Subwoofer device delay synchronization method and apparatus, device, and storage medium

Abstract

The application relates to the technical field of audio synchronization, and discloses a bass equipment delay synchronization method, device and equipment and a storage medium, which are used for effectively improving the synchronization precision of multi-room bass equipment. The bass equipment delay synchronization method comprises the following steps: acquiring initial delay data of bass sub-equipment in each room; constructing a hierarchical compensation model for the corresponding bass sub-equipment according to the initial delay data; calculating the preliminary compensation time length of each layer of each bass based on the hierarchical compensation model; in the audio playing process, the actual processing delay of each bass sub-equipment is monitored in real time, and a hierarchical delay error feedback is generated; according to the hierarchical delay error feedback, the preliminary compensation time length of each layer of each bass equipment is adjusted to obtain a target compensation time length; and based on the target compensation time length, the audio output time sequence of the multiple bass equipment is coordinated and controlled to realize multi-room synchronization.

Description

Technical Field

[0001] This invention relates to the field of audio synchronization technology, and in particular to a method, apparatus, device, and storage medium for delay synchronization of a subwoofer device. Background Technology

[0002] With the increasing prevalence of smart homes and wireless audio systems, multi-room audio playback is gradually becoming a standard feature of high-end audio systems. Traditional methods often employ the NTP protocol for system-level clock synchronization, achieving device alignment by sending timestamp data. However, subwoofers and other bass units inherently possess additional processing latency due to their unique signal processing paths. When these subwoofers are distributed across multiple rooms and used in combination with other speakers, the desynchronization becomes even more pronounced. Existing synchronization solutions often overlook the differentiated processing logic of subwoofers, lacking targeted processing for them and failing to effectively predict and correct the latency issues caused by these devices. Summary of the Invention

[0003] This invention provides a method, apparatus, device, and storage medium for delay synchronization of subwoofer devices, in order to solve the problem of poor synchronization of subwoofer devices in multi-room audio playback in the prior art.

[0004] The first aspect of this invention provides a method for delay synchronization of subwoofer devices, comprising: acquiring initial delay data of subwoofer sub-devices in each room; adjusting a preset layered compensation model based on the initial delay data to generate a target layered compensation model corresponding to each subwoofer sub-device; calculating the preliminary compensation duration of each subwoofer sub-device at the hardware layer, software processing layer, and transmission layer based on the target layered compensation model; monitoring the actual processing delay of each subwoofer sub-device in real time during audio playback and generating layered delay error feedback; adjusting the preliminary compensation duration of each layer of each subwoofer sub-device based on the layered delay error feedback to obtain a target compensation duration; and coordinating and controlling the audio output timing of multiple subwoofer devices to achieve multi-room synchronization based on the target compensation duration.

[0005] In one feasible implementation, obtaining the initial delay data of each room's subwoofer device includes: sending a test audio signal to each room's subwoofer device; recording the time point at which each subwoofer device receives the test audio signal and generates an initial audio response; and comparing the time point at which the test audio signal is sent with the time point at which each subwoofer device generates an initial audio response to obtain the initial delay data of each room's subwoofer device.

[0006] In one feasible implementation, before obtaining the initial delay data of each room's subwoofer sub-device, the method further includes: constructing a hierarchical compensation model for the subwoofer device, wherein the hierarchical compensation model includes a hardware layer compensation sub-model, a software processing layer compensation sub-model, and a transmission layer compensation sub-model.

[0007] In one feasible implementation, the construction of the hardware layer compensation sub-model includes: collecting hardware delay reference data of different models of subwoofer devices, the data including signal conversion delay, power amplifier response delay and physical transmission delay; generating a hardware delay lookup table based on the mapping relationship between device model and delay data; fitting the correlation function between hardware parameters and delay to form a fixed offset compensation rule.

