Multimedia data preloading method, device, electronic device and storage medium

Abstract

The present disclosure relates to a multimedia data preloading method, device, electronic device and storage medium, the method comprising: obtaining target operation data for multimedia that has been played; obtaining target feature data for multimedia to be played; and preloading the multimedia to be played based at least on the target operation data and the target feature data. Since the preloading data of the preloaded target multimedia is related to the target operation data and the target feature data of the multimedia to be played, the multimedia to be played can be accurately preloaded, greatly improving the preloading efficiency.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular to a multimedia data preloading method, device, electronic device and storage medium. Background Art

[0002] As terminal products such as mobile phones become more popular, users can easily play their favorite music on the terminal. If the user's network environment is not very good, in many cases, it will affect the music played on the terminal, such as slow data loading, resulting in playback jams. Therefore, it is necessary to preload the music to avoid jams caused by network quality.

[0003] In the related art, when music is preloaded, a large range of music is often preloaded. Although this can ensure the early loading of music, the loaded data may not be the data that the user wants to play, which may cause a waste of user traffic and lead to low preloading efficiency. Summary of the invention

[0004] The present disclosure provides a multimedia data preloading method, device, electronic device and storage medium.

[0005] According to one aspect of the present disclosure, a multimedia data preloading method is provided, the method comprising:

[0006] Obtaining target operation data for the played multimedia;

[0007] Acquire target feature data of the multimedia to be played;

[0008] The multimedia to be played is preloaded at least based on the target operation data and the target characteristic data.

[0009] Optionally, the target operation data includes multiple target operation behaviors;

[0010] The preloading of the multimedia to be played includes:

[0011] Determine target weights corresponding to the multiple target operation behaviors respectively;

[0012] The multimedia to be played is preloaded based on the target weight and the target characteristic data to obtain preload data.

[0013] Optionally, the preloading the to-be-played multimedia based on the target weight and the target feature data includes:

[0014] Based on the target weights, determining the priorities corresponding to the multiple target operation behaviors respectively;

[0015] Preload data corresponding to the target feature data is preloaded based on the priority.

[0016] Optionally, the played multimedia includes a first multimedia and a second multimedia having adjacent play periods, and the first multimedia and the multimedia to be played have adjacent play periods;

[0017] The determining target weights corresponding to the multiple target operation behaviors respectively includes:

[0018] Determining initial weights corresponding to the plurality of target operation behaviors respectively based on the feature data of the second multimedia;

[0019] The initial weight is adjusted according to the feature data of the first multimedia to obtain target weights corresponding to the multiple target operation behaviors respectively.

[0020] Optionally, the method further comprises:

[0021] Get network status information;

[0022] The target number of the preloaded multimedia to be played is determined based on the network status information.

[0023] Optionally, the preloading the multimedia to be played includes:

[0024] Based on the network status information, the target operation data and the target characteristic data, the target number of preloaded data of the multimedia to be played is obtained.

[0025] According to a second aspect of the present disclosure, a multimedia data preloading device is provided, the device comprising:

[0026] A target operation data acquisition module is used to acquire target operation data for the played multimedia;

[0027] A target feature data acquisition module, used to acquire target feature data of the multimedia to be played;

[0028] A preloading module is used to preload the multimedia to be played based on at least the target operation data and the target characteristic data.

[0029] Optionally, the target operation data includes a plurality of target operation behaviors; the preloading module is specifically used to:

[0030] Determine target weights corresponding to the multiple target operation behaviors respectively;

[0031] The multimedia to be played is preloaded based on the target weight and the target characteristic data to obtain preload data.

[0032] Optionally, the preloading module is further used to:

[0033] Based on the target weights, determining the priorities corresponding to the multiple target operation behaviors respectively;

[0034] Preload data corresponding to the target feature data is preloaded based on the priority.

[0035] Optionally, the played multimedia includes a first multimedia and a second multimedia having adjacent play periods, and the first multimedia and the to-be-played multimedia have adjacent play periods; the preloading module is specifically configured to:

[0036] Determining initial weights corresponding to the plurality of target operation behaviors respectively based on the feature data of the second multimedia;

[0037] The initial weight is adjusted according to the feature data of the first multimedia to obtain target weights corresponding to the multiple target operation behaviors respectively.

[0038] Optionally, the device further comprises:

[0039] An information acquisition module, used to obtain network status information;

[0040] The quantity determination module is used to determine the target quantity of the preloaded multimedia to be played based on the network status information.

