Music interaction processing method and device, program product and electronic equipment

Abstract

The invention provides a music interaction processing method and device, a program product and electronic equipment, and relates to the technical field of computers. The method comprises the following steps: determining first digital music of a target user with a preset permission; processing a first interaction instruction of the target user and the first digital music based on a first interaction strategy; processing a second interaction instruction of the target user and second digital music which does not have the preset authority based on a second interaction strategy; the first interaction strategy is different from the second interaction strategy. The diversity of interaction modes is improved, abundant interaction functions and interaction effects can be realized, and the user experience is improved.

Description

Technical Field

[0001] The embodiments of the present disclosure relate to the field of computer technology, and more specifically, to a music interaction processing method, a music interaction processing device, a computer program product, and an electronic device. Background Art

[0002] This section is intended to provide a background or context for the technical solutions stated in the claims. The description of the relevant content in this section does not constitute an admission that it is prior art.

[0003] With the development of computers and electronic devices, more and more users are using music software to listen to digital music. In music software, users can obtain specific rights to digital music through purchase, collection, and other methods. For example, purchasing a piece of digital music grants users the right to listen to the entire piece. Summary of the Invention

[0004] However, current music software offers a relatively limited range of user interaction options for digital music. For example, users can typically only control the playback of digital music through conventional operations. The interaction methods for digital music with specific permissions (e.g., purchased digital music) and digital music without specific permissions (e.g., unpurchased digital music) are essentially the same. This hinders the realization of rich interactive features and user experiences.

[0005] In view of the above problems, embodiments of the present disclosure provide a music interaction processing method, a music interaction processing device, a computer program product, and an electronic device.

[0006] According to a first aspect of the present disclosure, a music interaction processing method is provided, the method comprising: determining a first digital music for which a target user has preset permissions; processing a first interaction instruction between the target user and the first digital music based on a first interaction strategy; processing a second interaction instruction between the target user and a second digital music for which the target user does not have preset permissions based on a second interaction strategy; the first interaction strategy is different from the second interaction strategy.

[0007] Optionally, the first interaction strategy includes response control information; processing the first interaction instruction between the target user and the first digital music based on the first interaction strategy includes: determining the response control information based on the historical interaction information of the target user; and responding to the first interaction instruction between the target user and the first digital music based on the response control information.

[0008] Optionally, the response control information includes a first response sensitivity parameter; determining the response control information based on the historical interaction information of the target user includes: determining at least one of the target user's preferred operation type, preferred operation intensity, and preferred frequency pattern based on the target user's historical interaction information; determining the first response sensitivity parameter based on at least one of the target user's preferred operation type, preferred operation intensity, and preferred frequency pattern.

[0009] Optionally, the response control information includes a first interactive response mode; determining the response control information based on the historical interaction information of the target user includes: determining at least one of the target user's browsing depth, operation speed, operation repetition, and function usage rate based on the target user's historical interaction information; determining the first interactive response mode based on at least one of the target user's browsing depth, operation speed, operation repetition, and function usage rate.

[0010] Optionally, the processing of the first interaction instruction between the target user and the first digital music based on the first interaction strategy includes: during the interaction between the target user and the first digital music, obtaining posture information of the terminal device, and executing the corresponding first control instruction according to the posture information.

[0011] Optionally, obtaining the posture information of the terminal device includes: using a state equation and determining a state value of the posture of the terminal device at the current moment based on a process noise covariance matrix; using an observation equation and determining an update value regarding the state value based on an observation noise covariance matrix; updating the state value based on the update value to obtain the posture information of the terminal device at the current moment.

[0012] Optionally, the acquiring of the posture information of the terminal device further includes: determining a process noise covariance matrix at a current moment according to a current acceleration of the terminal device.

[0013] Optionally, the acquiring of the posture information of the terminal device further includes: determining an observation noise covariance matrix according to a credibility evaluation value of an inertial sensor of the terminal device for measuring the posture information.

[0014] Optionally, the adopting of a state equation and determining the state value of the posture of the terminal device at the current moment based on a process noise covariance matrix includes: adopting a state equation with an expanded correction term and determining the state value of the posture of the terminal device at the current moment based on a process noise covariance matrix.

[0015] Optionally, the first control instruction includes a display perspective control instruction; executing the corresponding first control instruction according to the posture information includes: determining the display perspective control instruction according to the posture information; and controlling the display effect of the first preset interface associated with the first digital music according to the display perspective control instruction.

[0016] Optionally, the processing of the first interaction instruction between the target user and the first digital music based on the first interaction strategy includes: determining the current usage scenario of the target user, and controlling the interactive elements in the first preset interface associated with the first digital music according to the current usage scenario; the interactive elements are used to trigger the first interaction instruction.

[0017] Optionally, the method further includes: determining a music interaction index of the target user; and determining the first interaction strategy based on the music interaction index.

[0018] Optionally, determining the music interaction index of the target user includes: obtaining the playback index, time investment index, and social interaction index of the target user; and weighting the playback index, time investment index, and social interaction index of the target user to obtain the music interaction index of the target user.

[0019] Optionally, weighting the target user's playback index, time investment index, and social interaction index to obtain the target user's music interaction index includes: determining a first weight parameter according to the type of the target user, the first weight parameter including weights corresponding to the playback index, time investment index, and social interaction index, respectively; weighting the target user's playback index, time investment index, and social interaction index based on the first weight parameter to obtain the target user's music interaction index.

[0020] Optionally, the weighting of the target user's playback index, time investment index, and social interaction index to obtain the target user's music interaction index also includes: updating the first weight parameter in at least one of the following ways to weight the target user's playback index, time investment index, and social interaction index based on the updated first weight parameter: updating the first weight parameter according to the target user's playback behavior preference parameters, time investment preference parameters, and social behavior preference parameters; updating the first weight parameter according to the target user's usage scenario; updating the first weight parameter according to the target user's usage feedback index.

[0021] Optionally, the method further includes: determining the first interaction strategy according to the performance of the terminal device.

[0022] Optionally, determining the first interaction strategy based on the performance of the terminal device includes: if the performance of the terminal device belongs to the first performance level, determining that the first interaction strategy includes: using a first pressure detection parameter to detect pressure operation; if the performance of the terminal device belongs to the second performance level, determining that the first interaction strategy includes: using a second pressure detection parameter to detect pressure operation; the second pressure detection parameter is greater than the first pressure detection parameter.

[0023] Optionally, determining the first interaction strategy based on the performance of the terminal device includes: if the performance of the terminal device belongs to the first performance level, determining that the first interaction strategy includes: using a fixed vibration frequency to present a vibration effect; if the performance of the terminal device belongs to the second performance level, determining that the first interaction strategy includes: using a dynamic vibration frequency to present a vibration effect.

[0024] Optionally, determining the first interaction strategy based on the performance of the terminal device includes: if the performance of the terminal device belongs to the first performance level, determining that the first interaction strategy includes: using basic tactile feedback parameters to present the touch effect; if the performance of the terminal device belongs to the second performance level, determining that the first interaction strategy includes: using material simulation tactile feedback parameters to present the touch effect.

[0025] Optionally, determining the first interaction strategy based on the performance of the terminal device includes: if the performance of the terminal device belongs to the first performance level, determining that the first interaction strategy includes: using stereo field parameters to play the first digital music; if the performance of the terminal device belongs to the second performance level, determining that the first interaction strategy includes: using spatial sound field parameters to play the first digital music.

[0026] Optionally, determining the first interaction strategy based on the performance of the terminal device includes: if the performance of the terminal device belongs to the first performance level, determining that the first interaction strategy includes: using first visual rendering parameters to produce a display effect; if the performance of the terminal device belongs to the second performance level, determining that the first interaction strategy includes: using second visual rendering parameters to produce a display effect; the second visual rendering parameters are greater than the first visual rendering parameters.

[0027] Optionally, the processing of the first interaction instruction between the target user and the first digital music based on the first interaction strategy includes: determining the number of operation points in the first interaction instruction; if the number of operation points is greater than or equal to K1, executing the control instructions corresponding to K1 operation points; if the number of operation points is greater than or equal to K2 and less than K1, executing the control instructions corresponding to K2 operation points; if the number of operation points is less than K2, executing the control instructions corresponding to K3 operation points; wherein, K1>K2>K3.

[0028] Optionally, the first interaction instruction includes a first display instruction; the processing of the first interaction instruction between the target user and the first digital music based on the first interaction strategy includes: displaying a second preset interface in response to the first display instruction, and displaying the icon of the first digital music at a corresponding position in the second preset interface according to the information of the first digital music.

[0029] Optionally, a music collection space is set in the second preset interface; displaying the icon of the first digital music at a corresponding position in the second preset interface according to the information of the first digital music includes: determining the X-axis coordinate according to the collection duration, music index information, and emotional characteristics of the first digital music; determining the Y-axis coordinate according to the collection duration, music index information, and music style of the first digital music; determining the Z-axis coordinate according to the music genre factor, rarity, audio characteristics, and matching degree with the music style preference of the target user of the first digital music; and displaying the icon of the first digital music in the music collection space according to the X-axis coordinate, the Y-axis coordinate, and the Z-axis coordinate.

[0030] Optionally, the method further includes: determining the collection weight of the first digital music based on the collection duration, playback intensity, and interaction coefficient of the first digital music; and controlling the state of the icon of the first digital music displayed in the second preset interface based on the collection weight.

[0031] Optionally, displaying the icon of the first digital music at a corresponding position in the second preset interface based on the information of the first digital music includes: mapping the first digital music to a corresponding level based on the behavior data of the target user listening to the first digital music, and displaying the icon of the first digital music in the second preset interface according to the level corresponding to the first digital music.

[0032] Optionally, the method further includes: determining a parallax parameter based on the posture information of the terminal device and the characteristics of the first digital music; and adjusting the position of the icon of the first digital music displayed in the second preset interface based on the parallax parameter.

[0033] Optionally, the first interaction instruction includes a second display instruction; the processing of the first interaction instruction between the target user and the first digital music based on the first interaction strategy includes: in response to the second display instruction, displaying an associated image of the first digital music based on information of the first digital music and environmental information.

[0034] Optionally, displaying the associated image of the first digital music based on the information of the first digital music and the environmental information includes: determining appearance simulation parameters based on the information of the first digital music; determining lighting effect parameters based on the environmental information; processing the associated image of the first digital music based on the appearance simulation parameters and the lighting effect parameters, and displaying the processed associated image.

[0035] Optionally, the appearance simulation parameters include at least one of era style parameters, color change parameters, material change parameters, and printing feature parameters. The determining of the appearance simulation parameters based on the information of the first digital music includes at least one of the following steps: obtaining era style characteristics of multiple reference times, and according to the release time of the first digital music, using the era style characteristics of the corresponding reference time as the era style parameter of the first digital music, or fusing the era style characteristics of at least two reference times to obtain the era style parameter of the first digital music; determining the color change parameters of the first digital music according to the simulation duration and color periodic change parameters of the first digital music; determining the material change parameters of the first digital music according to the characteristics of the cover material of the first digital music and the simulation duration of the first digital music; performing Fourier transform on the associated image and determining frequency domain parameters, and determining the printing feature parameters of the first digital music according to the frequency domain parameters and ink diffusion simulation parameters.

[0036] Optionally, the lighting effect parameters include at least one of lighting reflection parameters and hue adjustment parameters, and determining the lighting effect parameters based on the environmental information includes at least one of the following steps: determining incident light parameters based on the environmental information and posture information of the terminal device, determining specular reflection parameters and diffuse reflection parameters based on the incident light parameters, and weighting the specular reflection parameters and the diffuse reflection parameters to obtain the lighting effect parameters; determining light intensity parameters based on the environmental information, determining light response parameters based on the release time of the first digital music, and determining the hue adjustment parameters based on the light intensity parameters and the light response parameters.

[0037] Optionally, the method further includes: in response to detecting that the target user has obtained preset permissions for at least one first digital music and the performance of the terminal device meets preset requirements, providing an operation entry for triggering the first display instruction or the second display instruction.

[0038] Optionally, the first interaction instruction includes the first interaction instruction of the target user after obtaining the preset permission of the first digital music; the processing of the first interaction instruction between the target user and the first digital music based on the first interaction strategy includes: determining the target unblocking method according to the information of the first digital music; displaying unblocking guidance information in response to the first interaction instruction; the unblocking guidance information is used to guide the target user to perform the unblocking operation; in response to detecting the unblocking operation corresponding to the target unblocking method, setting the first digital music to an unblocked state, and the first digital music can be played in the unblocked state.

[0039] Optionally, determining a target unblocking method based on the information of the first digital music includes: determining a category of the first digital music based on the information of the first digital music; and using an unblocking method corresponding to the category of the first digital music as a target unblocking method.

[0040] Optionally, determining the category of the first digital music based on the information of the first digital music includes: constructing a feature vector of the first digital music based on the rhythm, harmonic complexity, and emotional characteristics of the first digital music; calculating the similarity between the feature vector of the first digital music and the benchmark feature vectors of each category, and determining the category of the first digital music based on the similarity.

[0041] Optionally, in response to detecting an unblocking operation corresponding to the target unblocking method, setting the first digital music to an unblocked state includes: obtaining operation data of the unblocking operation; determining whether the unblocking operation is completed based on the operation data and the emotional characteristics of the first digital music; and in response to the completion of the unblocking operation, setting the first digital music to an unblocked state.

[0042] Optionally, when the first digital music is set to an unblocked state, the method further includes: displaying a corresponding unblocking animation according to the music style and emotional characteristics of the first digital music.

[0043] Optionally, the method further includes: determining the comprehensive value of the first digital music according to the circulation volume, collection duration, and artistic rating of the first digital music.

[0044] Optionally, the first interaction strategy includes: providing a first audio-visual effect according to the first interaction instruction; the second interaction strategy includes: providing a second audio-visual effect according to the second interaction instruction; and the first audio-visual effect is different from the second audio-visual effect.

[0045] According to a second aspect of the present disclosure, a music interaction processing device is provided, which includes: a first digital music determination module, configured to determine a first digital music for which a target user has preset permissions; a first interaction processing module, configured to process a first interaction instruction between the target user and the first digital music based on a first interaction strategy; a second interaction processing module, configured to process a second interaction instruction between the target user and a second digital music for which the target user does not have preset permissions based on a second interaction strategy; the first interaction strategy is different from the second interaction strategy.

[0046] According to a third aspect of the present disclosure, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the method of the first aspect and possible implementations thereof are implemented.

[0047] According to a fourth aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute the method of the above-mentioned first aspect and its possible implementation methods by executing the executable instructions.

[0048] The embodiments of the present disclosure have the following technical effects:

[0049] For a first digital music track for which the target user has preset permissions, the first interaction instruction is processed based on the first interaction strategy. For a second digital music track for which the target user does not have preset permissions, the second interaction instruction is processed based on the second interaction strategy. On the one hand, this increases the diversity of interaction methods, facilitates the realization of rich interactive functions and interactive effects, and enhances the user experience. On the other hand, it simplifies the interaction processing for some digital music (such as the second digital music) and reduces the resource overhead of the terminal device or server. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 A schematic diagram showing a system architecture in an embodiment of the present disclosure.

[0051] Figure 2 A flowchart of a music interaction processing method in an embodiment of the present disclosure is shown.

[0052] Figure 3 A flowchart for determining posture information in an embodiment of the present disclosure is shown.

[0053] Figure 4 A schematic diagram illustrating a grading service for target users based on music interaction index in an embodiment of the present disclosure is shown.

[0054] Figure 5 A flowchart of displaying associated images in an embodiment of the present disclosure is shown.

[0055] Figure 6 A schematic flowchart of providing an operation entry in an embodiment of the present disclosure is shown.

[0056] Figure 7 A flowchart of an unpacking process in an embodiment of the present disclosure is shown.

[0057] Figure 8 A schematic structural diagram of a music interaction processing device in an embodiment of the present disclosure is shown.

[0058] Figure 9 A schematic structural diagram of an electronic device in an embodiment of the present disclosure is shown.

[0059] In the drawings, the same or corresponding reference numerals denote the same or corresponding parts. DETAILED DESCRIPTION

[0060] The principles and spirit of the present disclosure are described in detail below with reference to several representative embodiments of the present disclosure. It should be understood that these embodiments are provided solely to enable those skilled in the art to better understand and implement the present disclosure, and are not intended to limit the scope of the present disclosure in any way. On the contrary, these embodiments are provided to make the present disclosure more thorough and complete, and to fully convey the scope of the present disclosure to those skilled in the art.

[0061] The embodiments of the present disclosure may be implemented as systems, devices, apparatuses, methods, computer program products, etc. Therefore, the present disclosure may be implemented in the following forms: entirely in hardware, entirely in software (including firmware, resident software, microcode, etc.), or a combination of hardware and software. SUMMARY OF THE INVENTION

[0063] In related technologies, the interaction methods for users with digital music are relatively simple. For example, users can usually only control the playback of digital music through conventional operations. The interaction methods are basically the same for digital music with specific permissions (such as purchased digital music) and digital music without specific permissions (such as unpurchased digital music). This is not conducive to realizing rich interactive functions and experiences.