[0008] In one feasible implementation, the construction of the software processing layer compensation sub-model includes: performing code-level analysis on the audio processing algorithm, marking key processing nodes and their corresponding theoretical clock cycles; simulating multiple feature combinations of input audio data, and statistically analyzing the actual processing delay under each combination; and establishing a multi-dimensional lookup table or neural network prediction model based on the correspondence between feature combinations and delays.

[0009] In one feasible implementation, the construction of the transport layer compensation sub-model includes: deploying test nodes in a typical network environment to measure transmission delay under different bandwidths, packet loss rates, and topologies; extracting network state feature parameters, including round-trip time, jitter variance, and protocol overhead; and training a dynamic prediction model, which takes network state features as input and outputs delay compensation.

[0010] In one feasible implementation, the step of calculating the preliminary compensation duration of each subwoofer sub-device at the hardware layer, software processing layer, and transmission layer based on each target hierarchical compensation model includes: acquiring the current delay-related parameter data of each subwoofer sub-device, inputting the current delay-related parameter data into the corresponding target hierarchical compensation model; using the hierarchical compensation model to calculate the preliminary compensation duration of the hardware layer, software processing layer, and transmission layer respectively; summarizing and verifying the preliminary compensation duration of each layer to ensure that the sum of the compensation durations of each layer meets the overall delay requirements.

[0011] In one feasible implementation, the step of using the hierarchical compensation model to calculate the preliminary compensation duration for the hardware layer, software processing layer, and transmission layer respectively includes: using the hardware layer compensation sub-model to calculate the preliminary compensation duration for the hardware layer based on the current state and historical data of the hardware device; using the software processing layer compensation sub-model to calculate the preliminary compensation duration for the software processing layer based on the complexity of the input audio data and the software operating environment; and using the transmission layer compensation sub-model to calculate the preliminary compensation duration for the transmission layer based on the real-time monitored transmission network conditions.

[0012] In one feasible implementation, the real-time monitoring of the actual processing delay of each subwoofer device and the generation of layered delay error feedback includes: periodically sending monitoring audio signals to each subwoofer device; recording the actual processing delay of each subwoofer device after receiving the monitoring audio signals; and using the actual processing delay for analysis, layering the data according to the hardware layer, software processing layer, and transmission layer to generate layered delay error feedback.

[0013] In one feasible implementation, the step of analyzing the actual processing latency and layering it according to the hardware layer, software processing layer, and transmission layer to generate layered latency error feedback includes: comparing the actual processing latency data with historical latency data to analyze latency change trends; based on the latency change trends and combined with the performance characteristics of the hardware layer, software processing layer, and transmission layer, determining the layered attribution of the actual processing latency; and based on the latency data of each layer after the layered attribution determination, calculating the difference with the expected latency as the layered latency error, and feeding back the error information in a layered manner.

[0014] In one feasible implementation, the preliminary compensation duration of each layer of each subwoofer device is adjusted according to the layered delay error feedback to obtain the target compensation duration. This includes: parsing the layered delay error feedback to extract the delay error values ​​of the hardware layer, software processing layer, and transmission layer; comparing the delay error values ​​of each layer with a preset error threshold to determine whether the compensation duration needs to be adjusted; if the delay error value exceeds the error threshold, the preliminary compensation duration of the corresponding layer is increased or decreased according to the direction and magnitude of the delay error and a preset adjustment rule to obtain the target compensation duration of each layer.

[0015] In one feasible implementation, the step of increasing or decreasing the initial compensation duration of the corresponding layer according to a preset adjustment rule further includes: for the hardware layer, increasing the initial compensation duration if the latency error is positive, and decreasing the initial compensation duration if the latency error is negative; for the software processing layer, determining the specific magnitude of increasing or decreasing the compensation duration based on the characteristics of the software algorithm and historical adjustment data; and for the transmission layer, dynamically adjusting the magnitude of increasing or decreasing the compensation duration in conjunction with real-time monitoring data of network conditions to adapt to changes in network latency.

