding of the target detection method provided in the embodiment of the present application, the following description will be made with reference to a scenario example shown in fig. 1. Fig. 1 is a schematic diagram of a scene example provided in an embodiment of the present application. The method may be applied in the server 101.
In practical application, a server 101 acquires a speech message of a live viewer; filtering the speaking message according to preset pause keywords to obtain pause content messages with different weight types; carrying out de-duplication processing on the stuck content message to obtain stuck user quantities with different weight types; calculating the stuck value according to the stuck user quantities with different weight types; and when the stuck value is larger than the threshold value, pushing a stuck alarm prompt. The click-through analysis is carried out based on the interactive chat content of the audience and the anchor in the live broadcast, the interactive chat content analysis data volume is small, the analysis flow is short, the speed of generating the click-through condition warning message is high, the click-through alarm delay is small, and better audio-visual experience is provided for users.
Those skilled in the art will appreciate that the block diagram shown in fig. 1 is only one example in which embodiments of the present application may be implemented. The scope of applicability of the embodiments of the present application is not limited in any way by this framework.
Based on the above description, the live morton detection method provided by the embodiment of the present application will be described in detail below with reference to the accompanying drawings.
Referring to fig. 2, fig. 2 is a flowchart of a live morton detection method provided in an embodiment of the present application. As shown in fig. 2, the live broadcast stuck detection method includes:
s210, obtaining the speech message of the live audience, such as a network card, asynchronization of sound and picture, blocking and the like.
The speaking content of the user chat is a subjective index of live broadcast card pause inspection.
And S220, filtering the speaking message according to the preset morton keywords to obtain the morton content messages with different weight types.
And filtering out messages containing the stuck contents with different weights according to the stuck keywords preset by the system, and discarding most of normal chat content messages irrelevant to sticking.
In one example, different keywords correspond to different weight types of katon content messages, and different weight types of katon content messages correspond to different weight values.
And S230, carrying out de-duplication processing on the stuck content message to obtain stuck user quantities with different weight types.
In some embodiments, S230 comprises:
and in a preset time, the pause content message of each user is de-duplicated, so that only one pause content message of each user with different weight types is reserved, and the pause user amount with different weight types is obtained according to the number of the pause content messages with different weight types after the duplication removal.
In one example, the preset time may be a short period of time on the order of 10 seconds, 5 seconds, or the like.
In the filtered stuck content messages, messages which are repeatedly sent by users for expressing the needs exist, in order to remove the interference of the situation on the stuck situation analysis, the messages of each user are subjected to de-weighting within a preset time (such as 10 seconds), and only one stuck message of a single user with different weight types is reserved. And equivalently, after the weight is removed, the amount of the stuck users with different weight types in the preset time is obtained.
And S240, calculating the stuck value according to the stuck user quantities with different weight types.
In some embodiments, S240 comprises:
and calculating the Caton value according to the Caton user quantity of different weight types, the weight value and the number of the online live audiences.
The specific calculation method of the katon value is as follows:
calculating the product of the amount of the katton user of each weight type and the corresponding weight value to obtain a first result;
cumulatively summing the first results of different types to obtain a second result;
and calculating the second result to be divided by the number of the online live audiences to obtain a pause value.
In one example, the calculation of the katon value is as follows:
wherein y represents the katon value, x represents the user quantity of different types of katon messages, a represents the weight corresponding to the interaction type, and n represents the online watching mode number of the live broadcast room. The stuck value is a corresponding stuck value within a relatively short preset time (e.g., 10 seconds).
And S250, when the stuck value is larger than a threshold value, pushing a stuck alarm prompt.
In one example, the stuck alert prompt may be pushed to a viewer, a anchor, or a maintenance platform of a live platform.
The live broadcast pause detection method provided by the embodiment of the application can perform pause analysis based on the interactive chat content of the audience and the anchor in live broadcast, the interactive chat content analysis data volume is small, the analysis flow is short, and the pause condition warning message generation speed is high, so that pause alarm delay is small, and better audio-visual experience is provided for users.
Referring to fig. 3, fig. 3 is a structural diagram of a live broadcast stuck detection system according to an embodiment of the present application. As shown in fig. 3, a live morton detection system 300 includes: chat room server 310 and katton analysis server 320;
the chat room server 310 is configured to receive an utterance message of a live viewer;
the morton analysis server 320 is configured to obtain a speech message of a live audience; filtering the speaking message according to preset pause keywords to obtain pause content messages with different weight types; carrying out de-duplication processing on the stuck content message to obtain stuck user quantities with different weight types; calculating the stuck value according to the stuck user quantities with different weight types; and when the stuck value is larger than the threshold value, pushing a stuck alarm prompt.
In some embodiments, the katton analysis server is specifically configured to calculate a katton value based on the katton user amounts, the weight values, and the number of live viewers of different weight types.
In some embodiments, the katton analysis server is specifically configured to calculate a product of a katton user amount of each weight type and a corresponding weight value, and obtain a first result; cumulatively summing the first results of different types to obtain a second result; and calculating the second result to be divided by the number of the online live audiences to obtain a pause value.
In some embodiments, the morton analysis server is specifically configured to remove the weight of the morton content message of each user within a preset time, so that only one morton content message of each user with a different weight type is reserved, and the amount of the morton users with different weight types is obtained according to the number of the morton content messages with different weight types after the removal of the weight.
The live broadcast card pause detection system provided by the embodiment of the application can perform card pause analysis based on the interactive chat content of the audience and the anchor in live broadcast, the interactive chat content analysis data volume is small, the analysis flow is short, and the card pause condition warning message generation speed is high, so that the card pause alarm time delay is small, and better audio-visual experience is provided for users.