[0064] In view of the above, the present disclosure provides a music interaction processing method, a music interaction processing device, a program product, and an electronic device. For a first digital music for which a target user has preset permissions, a related first interaction instruction is processed based on a first interaction strategy. For a second digital music for which the target user does not have preset permissions, a related second interaction instruction is processed based on a second interaction strategy. On the one hand, the diversity of interaction methods is improved, which is conducive to achieving rich interactive functions and interactive effects and improving user experience. On the other hand, it can simplify the interactive processing for some digital music (such as the second digital music) and reduce the resource overhead of the terminal device or the server.

[0065] After introducing the basic principles of the present disclosure, various non-limiting embodiments of the present disclosure are described in detail below.

[0066] Application Scenario Overview

[0067] It should be noted that the following application scenarios are only shown to facilitate understanding of the spirit and principles of the present disclosure. The embodiments of the present disclosure are not limited in this respect and can be applied to any applicable scenarios.

[0068] The embodiments of the present disclosure may be used in digital music scenarios, such as music apps (Applications) and music websites. Figure 1 The system architecture of the operating environment of the embodiment of the present disclosure is shown. The system architecture may include a terminal device 110 and a server 120. The terminal device 110 may be a mobile phone, a personal computer, a tablet computer, a smart wearable device, etc., and has an audio function and can play digital music. In addition, it may have a display function to display one or more related music interfaces. The server 120 is a background for providing music-related services, and may be a server or a cluster formed by multiple servers. The terminal device 110 and the server 120 can be connected through a wired or wireless communication link to achieve information exchange.

[0069] The terminal device 110 can run a digital music application, such as a music app or a music website, and the user logged into the application is referred to as a target user. The disclosed embodiment processes related interaction instructions based on different interaction strategies for a first digital music program for which the target user has preset permissions, and a second digital music program for which the target user does not have preset permissions, thereby achieving different interaction effects and richer interaction functions, thereby increasing the diversity of interaction methods.

[0070] The music interaction processing method in the disclosed embodiments can be executed independently by the terminal device 110 or the server 120, or can be executed jointly by the terminal device 110 and the server 120. In one embodiment, the music interaction processing method can be executed independently by the terminal device 110 without providing the server 120. For example, in a standalone environment, the terminal device 110 can run a music app to process the target user's interaction instructions with the digital music.

[0071] Exemplary Methods

[0072] The following is an exemplary description of the music interaction processing method in the embodiment of the present disclosure. Figure 2 The flow of the music interaction processing method is shown, which may include steps S210 to S230.

[0073] Below Figure 2 Provide detailed instructions for each step.

[0074] refer to Figure 2 In step S210, a first digital music for which the target user has preset authority is determined.

[0075] In the disclosed embodiments, digital music is divided into first and second digital music categories based on whether the target user has preset permissions. Different interaction strategies are then used to process their related interaction instructions. The target user has preset permissions for the first digital music and general permissions for the second digital music. Preset permissions are typically higher than general permissions and can be determined based on specific needs and by the service provider. For example, preset permissions include, but are not limited to, full listening permissions, permanent listening permissions, offline download and storage permissions, and so on.

[0076] In one embodiment, preset permissions can be obtained in one or more of the following ways: obtaining preset permissions by purchasing digital music; obtaining preset permissions for the digital music when accepting digital music as a gift from other users; obtaining preset permissions by collecting digital music; obtaining preset permissions when the interaction with digital music reaches a certain level (such as the number of times or duration of listening to digital music reaches a certain threshold).

[0077] A first digital music can be a single song or a music collection (such as an album). For example, the disclosed embodiment can determine the first digital music based on the target user's purchase method. For example, if the target user purchases a single song, the single song will be managed as a first digital music. If the target user purchases an album, the album will be managed as a first digital music.

[0078] Continue to refer Figure 2In step S220, a first interaction instruction between the target user and the first digital music is processed based on the first interaction strategy.

[0079] The first interaction instruction refers to an interaction instruction between the target user and the first digital music, including but not limited to: an interaction instruction for controlling the playback of the first digital music, an interaction instruction for images associated with the first digital music (such as a song or album cover, poster, or artist image), an interaction instruction for text associated with the first digital music (such as lyrics, song introduction, and comments), an interaction instruction for interface elements in the playback interface of the first digital music, an interaction instruction for the icon of the first digital music in a music collection (such as a playlist), etc. When the target user triggers the first interaction instruction with the first digital music, the first interaction strategy is used to process the first interaction instruction.

[0080] Continue to refer Figure 2 In step S230, a second interaction instruction between the target user and the second digital music for which the target user does not have preset authority is processed based on the second interaction strategy.

[0081] The second interaction instruction refers to an interaction instruction between the target user and the second digital music, including but not limited to: an interaction instruction for controlling the playback of the second digital music, an interaction instruction for an image associated with the second digital music, an interaction instruction for text associated with the second digital music, an interaction instruction for an interface element in the playback interface of the second digital music, an interaction instruction for an icon of the second digital music in the music collection, etc. When the target user triggers the second interaction instruction with the second digital music, the second interaction strategy is used to process the second interaction instruction.

[0082] The first interaction strategy is different from the second interaction strategy. Exemplarily, the two may differ in one or more of the following aspects:

[0083] The first interaction strategy includes: providing a first audio-visual effect according to a first interaction instruction; the second interaction strategy includes: providing a second audio-visual effect according to a second interaction instruction; the first audio-visual effect is different from the second audio-visual effect. For example, in response to a display triggering operation for an associated image of a first digital music (such as an operation that triggers the opening of a playback interface of the first digital music, in which the associated image of the first digital music is displayed), the associated image of the first digital music is displayed, and a real-time lighting effect is displayed to simulate the effect of light in a real environment shining on a physical album cover. In response to a display triggering operation for an associated image of a second digital music (such as an operation that triggers the opening of a playback interface of the second digital music, in which the associated image of the second digital music is displayed), the associated image of the second digital music is displayed, but the real-time lighting effect is not displayed.

[0084] The first interaction strategy supports responding to the target user's preset interaction behaviors, while the second interaction strategy does not support responding to the target user's preset interaction behaviors. The preset interaction behaviors can be determined by the service provider based on specific needs. For example, the preset interaction behaviors include the target user's gesture interaction behaviors in the playback interface. When playing the first digital music, the target user is supported to control the volume, playback progress, etc. through gesture interaction behaviors. When playing the second digital music, the target user is not supported to control through gesture interaction behaviors.

[0085] The first interaction strategy provides a preset interaction effect, while the second interaction strategy does not. The preset interaction effect can be determined by the service provider based on specific needs. For example, the preset interaction effect includes a vibration effect during digital music playback. When playing the first digital music, if the user presses the touch screen of the terminal device, the terminal device will vibrate to simulate the vibration effect of the audio pulse. When playing the second digital music, this vibration effect is not provided.

[0086] The disclosed embodiment implements different interaction modes and interaction functions for the first digital music and the second digital music, thereby improving interaction diversity.

[0087] In one embodiment, the first interaction strategy includes response control information. The above-mentioned processing of the first interaction instruction between the target user and the first digital music based on the first interaction strategy includes the following steps:

[0088] Determine response control information based on historical interaction information of the target user;

[0089] The first interactive instruction between the target user and the first digital music is responded to based on the response control information.

[0090] The response control information is used to control the response to the interaction instruction, and may include, for example, response control parameters and response control methods. The response control information is determined based on the target user's historical interaction information, so that the response control information adapts to the historical interaction information, that is, conforms to the target user's interaction habits. This controls the response to the first interaction instruction, thereby generating personalized response control and interaction effects to meet user needs.

[0091] In one embodiment, a response is performed to the second interaction instruction between the target user and the second digital music based on preset response control information. The response control information may be uniformly set for different users and will not be adjusted based on the target user's historical interaction information, thereby not generating personalized response control and interaction effects.

[0092] In one embodiment, the response control information includes a first response sensitivity parameter. The above-mentioned determination of the response control information based on the historical interaction information of the target user includes the following steps:

[0093] Determining at least one of the target user's preferred operation type, preferred operation intensity, and preferred frequency pattern based on the target user's historical interaction information;

[0094] A first response sensitivity parameter is determined according to at least one of the target user's preferred operation type, preferred operation intensity, and preferred frequency pattern.

[0095] Among them, the historical interaction information of the target user can be statistically analyzed to obtain one or more information of the preferred operation type, preferred operation intensity, and preferred frequency mode (referring to the frequency mode commonly used by the target user), and this information can be digitized. Based on the pre-set calculation relationship, the corresponding first response sensitivity parameter is calculated according to this information. For example, the personalized interaction index P of the target user is calculated with reference to the following formula:

[0096] P = w1·preferred operation type + w2·preferred operation intensity + w3·preferred frequency pattern (1)

[0097] Among them, w1, w2, and w3 are weights and can be set based on experience or specific circumstances. When the P value is ≥ 0.7, a higher first response sensitivity parameter is determined, and the high response mode is adopted, which reduces the animation transition time by 20% and increases the touch sensitivity by 15%. When 0.4 ≤ P < 0.7, a moderate first response sensitivity parameter is determined, and the standard response mode is adopted, using the default animation and touch parameters. When P < 0.4, a lower first response sensitivity parameter is determined, and the guided mode is enabled, which increases the animation transition time by 10% and provides a more obvious visual cue.

[0098] In addition, when the preferred action type is obvious (e.g., w1·Preferred Action Type>0.6), the interaction entry for that preferred action type will be displayed first. When the preferred action strength is high (e.g., w2·Preferred Action Strength>0.5), the pressure trigger threshold will be adjusted by ±15%. When the preferred frequency mode is high (e.g., w3·Preferred Frequency Mode>0.5), multi-step actions will be simplified and merged into single-step shortcuts.

[0099] In one embodiment, the response control information includes a first interactive response mode. The above-mentioned determination of the response control information based on the historical interactive information of the target user includes the following steps:

[0100] Determine at least one of the following information: browsing depth, operation speed, operation repetition, and function usage rate of the target user based on the target user's historical interaction information;

[0101] The first interactive response mode is determined according to at least one of the following information: browsing depth, operation speed, operation repetition, and function usage rate of the target user.

[0102] Among them, browsing depth can be the average number of music or albums browsed in each session. Operation speed can be the average time to complete a standard operating procedure. Operation repetition can be the frequency of repeating the same operation. Function utilization rate can be the frequency of using a specific function (such as an advanced function). The system can provide a variety of preset interactive response modes, such as an exploratory interactive response mode, an efficiency interactive response mode, and an immersive interactive response mode. The first interactive response mode refers to the interactive response mode currently adopted. The historical interaction information of the target user can be statistically analyzed, including one or more information of browsing depth, operation speed, operation repetition, and function utilization rate. The first interactive response mode is determined based on this information.

[0103] For example, when the browsing depth is >8 and the operation speed is <60% of the standard time, the efficiency-type interactive response mode is used as the first interactive response mode. This mode simplifies the interface hierarchy, reduces animation transitions, optimizes quick operations, and can improve user operating efficiency. When the function usage rate is >70% and the operation speed is close to the standard time (such as within ±15% of the standard time), the exploration-type interactive response mode is used as the first interactive response mode. This mode highlights advanced functions, provides function guidance, and enhances the exploration and discovery experience. When the operation dwell time on a single album is >200% of the average value and the repetition rate is <30%, the immersive interactive response mode is used as the first interactive response mode. This mode can minimize interface elements, reduce interruptions, and enhance the audio-visual experience and immersion.

[0104] In one embodiment, the above-mentioned processing of the first interaction instruction between the target user and the first digital music based on the first interaction strategy includes the following steps:

[0105] During the interaction between the target user and the first digital music, the posture information of the terminal device is obtained, and the corresponding first control instruction is executed according to the posture information.

[0106] Among them, the first interaction strategy supports the target user to interact by controlling the posture of the terminal device. The posture information of the terminal device can be detected by its built-in inertial sensor (such as a gyroscope, accelerometer, magnetometer), and may include data in the form of 6DOF (Degree of Freedom), quaternion, etc. The correspondence between posture information and control instructions can be pre-set. During the interaction between the target user and the first digital music, if it is detected that the terminal device is in a specific posture or a specific posture change occurs, the corresponding first control instruction is executed. This realizes the posture interaction function.

[0107] In one embodiment, reference Figure 3 As shown, the above-mentioned acquisition of the posture information of the terminal device includes the following steps S310 to S330:

[0108] Step S310 , using the state equation and according to the process noise covariance matrix, determine the state value of the posture of the terminal device at the current moment.

[0109] Among them, the state value of the posture can be expressed by the state vector, and the state equation is as follows:

[0110] X k =AX {k-1} +BU k +W k (2)

[0111] X k is the state vector at the current moment (i.e., moment k), X {k-1} is the state vector of the previous moment (i.e., moment k-1), A is the state transfer matrix, which describes the evolution of the system state, B is the control input matrix, and U k is the control input vector, W k is the process noise. The statistical characteristics of the process noise can be described by the process noise covariance matrix Q, and the process noise covariance matrix can be introduced into the covariance matrix prediction of state estimation and the state prediction calculation process to reflect the uncertainty in the state transfer process.

[0112] A fixed or dynamic process noise covariance matrix can be used. In one embodiment, the process noise covariance matrix at the current moment can be determined based on the current acceleration of the terminal device. The calculation process is as follows:

[0113] Q k =Q base +ΔQ k (3)

[0114] ΔQ k =λ·||a k -g||·I (4)

[0115] Among them, Q k is the process noise covariance matrix at the current moment (i.e., moment k), Q base is the basis value of the process noise covariance matrix, a k is the current acceleration, g is the gravity acceleration vector, and λ is the proportional coefficient, which can be set based on experience or specific circumstances, such as a value within the range of 0.5 to 2.0. k The difference between g and g is used to calculate the change value ΔQ of the process noise covariance matrix at the current moment k , plus Q base , get Q k .

[0116] In one embodiment, the proportional coefficients λ, Q base etc., set the acceleration threshold ε. When ||ak When -g||<ε, the terminal device is in a stationary or nearly stationary state, and Q can be calculated. k =0.01I, thus reducing the process noise sensitivity. k -g||≥ε, the terminal device is in motion, Q k Increasing it to 0.1I or higher is beneficial to improving the state update response speed. This dynamic adjustment of the process noise covariance matrix can improve the accuracy of state prediction.

[0117] Furthermore, a smooth transition function can be used to calculate the process noise covariance matrix under various motion states, referring to the following formula:

[0118] Q(t) = Qstationary + (Qmoving - Qstationary) · S(t) (5)

[0119] S(t)=1 / (1+e^ (-k·(a(t)-a阈值)) ) (6)

[0120] Where S(t) represents the degree of motion of the terminal device. For example, a sliding window analysis can be used to detect the motion or stationary state of the terminal device. The window size can be 200ms. k is the switching steepness parameter, which can be set to a value in the range of 5 to 15 based on experience. The threshold value of acceleration can also be set based on experience. 静止 =0.01I,Q 运动 =0.1I, and the process noise covariance matrix under any degree of motion is calculated by interpolation.

[0121] Step S320: Using the observation equation and based on the observation noise covariance matrix, determine an update value for the state value.

[0122] The observation equation is as follows:

[0123] Z k =HX k +V k (7)

[0124] Z k is the observation vector at the current moment, that is, the observation value of the posture at the current moment. H is the observation matrix, V k is the observation noise. The statistical characteristics of the observation noise can be described by the observation noise covariance matrix R. After calculating the observation vector using the observation equation, the observation noise covariance matrix is introduced to calculate the Kalman gain and the state update, resulting in the updated state value. The observation noise covariance matrix can reflect the uncertainty in the observation process.

[0125] A fixed or dynamic observation noise covariance matrix can be used. In one embodiment, the observation noise covariance matrix can be determined based on the credibility evaluation value of the inertial sensor used to measure the posture information of the terminal device. The calculation process is as follows:

[0126] R k =R base ·diag(1+δ1,1+δ2,...,1+δ n ) (8)

[0127]

[0128] Among them, R k is the observation noise covariance matrix at the current moment (i.e., moment k), Q base is the basis value of the observation noise covariance matrix, z i,k is the observation value of the i-th inertial sensor, Its predicted value, σ i is the standard deviation, α is the scaling factor, δ i represents the credibility evaluation value of the i-th inertial sensor, δ i The smaller the value, the higher the credibility assessment value. When a particular inertial sensor's data is abnormal, its weight in the fusion can be reduced. This ensures that the calculated observation noise covariance matrix includes the reliability factor of the inertial sensor, resulting in higher accuracy.

[0129] Step S330: Update the status value based on the updated value to obtain the posture information of the terminal device at the current moment.

[0130] For example, a state update equation can be used to update the state value based on the updated value to obtain the terminal device's current posture information. This posture information is the result of posture optimization that combines state prediction and observation, and has high accuracy.

[0131] In one embodiment, the above-mentioned use of the state equation and determining the state value of the posture of the terminal device at the current moment according to the process noise covariance matrix includes the following steps:

[0132] The state value of the terminal device's posture at the current moment is determined by using the state equation with the expansion correction term and according to the process noise covariance matrix.