[0016] A second aspect of the present invention provides a subwoofer device delay synchronization device, comprising: an acquisition module for acquiring initial delay data of subwoofer sub-devices in each room; a generation module for adjusting a preset layered compensation model based on the initial delay data to generate a target layered compensation model corresponding to each subwoofer sub-device; a calculation module for calculating the preliminary compensation duration of each subwoofer sub-device at the hardware layer, software processing layer, and transmission layer based on the target layered compensation model; a processing module for monitoring the actual processing delay of each subwoofer device in real time during audio playback and generating layered delay error feedback; an adjustment module for adjusting the preliminary compensation duration of each layer of each subwoofer device based on the layered delay error feedback to obtain a target compensation duration; and a synchronization module for coordinating and controlling the audio output timing of multiple subwoofer devices to achieve multi-room synchronization based on the target compensation duration.

[0017] In one feasible implementation, the acquisition module is specifically used to: send test audio signals to subwoofer devices in each room; record the time point when each subwoofer device receives the test audio signal and generates an initial audio response; and compare the time point when the test audio signal is sent with the time point when each subwoofer device generates an initial audio response to obtain the initial delay data of each subwoofer device in each room.

[0018] In one feasible implementation, the device further includes: a construction module for constructing a layered compensation model for the subwoofer device, the layered compensation model including a hardware layer compensation sub-model, a software processing layer compensation sub-model, and a transmission layer compensation sub-model.

[0019] In one feasible implementation, the construction module is specifically used to: collect hardware delay reference data of different models of subwoofer devices, the data including signal conversion delay, power amplifier response delay and physical transmission delay; generate a hardware delay comparison table based on the mapping relationship between device model and delay data; fit the correlation function between hardware parameters and delay to form a fixed offset compensation rule.

[0020] In one feasible implementation, the building module is further specifically used for: performing code-level profiling of the audio processing algorithm, marking key processing nodes and their corresponding theoretical clock cycles; simulating multiple feature combinations of input audio data, and statistically analyzing the actual processing delay under each combination; and establishing a multidimensional lookup table or neural network prediction model based on the correspondence between feature combinations and delays.

[0021] In one feasible implementation, the building module is further specifically used for: deploying test nodes in a typical network environment to measure transmission delay under different bandwidths, packet loss rates, and topologies; extracting network state feature parameters, including round-trip time, jitter variance, and protocol overhead; and training a dynamic prediction model, which takes network state features as input and outputs delay compensation.

[0022] In one feasible implementation, the calculation module includes: an input unit for acquiring current delay-related parameter data of each subwoofer device and inputting the current delay-related parameter data into the corresponding target hierarchical compensation model; a calculation unit for using the hierarchical compensation model to calculate the preliminary compensation duration of the hardware layer, software processing layer, and transmission layer respectively; and a verification unit for summarizing and verifying the preliminary compensation duration of each layer to ensure that the sum of the compensation durations of each layer meets the overall delay requirements.

[0023] In one feasible implementation, the computing unit is specifically used to: calculate the initial compensation duration of the hardware layer based on the current state and historical data of the hardware device using the hardware layer compensation sub-model; calculate the initial compensation duration of the software processing layer based on the complexity of the input audio data and the software operating environment using the software processing layer compensation sub-model; and calculate the initial compensation duration of the transmission layer based on the real-time monitored transmission network conditions using the transmission layer compensation sub-model.

[0024] In one feasible implementation, the processing module includes: a sending unit for periodically sending monitoring audio signals to each subwoofer device; a recording unit for recording the actual processing delay of each subwoofer device after receiving the monitoring audio signals; and an analysis unit for analyzing the actual processing delay, dividing it into hardware, software processing, and transmission layers, and generating layered delay error feedback.