[0041] Optionally, the preloading module is further used to:

[0042] Based on the network status information, the target operation data and the target characteristic data, the target number of preloaded data of the multimedia to be played is obtained.

[0043] According to a third aspect of the present disclosure, an electronic device is provided, which includes a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the program, the method described above is implemented.

[0044] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the above method of the present disclosure is implemented.

[0045] The multimedia data preloading method, device, electronic device and storage medium provided by the embodiments of the present disclosure obtain the target operation data for the multimedia that has been played and the target feature data for the multimedia to be played, and obtain the preloading data of the multimedia to be played at least based on the target operation data and the target feature data. Since the preloading data of the preloaded target multimedia is related to the target operation data and the target feature data of the multimedia to be played, the multimedia to be played can be accurately preloaded, which can improve the preloading efficiency of the multimedia. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Further details, features and advantages of the present disclosure are disclosed in the following description of exemplary embodiments in conjunction with the accompanying drawings, in which:

[0047] Figure 1 A flowchart of a multimedia data preloading method provided by an exemplary embodiment of the present disclosure;

[0048] Figure 2 This is a schematic diagram of a scenario of an operation behavior of a user during music playing in an exemplary embodiment of the present disclosure;

[0049] Figure 3 A schematic block diagram of functional modules of a multimedia data preloading device provided by an exemplary embodiment of the present disclosure;

[0050] Figure 4 A structural block diagram of an electronic device provided for an exemplary embodiment of the present disclosure;

[0051] Figure 5 A structural block diagram of a computer system provided for an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0052] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0053] It should be understood that the various steps described in the method embodiments of the present disclosure may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect.

[0054] The term "including" and its variations used in this document are open inclusions, that is, "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one other embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions of other terms will be given in the description below. It should be noted that the concepts of "first", "second", etc. mentioned in this disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0055] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0056] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0057] It is understandable that before using the technical solutions disclosed in the embodiments of the present disclosure, the types, scope of use, usage scenarios, etc. of the personal information involved in the present disclosure should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations.

[0058] For example, in response to receiving an active request from a user, a prompt message is sent to the user to clearly prompt the user that the operation requested to be performed will require obtaining and using the user's personal information. Thus, the user can autonomously choose whether to provide personal information to software or hardware such as an electronic device, application, server, or storage medium that performs the operation of the technical solution of the present disclosure according to the prompt message.

[0059] As an optional but non-limiting implementation, in response to receiving an active request from the user, the method of sending a prompt message to the user may be, for example, a pop-up window, in which the prompt message may be presented in text. In addition, the pop-up window may also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device. It is understandable that the above notification and the process of obtaining user authorization are only illustrative and do not constitute a limitation on the implementation of the present disclosure. Other methods that meet relevant laws and regulations may also be applied to the implementation of the present disclosure.

[0060] When a certain user type plays multimedia through a terminal such as a mobile phone, the user type often operates on the multimedia playback interface, such as dragging a progress bar or fast-forwarding, to watch or listen to a favorite part, or repeatedly watch or listen to the favorite part of the multimedia.

[0061] Therefore, in order to improve the efficiency of multimedia preloading, so that the preloaded data obtained by preloading in advance is as much as possible the data that a certain user type likes or wants to play, the embodiments provided by the present disclosure will obtain the preloaded data of the multimedia to be played according to the relevant operation data of the multimedia by a certain user type and the characteristic data of the multimedia to be played, so as to realize the preloading of the multimedia to be played. The preloaded data obtained in this way can meet the playing habits and preferences of a certain user type, and can greatly improve the efficiency of multimedia preloading. Among them, the multimedia in the embodiment can be data such as music or video. The embodiment is described by taking the multimedia as music as an example, and the embodiment is not limited to this.

[0062] In an embodiment, historical operation behavior data of a certain user type on music can be obtained, such as the song switching behavior of a certain user type during the previous music playing process, and can also include operation behaviors such as dragging a progress bar, fast forward operation or slow forward operation. For example, a certain user type has listened to m% of song switching, dragging a progress bar, fast forwarding songs or slow forwarding songs, etc. At least one of these historical operation behavior data can be input into a behavior adjuster to adjust the weight of each operation behavior of a certain user type.