[0133] For example, a second-order Taylor expansion correction term can be introduced into the state equation as follows:

[0134]

[0135] Among them, J f is the Jacobian matrix, H fis the Hessian matrix. This can further reduce the error. For example, in large-angle rotation scenarios, the estimation error can be reduced by 25-40%.

[0136] based on Figure 3 The method shown here can effectively reduce attitude estimation errors, for example, keeping them below 0.8°. Compared to traditional methods, it reduces the average attitude estimation error by approximately 33% in typical usage scenarios. The reduction is even more significant in fast-moving scenarios, reaching 45%. In static conditions, drift is reduced by 60%, improving stability during long-term interactions.

[0137] In one embodiment, the first control instruction includes a display viewing angle control instruction. The above-mentioned execution of the corresponding first control instruction according to the posture information includes the following steps:

[0138] Determining a display viewing angle control instruction according to the posture information;

[0139] The display effect of the first preset interface associated with the first digital music is controlled according to the display viewing angle control instruction.

[0140] The first preset interface includes, but is not limited to, one or more of the following interfaces: a playback interface, a details interface, a display interface, and a comment interface for the first digital music. A display angle control instruction is determined based on the posture information, and the display effect of the first preset interface is controlled so that the display angle of the first preset interface is adapted to the posture of the terminal device. For example, the following display angle mapping function can be used to calculate the angle offset:

[0141]

[0142] Where α is the tilt angle of the terminal device, and k is the mapping coefficient, which can be set based on experience. After calculating the offset, the first preset interface can be controlled to deflect the offset angle to achieve an immersive visual experience.

[0143] In one embodiment, response delay optimization can be used to control the total delay within 16ms to match the 60fps refresh rate of the terminal device. Exemplarily, a prediction compensation mechanism is used to predict the next frame posture based on the current posture change rate, and then determine the display perspective control instruction to improve the response speed. A motion pattern memory cache can be introduced to record the target user's commonly used posture change patterns to optimize prediction accuracy. The sampling rate of the inertial sensor can be adaptively adjusted, such as using a 60Hz sampling rate when the terminal device is stationary, and increasing the sampling rate according to the degree of motion when the terminal device is in motion, such as up to 120Hz.

[0144] In one embodiment, the above-mentioned processing of the first interaction instruction between the target user and the first digital music based on the first interaction strategy includes the following steps:

[0145] Determine the current usage scenario of the target user, and control the interactive elements in the first preset interface associated with the first digital music according to the current usage scenario; the interactive elements are used to trigger the first interactive instructions.

[0146] The current usage scenario may refer to the target user's current behavior pattern or external environment while using the terminal device. The target user's current usage scenario can be determined based on one or more of the following: time, location, terminal device posture information, target user's health information, and environmental information. For example, if the current time is between 7:00 and 9:00 or 17:00 and 19:00 on a weekday, and the terminal device's position is moving linearly at a speed of 5-60 km / h, the current usage scenario is determined to be a commuting scenario. If the current time is during weekends or non-working hours, and the terminal device's position is relatively fixed with low posture changes, the current usage scenario is determined to be a leisure scenario. If the current time is during regular exercise and the target user's heart rate exceeds 100 bpm, the current usage scenario is determined to be a sports scenario. If the current time is between 9:00 and 11:00 PM, the ambient light is less than 10 lux, and the terminal device remains stationary for more than 5 minutes, the current usage scenario is determined to be a bedtime scenario. If multiple Bluetooth devices are detected in the environment and the target user's microphone detects multiple voices, the current usage scenario is determined to be a social scenario.

[0147] In one embodiment, the current usage scenario of the target user can be determined by feature matching. Refer to the following formula:

[0148] C=Σ(w i Feature matching i )(12)

[0149] Among them, w i The weight of each feature can be set based on experience or specific circumstances, such as the time feature weight is 0.3, the location feature weight is 0.3, and the behavior feature weight is 0.4. i Indicates the degree of match between the target user or terminal device's current characteristics and those of various typical usage scenarios. For example, time match = 1 - |Current time - Reference time for typical usage scenario| / Maximum deviation. By combining the feature match of different characteristics, the degree of match between the target user or terminal device and various typical usage scenarios is determined, thereby determining the current usage scenario.

[0150] According to the current usage scenario, the interactive elements in the first preset interface can be adjusted, such as the position, size, type, etc. of the interactive elements, to meet the needs of the target user in the current usage scenario. The following three aspects are used as examples:

[0151] i. Adjust the layout and response of the interactive elements of the first preset interface based on the current usage scenario. For example, in the commuting scenario, move the bottom control area up by 15%, increase the click area by 30%, and simplify the hierarchical structure. In the sports scenario, enable large font mode, such as increasing the font size by 25%, and enable the motion anti-mistouch algorithm, such as extending the long press judgment by 50ms. In the bedtime scenario, lower the color temperature, such as reducing blue light output by 30%, reducing contrast by 20%, and simplifying the visual effect. In the work scenario, optimize background playback control, reduce visual interference elements, and enhance the focus mode.

[0152] ii. Adjust the target user's interaction methods with the interactive elements of the first preset interface based on the current usage scenario. For example, in commuting scenarios, enable one-handed operation mode, such as moving the control area closer to a single edge and increasing gesture control sensitivity by 20%. In sports scenarios, enable voice control and simplify the operation process, such as reducing the number of confirmation steps. In bedtime scenarios, add a timed stop playback function and optimize the volume gradient curve, such as extending the gradient time by 200%. In social scenarios, optimize the shared playlist function and simplify the sharing operation process, such as reducing the number of operation steps by 50%.

[0153] iii. Enable interactive effects based on the current usage scenario. For example, in commuting scenarios, reduce complex visual effects, such as reducing particle count by 50%, and optimize the one-handed swipe response curve. In leisure scenarios, enhance visual effects, such as increasing light and shadow details by 30%, to provide more exploratory interactions. In sports scenarios, simplify visual feedback and enhance tactile and audio feedback, such as increasing vibration intensity by 25%. In bedtime scenarios, reduce animation speed, such as by 30%, and reduce high-frequency visual stimulation elements.

[0154] In one embodiment, the music interaction processing method further includes the following steps:

[0155] Determine the music interaction index of target users;

[0156] Determine the first interaction strategy based on the music interaction index.

[0157] The target user's music interaction index is a numerical value obtained by statistically evaluating the target user's interaction behavior with digital music, reflecting characteristics such as the target user's interaction intensity and interaction habits. A correspondence between the music interaction index and interaction strategies can be pre-set. Based on the target user's music interaction index, a corresponding first interaction strategy can be determined, allowing the first interaction strategy to adapt to the target user's interaction characteristics and meet user needs.

[0158] In one embodiment, the above-mentioned determination of the music interaction index of the target user includes the following steps:

[0159] Obtain the target user's playback index, time investment index, and social interaction index;

[0160] The target user's playback index, time investment index, and social interaction index are weighted to obtain the target user's music interaction index.

[0161] Among them, the historical interaction information between the target user and digital music can be counted to obtain the target user's playback index, time investment index, and social interaction index. For example, the target user's behavioral data can be obtained, including but not limited to playback data (such as playback duration, playback frequency, playback completion rate, etc.), collection data (such as collection events, persistence, related behaviors, etc.), advanced interaction data (such as operation frequency, complexity, the length of time the target user stays in different areas of the interface obtained by eye tracking, etc.), social data (such as sharing, commenting, and other behavioral data). Statistics of playback data, playback duration, playback frequency, playback completion rate and other indicators are integrated (such as weighted integration) to obtain a playback index. Calculate the target user's attention distribution AD based on advanced interaction data, refer to the following formula:

[0162] AD=Σ(w i ·t i / T total ) (13)

[0163] Among them, t i is the target user’s stay time in the i-th area of the interface, T total is the total interaction time, w i is the regional importance weight, for example, the importance weight of the core functional area is 1.0, the importance weight of the secondary area is 0.6, and the importance weight of the peripheral area is 0.3. Based on attention distribution and combined with collection data, a time investment index can be derived. For example, attention distribution can be used as the time investment index, or attention distribution and collection data indicators can be further integrated to obtain the time investment index. The social interaction index is obtained by summarizing various indicators in social data.

[0164] The target user's music interaction index is obtained by weighting the target user's playback index, time investment index, and social interaction index. For example, the following formula can be used:

[0165] I=α·P+β·T+γ·S (14)

[0166] Among them, P is the playback index, T is the time investment index, S is the social interaction index, and α, β, and γ are the weights corresponding to the three indexes respectively, satisfying α+β+γ=1. The values of α, β, and γ can be set according to experience or business needs.

[0167] In one embodiment, the weighting of the target user's play index, time investment index, and social interaction index to obtain the target user's music interaction index includes the following steps:

[0168] Determine a first weight parameter according to the type of target user, the first weight parameter including weights corresponding to the play index, the time investment index, and the social interaction index respectively;

[0169] The target user's playback index, time investment index, and social interaction index are weighted based on the first weight parameter to obtain the target user's music interaction index.

[0170] Among them, the first weight parameter includes the three weights α, β, and γ mentioned above. The type of the target user can be determined based on the registration information, behavioral characteristics, etc., and the corresponding first weight parameter is determined based on the type. For example, if the target user is a new user, the first weight parameter includes: α0=0.5, β0=0.3, γ0=0.2; if the target user is a collection user, the first weight parameter includes: α0=0.4, β0=0.4, γ0=0.2; if the target user is a social user, the first weight parameter includes: α0=0.3, β0=0.3, γ0=0.4. In this way, the first weight parameter is adapted to the type of the target user, and the calculated music interaction index of the target user can more accurately reflect the characteristics of the target user.

[0171] In one embodiment, the weighting of the target user's play index, time investment index, and social interaction index to obtain the target user's music interaction index further includes the following steps:

[0172] The first weight parameter is updated in at least one of the following ways, so as to weight the target user's play index, time investment index, and social interaction index based on the updated first weight parameter:

[0173] Update the first weight parameter according to the target user's playback behavior preference parameter, time investment preference parameter, and social behavior preference parameter;

[0174] Updating the first weight parameter according to the usage scenario of the target user;

[0175] The first weight parameter is updated according to the usage feedback indicator of the target user.

[0176] That is, after determining the first weight parameter, it can be dynamically updated and adjusted as the target user's preferences change. Furthermore, the first weight parameter can be updated and adjusted based on the target user's usage scenarios, usage feedback indicators, and other factors to meet the target user's current needs.

[0177] For example, the behavior pattern of the target user can be analyzed by the user behavior influence function system to calculate its behavior preference vector B = [B P ,B T ,B S ], where B P is the playback behavior preference parameter, which can be calculated based on indicators such as playback completion rate and number of loops. T is the time investment preference parameter, which can be calculated based on indicators such as residence time and interaction frequency. S is a social behavior preference parameter, which can be calculated based on indicators such as sharing frequency and comment interaction, and the parameter value range can be [-1, 1]. The following weight update formula is used to update the first weight parameter:

[0178] α t+1 =α t +η·(B P -α t )·(1-|B P -α t | / 2)

[0179] β t+1 =β t +η·(B T -β t )·(1-|B T -β t | / 2)

[0180] γ t+1 =γ t +η·(B S -γ t )·(1-|B S -γ t | / 2) (15)

[0181] Where η is the learning rate, which can be set to a value in the range of 0.05 to 0.15 based on experience or business needs. The term multiplied by η is a nonlinear term that ensures smooth updates and convergence. Based on formula (15), the following formula can be further used to normalize the weights to ensure that the first weight coefficient after each update satisfies α + β + γ = 1.

[0182] [α',β',γ']=[α,β,γ] / Σ(α,β,γ) (16)

[0183] For example, if the target user's usage scenario is a commuting scenario, the playback index weight α can be increased, for example, by 20%, and the time investment index weight β can be reduced, for example, by 15%. If the target user's usage scenario is a social scenario, the social interaction index weight γ can be increased, for example, by 25%. If the target user's usage scenario is a leisure scenario, the three weights can be balanced and the time investment index weight β can be slightly increased, for example, by 10%. The update of the first weight parameter based on the target user's usage scenario is temporary and does not directly affect the long-term learning results of the first weight parameter. When the target user's usage scenario changes, dynamic adjustments can be made in real time.

[0184] For another example, the system can obtain the impact of the calculated change in the music interaction index of the target user on the target user's behavior. After updating the first weight parameter, the change in the behavioral characteristics of the target user over a period of time is obtained, and the correlation between the change in the music interaction index and the user satisfaction index is determined. User satisfaction indicators include but are not limited to the usage frequency growth rate, session duration change rate, function attempt rate, etc. If the user satisfaction index increases overall, it means that the update of the first weight parameter and the change in the music interaction index have produced positive effects, and the learning rate can be appropriately increased. Otherwise, it means that the update of the first weight parameter and the change in the music interaction index have not produced positive effects, and the learning rate can be appropriately reduced. For example, when the positive correlation between the satisfaction index and the change in the music interaction index is greater than 0.6, the learning rate is increased by 50%. When the negative correlation between the satisfaction index and the change in the music interaction index is greater than 0.4, the learning rate is reduced by 50%, and part of the adjustment of the first weight parameter can be rolled back, that is, the first weight parameter returns to the value at a previous moment.

[0185] In one embodiment, the music interaction index can be decayed over time. For example, if the target user does not engage in any interactive behavior, the music interaction index will gradually decrease over time, indicating that the target user's interactivity is gradually decreasing. The decay value D can be calculated by referring to the following formula:

[0186] D=e -λt (17)

[0187] Where t is the time interval between the current and the last calculation of the music interaction index, and λ is the attenuation coefficient, which can be set based on experience or specific business needs and can be adjusted adaptively. For example, the λ value can be adjusted based on the type of digital music interacted with by the target user, with λ = 0.03 for popular albums and λ = 0.015 for classic albums. The λ value can also be adjusted based on the stickiness of the target user, with λ reduced by 20% for high-frequency users and increased by 30% for low-frequency users. The λ value can also be adjusted periodically, such as temporarily reducing λ by 50% during specific holidays or events to prolong the event's effect.

[0188] In one embodiment, the user level of the target user can be determined based on the music interaction index of the target user, and the interaction strategy corresponding to the user level can be used as the first interaction strategy. For example, the user level of the target user can be determined by referring to the following formula:

[0189] Level=floor(3I)+1 (18)

[0190] For example, you can set three user levels (normal, advanced, and senior), each corresponding to a different interaction strategy. The interaction strategies corresponding to normal users include: standard sound quality, basic interaction effects, and 2D display effects. The interaction strategies corresponding to advanced users include: high-quality sound quality, enhanced interaction effects, and 2.5D display effects. The interaction strategies corresponding to senior users include: Hi-Res (HighResolution Audio, high-resolution sound source) sound quality, complete interaction features, and 3D display effects. In addition, you can also provide more exclusive interaction methods or interaction effects for advanced or senior users, such as collection effects, social display effects, etc.

[0191] Figure 4 This diagram shows a tiered service for target users based on their music interaction index. Play data, interaction data, and social data are obtained from data sources. A calculation model is used to calculate the play index, time investment index, and social interaction index. This is combined with time decay and a weight coefficient to calculate the target user's music interaction index. Target users are then classified based on their music interaction index and provided with corresponding permission-based services.

[0192] Through the above methods, refined services are achieved for target users, which is conducive to providing interactive strategies and services that meet the needs of target users.

[0193] In one embodiment, the music interaction processing method further includes the following steps:

[0194] A first interaction strategy is determined according to the performance of the terminal device.

[0195] The performance of the terminal device may include the performance of its hardware (such as a processor, memory, touch screen, and sensors), reflecting the terminal device's ability to provide physical interaction effects. Determining a first interaction strategy appropriate to the terminal device's performance can effectively maximize the terminal device's performance and avoid interactive responses that exceed its performance, thereby protecting the terminal device.

[0196] In one embodiment, the performance of the terminal device can be graded based on its performance. This disclosure does not limit the specific grading standards. For example, the grading can be based on the sampling rate, accuracy, detection range, etc. of the terminal device's sensor. The following uses the first performance level and the second performance level as examples for explanation. The second performance level is higher than the first performance level, indicating that the terminal device of the second performance level has higher performance than the terminal device of the first performance level. For example, if the pressure sensor of the terminal device is configured with 256 levels of pressure value, it belongs to the first performance level. If the pressure sensor of the terminal device is configured with 1024 levels of pressure value, it belongs to the second performance level.

[0197] In one embodiment, the method of determining the first interaction strategy based on the performance of the terminal device includes the following steps:

[0198] If the performance of the terminal device belongs to the first performance level, determining the first interaction strategy includes: detecting a pressure operation using a first pressure detection parameter;

[0199] If the performance of the terminal device belongs to the second performance level, determining the first interaction strategy includes: using a second pressure detection parameter to detect pressure operation; the second pressure detection parameter is greater than the first pressure detection parameter.