Referring to fig. 4, fig. 4 is a schematic view of a detection process performed by the live video morton detection system according to the embodiment of the present application. As shown in fig. 4, a live broadcast audience inputs a speech message through a live broadcast terminal application, the live broadcast terminal sends the speech message to a chat room server, the chat room server sends the speech message of the audience to a stuck analysis server, the stuck analysis server obtains the speech of the live broadcast audience, the speech message is filtered according to preset stuck keywords to obtain stuck content messages of different weight types, the stuck content is subjected to de-weight processing to obtain stuck user amounts of different weight types, stuck values are calculated according to the stuck user amounts of different weight types, and when the stuck value is greater than a threshold value, a stuck alarm prompt is pushed to a user concerning the stuck condition.
It should be noted that computer program code for carrying out operations of the present application may be written in any combination of one or more programming languages, including but not limited to an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, 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 the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
Referring to fig. 5, a schematic structural diagram of an electronic device 700 suitable for implementing the embodiment of the present disclosure is shown, and the electronic device is configured to implement the corresponding functions of the live morton detection system shown in fig. 3. The electronic device shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 5, electronic device 700 may include a processing means (e.g., central processing unit, graphics processor, etc.) 701 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM) 702 or a program loaded from storage 708 into a Random Access Memory (RAM) 703. In the RAM 703, various programs and data necessary for the operation of the electronic apparatus 700 are also stored. The processing device 701, the ROM 702, and the RAM 703 are connected to each other by a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.
Generally, the following devices may be connected to the I/O interface 705: input devices 706 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; an output device 707 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 708 including, for example, magnetic tape, hard disk, etc.; and a communication device 709. The communication means 709 may allow the electronic device 700 to communicate with other devices, wireless or wired, to exchange data. While fig. 5 illustrates an electronic device 700 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a non-transitory computer readable medium, the computer program containing program code for performing the method illustrated by the flow chart. In such embodiments, the computer program may be downloaded and installed from a network via the communication means 709, or may be installed from the storage means 708, or may be installed from the ROM 702. The computer program, when executed by the processing device 701, performs the above-described functions defined in the methods of embodiments of the present disclosure.
It should be noted that the computer readable medium of the present application can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In this application, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
It is noted that, as used herein, the term "include" and its variants are intended to be inclusive, i.e., "including but not limited to". The term "based on" is "based, at least in part, on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions for other terms will be given in the following description.
It should be noted that the terms "first", "second", and the like in the present application are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence relationship of the functions performed by the devices, modules or units.
It is noted that, although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.
While several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of the application. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination.
The above description is only a preferred embodiment of the application and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the disclosure herein is not limited to the particular combination of features described above, but also encompasses other arrangements formed by any combination of the above features or their equivalents without departing from the spirit of the disclosure. For example, the above features may be replaced with (but not limited to) features having similar functions disclosed in the present application.
Claims (10)
1. A live broadcast stuck detection method is characterized by comprising the following steps:
acquiring a speech message of a live audience;
filtering the speaking message according to preset pause keywords to obtain pause content messages with different weight types;
carrying out de-duplication processing on the stuck content message to obtain stuck user quantities with different weight types;
calculating the stuck value according to the stuck user quantities with different weight types;
and when the stuck value is larger than the threshold value, pushing a stuck alarm prompt.
2. The method of claim 1, wherein calculating the katon value from the katon user quantities of different weight types comprises:
and calculating the Caton value according to the Caton user quantity of different weight types, the weight value and the number of the online live audiences.
3. The method of claim 2, wherein the calculation of the katon value is performed by:
calculating the product of the amount of the katton user of each weight type and the corresponding weight value to obtain a first result;
cumulatively summing the first results of different types to obtain a second result;
and calculating the second result to be divided by the number of the online live audiences to obtain a pause value.
4. The method of claim 1, wherein the performing the deduplication processing on the katton content message to obtain different weight types of resulting katton user amount comprises:
and in a preset time, the pause content message of each user is de-duplicated, so that only one pause content message of each user with different weight types is reserved, and the pause user amount with different weight types is obtained according to the number of the pause content messages with different weight types after the duplication removal.
5. A live broadcast stuck detection system, comprising: a chat room server and a katton analysis server;
the chat room server is used for receiving the speaking message of the live audience;
the morton analysis server is used for acquiring a speech message of a live audience; filtering the speaking message according to preset pause keywords to obtain pause content messages with different weight types; carrying out de-duplication processing on the stuck content message to obtain stuck user quantities with different weight types; calculating the stuck value according to the stuck user quantities with different weight types; and when the stuck value is larger than the threshold value, pushing a stuck alarm prompt.
6. The system of claim 5, wherein the katon analysis server is further configured to calculate a katon value based on the katon user amounts, weight values, and on-line live audience amounts for different weight types.
7. The system of claim 6, wherein the katon analysis server is specifically configured to calculate a product of the amount of katon users of each weight type and the corresponding weight value, resulting in a first result; cumulatively summing the first results of different types to obtain a second result; and calculating the second result to be divided by the number of the online live audiences to obtain a pause value.
8. The system of claim 5, wherein the morton analysis server is specifically configured to, within a preset time, remove the weight of the morton content message of each user, so that only one morton content message of each user with a different weight type is reserved, and obtain the amount of the morton users with different weight types according to the number of the morton content messages with different weight types after removal of the weight.
9. The utility model provides a live card pause check out test set which characterized in that includes: a processor, a memory, a system bus;
the processor and the memory are connected through the system bus;
the memory to store one or more programs, the one or more programs including instructions, which when executed by the processor, cause the processor to perform the live stuck detection method of any of claims 1-4.
10. A computer-readable storage medium having instructions stored thereon, which when run on a terminal device, cause the terminal device to perform the live stuck detection method of any one of claims 1-4.
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