[0063] For example, one day can be a playback cycle. If a certain user type plays music through a music player for 5 days, the operation behavior data during the first day of playing music can be input into the behavior adjuster to obtain the initial weight of the behavior operation of the certain user type. The subsequent 4 days can be input into the behavior adjuster in sequence according to the number of days, and the weight of the behavior operation of the certain user type can be continuously adjusted to obtain the final adjusted target weight. In an embodiment, the proportion of historical operation behavior data of a certain user type can be inversely correlated with the time from the current time. That is, the longer the operation behavior is from the current time, the lower the proportion it occupies in the entire historical operation behavior data, and vice versa.

[0064] In the embodiment, the first four days of a certain user type's music playing can be used as a music playing cycle, and the operation behavior of the certain user type in these four days can be input into the behavior adjuster to obtain the initial weight of the behavior operation of the certain user type, and the operation behavior data of the fifth day can be input into the behavior adjuster to adjust the weight of the behavior operation of the certain user type, optimize the initial weight, and obtain the adjusted target weight. Subsequently, the latest operation behavior data of a certain user type on music within one day can be continuously input into the adjuster to continuously adjust the weight of the behavior operation, so that the adjusted weight can be more in line with the operation habits and music playing preferences of the certain user type.

[0065] The target weight obtained by the behavior adjuster can be prepared for preloading of the next playback cycle. In an embodiment, the behavior adjuster can be a preset model, such as a neural network model, which is continuously trained by the historical operation behavior data of a certain user type, and then the target weight can be obtained by the trained preset model.

[0066] In the embodiments provided by the present disclosure, still taking multimedia as music as an example, by obtaining the multimedia to be played, the multimedia to be played can be the music that a certain user type directly selects to play, for example, a certain user type generates a music list to be played by selecting the music they like, and the music list includes multiple music. The multimedia to be played can also be a music playlist automatically generated by the system for a certain user type, for example, a music playlist can be recommended for a certain user type based on the music played by the certain user type in the past. Of course, the music in the music playlist can also be randomly generated, or other music played more by a certain user type, etc. The embodiments are not limited to this.

[0067] In an embodiment, the multimedia to be played may include a music playlist, which may include one or more music, and the multimedia to be played may also carry target feature data of the music in the music playlist. The target feature data may be at least one of a chorus, a verse, a drum beat, and a song type, etc. The target feature data may also include the range of each part of the chorus, the verse, and the drum beat, and the song type may include DJ, pop, or folk songs, etc.

[0068] In the embodiment provided by the present disclosure, by determining the target weights corresponding to multiple target operation behaviors of a certain user type as described above, and combining the target feature data of the multimedia to be played, the multimedia to be played can be preloaded, for example, determining the data to be loaded first and the range of the loaded data.

[0069] In the embodiment, the current network status information, such as network quality and network type, etc., can also be obtained, and the number of multimedia to be played and the preloaded data of these multimedia can be determined by combining the network status information, target weight and target feature data. That is, it can be determined how many songs need to be loaded, the range of preloaded data in each song, etc. For example, the music playlist includes 10 songs, and it is determined that 5 of them need to be preloaded, and the corresponding loading ratio of the chorus part or drum part in each song needs to be loaded, etc. The embodiment is not limited to this.

[0070] Based on the above embodiment, in another embodiment provided by the present disclosure, a multimedia data preloading method is also provided, such as Figure 1 As shown, the method may include the following steps:

[0071] In step S110 , target operation data for the played multimedia is obtained.

[0072] In the embodiment, when obtaining relevant data of a certain user type, a certain user type may be consulted through a pop-up window or the like, and the data will be obtained only after obtaining the consent of the certain user type. The multimedia in the embodiment may be music or video data, and the target operation data may include behavior data such as song switching, fast forward, rewind, or playing a specific part of a song of a certain user type, for example, song switching, dragging a progress bar, or fast or slow forward of a certain user type.

[0073] In step S120, target feature data of the multimedia to be played is obtained.

[0074] In the embodiment, taking the multimedia to be played as music as an example, the target feature data may include at least one of a chorus, a verse, drum beats, and a song type, and the target feature data may also include the range of each part of the chorus, the verse, and the drum beats. The song type may include DJ, pop, or folk songs, etc.

[0075] This can be done by performing feature extraction and feature recognition on the multimedia to be played. For example, when the multimedia to be played is music, features such as the chorus part and the drum part in the music can be recognized.