[0025] In one feasible implementation, the analysis unit is specifically used to: compare the actual processing delay data with historical delay data to analyze the delay change trend; based on the delay change trend, and combined with the performance characteristics of the hardware layer, software processing layer, and transmission layer, to perform a hierarchical classification judgment on the actual processing delay; based on the delay data of each layer after the hierarchical classification judgment, to calculate the difference with the expected delay as the hierarchical delay error, and to feed back the error information in a hierarchical form.

[0026] In one feasible implementation, the adjustment module includes: an extraction unit, used to analyze the layered delay error feedback and extract the delay error values ​​of the hardware layer, software processing layer, and transmission layer respectively; a judgment unit, used to compare the delay error values ​​of each layer with a preset error threshold to determine whether the compensation duration adjustment is required; and an adjustment unit, used to, if the delay error value exceeds the error threshold, increase or decrease the initial compensation duration of the corresponding layer according to the direction and magnitude of the delay error and a preset adjustment rule to obtain the target compensation duration of each layer.

[0027] In one feasible implementation, the adjustment unit is specifically used to: for the hardware layer, if the delay error is positive, increase the initial compensation duration; if the delay error is negative, decrease the initial compensation duration; for the software processing layer, determine the specific magnitude of the increase or decrease in compensation duration based on the characteristics of the software algorithm and historical adjustment data; for the transmission layer, dynamically adjust the magnitude of the increase or decrease in compensation duration in conjunction with real-time monitoring data of network conditions to adapt to changes in network latency.

[0028] A third aspect of the present invention provides an electronic device, comprising: a memory and at least one processor, wherein the memory stores instructions; the at least one processor invokes the instructions in the memory to cause the electronic device to perform the subwoofer device delay synchronization method described above.

[0029] A fourth aspect of the present invention provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the above-described subwoofer device delay synchronization method.

[0030] The technical solution provided by this invention involves: acquiring initial delay data for each subwoofer device in each room; constructing a layered compensation model for each subwoofer device based on the initial delay data; calculating the preliminary compensation duration for each layer of each subwoofer device based on the layered compensation model; monitoring the actual processing delay of each subwoofer device in real time during audio playback and generating layered delay error feedback; adjusting the preliminary compensation duration for each layer of each subwoofer device based on the layered delay error feedback to obtain target compensation durations; and coordinating and controlling the audio output timing of multiple subwoofer devices to achieve multi-room synchronization based on the target compensation durations. In this embodiment of the invention, by acquiring the initial delay data of each subwoofer device in each room and utilizing the layered compensation model, the preliminary compensation duration for each layer can be accurately calculated. Combined with the real-time monitoring of the layered delay error feedback, the compensation parameters are dynamically adjusted, ultimately achieving high-precision timing synchronization of subwoofer devices in multiple rooms. This effectively reduces audio transmission delay differences, improves the sound field consistency of the multi-room subwoofer system, enhances the user's immersive listening experience, adapts to dynamic delay changes in complex environments, and ensures the stability and synchronization of audio playback. Attached Figure Description

[0031] Figure 1 This is a schematic diagram of one embodiment of the subwoofer device delay synchronization method in the present invention;

[0032] Figure 2 This is a schematic diagram of another embodiment of the subwoofer device delay synchronization method in this invention;

[0033] Figure 3 This is a schematic diagram of one embodiment of the subwoofer device delay synchronization device in the present invention;

[0034] Figure 4 This is a schematic diagram of another embodiment of the subwoofer device delay synchronization device in this invention;

[0035] Figure 5 This is a schematic diagram of one embodiment of the electronic device in this invention. Detailed Implementation

[0036] This invention provides a method, apparatus, device, and storage medium for synchronizing subwoofer devices with time delay, which effectively reduces audio transmission delay differences and achieves high synchronization of subwoofer devices in multiple rooms.

[0037] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” or “having,” and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0038] It is understood that the executing entity of this invention can be a subwoofer device delay synchronization device, or it can be a terminal or a server; no specific limitation is made here. This embodiment of the invention will be described using a server as an example.