[0200] For example, the first pressure detection parameter includes a detection range of 0.1 to 2N and a resolution of 256 levels; the second pressure detection parameter includes a detection range of 0.1 to 5N and a resolution of 1024 levels. Compared to the first pressure detection parameter, the second pressure detection parameter can obtain more refined pressure detection results, thereby achieving richer interactive effects.

[0201] When the target user triggers the first interaction instruction, the following pressure mapping function may be used to convert the detected pressure value into a numerical value:

[0202] f(p)=a*ln(p / p0)+b (19)

[0203] Where a is the amplification factor, which can be set to a value between 1 and 3 based on experience or specific business needs. p0 is the baseline pressure value, which can be 0.1N. b is the offset, which can be set to a value between 0 and 1 based on experience or specific business needs. The corresponding pressure response is executed based on the pressure value after numerical conversion.

[0204] In one embodiment, when the performance of the terminal device degrades, a smooth reduction in pressure detection can be performed. For example, when the terminal device is downgraded from the second performance level (1024-level pressure detection) to the first performance level (256-level pressure detection), the system performs the following mapping to ensure that the pressure sensitivity values maintain relative proportions after the downgrade.

[0205] P_LV1=floor(P_LV2*256 / 1024) (20)

[0206] Among them, P_LV1 represents the pressure level detected at the first performance level, and P_LV2 represents the pressure level detected at the second performance level. For terminal devices at the first performance level, the system redesigns the pressure response curve, as shown below:

[0207] F_LV1(p)=a·(e b·p -1) / (e b -1) (21)

[0208] Parameters a and b control the maximum output value and shape of the curve, respectively. By adjusting parameters such as a = 1.2 and b = 3.5, the problem of insufficient pressure sensitivity resolution in terminal devices of the first performance level can be compensated. Through pressure sampling smoothing, sample point averaging and historical weight calculation are added to terminal devices of the first performance level, as shown below:

[0209] P'(t)=0.7·P(t)+0.2·P(t-1)+0.1·P(t-2) (22)

[0210] Here, t, t-1, and t-2 represent different moments. That is, at the first performance level, the detected pressure value is smoothed with the pressure value at the previous moment. This improves the smoothness of pressure detection and reduces jitter caused by low precision.

[0211] In one embodiment, the method of determining the first interaction strategy based on the performance of the terminal device includes the following steps:

[0212] If the performance of the terminal device belongs to the first performance level, determining the first interaction strategy includes: presenting a vibration effect using a fixed vibration frequency;

[0213] If the performance of the terminal device belongs to the second performance level, determining the first interaction strategy includes: using a dynamic vibration frequency to present a vibration effect.

[0214] For example, the fixed vibration frequency is 60Hz, and the dynamic vibration frequency is 50-200Hz. With a fixed vibration frequency, the vibration effect is generated regardless of the pressure applied by the target user. With a dynamic vibration frequency, the vibration effect is generated at a corresponding vibration frequency based on the pressure applied by the target user. The greater the pressure applied, the higher the vibration frequency, and the stronger the vibration effect felt by the user.

[0215] In one embodiment, the method of determining the first interaction strategy based on the performance of the terminal device includes the following steps:

[0216] If the performance of the terminal device belongs to the first performance level, determining the first interaction strategy includes: using basic tactile feedback parameters to present the touch effect;

[0217] If the performance of the terminal device belongs to the second performance level, determining the first interaction strategy includes: using material simulation tactile feedback parameters to present a touch effect.

[0218] The tactile feedback parameters may include one or more of vibration parameters, electrostatic parameters, and friction parameters to simulate the tactile effect of a user touching a real material. Basic tactile feedback parameters are used to provide basic tactile feedback effects and may be fixed tactile feedback parameters. Material simulation tactile feedback parameters are used to provide tactile feedback effects that simulate the material of the current first digital music album, and can simulate the tactile feel of vinyl, CDs, tapes, and the like.

[0219] In one embodiment, if the performance of the terminal device belongs to the second performance level, the complex vibration parameter V S = {A, f, d, e, p} to achieve vibration and touch effects. Complex vibration parameters include amplitude A, frequency f, duration d, envelope e, phase p and other multi-dimensional parameters. If the performance of the terminal device belongs to the first performance level, the simplified vibration parameter V is used. A ={A', f', d'} to achieve vibration and touch effects. The simplified vibration parameters include amplitude A', frequency f', and duration d'.

[0220] In one embodiment, when the performance of the terminal device is reduced, a smooth reduction process of the tactile feedback can be performed. Exemplarily, at the first performance level, the amplitude A', frequency f', and duration d' are enhanced by the following formula.

[0221] A'=min(1.0,A·1.2)

[0222] f'=quantize(f,{40,60,80})

[0223] d'=d·(1+0.5·complexity) (23)

[0224] Complexity is a measure of vibration complexity, calculated from the diversity of the original parameters. This calculation method can moderately enhance the expressiveness of amplitude compensation, map continuous frequencies to discrete values, and extend the expressiveness of duration compensation.

[0225] In one embodiment, material simulation optimization of the first digital music can be achieved. Specifically, the vibration characteristics of the album material of the first digital music are simplified. For example, if the first digital music is a vinyl record, at the first performance level, a single 60Hz vibration superimposed with 20Hz low-frequency modulation can be used. If the first digital music is a CD record, at the first performance level, an 80Hz fixed vibration combined with short pulses can be used. If the first digital music is a magnetic tape, at the first performance level, a 40Hz continuous vibration combined with an attenuation envelope can be used.

[0226] In one embodiment, the method of determining the first interaction strategy based on the performance of the terminal device includes the following steps:

[0227] If the performance of the terminal device belongs to the first performance level, determining the first interaction strategy includes: playing the first digital music using stereo field parameters;

[0228] If the performance of the terminal device belongs to the second performance level, determining the first interaction strategy includes: using spatial sound field parameters to play the first digital music.

[0229] For example, stereo field parameters may include: sound field range of 360°, sound source positioning accuracy of ±5° (that is, the error of sound source positioning does not exceed ±5°), HRTF (Head Related Transfer Functions) supports personalized head model, supports dynamic reverberation parameters (such as adaptive adjustment according to the album style and era characteristics of the first digital music), and supports progressive audio guidance (used to create a sense of album space transition). Spatial sound field parameters may include: sound field range of ±45°, volume balance of -1 to 1, support for fixed reverberation parameters, RT60 (the time required for sound energy density to decay by 60dB) is fixed at 1.2s, early reflection gain is -6dB, and supports basic volume gradient (used to achieve a simplified entrance sound effect).

[0230] In one embodiment, when the performance of the terminal device is reduced, spatial audio degradation processing can be performed. Specifically, based on the 360° to stereo mapping algorithm, the omnidirectional spatial audio of the second performance level terminal device is mapped to the stereo of the first performance level terminal device, referring to the following formula:

[0231] L A =Σ(S i max(0,cos(θ i -π / 2)) n

[0232] R A =Σ(S i max(0,cos(θ i +π / 2))n (twenty four)

[0233] Among them, L A 、R A They represent the left stereo angle and the right stereo angle under the first performance level, S i is the intensity of the i-th sound source, θ i is the azimuth angle of the sound source, and n is the directivity coefficient, which can be set to a value within the range of 1.5 to 2.5 based on experience or specific needs. Dynamic HRTF conversion is then performed to simplify the complex HRTF at the second performance level into a stereo enhancement model at the first performance level. For example, the key features of the original HRTF can be extracted through principal component analysis (PCA), and the principal components (such as the first 3 principal components) can be retained. This can capture a larger proportion (such as about 85%) of the spatial positioning information. In order to compensate for the insufficient spatial positioning capability of the terminal equipment at the first performance level, one or more of the following sense of direction compensation schemes can be adopted: enhance the difference in stereo sound and image, such as increasing ±15% to improve channel separation; adopt a moderate delay difference (such as 5-15ms) to enhance the sense of direction; add auxiliary sound effects at key scene transition points to enhance the perception of spatial transition.

[0234] In one embodiment, when the performance of the terminal device is reduced, the reverberation parameters can be adaptively adjusted. Specifically, the system analyzes the reverberation parameter curve R_S(t)={RT t ,ER t ,DR t}, including reverberation time, early reflections and diffusivity, extract key feature points, and generate the optimal reverberation parameters R_A = {RT_A, ER_A, DR_A} under the first performance level. Each parameter can be calculated by weighted average according to the following formula:

[0235]

[0236] Among them, the weight w t The calculation formula is as follows:

[0237] w t =α·B t +β·E t +γ·C t (26)

[0238] Among them, α, β, and γ are weight coefficients, satisfying α+β+γ=1. The default values can be 0.5, 0.3, and 0.2. Bt is the rhythm intensity factor, which can be a value in the range of 0 to 1 and is calculated by the music transient detection algorithm. The reference is as follows:

[0239] B t =(P t-P min ) / (P max -P min ) (27)

[0240] Among them, P t is the instantaneous rhythm intensity, P max 、P min are the maximum and minimum values of rhythm intensity.

[0241] E t It is the emotional intensity factor, which can be a value in the range of 0 to 1, and is based on a comprehensive evaluation of pitch, harmonic complexity and timbre characteristics. t It is the content complexity factor, which can be a value in the range of 0 to 1 and is obtained through spectral entropy and dynamic range analysis.

[0242] The sense of space can be enhanced through frequency-selective reverberation. For example, a terminal device with the first performance level applies stronger reverberation to the mid- and high-frequency (2-8kHz) frequencies to enhance the sense of space. The mid- and high-frequency reverberation gain coefficients are as follows:

[0243] G_HF=1.3+0.2·(1-DR_A) (28)

[0244] You can adjust the ratio of direct sound to reflected sound to compensate for the lack of spatial localization. The ratio of direct sound to reflected sound is as follows:

[0245] R_DR=0.7-0.3·ER_A (29)

[0246] Frequency dependent reverberation time adjustments can be applied as follows:

[0247] RT_f=RT_A·(f / 1000)^-0.15 (30)

[0248] This ensures that the low-frequency reverberation time is slightly longer and the high-frequency reverberation time is slightly shorter, which is in line with natural acoustic characteristics.

[0249] In one embodiment, the allocation of audio processing resources can be adjusted based on the performance level of the terminal device. For example, for a terminal device at the second performance level, 80% of the processing capacity is allocated to spatial audio calculations and 20% to sound effects processing. For a terminal device at the first performance level, 40% of the processing capacity is allocated to simplified spatial processing, 40% to sound quality enhancement, and 20% to sound effects processing.

[0250] In addition, for terminal devices of the first performance level, a simplified audio processing pipeline can be used to reduce the number of HRTF calculation points (such as from 1024 to 256), reduce the spatial resolution but maintain the accuracy of key orientations, simplify the reverberation algorithm (such as from convolution reverberation to feedback delay network), reduce the amount of calculation by 40% while maintaining 80% of the perceived quality.

[0251] In one embodiment, an adaptive resolution control mechanism can be employed to dynamically adjust processing accuracy based on the complexity of the first digital music content. For example, basic processing can be used for mono or simple stereo content, while processing accuracy can be increased for complex multi-track mixes to ensure accurate spatial positioning of key audio elements.

[0252] In one embodiment, the method of determining the first interaction strategy based on the performance of the terminal device includes the following steps:

[0253] If the performance of the terminal device belongs to the first performance level, determining the first interaction strategy includes: using the first visual rendering parameter to generate a display effect;

[0254] If the performance of the terminal device belongs to the second performance level, determining the first interaction strategy includes: using a second visual rendering parameter to generate a display effect; the second visual rendering parameter is greater than the first visual rendering parameter.

[0255] For example, the second visual rendering parameters include: support for real-time ray tracing, such as a sampling rate of ≥60fps per frame and ≥4 light bounces; support for a complete material system, such as PBR (Physically-Based Rendering) materials, subsurface scattering, anisotropic reflections, etc.; support for a particle effects system, such as supporting up to 1000+ particles and providing complete physical behavior simulation; support for advanced post-processing, such as depth of field blur, motion blur, tone mapping, and high-precision HDR (High Dynamic Range Imaging); use of advanced ambient lighting models, such as third-order spherical harmonics. The first visual rendering parameters include: support for pre-calculated ambient occlusion (SSAO), which is equivalent to reducing parameters compared to real-time ray tracing and can reduce the amount of calculation by 80%; support for retaining dynamic shadows for critical perspectives and using baked shadows for non-critical perspectives; support for simplified ambient lighting models, such as using second-order spherical harmonics to retain 70% of ambient light details.

[0256] In one embodiment, when the performance of the terminal device is reduced, the visual rendering parameters of the material simulation can be degraded in the following manner: The PBR material is simplified to a modified Blinn-Phong model, as shown below:

[0257] F A(N·H) =k d·(N·L) +(k s·(N·H) ) m ·F(V·H) (31)

[0258] The complete Fresnel term is simplified to the Schlick approximation as follows:

[0259] F(V·H)≈F0+(1-F0)·(1-(V·H)) 5 (32)

[0260] Subsurface scattering effects are replaced with pre-calculated textures and a simplified diffuse model. The special effects system has been optimized, such as limiting the number of particles to a maximum of 500, simplifying physical behavior calculations, using texture sequences instead of real-time simulated fluid and smoke effects, and using billboard technology instead of complex 3D particle geometry, reducing the rendering burden by 60%. The post-processing process has been simplified, such as merging multiple rendering passes into a single pass, reducing draw calls, using a circular blur depth of field effect instead of bokeh blur, retaining the sense of depth but reducing the amount of calculation by 50%, and using a simplified Reinhard operator for HDR processing instead of an adaptive local operator.

[0261] In one embodiment, the first interaction strategy may include a visual consistency guarantee mechanism. Specifically, ensure the identification and retention of core visual elements, such as through target user gaze heat map analysis, identify key visual elements, retain 90% of the details of album covers and major interactive elements, and simplify secondary elements by 40-60%. Adopt an intelligent LOD (Level of Details) strategy to dynamically adjust the model detail level based on viewing distance and importance, improve rendering accuracy at key interaction moments, reduce accuracy in non-interactive states, and use fade-in and fade-out effects to mask changes in details when visual elements enter or exit the field of view. Adopt a preloading and caching mechanism, increase preloading resources by 50% for terminal devices of the first performance level, reduce real-time computing requirements, use result caching for commonly used visual effects, and reduce repeated calculations.

[0262] In one embodiment, the above-mentioned processing of the first interaction instruction between the target user and the first digital music based on the first interaction strategy includes the following steps:

[0263] determining the number of operation points in the first interaction instruction;

[0264] If the number of operating points is greater than or equal to K1, the control instructions corresponding to K1 operating points are executed;

[0265] If the number of operating points is greater than or equal to K2 and less than K1, the control instructions corresponding to K2 operating points are executed;

[0266] If the number of operating points is less than K2, the control instruction corresponding to the K3 operating point is executed;

[0267] Among them, K1>K2>K3. For example, K1=3, K2=2, K3=1. If it is detected that the number of operation points in the first interaction instruction of the target user is greater than or equal to 3, the control instructions corresponding to multi-finger operations are given priority, such as instructions for switching albums and songs. If it is detected that the number of operation points in the first interaction instruction of the target user is 2, the control instructions corresponding to two-finger operations are given priority, such as instructions for adjusting the volume. If it is detected that the number of operation points in the first interaction instruction of the target user is 1, the control instructions corresponding to single-finger operations are used, such as instructions for controlling the playback progress. In one embodiment, a time window of a specific duration (such as 200ms) can be used to detect the number of operation points in the first interaction instruction. The highest priority gesture detected within the time window will be executed, and low-priority gestures will be ignored, thereby improving operational efficiency.

[0268] For example, for single-finger operation, the following relationship between sliding distance and music playback progress can be set:

[0269] d=k·log(1+t / 1000) (33)

[0270] Where d represents the sliding distance, and t represents the music playing progress (in time units).

[0271] For two-finger operation, you can set the following relationship between the operation angle (the angle of the two-finger pinch gesture) and the volume change:

[0272] ΔV=0.5*(1-cosθ) (34)

[0273] In one embodiment, the first interaction instruction includes a first display instruction. The above-mentioned processing of the first interaction instruction between the target user and the first digital music based on the first interaction strategy includes the following steps:

[0274] In response to the first display instruction, the second preset interface is displayed, and the icon of the first digital music is displayed at a corresponding position in the second preset interface according to the information of the first digital music.

[0275] The second preset interface may be a display interface of one or more first digital music items. For example, after the target user purchases the first digital music item, the target user may view icons of all purchased first digital music items on the second preset interface, thereby increasing the target user's sense of acquisition.

[0276] The first display instruction triggers the display of the second preset interface, such as an instruction to click on an entry to the second preset interface. Within the second preset interface, the position of the first digital music icon can be determined based on the information about the first digital music. For example, the icons can be arranged based on the chronological order in which the target user acquired each first digital music item. The second preset interface can simulate a user's real-life collection of physical albums, giving the target user a similar experience to a real-life collection.