[0076] In step S130, the multimedia to be played is preloaded based at least on the target operation data and the target characteristic data.

[0077] In an embodiment, the multimedia to be played can be preloaded based on the target operation data and the target feature data. For example, the weight corresponding to each operation behavior in the target operation data can be obtained based on the target operation data, and the parts of the target multimedia corresponding to each operation behavior can be preloaded in sequence according to the weight. For example, the weight corresponding to the operation behavior of playing the chorus of a certain user type is the highest, and the chorus part can be loaded first. After the chorus part is preloaded, the other parts are preloaded. In an embodiment, when the chorus part is preloaded, the preload amount can be set, such as the preloaded part accounts for 10% of the weight data of the part, etc. For example, for a piece of music, when the chorus part preloads 10% of the total amount of the chorus, it is determined that the chorus part is preloaded. In an embodiment, the preload amount and the number of preloaded multimedia can also be determined according to the network quality or network type. For example, in the case of good network quality or WIFI, the preload amount or the number of preloaded multimedia can be increased, and in the case of weak network or 4G, the preload amount or the number of preloaded multimedia can be reduced, etc.

[0078] The multimedia data preloading method provided by the embodiment of the present disclosure obtains the target operation data of a certain user type for the multimedia that has been played, and obtains the target feature data of the multimedia to be played, and obtains the preloading data of the multimedia to be played based on at least the target operation data and the target feature data. Since the preloading data of the preloaded target multimedia is related to the operation data of a certain user type and the target feature data of the multimedia to be played, the multimedia to be played can be accurately preloaded, greatly improving the preloading efficiency.

[0079] Based on the above embodiment, in another embodiment provided by the present disclosure, the target operation data includes multiple target operation behaviors, and the above step S130 may further specifically include the following steps:

[0080] S131, determining target weights corresponding to a plurality of target operation behaviors respectively.

[0081] In an embodiment, the target operation data may include multiple target operation behaviors. The target operation data performed by a certain user type when playing multimedia in a historical stage may be input into a behavior adjuster to obtain weights corresponding to the multiple target operation behaviors. After obtaining the target operation data of the next playback cycle, it may be input into the behavior adjuster to adjust the weights corresponding to the multiple target operation behaviors to obtain the target weights. The behavior adjuster may determine or adjust the weights corresponding to the multiple target operation behaviors according to the operation frequency, number of times, or duration corresponding to the multiple target operation behaviors.

[0082] S132, preloading the multimedia to be played based on the target weight and the target feature data to obtain preloaded data.

[0083] In an embodiment, in the process of preloading the multimedia to be played according to the target weight and the target feature data, the target feature data corresponding to the target operation behavior with a high weight may be loaded first.

[0084] For example, the weight corresponding to the multiple target operation behaviors including the operation behavior of playing the chorus is the highest, and the chorus part can be loaded first, and then the other parts are loaded.

[0085] Therefore, in the embodiment, the priorities corresponding to the multiple target operation behaviors can be determined based on the target weights, and the preloaded data corresponding to the target feature data can be preloaded based on the priorities.

[0086] For example, Figure 2 As shown, Figure 2 is an operation behavior of a certain user type during music playing in an exemplary embodiment of the present disclosure, Figure 211 represents the song progress control, 12 represents the chorus part, and 13 represents the drum part. Among them, in the embodiment, the data range of the chorus part in the multimedia to be played is between 10s and 16s, and the data range of the drum part in the multimedia to be played is between 1min20s and 1min25s. Then, when the multimedia to be played is preloaded according to the target weight and target feature data, since the weight of the operation behavior of playing the chorus is the highest, the chorus part between 10s and 16s in the multimedia to be played can be loaded first, and after the preloading is completed, the drum part between 20s and 25s in the multimedia to be played can be preloaded, and finally the other data of the multimedia to be played can be preloaded. In the embodiment, according to needs or network factors, the corresponding parts such as chorus or drums can be fully preloaded 100%, or a part of them, such as 20%, can be preloaded, and the embodiment is not limited to this.

[0087] Based on the above embodiment, in order to continuously optimize and adjust the weights corresponding to the multiple target operation behaviors, in another embodiment provided by the present disclosure, the played multimedia includes a first multimedia and a second multimedia having adjacent playback cycles, and the first multimedia and the multimedia to be played have adjacent playback cycles; the above step S131 may further specifically include the following steps:

[0088] Step S11: determining initial weights corresponding to a plurality of target operation behaviors respectively based on the feature data of the second multimedia.

[0089] Step S12, adjusting the initial weights according to the characteristic data of the first multimedia to obtain target weights corresponding to the multiple target operation behaviors.

[0090] In an embodiment, multimedia playback of a certain user type within a day can be regarded as a playback cycle according to a multimedia playback cycle, such as a day. In this way, target operation data for a certain user type for multiple multimedia playback cycles can be obtained, and the initial weights corresponding to multiple target operation behaviors can be determined based on the multimedia played in an earlier playback cycle in time order according to the time sequence of the playback cycles, and the initial weights corresponding to multiple target operation behaviors can be optimized based on the multimedia played in a later playback cycle to obtain the target weight. In the embodiment, the feature data of the first multimedia and the feature data of the second multimedia can respectively include feature data such as drum beats, chorus or main song.

[0091] Therefore, in the embodiment, the second multimedia can be multimedia that has been played in an earlier playback cycle, and the first multimedia can be multimedia that has been played in a later playback cycle. The initial weights corresponding to the multiple target operation behaviors can be determined through the corresponding multiple target operation behaviors in the feature data of the second multimedia, and then the initial weights can be adjusted through the corresponding multiple target operation behaviors in the feature data of the first multimedia to obtain the target weights. In this way, when obtaining multiple target operation behaviors in the latest playback cycle, the weights corresponding to the multiple target operation behaviors previously obtained can be adjusted and optimized through the multiple target operation behaviors in the latest playback cycle, so as to obtain more accurate preloaded data.

[0092] Based on the above embodiment, in another embodiment provided by the present disclosure, the above method may further include the following steps:

[0093] Step S140, obtaining network status information.

[0094] Step S150: determining a target number of the preloaded multimedia to be played based on the network status information.

[0095] In an embodiment, the current network status information may be obtained, and the network status information may include the transmission bit rate of the current network, and the quality of the current network may be determined by the transmission bit rate, such as good, medium or poor. The network status information may also include the network type, such as WIFI, 4G or 5G.

[0096] For example, the target number of multimedia to be played that needs to be preloaded can be determined within the threshold range of the current network transmission bit rate, and the target number can be positively correlated with the transmission bit rate. In addition, the network type can also be combined, for example, in the case of WIFI, the target data can be greater than the preset number, otherwise in the case of 4G or 5G, the target number is not greater than the preset number.

[0097] Therefore, in an embodiment, the preload data of the target number of multimedia to be played can be obtained based on the network status information, the target operation data and the target characteristic data. After determining the target number of preloaded multimedia to be played, the target number of multimedia to be played can be preloaded to obtain the preload data of the target number of multimedia to be played. For example, since some music may not completely contain the target characteristic data, or the proportion of target characteristic data in different multimedia to be played is different, each multimedia to be played can be preloaded according to the target operation data and the target characteristic data, and it is determined how much corresponding preload data needs to be preloaded for each multimedia to be played, such as how much the chorus part needs to be preloaded, how much the drum part needs to be preloaded, and so on.

[0098] In the case of dividing each functional module according to each function, an embodiment of the present disclosure provides a multimedia data preloading device, which may be a server or a chip applied to a server. Figure 3 This is a schematic block diagram of the functional modules of a multimedia data preloading device provided by an exemplary embodiment of the present disclosure. Figure 3 As shown, the multimedia data preloading device includes:

[0099] The target operation data acquisition module 10 is used to acquire the target operation data for the played multimedia;

[0100] The target feature data acquisition module 20 is used to acquire the target feature data of the multimedia to be played;

[0101] The preloading module 30 is used to preload the multimedia to be played based on at least the target operation data and the target characteristic data.

[0102] Optionally, the target operation data includes a plurality of target operation behaviors; the preloading module is specifically used to:

[0103] Determine target weights corresponding to the multiple target operation behaviors respectively;

[0104] The multimedia to be played is preloaded based on the target weight and the target characteristic data to obtain preload data.

[0105] Optionally, the preloading module is further used to:

[0106] Based on the target weights, determining the priorities corresponding to the multiple target operation behaviors respectively;

[0107] Preload data corresponding to the target feature data is preloaded based on the priority.