[0277] In one embodiment, the second preset interface is provided with a music collection space, which may be a three-dimensional space. The above-mentioned displaying the icon of the first digital music at a corresponding position in the second preset interface according to the information of the first digital music includes the following steps:

[0278] Determine an X-axis coordinate according to the collection duration, music index information, and emotional characteristics of the first digital music;

[0279] Determine the Y-axis coordinate according to the collection duration, music index information, and music style of the first digital music;

[0280] Determining a Z-axis coordinate based on a music genre factor, rarity, and audio characteristics of the first digital music and a degree of matching with a target user's music style preference;

[0281] An icon of the first digital music is displayed in the music collection space according to the X-axis coordinate, the Y-axis coordinate, and the Z-axis coordinate.

[0282] For example, a spiral display structure may be constructed in the music collection space, and the position coordinates of the icons of each first digital music may refer to the following formula:

[0283] P(x,y,z)=(T(t)·cos(θ)·E(s),T(t)·sin(θ)·G(g),H(t)·M(a)) (35)

[0284] The following is an explanation of each part of the formula.

[0285] The X coordinate can be calculated by T(t)·cos(θ)·E(s), where:

[0286] T(t)=r+k·log(1+t) (36)

[0287] Where t is the collection duration (the unit can be days), r is the basic radius, which can be set to 100 to 500 units based on experience or specific business needs, and k is the time mapping coefficient, which can be set to a value in the range of 10 to 50 based on experience or specific business needs.

[0288] θ=2π·(i / N)+π / 6·A(a) (37)

[0289] Among them, i is music index information (such as an ordinal number), N is the total number of first digital music, and A(a) is the emotional angle of music, which can be calculated by setting a function based on experience or specific needs.

[0290] E(s) is the sentiment feature, and the calculation formula is as follows:

[0291] E(s)=0.8+0.4*(V·W X +A·W a +D·W d ) (38)

[0292] Where V is the music value, which can be set to a value within the range of 0-1 based on experience or specific business needs. X is the weight coefficient 0.4; A is the emotional activation degree, which can be set to a value within the range of 0-1 based on experience or specific business needs. a is the weight coefficient of 0.3; D is the emotional dominance, which can be set to a value in the range of 0-1 based on experience or specific business needs; W: is the weight coefficient of 0.3.

[0293] The Y coordinate can be calculated by T(t)·sin(θ)·G(g), where G(g) is the style grouping coefficient, and the calculation formula is as follows:

[0294]

[0295] Among them, S i is the spatial mapping value of the i-th music style, which can be a value in the range of 0.5 to 1.5. i is the confidence of the i-th music style, which can be a value in the range of 0 to 1.

[0296] The Z coordinate is calculated from H(t)·M(a), where:

[0297] H(t)=base height+20·(U·W U +F·W f +R·W r ) (40)

[0298] Wherein, U is the matching degree between the first digital music and the music style preference of the target user, which can be a value in the range of 0 to 1, and W U is the weight coefficient 0.5. F is the music genre factor, which can be a value in the range of 0 to 1. f is the weight coefficient 0.3. R is the rarity, which can be a value in the range of 0 to 1. r The weight coefficient is 0.2.

[0299] M(a) is the audio feature, and its calculation formula is as follows:

[0300] M(a)=1+0.3·(B·W b +K·W k +T·W t ) (41)

[0301] Where B is the normalized value of BPM (Beat Per Minute), W b is the weight coefficient of 0.4. K is the tonality eigenvalue, which can be a value in the range of 0 to 1, and Wc is the weight coefficient of 0.3. T is the principal component projection of the timbre eigenvector, which can be a value in the range of 0 to 1, and W t The weight coefficient is 0.3.

[0302] By calculating the coordinates of the icon of the first digital music in the music collection space through the above formula, the first digital music can be arranged in the music collection space in a reasonable and orderly manner according to factors such as collection duration, music index information, emotional characteristics, music characteristics, and matching degree with the target user's music style preference, thereby achieving a better classification and storage effect.

[0303] In one embodiment, the music interaction processing method further includes the following steps:

[0304] Determining the collection weight of the first digital music according to the collection duration, play intensity, and interaction coefficient of the first digital music;

[0305] The state of the icon of the first digital music displayed in the second preset interface is controlled according to the collection weight.

[0306] For example, the calculation formula of the collection weight w is as follows:

[0307]

[0308] Based on the collection weight, the icon of the first digital music can be highlighted. For example, the music collection space can be divided into multiple areas, and the icon of the first digital music with the highest collection weight in each area can be highlighted, such as displaying a larger icon size, displaying a highlighted icon effect, etc. In addition, the focus of the first digital music icon can be offset based on the collection weight. The offset is referred to the following formula:

[0309] offset=max(50,w*100)unit(43)

[0310] The effect of highlighting can be achieved by offsetting.

[0311] In one embodiment, the method of displaying the icon of the first digital music at a corresponding position in the second preset interface according to the information of the first digital music includes the following steps:

[0312] According to the behavior data of the target user listening to the first digital music, the first digital music is mapped to a corresponding level, and an icon of the first digital music is displayed in the second preset interface according to the level corresponding to the first digital music.

[0313] The behavior data of the target user listening to the first digital music can be quantified to calculate the behavior impact factor, referring to the following formula:

[0314]

[0315] Where λ is the decay coefficient, which can be set to a value between 0.1 and 0.5 based on experience or specific business requirements to control the decay rate of time. The complete play rate represents the average percentage of complete plays of the first digital music track. The number of loops represents the frequency with which users repeatedly play the first digital music track.

[0316] Then, we can perform hierarchical mapping on the behavioral influencing factors and calculate the level corresponding to the first digital music, referring to the following formula:

[0317] layer=floor(1+4*(1-α)) (45)

[0318] According to the above hierarchy, the icons of the first digital music are displayed in layers. The first digital music with a higher behavior influence factor indicates that the target user has a higher degree of interaction with it, and it is displayed at a higher level to be highlighted.

[0319] In one embodiment, the music interaction processing method further includes the following steps:

[0320] determining a parallax parameter based on the posture information of the terminal device and the characteristics of the first digital music;

[0321] The position of the first digital music icon displayed in the second preset interface is adjusted according to the parallax parameter.

[0322] For example, the inertial sensor configured in the terminal device can be used to obtain attitude information, such as setting the sampling frequency to 60Hz, and configuring the angle range to be pitch (pitch angle) ±30° and yaw (yaw angle) ±45°. Based on the attitude information and the characteristics of the first digital music, the parallax parameter is calculated, which may include a response parameter, according to the following formula:

[0323] S(θ)=k*sin(θ / 2)*(1+0.2*emotional intensity coefficient) (46)

[0324] Where k is the response coefficient, and the default value can be 1.5. The emotion intensity coefficient = 0.5 (emotion activation + emotion dominance), which is obtained based on audio emotion analysis and can be a value in the range of 0 to 1. θ represents the inclination angle in the posture information.

[0325] Alternatively, the parallax parameter may include a displacement parameter, referring to the following formula:

[0326] D(z)=0.2*z*(1+0.1*music complexity) (47)

[0327] offset(x,y)=D(z)*(device tilt vector)*(1+0.15*user interaction frequency) (48)

[0328] Where z can represent a level, such as the layer calculated by formula (45). Music complexity = 0.4·harmonic complexity + 0.3·rhythm variation rate + 0.3·timbre diversity, which can be a value in the range of 0 to 1. By adjusting the position of the first digital music icon displayed in the second preset interface according to the displacement parameter, a differentiated display effect can be achieved.

[0329] In addition, different display effects are achieved for different levels. For example, for the focus level, the clarity is maintained at 100%; for the adjacent levels of the focus level, the clarity is reduced by 20% per level; for the farthest level, the clarity can be reduced to a minimum of 40%. When the clarity is reduced, a blur effect can be added to the first digital music icon. The blur radius is calculated as follows:

[0330]

[0331] In one embodiment, the first interaction instruction includes a second display instruction. The above-mentioned processing of the first interaction instruction between the target user and the first digital music based on the first interaction strategy includes the following steps:

[0332] In response to the second display instruction, an image associated with the first digital music is displayed according to the information of the first digital music and the environmental information.

[0333] The second display instruction triggers the display of an associated image for the first digital music track, such as a command that triggers the opening of an interface containing the associated image. For example, the second preset interface displays icons for the first digital music track. If the target user clicks on a first digital music track icon, the user is prompted to enter a detailed interface for the first digital music track, which includes the associated image for the first digital music track. Therefore, the aforementioned icon-clicking operation triggers the second display instruction. When displaying the associated image, a display effect simulating the real world can be achieved based on the information about the first digital music track and the surrounding environment.

[0334] In one embodiment, reference Figure 5 As shown, the above-mentioned display of the associated image of the first digital music according to the information of the first digital music and the environmental information includes the following steps S510 to S530:

[0335] Step S510: determining appearance simulation parameters according to information of the first digital music.

[0336] The appearance simulation parameters are parameters used to simulate the appearance of a real album, including but not limited to at least one of a period style parameter, a color variation parameter, a material variation parameter, and a printing feature parameter. In one embodiment, determining the appearance simulation parameters based on the information of the first digital music includes at least one of the following steps:

[0337] Obtaining era style features of multiple reference times, and using the era style features of the corresponding reference time as the era style parameter of the first digital music according to the release time of the first digital music, or fusing the era style features of at least two reference times to obtain the era style parameter of the first digital music;

[0338] determining a color change parameter of the first digital music according to a simulation duration of the first digital music and a color periodic change parameter;

[0339] determining a material change parameter of the first digital music according to characteristics of the cover material of the first digital music and a simulation duration of the first digital music;

[0340] Performing Fourier transform on the associated image and determining frequency domain parameters, and determining printing characteristic parameters of the first digital music according to the frequency domain parameters and ink diffusion simulation parameters.

[0341] For example, we can input physical album images from different eras, using high-resolution source files (e.g., ≥2000x2000px) to improve quality. We map image features to a feature space based on the time dimension (e.g., a continuous feature space covering the years 1950-2023), and construct a decade feature library E = {E_1950, E_1960, ..., E_2020}, where 1950, 1960, etc. represent reference times, and E_1950 represents the style features of the 1950s.

[0342] The release time of the first digital music is recorded as T, which can be expressed in years. If T is equal to a certain reference time, the style characteristics of the era of the reference time are used as the era style parameters of the first digital music. If T is not equal to a certain reference time, the two most recent reference times E can be found. i and E j , cubic spline interpolation and other methods are used to calculate the era style parameters of the first digital music, as shown below:

[0343] E(T)=a·E i +b·E j +c·E′ i +d·E′ j (50)

[0344] Among them, a, b, c, and d are empirical coefficients that can be calculated by Hermite interpolation to ensure the continuity of C1.

[0345] In one embodiment, a randomness introduction mechanism may be used, such as constructing a Perlin noise field N(x, y, t), where t is a time parameter, and applying noise modulation, as shown in the following formula:

[0346]

[0347] Here, x and y may represent the position coordinates in the associated image of the first digital music, and σ is the noise intensity, which may be a value within the range of 0.05 to 0.15 to achieve a randomized aging effect.

[0348] In one embodiment, a local variation algorithm can be used to achieve different degrees of aging effects in different regions of the associated image. For example, enhanced aging is performed on the edge region, and the corresponding aging weight w is edge =1+0.3·edge detection(I) , weaken the aging of the highlight area, the corresponding aging weight w highlight =1-0.2·highlight mask(I) .

[0349] In one embodiment, the following color change parameters may be used:

[0350]

[0351] Among them, C0 is the original color value, which can be in the form of [R, G, B]. α is the basic attenuation coefficient, which can be set to a value in the range of 0.2 to 0.8 based on experience or specific business needs to control the overall fading degree. β is the time sensitivity, which can be set to a value in the range of 0.001 to 0.01 based on experience or specific business needs to control the fading rate. t is the simulation duration, which simulates the length of time the album has been collected and placed. γ is a periodic change parameter, such as the periodic change amplitude, which can be set to a value in the range of 0.05 to 0.15 based on experience or specific business needs to simulate the periodic changes in color styles of different eras. ω is a periodic parameter, such as π / 30, is the phase shift, which is used to adjust the color characteristics of different eras. By substituting the simulation duration of the first digital music and the color periodic change parameter and other parameters into formula (52), the color change parameter of the first digital music can be calculated, which can represent the color attenuation.

[0352] In one embodiment, the following material change model may be used:

[0353]

[0354] Among them, M0 is the initial material parameter, such as the initial material state vector [gloss, flatness, texture intensity], k is the aging rate coefficient, which can be set to a value in the range of 0.1 to 0.5 based on experience or specific business needs, t0 is the reference duration (such as 1 year), σ is the first characteristic of the cover material, such as the first characteristic vector [durability, environmental sensitivity, wear coefficient], ρ is the second characteristic of the cover material, such as the second characteristic vector [fiber orientation, surface microstructure, hygroscopicity], δ is the random perturbation coefficient, which can be set to a value in the range of 0.05 to 0.2 based on experience or specific business needs to simulate the uncertainty of natural aging, and λ is the aging saturation coefficient, which can be set to a value in the range of 0.05 to 0.2 based on experience or specific business needs to control the saturation speed of the aging effect. By substituting the characteristics of the cover material of the first digital music, the simulation duration and other parameters into formula (53), the material change parameter of the first digital music can be calculated, which can represent the amount of material aging.

[0355] In one embodiment, the associated image can be transformed from the spatial domain to the frequency domain using a method such as FFT (Fast Fourier Transform), and the frequency domain parameters can be extracted to reconstruct the dot structure of the associated image based on the frequency domain parameters, as shown in the following function:

[0356]

[0357] Among them, the frequency domain parameters include amplitude and frequency, A i is the amplitude, which satisfies the relationship with the analog duration t of the first digital music: A i =A0·(1-0.5·e -0.03t ). f i is the frequency, which can be mapped according to the age characteristics: f i =f0+0.2·sin(t / 10). For phase shift, randomness is introduced to simulate printing unevenness.

[0358] In addition, ink diffusion simulation can be added, such as applying anisotropic diffusion filtering and calculating the ink diffusion coefficient D, as shown below:

[0359] D=D0·(1+0.3·(1-e -0.02t )) (55)

[0360] The printing characteristic parameters may include the dot structure reconstruction parameters P(x, y) and the ink diffusion coefficient D of the associated image. By performing dot structure reconstruction and ink offset simulation on the associated image, the surface visual effect of the simulated real printed object can be achieved.

[0361] The above examples illustrate how to determine the era style parameters, color variation parameters, material variation parameters, and printing characteristic parameters for a first digital music piece. Based on specific business needs and available computing resources, one or more of the above algorithms can be used to calculate one or more of these era style parameters, color variation parameters, material variation parameters, and printing characteristic parameters to obtain the appearance simulation parameters for the first digital music piece, which can then be used to enhance the visual effects of the image associated with the first digital music piece.

[0362] Step S520: determining lighting effect parameters according to the environmental information.

[0363] The environmental information includes information about the actual environment in which the terminal device is currently located, such as lighting information. The terminal device may be configured with an ambient light sensor, etc., to detect the environmental information. The lighting effect parameter represents the effect produced by lighting on the associated image of the first digital music, simulating real-world lighting effects.

[0364] In one embodiment, the lighting effect parameter includes at least one of a lighting reflection parameter and a color tone adjustment parameter. The above-mentioned determination of the lighting effect parameter based on the environmental information includes at least one of the following steps:

[0365] Determine incident light parameters based on environmental information and terminal device posture information, determine specular reflection parameters and diffuse reflection parameters based on the incident light parameters, and weight the specular reflection parameters and diffuse reflection parameters to obtain lighting effect parameters;

[0366] A light intensity parameter is determined according to the environmental information, a light response parameter is determined according to the release time of the first digital music, and a hue adjustment parameter is determined according to the light intensity parameter and the light response parameter.

[0367] For example, the posture information and lighting mapping of the terminal device are performed, such as calculating the incident angle of light:

[0368] θ i =arccos(n·l) (56)

[0369] Where n is the surface normal vector, which can be determined by the posture information of the terminal device, such as obtained by an inertial sensor. l is the light source direction vector, which can be obtained by an ambient light sensor.

[0370] Map the incident angle to calculate the basic lighting value. The mapping function is as follows:

[0371]

[0372] The above formula introduces the age characteristic t to simulate the response differences of materials of different ages to the incident angle.

[0373] Specular reflection simulation can be achieved using the Cook-Torrance model, which is a model used to describe the microsurface BRDF (Bidirectional Reflectance Distribution Function). Refer to the following relationship:

[0374] f r =(D·F·G) / (4·(n·l)·(n·v)) (58)

[0375] Where D is the normal distribution function, which can be related to the age, such as D = D0 (1 + 0.3 (1-e -0.02t )). F is the Fresnel term, G is the geometric occlusion term. According to the basic lighting value f(θ i ) and the specular reflection response value f r , and obtain the specular reflection parameters, expressed in Cook-Torrance.

[0376] Diffuse reflection simulation can be achieved using the Oren-Nayar model, which is a model used to simulate the BRDF of diffuse reflection surfaces. Refer to the following relationship:

[0377]

[0378] A=1-0.5·σ 2 / (σ 2 +0.33), B=0.45·σ 2 / (σ 2 +0.09) (59)

[0379] Where σ is the roughness parameter, which can change with age and satisfy σ=σ0·(1+0.6·(1-e -0.02t )). According to the basic lighting value f(θ i ) and the diffuse reflection response value L to obtain the diffuse reflection parameters, expressed in Oren-Nayar.