[0108] Optionally, the played multimedia includes a first multimedia and a second multimedia having adjacent play periods, and the first multimedia and the multimedia to be played have adjacent play periods; the preloading module is specifically further used for:

[0109] Determining initial weights corresponding to the plurality of target operation behaviors respectively based on the feature data of the second multimedia;

[0110] The initial weight is adjusted according to the feature data of the first multimedia to obtain target weights corresponding to the multiple target operation behaviors respectively.

[0111] Optionally, the device further comprises:

[0112] An information acquisition module, used to obtain network status information;

[0113] The quantity determination module is used to determine the target quantity of the preloaded multimedia to be played based on the network status information.

[0114] Optionally, the preloading module is further used to:

[0115] Based on the network status information, the target operation data and the target characteristic data, the target number of preloaded data of the multimedia to be played is obtained.

[0116] The relevant device part corresponds to the above method. For details, please refer to the description of the above method embodiment, which will not be repeated here.

[0117] An embodiment of the present disclosure also provides an electronic device, comprising: at least one processor; and a memory for storing instructions executable by the at least one processor; wherein the at least one processor is configured to execute the instructions to implement the above method disclosed in the embodiment of the present disclosure.

[0118] Figure 4 The structure diagram of an electronic device provided by an exemplary embodiment of the present disclosure is shown in FIG. Figure 4 As shown, the electronic device 1800 includes at least one processor 1801 and a memory 1802 coupled to the processor 1801 , and the processor 1801 can execute corresponding steps in the above method disclosed in the embodiment of the present disclosure.

[0119] The processor 1801 may also be referred to as a central processing unit (CPU), which may be an integrated circuit chip having signal processing capabilities. Each step in the method disclosed in the embodiment of the present disclosure may be completed by an integrated logic circuit of hardware in the processor 1801 or by instructions in the form of software. The processor 1801 may be a general-purpose processor, a digital signal processor (DSP), an ASIC, a field-programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in the embodiment of the present disclosure may be directly embodied as being executed by a hardware decoding processor, or may be executed by a combination of hardware and software modules in a decoding processor. The software module may be located in a memory 1802, such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, or other mature storage media in the art. The processor 1801 reads the information in the memory 1802 and completes the steps of the method in combination with its hardware.

[0120] In addition, when various operations / processes according to the present disclosure are implemented by software and / or firmware, they can be transmitted from a storage medium or a network to a computer system having a dedicated hardware structure, such as Figure 5 The computer system 1900 shown is installed with the programs constituting the software. When the various programs are installed, the computer system can perform various functions, including the functions described above. Figure 5 A structural block diagram of a computer system provided for an exemplary embodiment of the present disclosure.

[0121] Computer system 1900 is intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0122] like Figure 5 As shown, the computer system 1900 includes a computing unit 1901, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 1902 or a computer program loaded from a storage unit 1908 to a random access memory (RAM) 1903. In the RAM 1903, various programs and data required for the operation of the computer system 1900 can also be stored. The computing unit 1901, the ROM 1902, and the RAM 1903 are connected to each other via a bus 1904. An input / output (I / O) interface 1905 is also connected to the bus 1904.

[0123] A plurality of components in the computer system 1900 are connected to the I / O interface 1905, including: an input unit 1906, an output unit 1907, a storage unit 1908, and a communication unit 1909. The input unit 1906 may be any type of device capable of inputting information to the computer system 1900, and the input unit 1906 may receive input digital or character information, and generate key signal inputs related to user settings and / or function control of the electronic device. The output unit 1907 may be any type of device capable of presenting information, and may include, but is not limited to, a display, a speaker, a video / audio output terminal, a vibrator, and / or a printer. The storage unit 1908 may include, but is not limited to, a disk, an optical disk. The communication unit 1909 allows the computer system 1900 to exchange information / data with other devices over a network such as the Internet, and may include, but is not limited to, a modem, a network card, an infrared communication device, a wireless communication transceiver, and / or a chipset, such as a Bluetooth™ device, a WiFi device, a WiMax device, a cellular communication device, and / or the like.

[0124] The computing unit 1901 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 1901 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 1901 performs the various methods and processes described above. For example, in some embodiments, the above methods disclosed in the embodiments of the present disclosure may be implemented as a computer software program, which is tangibly included in a machine-readable medium, such as a storage unit 1908. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 1900 via the ROM 1902 and / or the communication unit 1909. In some embodiments, the computing unit 1901 may be configured to perform the above methods disclosed in the embodiments of the present disclosure in any other appropriate manner (e.g., by means of firmware).