[0380] The specular reflection parameters and diffuse reflection parameters are weighted to calculate the lighting effect parameters taking reflection into account, expressed as BRDF:

[0381] BRDF=α·Oren-Nayar+(1-α)·Cook-Torrance

[0382] α=roughness 2 ·(1+0.2·sin(t / 25)) (60)

[0383] This can introduce periodic changes to simulate the characteristics of materials from different eras, and dynamically balance diffuse and specular reflections to achieve realistic age-appropriate material effects.

[0384] Adaptive processing of ambient light can also be performed. The light sensor data is sampled (e.g., at 10 Hz) to obtain the light intensity parameter lux. The light response parameter is determined based on the release time t of the first digital music. The two are combined to obtain the light intensity mapping value:

[0385] I=(lux-minLux) / (maxLux-minLux)·(1+0.1·sin(t / 30))(61)

[0386] Able to simulate the differences in how materials from different eras respond to ambient light.

[0387] Calculate the adaptive threshold:

[0388] T low =0.2·(1-0.3·e -0.02t ), T high =0.8·(1-0.2·e -0.01t ) (62)

[0389] In this way, the response threshold is adjusted according to the characteristics of the era, making the older albums more sensitive to light changes.

[0390] The tone adjustment parameters are determined based on the light intensity mapping value I and the release time t, which may include one or more of the exposure value, the brightness range compression parameter, and the gamma correction value. For details, refer to the following formula:

[0391] ev=ev0·(1+k·I)·(1+0.2·(1-e -0.01t )) (63)

[0392] Formula (63) is used to calculate the exposure value, k is the response coefficient, which can be a value in the range of 0.5 to 1.5, and ev0 is the basic exposure value.

[0393] L′=L / 1+L·(1+0.3·(1-e -0.02t )) (64)

[0394] Formula (64) is used to calculate the brightness range compression parameter, which can make the compression of old albums stronger and simulate the limited dynamic range characteristics of old photos.

[0395] γ=2.2·(1-0.4·I)·(1+0.3·(1-e -0.015t )) (65)

[0396] Formula (65) is used to calculate the gamma correction value, which can dynamically adjust the gamma value based on the ambient light intensity and age characteristics.

[0397] Furthermore, advanced optical effects can be simulated, such as improved Fresnel reflections:

[0398] R(θ)=R0+(1-R)(1-cos(θ)) 5 ·(1+k·S(1+0.3·(1-e -0.02t )) (66)

[0399] Among them, R0 is the normal reflectivity, which is related to the material and age, and can satisfy R0=R base (1-0.4·(1-e -0.01t S is the material characteristic factor, ranging from 0.1 to 0.9, determined by the album material type. k is the environmental adjustment coefficient, dynamically adjusted based on ambient light intensity: k = 0.5 + 0.5·I. t is the simulation duration, which affects the intensity and characteristics of the Fresnel effect. This results in older albums having stronger diffuse reflection characteristics and a weaker Fresnel effect.

[0400] Through the above calculations, the lighting effect parameters are obtained. For example, the lighting effect parameters may include one or more parameters of the basic lighting value, BRDF, light intensity mapping value, adaptive threshold, exposure value, brightness range compression parameter, gamma correction value, and Fresnel reflection value.

[0401] Step S530: Process the associated image of the first digital music based on the appearance simulation parameter and the lighting effect parameter, and display the processed associated image.

[0402] The associated images displayed in this way can simulate the material of the physical album cover and reflect the lighting effects in the environment, which enhances the authenticity of the display effect and brings visual immersion to the target users.

[0403] In one embodiment, the associated image of the first digital music can be divided into multiple layers and the display effects can be processed separately to better simulate the physical album cover. For example, the associated image can be divided into a base layer, a texture layer, and a microstructure layer, and processed in each layer.

[0404] For the base layer, the color space is converted from RGB to CIELAB, and the tone mapping function is used to perform era-specific color mapping:

[0405] L′=L^γ·(1+0.2·sin(t / 15)) (67)

[0406] Where γ is the age-related parameter, which satisfies γ=1.0+0.3·(1-ed 0.01t ).

[0407] The color separation algorithm is used to simulate the color registration error of printing in different eras, where the misalignment Δ=0.5+1.5·(1-e -0.02t ) and applied to the CMYK color separation channels to simulate printing registration shift.

[0408] Regarding the texture layer, multiple layers of Perlin noise are generated, including:

[0409] Basic noise N1: frequency f_1 = 0.1 + 0.1·t / 70, amplitude a1 = 0.9 - 0.4·e -0.01t ;

[0410] Detail noise N2: frequency f_2 = 0.5 + 0.3·t / 70, amplitude a2 = 0.5 - 0.3·e -0.02t ;

[0411] Microscopic noise N3: frequency f_3 = 2.0, amplitude a3 = 0.2-0.3·e -0.03t ;

[0412] Using the superposition algorithm:

[0413] N=N1+0.5·N2+0.25·N3 (68)

[0414] Add the above noise to the texture layer. And anisotropic filtering can be used, where the filter kernel K(θ)=G(x,y,σ x ,σ y ,θ), to simulate the fiber directionality, let σ x / σ y =1+2· (1-e -0.01t ), in order to simulate the fiber direction of paper of different ages, θ=θ0+0.2·sin(t / 20).

[0415] Regarding the microstructure layer, construct the height field H(x,y):

[0416] H(x,y)=h0·N(x,y)+h1·W(x,y) (69)

[0417] Where h0 is the base height, which varies with age and can be a value in the range of 0.5 to 2.0. N(x,y) is the noise field, and W(x,y) is the wear map. Further calculation of the displacement map:

[0418] D(x,y)=Dmax · H(x,y)·(1-0.5·e -0.02t ) (70)

[0419] Among them, D max is the maximum displacement, which can be 1 to 5 pixels.

[0420] The normal map is generated by the following formula:

[0421]

[0422] Among them, k t is the age correlation coefficient, which can satisfy k t =1.0+2.0·(1-e -0.015t ).

[0423] In order to simulate the wear and scratch effects, a Voronoi diagram can be generated, where S(x,y) simulates cracks and the scratch density d s =d0·(1-e -0.025t ), scratch depth h s =h0·(1-e -0.02t ).

[0424] In one embodiment, the image associated with the first digital music may be subjected to physical parameterization processing to enhance its visual display effect. For example, the surface roughness may be calculated as follows:

[0425] m=m0+0.8·(1-e -0.02t ) (72)

[0426] Here, m0 is the initial roughness, which can be a value in the range of 0.01 to 0.1, depending on the original material of the album of the first digital music.

[0427] The diffuse reflectance of a surface can be calculated:

[0428] kd=0.2+0.6·m·(1+0.1·sin(t / 25)) (73)

[0429] This can introduce periodic changes to simulate the characteristics of printing processes in different eras.

[0430] Anisotropic roughness can be calculated:

[0431] m x =m·(1+0.3·sin(t / 20)),m y =m·(1-0.3·sin(t / 20)) (74)

[0432] This can simulate the differences in fiber orientation of paper from different ages.

[0433] It can achieve realistic micro-geometry effects, such as sampling height fields to generate displacement vectors:

[0434] d(x,y)=d max ·H(x,y)·(1-0.5·e -0.02t ) (75)

[0435] Among them, d max The maximum displacement can be a value in the range of 0.5 to 2.0, which varies with the material type.

[0436] The normals are calculated as follows:

[0437]

[0438] Among them, k x ,k y is the directivity coefficient, which simulates the fiber direction and can satisfy k x =1+0.5·sin(t / 30).

[0439] The decay of the degree of concavity over time can be calculated:

[0440] d′=d·(e -0.05t +0.2·(1-e -0.01t )·N(x,y)) (77)

[0441] This allows for a combination of deterministic decay and random noise to simulate the natural aging process.

[0442] The microsurface distribution function can be calculated:

[0443] D(h)=(α 2 / π·(n·h 2 ·(α 2 -1)+1) 2 (78)

[0444] Where α is the roughness parameter, α=α0·(1+0.5·(1-e -0.02t )).

[0445] The material density ρ can be calculated, which varies with age and has the following relationship:

[0446] ρ=ρ0·(1-0.3·(1-e -0.01t )) (79)

[0447] Where ρ0 is the initial density, which depends on the original material of the album.

[0448] The scattering coefficient can be calculated:

[0449] σs=ρ·ks·(1+0.2·sin(t / 25)) (80)

[0450] Among them, ks is the intrinsic scattering coefficient of the material, which can be a value in the range of 0.3 to 0.8.

[0451] The absorption coefficient can be calculated:

[0452] σa=ρ·ka·(1+0.1·(1-e -0.03t )) (81)

[0453] Among them, ka is the intrinsic absorption coefficient of the material, which can be a value in the range of 0.1 to 0.5.

[0454] Subsurface scattering parameters can be calculated:

[0455] S=S0·(1-0.4·e -0.01t ) (82)

[0456] Wherein, S0 is the initial subsurface scattering intensity, which can be a value in the range of 0.1 to 0.5.

[0457] Apply one or more of the above calculation results to the associated image of the first digital music, optimize the pixel values, positions, etc. in the associated image, and display the associated graphics based on the optimized values to improve its display effect.

[0458] In one embodiment, the music interaction processing method further includes the following steps:

[0459] In response to detecting that the target user has obtained preset authority for at least one first digital music and the performance of the terminal device meets the preset requirements, an operation entry for triggering the first display instruction or the second display instruction is provided.

[0460] The operation portal is used to trigger the display of the second preset interface or the associated image of the first digital music using the first interaction strategy. Providing this operation portal requires that the target user has obtained preset permissions for at least one first digital music and that the terminal device's performance meets preset requirements. This ensures that the target user has sufficient permissions to receive services under the first interaction strategy, including services that display the second preset interface and services that display associated images that have undergone visual enhancement processing. Preset requirements are used to measure whether the terminal device's performance is sufficient to provide the aforementioned visual-related services, and may include requirements regarding display performance, graphics processing performance, etc.

[0461] Figure 6A schematic process for providing an operation entry is shown, including: step S610, obtaining the target user's information and the terminal device's information; step S620, detecting whether the target user has purchased digital music, if not, executing step S630, and if so, executing step S640; step S630, hiding the operation entry; step S640, detecting whether the performance of the terminal device meets the preset requirements, if not, executing step S630, and if so, executing step S650; step S650, providing the operation entry.

[0462] In one embodiment, the first interaction instruction includes the first interaction instruction of the target user after obtaining the preset authority of the first digital music. Figure 7 As shown, the above-mentioned processing of the first interaction instruction between the target user and the first digital music based on the first interaction strategy includes the following steps S710 to S730:

[0463] Step S710: determining a target unpacking method according to information of the first digital music.

[0464] Among them, after the target user obtains the preset permission of the first digital music, unblocking can be performed during the first interaction process to indicate that the first digital music is converted from an unblocked state to an unblocked state, thereby increasing the target user's sense of ceremony and gain.

[0465] A target unblocking method can be determined from a plurality of unblocking methods based on the information of the first digital music, so that the target unblocking method is suitable for the style of the first digital music. In one embodiment, the above-mentioned determination of the target unblocking method based on the information of the first digital music includes the following steps:

[0466] determining a category of the first digital music according to information of the first digital music;

[0467] The decryption method corresponding to the category of the first digital music is used as the target decryption method.

[0468] Exemplary categories of digital music include, but are not limited to, pop, dance, rock, electronic, classical, jazz, folk, country, rap, heavy metal, etc. A feature vector of the first digital music may be constructed based on the rhythm, harmonic complexity, and emotional characteristics of the first digital music; similarities are calculated between the feature vector of the first digital music and benchmark feature vectors of various categories, and the category of the first digital music is determined based on the similarities.

[0469] For example, the rhythm of the first digital music includes two parameters: BPM value and rhythm density value RD. Wavelet transform can be performed on the audio signal of the first digital music to extract the BPM value and RD. Among them, BPM can be calculated by the autocorrelation function:

[0470] R(τ)=Σ(x(t)·x(t+τ)) (83)

[0471] The peak position can be selected to determine the period. Calculate RD = (number of drum beats / time period) by energy envelope detection. And the following normalization processing can be performed:

[0472] BPM'=min(1.0,BPM / 180), RD'=min(1.0,RD / 4) (84)

[0473] The spectral characteristics of the audio can be obtained through wavelet transform, and the harmonic complexity HC can be calculated:

[0474] HC=0.5·chord change frequency+0.5·(dissonance / maximum dissonance) (85)

[0475] Here, chord change frequency = number of chord changes per unit time / base change rate (4 times / minute). Dissonance can be calculated using inter-peak interference: D = Σ(fi - fj)^2·A(fi)·A(fj), where f is frequency and A is amplitude.

[0476] Based on the Russell sentiment model, we can calculate the two dimensions of energy (E) and valence (V). Energy (E) can be calculated using RMS energy and spectral flatness: E = 0.7·RMS energy + 0.3·spectral flatness. Valence (V) can be calculated using tonality analysis: V = -0.8·(minor key probability) + 0.8·(major key probability) + 0.4·(high frequency energy ratio). This then forms the sentiment feature, represented as a vector: EV = (E, V), with values ranging from -1 to 1.

[0477] Construct the feature vector of the first digital music: MV = [BPM', RD', HC, E, V]. And calculate the similarity with the benchmark feature vectors of each category. For example, the system can preset the benchmark feature vectors of 5 categories as follows:

[0478] Pop / Dance category, baseline feature vector MP = [0.7, 0.6, 0.4, 0.8, 0.6] (high tempo, medium harmonic complexity, high energy, positive valence);

[0479] Rock / Electronic category, baseline feature vector MR = [0.8, 0.8, 0.5, 0.9, 0.2] (high tempo, medium-high harmonic complexity, high energy, neutral emotional valence);

[0480] Classical / Jazz category, baseline feature vector MC = [0.4, 0.3, 0.8, 0.5, 0.7] (low tempo, high harmonic complexity, medium energy, positive valence);

[0481] Folk / country category, baseline feature vector MF = [0.5, 0.4, 0.5, 0.4, 0.8] (medium tempo, medium harmonic complexity, medium-low energy, high positive valence);

[0482] For the rap / heavy metal category, the baseline feature vector MH = [0.6, 0.7, 0.6, 0.9, -0.4] (medium-high tempo, medium-high harmonic complexity, high energy, negative valence).

[0483] The distance between the feature vector of the first digital music and each reference feature vector can be calculated using a weighted Euclidean distance or other method to indirectly represent the similarity. The distance calculation formula is as follows:

[0484]

[0485] Among them, the weights corresponding to different dimensions in the features can be w = [0.25, 0.15, 0.2, 0.2, 0.2], giving the rhythm feature a relatively higher weight. The larger the calculated distance, the less similar the feature vector is to the benchmark feature vector. "1-distance" can be used as the similarity. The category with the smallest distance can be selected as the category of the first digital music. If the feature vector of the first digital music has a high similarity to the benchmark feature vectors of multiple categories (such as the distance is less than 0.15), the category of the first digital music can be determined based on multiple categories, such as determining that the first digital music is a mixed category of multiple categories.

[0486] Each category can correspond to a specific unblocking method. For example: the pop / dance category corresponds to the horizontal sliding unblocking method (corresponding to intuitive and smooth listening); the rock / electronic category corresponds to the pressure unblocking method (corresponding to strong and powerful music characteristics); the classical / jazz category corresponds to the rotation unblocking method (corresponding to delicate and complex music structure); the folk / country category corresponds to the oblique sliding unblocking method (corresponding to friendly and natural music characteristics); the rap / heavy metal category corresponds to the multi-point pressure unblocking method (corresponding to complex rhythm and strength contrast). If the category of the first digital music is a mixed category, the parameters of multiple unblocking methods can be fused according to the mixing coefficient α. Exemplarily, the mixing coefficient reference is as follows:

[0487] α=D(MV,M1) / (D(MV,M1)+D(MV,M2)) (87)

[0488] Parameters of decapsulation methods corresponding to the multiple categories are mixed according to the mixing coefficient, and a target decapsulation method is determined according to the mixed parameters.

[0489] Step S720: In response to the first interaction instruction, display unblocking guidance information; the unblocking guidance information is used to guide the target user to perform an unblocking operation.

[0490] Among them, the first interaction instruction can be an instruction triggered by any interactive operation performed by the target user after obtaining the preset permission of the first digital music (such as purchasing the first digital music), such as an instruction to play the first digital music, an instruction to click to view the detailed information of the first digital music, an instruction to enter the second preset interface to view the first digital music, etc.

[0491] The unblocking guidance information is used to guide the target user to perform the unblocking operation according to the target unblocking method, including but not limited to text guidance information, voice guidance information, graphic guidance information, video guidance information, etc.

[0492] Step S730: In response to detecting an unblocking operation corresponding to the target unblocking method, the first digital music is set to an unblocked state, and the first digital music can be played in the unblocked state.

[0493] For example, in step S710, it is determined that the target unblocking method is the horizontal sliding unblocking method, then in response to the first interaction instruction, the unblocking guidance information is displayed, and then it is detected whether the target user has performed a horizontal sliding unblocking operation. If detected, the first digital music is set to the unblocked state, thereby completing the unblocking process.

[0494] In one embodiment, in response to detecting an unblocking operation corresponding to a target unblocking method, setting the first digital music file to an unblocked state includes the following steps:

[0495] Get the operation data of the unblocking operation;

[0496] determining whether the unblocking operation is completed based on the operation data and the emotional characteristics of the first digital music;

[0497] In response to the unsealing operation being completed, the first digital music is set to an unsealed state.

[0498] The unblocking threshold can be determined based on the emotional characteristics of the first digital music. The unblocking threshold represents the threshold corresponding to the unblocking operation, that is, when the unblocking operation reaches this threshold, it indicates that the target user has completed the unblocking operation. Generally, the stronger the emotion of the first digital music, the higher the unblocking threshold. For example, the unblocking threshold can be calculated as follows:

[0499] T=T0·(0.8+0.4·E) (88)

[0500] Among them, E represents energy. The higher E is, the higher the unblocking threshold is.

[0501] You can also adjust the response curve:

[0502] R(x)=x γ (89)

[0503] Where γ = 1.0 + 0.5·|V|. The larger the absolute value of the emotional valence V, the steeper the response curve.

[0504] Calculate the completion rate C of the user's unblocking operation:

[0505] C=min(1.0,p / P0+d / D0+t / T0) (90)

[0506] Where p is the pressure value, d is the movement distance, t is the duration, and P0, D0, and T0 are baseline values. For high-energy music, the pressure weight is increased; for music with high harmonic complexity, the duration weight is increased.

[0507] The parameter calculation example is as follows: For the rock style (such as E = 0.9, HC = 0.5), the pressure weight w p =0.5+0.3·E=0.77; For classical style (such as E=0.5, HC=0.8), the time weight w t =0.4+0.4·HC=0.72.

[0508] Through the above methods, the organic integration of music characteristics and unblocking experience is achieved.

[0509] In one embodiment, the system can adjust the interaction parameters based on the emotional characteristics of the music to form a differentiated experience. For example, the target user's operation data is recorded to determine the completion time, operation accuracy, and operation path. Among them, the completion time can be the time interval T from the prompt unblocking to the successful completion. The operation accuracy can be the matching degree between the actual operation trajectory of the target user and the ideal trajectory. The operation path can be a pressure-time curve P(t) or a position-time curve X(t), Y(t). The operation accuracy can be calculated by referring to the following formula:

[0510] M=1-D / D max (91)

[0511] D is the deviation distance.

[0512] Extract features such as velocity, acceleration, and pressure change rate from the operating data, and standardize each feature, such as normalizing it to the [0,1] interval, to facilitate comprehensive analysis.

[0513] Establish an association between music categories and user operation preferences. The target user's operation efficiency and comfort level under various unblocking methods can be calculated to obtain the preference level:

[0514] E i =0.4·(1-T i / T max )+0.3·M i +0.3·F i (92)

[0515] Among them, T i is the completion time, M i is the accuracy, F i It is the operation smoothness (the smoothness of acceleration changes).

[0516] Establish a category-preference mapping matrix PM[5×5], that is, matrix the preference scores of the five categories and the five unblocking methods, and update the matrix after each unblocking operation:

[0517] PM[i,j]=(1-λ)·PM[i,j]+λ·E j (93)

[0518] Where λ is the learning rate, which can be set to a value in the range of 0.1 to 0.3 based on experience or specific business requirements. i is the music style index, and j is the unblocking method index.

[0519] This generates a personalized unblocking method. For example, based on the PM matrix, the category of the first digital music is used as input, and the unblocking method with the highest score in the corresponding row of the matrix is selected and recommended to the target user as the target unblocking method. This can improve the target user's unblocking experience.

[0520] In one embodiment, preference analysis can be performed on the target user's unblocking operation to update relevant information. For example, a preference analysis update is performed every 10 unblocking operations, and a moving weighted average is used to detect the trend of user preference changes:

[0521] P'[i,j]=Σ(w t PM t [i,j]) / Σ(w t ) (94)

[0522] Among them, t is the time index, w t The time weighting is used. Unblocking parameters can be adaptively and dynamically adjusted based on preference trends. For example, if preference for a particular unblocking method continues to increase, its difficulty can be reduced by 10-20%. If preference for a particular unblocking method continues to decrease, the system proactively provides guidance for that method. For new users, a general parameter with a 30% difficulty reduction is used to quickly establish a preference model and achieve cold start optimization.

[0523] In one embodiment, when the first digital music is set to an unblocked state, a corresponding unblocking animation is displayed according to the music style and emotional characteristics of the first digital music.

[0524] The unblocking animation may include an animation of the cover of the first digital music, etc. The unblocking animation is determined and displayed according to the music style and emotional characteristics of the first digital music, so that the unblocking animation adapts to the characteristics of the first digital music and increases the immersion of the target user.

[0525] For example, the system can map the musical style and emotional characteristics (energy, emotional valence, tension) of the first digital music to animation parameters. For example, high-energy music (such as rock): use a fast, explosive expansion animation with an animation duration of 0.5-0.8 seconds; soothing music (such as folk): use a slow, smooth expansion animation with an animation duration of 1.2-1.8 seconds. After the target user completes the unblocking operation, the system selects a preset animation template based on the musical style and emotional characteristics of the first digital music, and adjusts the animation parameters (such as speed, amplitude, color change) to present a cover expansion effect that matches the music style of the unblocking animation that matches the first digital music.

[0526] Different textures can be simulated based on the vibration waveform of the Bézier curve. Texture mapping rules may include: selecting different Bézier curve control points according to the album type (vinyl / CD / tape). For example, vinyl records: use the third-order Bézier curve of P1 (0.2, 0.1), P2 (0.4, 0.8), and P3 (0.8, 0.3) to generate a vibration waveform with a micro-granular feel, and the vibration duration is 300-400ms; CD records: use the third-order Bézier curve of P1 (0.1, 0.2), P2 (0.5, 0.9), and P3 (0.9, 0.1) to generate a smooth transition vibration waveform, and the vibration duration is 200-250ms. After the target user completes the unpacking operation, the system selects the corresponding Bézier curve parameters according to the album type, controls the vibration motor to generate tactile feedback of a specific waveform, and simulates the physical texture of the physical album.

[0527] In addition, an unpacking sound effect may be played, which may match the characteristics of the first digital music and may last for 2 to 3 seconds.

[0528] In one embodiment, interactive feedback can be provided based on the target user's interaction with the first digital music. For example, pressure-graded feedback can be used. The system collects pressure values P(t) at a frequency of 120 Hz, records the touch start time t0 and the current time t, calculates the duration Δt = t-t0, and performs signal smoothing, such as using a weighted moving average filter to eliminate noise, as shown in the following formula:

[0529]

[0530] Among them, the weight w i=(n - i) / Σ(n - j), which assigns higher weights to recent samples. Here, n is the window size and is a value within the range of 3 to 5.

[0531] Detect key feature points in the pressure curve, such as local maximum points (which can be marked when P(t) > P(t - 1) and P(t) > P(t + 1)), pressure threshold crossing points (marked when P(t) < P_th and P(t + 1) ≥ P th ), and stable interval points (marked when |P(t) - P(t - 1)| < ε continuously exceeds τ time). Extract pressure-time composite features. For example, first construct a basic feature vector F = [P max , P avg , T total , dP / dt max , dP / dt avg , P var , T stable . Among them, P max is the maximum pressure value, P avg is the average pressure value, T total is the total duration, dP / dt max is the maximum pressure change rate, dP / dt avg is the average pressure change rate, P var is the variance of pressure values, T stable is the stable pressure duration. Normalize each feature to the [0, 1] interval. The normalization method is as follows:

[0532] F' i =(F i - F i,min ) / (F i,max - F i,min ) (96)

[0533] Assign different weights to time features according to different operation types for time feature weighting. For example, for a light press operation: the weight of the time feature is reduced (×0.7), and the weight of the pressure peak feature is increased (×1.3). For a long press operation: the weight of the duration feature is increased (×1.5), and the weight of the pressure change rate feature is reduced (×0.6).

[0534] Extract sequence pattern features, such as calculating the similarity between the pressure-time curve and a preset template. The reference is as follows:

[0535] S = exp(-D 2 / σ 2 ) (97)

[0536] Among them, D is the Euclidean distance between the feature vector and the template vector, and σ is the scaling factor.

[0537] The system can preset a mode library of five basic operation modes. For example, the light press mode: low pressure (0.2 - 0.4), short time (0.1 - 0.3s), P var is small. The heavy press mode: high pressure (0.7 - 0.9), medium time (0.2 - 0.5s), dP / dt max is large. The progressive press mode: the pressure gradually changes from low to high, T total is long (0.5 - 1.0s). The stable press mode: medium pressure (0.4 - 0.6), long time (>0.8s), P var is extremely small. The rhythm press mode: multiple pressure peaks, specific time intervals, suitable for music rhythm matching. By using the weighted nearest neighbor and threshold determination method, identify the operation mode of the target user's interaction with the first digital music. For example, for the input feature vector F, calculate the weighted distance from each mode template M i :

[0538]

[0539] Determine the mode corresponding to the interaction operation as the mode with the highest matching degree and D i < D_threshold. Combine the interface state and the user operation history for verification, improve the matching priority of the corresponding mode according to the expected operation type of the current interface, and adjust the mode matching threshold (±15%) according to the user's historical operation habits.

[0540] Perform accidental touch protection on the target user's interaction operation. Specifically, for the interaction operation, calculate the deliberateness of the operation:

[0541] I = P max ·T total ·(1 + α·dP / dt avg ) (99)

[0542] where, when I > I threshold , it is determined as an intentional operation, and dynamically adjust I threshold .

[0543] When dealing with boundary situations between two modes, when the difference between the two modes with the highest matching degrees < 0.2, the system will mix the effects of the two modes according to the weights, and the mixing coefficient is as follows:

[0544] β = D2 / (D1 + D2) (100)

[0545] D1 and D2 are the distances of the two modes.

[0546] For target users' interactive operations, provide progressive feedback as the operation progresses to reduce the impact of misjudgment. For example, provide mild feedback at the beginning of the operation (0-30%), moderate feedback at the middle of the operation (30-70%), and complete feedback at the completion of the operation (70-100%).

[0547] Adaptively calibrate the target user's interactive operations. For example, the system records the statistical distribution of the target user's operational characteristics and regularly updates the model template. For example, it retains the target user's recent 100 operational data and updates the personalized model parameters. The matching threshold is increased for scenarios requiring high operational accuracy, and lowered for scenarios requiring low accuracy.

[0548] A pressure mapping function can be used for interactive feedback, where:

[0549] Vibration frequency = basic frequency + pressure coefficient * pressure value

[0550] Vibration duration = base time + 20 * pressure level (101)

[0551] Light pressure: slight vibration feedback (40Hz, lasting 100ms); Medium pressure: medium vibration feedback (60Hz, lasting 200ms); Heavy pressure: strong vibration feedback (80Hz, lasting 300ms).

[0552] It can memorize and tag the target user's interaction process. For example, it can tag data structures such as ID, timestamp, type, content, and related information. It can also tag text, images, locations, time points, and other data. It also provides organization and retrieval functions.

[0553] In one embodiment, the music interaction processing method further includes:

[0554] The comprehensive value of the First Digital Music is determined based on its circulation, collection duration, and artistic rating.

[0555] For example, the following formula is used to calculate the comprehensive value:

[0556] V=k1·log(1 / N)+k2·T+k3·A (102)

[0557] Among them, N is the circulation volume, T is the collection time (days), A is the artistic score, k1, k2, and k3 are weight coefficients, which can be set according to experience or specific business needs and can satisfy k1+k2+k3=1.

[0558] After determining the comprehensive value of the first digital music, the comprehensive value can be displayed and the first digital music can be sorted according to the comprehensive value, thereby increasing the target user's willingness and sense of achievement in collecting the first digital music.

[0559] Exemplary devices

[0560] The following is an explanation of the music interaction processing device in the embodiment of the present disclosure. Figure 8 As shown, the music interaction processing device 800 may include the following modules:

[0561] The first digital music determining module 810 is configured to determine the first digital music that the target user has preset authority;

[0562] A first interaction processing module 820 is configured to process a first interaction instruction between the target user and the first digital music based on a first interaction strategy;

[0563] The second interaction processing module 830 is configured to process a second interaction instruction between the target user and the second digital music for which the target user does not have preset authority based on a second interaction strategy; the first interaction strategy is different from the second interaction strategy.

[0564] In one embodiment, the first interaction strategy includes response control information; processing the first interaction instruction between the target user and the first digital music based on the first interaction strategy includes: determining the response control information based on the historical interaction information of the target user; and responding to the first interaction instruction between the target user and the first digital music based on the response control information.

[0565] In one embodiment, the response control information includes a first response sensitivity parameter; determining the response control information based on the historical interaction information of the target user includes: determining at least one of the target user's preferred operation type, preferred operation intensity, and preferred frequency pattern based on the target user's historical interaction information; determining the first response sensitivity parameter based on at least one of the target user's preferred operation type, preferred operation intensity, and preferred frequency pattern.

[0566] In one embodiment, the response control information includes a first interactive response mode; the determining of the response control information based on the historical interaction information of the target user includes: determining at least one of the target user's browsing depth, operation speed, operation repetition, and function usage rate based on the target user's historical interaction information; determining the first interactive response mode based on at least one of the target user's browsing depth, operation speed, operation repetition, and function usage rate.

[0567] In one embodiment, the processing of the first interaction instruction between the target user and the first digital music based on the first interaction strategy includes: during the interaction between the target user and the first digital music, obtaining posture information of the terminal device, and executing the corresponding first control instruction according to the posture information.

[0568] In one embodiment, the acquiring of the posture information of the terminal device includes: using a state equation and determining a state value of the posture of the terminal device at the current moment based on a process noise covariance matrix; using an observation equation and determining an update value regarding the state value based on an observation noise covariance matrix; and updating the state value based on the update value to obtain the posture information of the terminal device at the current moment.

[0569] In one embodiment, the acquiring of the posture information of the terminal device further includes: determining a process noise covariance matrix at a current moment according to a current acceleration of the terminal device.

[0570] In one embodiment, the acquiring of the posture information of the terminal device further includes: determining an observation noise covariance matrix according to a credibility evaluation value of an inertial sensor of the terminal device for measuring the posture information.

[0571] In one embodiment, the state equation is used to determine the state value of the posture of the terminal device at the current moment based on the process noise covariance matrix, including: using a state equation with an expanded correction term and determining the state value of the posture of the terminal device at the current moment based on the process noise covariance matrix.

[0572] In one embodiment, the first control instruction includes a display perspective control instruction; executing the corresponding first control instruction according to the posture information includes: determining the display perspective control instruction according to the posture information; and controlling the display effect of the first preset interface associated with the first digital music according to the display perspective control instruction.

[0573] In one embodiment, the processing of the first interaction instruction between the target user and the first digital music based on the first interaction strategy includes: determining the current usage scenario of the target user, and controlling the interactive elements in the first preset interface associated with the first digital music according to the current usage scenario; the interactive elements are used to trigger the first interaction instruction.

[0574] In one embodiment, the device is further configured to: determine a music interaction index of the target user; and determine the first interaction strategy based on the music interaction index.

[0575] In one embodiment, determining the music interaction index of the target user includes: obtaining the playback index, time investment index, and social interaction index of the target user; and weighting the playback index, time investment index, and social interaction index of the target user to obtain the music interaction index of the target user.

[0576] In one embodiment, weighting the target user's playback index, time investment index, and social interaction index to obtain the target user's music interaction index includes: determining a first weight parameter according to the type of the target user, the first weight parameter including weights corresponding to the playback index, time investment index, and social interaction index, respectively; weighting the target user's playback index, time investment index, and social interaction index based on the first weight parameter to obtain the target user's music interaction index.

[0577] In one embodiment, the weighting of the target user's playback index, time investment index, and social interaction index to obtain the target user's music interaction index also includes: updating the first weight parameter in at least one of the following ways to weight the target user's playback index, time investment index, and social interaction index based on the updated first weight parameter: updating the first weight parameter according to the target user's playback behavior preference parameters, time investment preference parameters, and social behavior preference parameters; updating the first weight parameter according to the target user's usage scenario; updating the first weight parameter according to the target user's usage feedback index.

[0578] In one embodiment, the apparatus is further configured to: determine the first interaction strategy according to the performance of the terminal device.

[0579] In one embodiment, determining the first interaction strategy based on the performance of the terminal device includes: if the performance of the terminal device belongs to the first performance level, determining the first interaction strategy includes: using a first pressure detection parameter to detect pressure operation; if the performance of the terminal device belongs to the second performance level, determining the first interaction strategy includes: using a second pressure detection parameter to detect pressure operation; the second pressure detection parameter is greater than the first pressure detection parameter.