[0125] The embodiment of the present disclosure further provides a computer-readable storage medium, wherein when instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the above method disclosed in the embodiment of the present disclosure.

[0126] The computer-readable storage medium in the disclosed embodiments may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. The computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. More specifically, the computer-readable storage medium may include an electrical connection based on one or more lines, 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 foregoing.

[0127] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0128] The embodiments of the present disclosure further provide a computer program product, including a computer program, wherein when the computer program is executed by a processor, the above method disclosed in the embodiments of the present disclosure is implemented.

[0129] In embodiments of the present disclosure, computer program codes for performing the operations of the present disclosure may be written in one or more programming languages ​​or combinations thereof, including but not limited to object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code may be executed entirely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer.

[0130] 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.

[0131] The modules, components or units involved in the embodiments described in the present disclosure may be implemented by software or hardware, wherein the names of the modules, components or units do not, in some cases, limit the modules, components or units themselves.

[0132] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chip (SOCs), complex programmable logic devices (CPLDs), and the like.

[0133] The above descriptions are only some embodiments of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present disclosure is not limited to the technical solutions formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosed concept. For example, a technical solution formed by replacing the above features with the technical features with similar functions disclosed in the present disclosure (but not limited to).

[0134] Although some specific embodiments of the present disclosure have been described in detail by way of example, it should be understood by those skilled in the art that the above examples are for illustration only and are not intended to limit the scope of the present disclosure. It should be understood by those skilled in the art that the above embodiments may be modified without departing from the scope and spirit of the present disclosure. The scope of the present disclosure is defined by the appended claims.

Claims

1. A multimedia data preloading method, characterized in that: The method comprises: Acquire target operation data for the played multimedia; wherein the target operation data includes a plurality of target operation behaviors; Acquire target feature data of the multimedia to be played; wherein the target feature data includes at least one of a chorus, a verse, a drum beat, and a song type; Preloading the multimedia to be played based at least on the target operation data and the target characteristic data; The preloading of the multimedia to be played includes: Determine target weights corresponding to the multiple target operation behaviors respectively; Based on the target weight and the target feature data, the corresponding part of the multimedia to be played is preloaded to obtain preload data; wherein the corresponding part of the multimedia to be played includes at least one of a chorus part, a verse part, a drum beat part and a song type part.

2. The method according to claim 1, characterized in that The preloading of the multimedia to be played based on the target weight and the target feature data includes: Based on the target weights, determining the priorities corresponding to the multiple target operation behaviors respectively; Preload data corresponding to the target feature data is preloaded based on the priority.

3. The method according to claim 1, characterized in that The played multimedia includes a first multimedia and a second multimedia having adjacent play periods, and the first multimedia and the to-be-played multimedia have adjacent play periods; The determining target weights corresponding to the multiple target operation behaviors respectively includes: Determining initial weights corresponding to the plurality of target operation behaviors respectively based on the feature data of the second multimedia; The initial weight is adjusted according to the feature data of the first multimedia to obtain target weights corresponding to the multiple target operation behaviors respectively.

4. The method according to claim 2 or 3, characterized in that The method further comprises: Get network status information; The target number of the preloaded multimedia to be played is determined based on the network status information.

5. The method according to claim 4, characterized in that The preloading of the multimedia to be played includes: Based on the network status information, the target operation data and the target characteristic data, the target number of preloaded data of the multimedia to be played is obtained.

6. A multimedia data preloading device, characterized in that: The device comprises: A target operation data acquisition module, used to acquire target operation data for the played multimedia; wherein the target operation data includes a plurality of target operation behaviors; A target feature data acquisition module, used to acquire target feature data of the multimedia to be played; wherein the target feature data includes at least one of a chorus, a verse, a drum beat, and a song type; A preloading module, configured to preload the multimedia to be played based at least on the target operation data and the target characteristic data; The preloading module is specifically used for: Determine target weights corresponding to the multiple target operation behaviors respectively; Based on the target weight and the target feature data, the corresponding part of the multimedia to be played is preloaded to obtain preload data; wherein the corresponding part of the multimedia to be played includes at least one of a chorus part, a verse part, a drum beat part and a song type part.

7. An electronic device, characterized in that: include: at least one processor; a memory for storing the at least one processor-executable instruction; The at least one processor is configured to execute the instructions to implement the method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: When the instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to perform the method as claimed in any one of claims 1 to 5.

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