[0580] In one embodiment, determining the first interaction strategy based on the performance of the terminal device includes: if the performance of the terminal device belongs to the first performance level, determining that the first interaction strategy includes: using a fixed vibration frequency to present a vibration effect; if the performance of the terminal device belongs to the second performance level, determining that the first interaction strategy includes: using a dynamic vibration frequency to present a vibration effect.

[0581] In one embodiment, determining the first interaction strategy based on the performance of the terminal device includes: if the performance of the terminal device belongs to the first performance level, determining that the first interaction strategy includes: using basic tactile feedback parameters to present the touch effect; if the performance of the terminal device belongs to the second performance level, determining that the first interaction strategy includes: using material simulation tactile feedback parameters to present the touch effect.

[0582] In one embodiment, determining the first interaction strategy based on the performance of the terminal device includes: if the performance of the terminal device belongs to the first performance level, determining that the first interaction strategy includes: using stereo field parameters to play the first digital music; if the performance of the terminal device belongs to the second performance level, determining that the first interaction strategy includes: using spatial sound field parameters to play the first digital music.

[0583] In one embodiment, determining the first interaction strategy based on the performance of the terminal device includes: if the performance of the terminal device belongs to the first performance level, determining that the first interaction strategy includes: using first visual rendering parameters to produce a display effect; if the performance of the terminal device belongs to the second performance level, determining that the first interaction strategy includes: using second visual rendering parameters to produce a display effect; the second visual rendering parameters are greater than the first visual rendering parameters.

[0584] In one embodiment, the processing of the first interaction instruction between the target user and the first digital music based on the first interaction strategy includes: determining the number of operation points in the first interaction instruction; if the number of operation points is greater than or equal to K1, executing the control instructions corresponding to K1 operation points; if the number of operation points is greater than or equal to K2 and less than K1, executing the control instructions corresponding to K2 operation points; if the number of operation points is less than K2, executing the control instructions corresponding to K3 operation points; wherein, K1>K2>K3.

[0585] In one embodiment, the first interaction instruction includes a first display instruction; the processing of the first interaction instruction between the target user and the first digital music based on the first interaction strategy includes: displaying a second preset interface in response to the first display instruction, and displaying the icon of the first digital music at a corresponding position in the second preset interface according to the information of the first digital music.

[0586] In one embodiment, a music collection space is provided in the second preset interface; displaying the icon of the first digital music at a corresponding position in the second preset interface according to the information of the first digital music includes: determining an X-axis coordinate according to the collection duration, music index information, and emotional characteristics of the first digital music; determining a Y-axis coordinate according to the collection duration, music index information, and music style of the first digital music; determining a Z-axis coordinate according to the music genre factor, rarity, audio characteristics, and matching degree with the music style preference of the target user of the first digital music; and displaying the icon of the first digital music in the music collection space according to the X-axis coordinate, the Y-axis coordinate, and the Z-axis coordinate.

[0587] In one embodiment, the device is further configured to: determine the collection weight of the first digital music based on the collection duration, playback intensity, and interaction coefficient of the first digital music; and control the state of the icon of the first digital music displayed in the second preset interface based on the collection weight.

[0588] In one embodiment, displaying the icon of the first digital music at a corresponding position in the second preset interface according to the information of the first digital music includes:

[0589] According to the behavior data of the target user listening to the first digital music, the first digital music is mapped to a corresponding level, and an icon of the first digital music is displayed in the second preset interface according to the level corresponding to the first digital music.

[0590] In one embodiment, the apparatus is further configured to: determine a parallax parameter based on the posture information of the terminal device and the characteristics of the first digital music; and adjust the position of the icon of the first digital music displayed in the second preset interface based on the parallax parameter.

[0591] In one embodiment, the first interaction instruction includes a second display instruction; the processing of the first interaction instruction between the target user and the first digital music based on the first interaction strategy includes: in response to the second display instruction, displaying an associated image of the first digital music based on information of the first digital music and environmental information.

[0592] In one embodiment, the displaying of the associated image of the first digital music based on the information of the first digital music and the environmental information includes: determining appearance simulation parameters based on the information of the first digital music; determining lighting effect parameters based on the environmental information; processing the associated image of the first digital music based on the appearance simulation parameters and the lighting effect parameters, and displaying the processed associated image.

[0593] In one embodiment, the appearance simulation parameters include at least one of era style parameters, color change parameters, material change parameters, and printing feature parameters. The determining of the appearance simulation parameters based on the information of the first digital music includes at least one of the following steps: obtaining era style characteristics of multiple reference times, and according to the release time of the first digital music, using the era style characteristics of the corresponding reference time as the era style parameter of the first digital music, or fusing the era style characteristics of at least two reference times to obtain the era style parameter of the first digital music; determining the color change parameters of the first digital music according to the simulation duration and color periodic change parameters of the first digital music; determining the material change parameters of the first digital music according to the characteristics of the cover material of the first digital music and the simulation duration of the first digital music; performing Fourier transform on the associated image and determining frequency domain parameters, and determining the printing feature parameters of the first digital music according to the frequency domain parameters and ink diffusion simulation parameters.

[0594] In one embodiment, the lighting effect parameters include at least one of lighting reflection parameters and hue adjustment parameters, and the determining of the lighting effect parameters based on the environmental information includes at least one of the following steps: determining incident light parameters based on the environmental information and posture information of the terminal device, determining specular reflection parameters and diffuse reflection parameters based on the incident light parameters, and weighting the specular reflection parameters and the diffuse reflection parameters to obtain the lighting effect parameters; determining light intensity parameters based on the environmental information, determining light response parameters based on the release time of the first digital music, and determining the hue adjustment parameters based on the light intensity parameters and the light response parameters.

[0595] In one embodiment, the device is further configured to: in response to detecting that the target user has obtained preset permissions for at least one first digital music and the performance of the terminal device meets preset requirements, provide an operation entry for triggering a first display instruction or a second display instruction.

[0596] In one embodiment, the first interaction instruction includes the first interaction instruction of the target user after obtaining the preset permission of the first digital music; the processing of the first interaction instruction between the target user and the first digital music based on the first interaction strategy includes: determining the target unblocking method according to the information of the first digital music; displaying unblocking guidance information in response to the first interaction instruction; the unblocking guidance information is used to guide the target user to perform the unblocking operation; in response to detecting the unblocking operation corresponding to the target unblocking method, setting the first digital music to an unblocked state, and the first digital music can be played in the unblocked state.

[0597] In one embodiment, determining a target unblocking method based on the information of the first digital music includes: determining a category of the first digital music based on the information of the first digital music; and using an unblocking method corresponding to the category of the first digital music as a target unblocking method.

[0598] In one embodiment, determining the category of the first digital music based on the information of the first digital music includes: constructing a feature vector of the first digital music based on the rhythm, harmonic complexity, and emotional characteristics of the first digital music; calculating the similarity between the feature vector of the first digital music and the benchmark feature vectors of each category, and determining the category of the first digital music based on the similarity.

[0599] In one embodiment, in response to detecting an unblocking operation corresponding to the target unblocking method, setting the first digital music to an unblocked state includes: obtaining operation data of the unblocking operation; determining whether the unblocking operation is completed based on the operation data and the emotional characteristics of the first digital music; and in response to the completion of the unblocking operation, setting the first digital music to an unblocked state.

[0600] In one embodiment, when the first digital music is set to an unblocked state, the device is further configured to: display a corresponding unblocking animation according to the music style and emotional characteristics of the first digital music.

[0601] In one embodiment, the device is further configured to determine the comprehensive value of the first digital music based on the circulation volume, collection duration, and artistic rating of the first digital music.

[0602] In one embodiment, the first interaction strategy includes: providing a first audio-visual effect according to the first interaction instruction; the second interaction strategy includes: providing a second audio-visual effect according to the second interaction instruction; and the first audio-visual effect is different from the second audio-visual effect.

[0603] In addition, other specific details of the embodiments of the present disclosure have been described in detail in the embodiments of the above method and will not be repeated here.

[0604] Exemplary Program Products

[0605] The computer program product in the embodiment of the present disclosure is described below. The computer program product includes a computer program, and when the computer program is executed by a processor, the above method of the present disclosure is implemented.

[0606] In one embodiment, a computer program product may be a tangible product, such as a computer-readable storage medium storing a computer program. The computer-readable storage medium may be based on electrical, magnetic, optical, electromagnetic, infrared, or other signals, and includes, but is not limited to, random access memory (RAM), read-only memory (ROM), magnetic tape, floppy disk, flash memory (Flash), hard disk drive (HDD), solid-state drive (SSD), and the like. Exemplarily, the computer program product may be a non-volatile storage medium storing the computer program, such as a read-only memory (ROM) or NAND flash memory.

[0607] In one embodiment, the computer program product may be an intangible product. For example, the computer program product may be a virtual digital product, such as an executable file or installation package containing a computer program.

[0608] The code of the computer program can be written in one or more programming languages. Programming languages include, but are not limited to, C, Java, C++, etc. The program code can be executed entirely on the user computing device, or partially on the user computing device, or as a separate software package, or partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device via any type of network, such as a local area network (LAN), a wide area network (WAN), etc., or can be connected to an external computing device (e.g., via an Internet connection provided by a carrier).

[0609] Computer programs can be carried or transmitted through electrical, magnetic, optical, electromagnetic, infrared and other signals. Electronic devices can convert signals carrying computer programs into digital signals, thereby running the computer programs. When a computer program is run on an electronic device, its code is used to enable the electronic device to execute (more specifically, it can enable the processor of the electronic device to execute) the method steps of various embodiments of the present disclosure, for example: step S210, determining the first digital music for which the target user has preset permissions; step S220, processing the first interaction instruction between the target user and the first digital music based on the first interaction strategy; step S230, processing the second interaction instruction between the target user and the second digital music for which the target user does not have preset permissions based on the second interaction strategy.

[0610] By executing the above steps through a computer program, a first interaction instruction is processed based on a first interaction strategy for a first digital music track for which the target user has preset permissions. A second interaction instruction is processed based on a second interaction strategy for a second digital music track for which the target user does not have preset permissions. This increases the diversity of interaction methods, facilitates the realization of richer interactive functions and effects, and enhances the user experience. Furthermore, it simplifies the interaction processing for some digital music tracks (such as the second digital music track), reducing resource overhead on the terminal device or server.

[0611] Exemplary electronic devices

[0612] The electronic device in the embodiment of the present disclosure is described below. The electronic device includes a processor and a memory, wherein the memory is used to store executable instructions of the processor. The processor is configured to execute the above-mentioned method of the present disclosure by executing the executable instructions.

[0613] refer to Figure 9 An electronic device according to an embodiment of the present disclosure will be exemplified. Figure 9 The electronic device 900 shown is merely an example and should not limit the functions and scope of use of the embodiments of the present disclosure.

[0614] like Figure 9 As shown, electronic device 900 is presented in the form of a general-purpose computing device. Components of electronic device 900 may include, but are not limited to, a processor 910, a memory 920, a bus 930 connecting various system components (including the memory 920 and the processor 910), an I / O (input / output) interface 940, and a network adapter 950.

[0615] Among them, the memory 920 stores program code, and the program code can be executed by the processor 910, so that the processor 910 executes the method steps of the embodiment of the present disclosure, for example: step S210, determining the first digital music for which the target user has preset permissions; step S220, processing the first interaction instruction between the target user and the first digital music based on the first interaction strategy; step S230, processing the second interaction instruction between the target user and the second digital music for which the target user does not have preset permissions based on the second interaction strategy.

[0616] By executing the above steps through processor 910, a first interaction instruction is processed based on a first interaction strategy for a first digital music for which the target user has preset permissions, and a second interaction instruction is processed based on a second interaction strategy for a second digital music for which the target user does not have preset permissions. On the one hand, this increases the diversity of interaction methods, facilitates the realization of rich interactive functions and interactive effects, and enhances the user experience. On the other hand, it can simplify the interaction processing for some digital music (such as the second digital music), reducing the resource overhead of the terminal device or the server.

[0617] The memory 920 may include volatile memory, such as random access memory (RAM) 921 and / or cache unit 922, and may also include non-volatile memory, such as read-only memory (ROM) 923. The memory 920 may also include one or more program modules 924. Such program modules 924 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each of these examples, or some combination thereof, may include an implementation of a network environment. For example, the program modules 924 may include the modules described above.

[0618] The processor 910 may include processing units such as an AP (Application Processor), a modem processor, a GPU (Graphics Processing Unit), an ISP (Image Signal Processor), a controller, an encoder, a decoder, a DSP (Digital Signal Processor), a baseband processor and / or an NPU (Neural-Network Processing Unit).

[0619] The bus 930 is used to connect different parts of the electronic device 900 and may include a data bus, an address bus, a control bus, and the like.

[0620] The electronic device 900 may also communicate with one or more external devices 1000 (eg, a keyboard, a pointing device, a Bluetooth device, etc.), and such communication may be performed through the I / O interface 940 .

[0621] The electronic device 900 can also communicate with one or more networks through the network adapter 950. For example, the network adapter 950 can provide mobile communication solutions such as 3G / 4G / 5G, or wireless communication solutions such as wireless LAN, Bluetooth, near-field communication, etc. The network adapter 950 can communicate with other modules of the electronic device 900 through the bus 930.

[0622] Although not shown in the figure, other hardware and / or software modules may also be set in the electronic device 900, including but not limited to: a display, a microcode, a device driver, a redundant processing unit, an external disk drive array, a RAID (Redundant Arrays of Independent Disks) system, a tape drive, and a data backup storage system.

[0623] It should be noted that although several modules or submodules of the device are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more units / modules described above can be embodied in a single unit / module. Conversely, the features and functions of a single unit / module described above can be further divided and embodied by multiple units / modules.

[0624] Furthermore, although the operations of the disclosed method are described in a particular order in the accompanying drawings, this does not require or imply that the operations must be performed in this particular order, or that all illustrated operations must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps.

[0625] Although the spirit and principles of the present disclosure have been described with reference to several specific embodiments, it should be understood that the present disclosure is not limited to the specific embodiments disclosed, and the division into various aspects does not mean that the features in these aspects cannot be combined to benefit. Such division is only for the convenience of expression. The present disclosure is intended to cover various modifications and equivalent arrangements included in the spirit and scope of the appended claims.

Claims

1. A music interaction processing method, characterized in that: The method comprises: Determining a first digital music with preset permissions for the target user; processing a first interaction instruction between the target user and the first digital music based on a first interaction strategy; A second interaction instruction of the target user and the second digital music for which the target user does not have preset authority is processed based on a second interaction strategy; the first interaction strategy is different from the second interaction strategy.

2. The method according to claim 1, characterized in that The first interaction strategy includes response control information; and processing the first interaction instruction between the target user and the first digital music based on the first interaction strategy includes: determining response control information according to historical interaction information of the target user; The first interactive instruction between the target user and the first digital music is responded to based on the response control information.

3. The method according to claim 2, characterized in that The response control information includes a first response sensitivity parameter; and determining the response control information according to the historical interaction information of the target user includes: Determining at least one of the target user's preferred operation type, preferred operation intensity, and preferred frequency pattern based on the target user's historical interaction information; The first response sensitivity parameter is determined according to at least one of the target user's preferred operation type, preferred operation intensity, and preferred frequency pattern.

4. The method according to claim 2, characterized in that The response control information includes a first interactive response mode; and determining the response control information according to the historical interactive information of the target user includes: Determining at least one of the target user's browsing depth, operation speed, operation repetition, and function usage rate based on the target user's historical interaction information; The first interactive response mode is determined according to at least one of the target user's browsing depth, operation speed, operation repetition, and function usage rate.

5. The method according to claim 1, wherein The processing of the first interaction instruction between the target user and the first digital music based on the first interaction strategy includes: During the interaction between the target user and the first digital music, the posture information of the terminal device is obtained, and the corresponding first control instruction is executed according to the posture information.

6. The method according to claim 5, characterized in that The acquiring of the posture information of the terminal device includes: Determining the state value of the posture of the terminal device at the current moment using a state equation and according to a process noise covariance matrix; Determining an update value for the state value using an observation equation and based on an observation noise covariance matrix; The state value is updated based on the updated value to obtain the posture information of the terminal device at the current moment.

7. The method according to claim 6, characterized in that The acquiring of the posture information of the terminal device further includes: The process noise covariance matrix at the current moment is determined according to the current acceleration of the terminal device.

8. A music interactive processing device, characterized in that: The device comprises: A first digital music determining module is configured to determine a first digital music for which a target user has preset authority; A first interaction processing module is configured to process a first interaction instruction between the target user and the first digital music based on a first interaction strategy; The second interaction processing module is configured to process a second interaction instruction of the target user with a second digital music for which the target user does not have preset authority based on a second interaction strategy; the first interaction strategy is different from the second interaction strategy.

9. A computer program product comprising a computer program, characterized in that When the computer 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: processor; as well as a memory for storing executable instructions of the processor; The processor is configured to perform the method according to any one of claims 1 to 7 by executing the executable instructions.

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