[0039] For ease of understanding, the specific process of the embodiments of the present invention is described below. Please refer to [link / reference]. Figure 1 One embodiment of the subwoofer device delay synchronization method in this invention includes:

[0040] 101. Obtain the initial delay data of the subwoofer devices in each room;

[0041] The system can join the local synchronization protocol via UDP broadcast or Multicast networking, enabling all devices to obtain the system timestamp of the master control device and complete local clock correction. The devices include the master control device and multiple subwoofer devices. By detecting PING packets or network frames, the system measures the data transmission delay from the master control device to each subwoofer device and records the device's own decoding buffer delay, DSP processing delay, DAC output delay, etc., to form a complete delay configuration table.

[0042] 102. Based on the initial delay data, adjust the preset hierarchical compensation model to generate the target hierarchical compensation model corresponding to each subwoofer device.

[0043] The latency configuration table is parsed, and the total latency is decomposed into three levels: transport layer latency, hardware processing latency, and software processing latency. For transport layer latency, a network state matrix is ​​established, including dynamic parameters such as PING latency, jitter rate, and packet loss rate of each sub-device. A network transport latency prediction model is fitted using the least squares method, and the weight coefficients are updated in real time. Hardware layer processing latency is adjusted by querying the device feature database. Based on the subwoofer sub-device model identifier, a preset DAC output latency benchmark value, decoding buffer latency curve, and DSP processing latency parameter table are matched. Combined with current temperature sensor data and operating voltage, a linear interpolation algorithm is used to dynamically correct the fixed compensation value. Software processing layer adjustment is achieved by analyzing the metadata characteristics of the audio stream, including parameters such as sampling rate, bit depth, and frequency band energy distribution. The corresponding processing algorithm optimization module is activated, and key parameters such as FFT transform window length and filter order are adaptively configured to establish a nonlinear mapping relationship between audio features and processing latency. After the adjustment of each layer model is completed, a collaborative verification test is performed. Standard test signals are sent to verify whether the actual response latency of each sub-device is within the expected range. Finally, a target hierarchical compensation model containing transport layer dynamic prediction coefficients, hardware layer calibration parameters, and software layer feature mapping table is generated.

[0044] 103. Calculate the initial compensation time of each subwoofer device at the hardware layer, software processing layer, and transmission layer based on the hierarchical compensation model of each target;

[0045] The calculation of hardware-layer compensation duration directly calls the calibration parameters in the model, including the basic DAC output delay, temperature compensation offset, and aging correction coefficient, and obtains the accurate hardware compensation value through weighted summation. The calculation of software processing layer compensation duration adopts a feature-driven dynamic query mechanism. The system analyzes the spectral characteristics of the current audio frame in real time and quickly matches the closest predicted processing delay value through the feature mapping table in the model. For complex audio scenarios, a neural network sub-model is used to estimate the delay at the millisecond level. The calculation of transmission layer compensation duration relies on the network status monitoring module. The network quality indicators of each sub-device are collected every 100ms. After being input into the transmission layer dynamic prediction model, the delay compensation value based on the current network condition is output, and the anti-jitter buffer is automatically added. Finally, the three-layer compensation durations are synthesized according to the sequential superposition principle, and extreme value verification is performed. If the total compensation amount exceeds the preset synchronization tolerance window, the dynamic scaling algorithm is activated to prioritize compressing the transmission layer compensation amount to ensure system stability, forming the final preliminary compensation duration configuration for each subwoofer sub-device.

[0046] 104. During audio playback, monitor the actual processing delay of each subwoofer device in real time and generate layered delay error feedback;

[0047] Each subwoofer integrates a high-precision clock synchronization module and an audio processing timestamp recording unit to ensure that the device can accurately record the arrival timestamp of audio data packets received from the main control device. Monitoring points for key processing nodes are set inside the subwoofer, including but not limited to the start time of audio decoding, the completion time of DSP processing, and the start time of DAC output. Through the timestamp recording of these nodes, the actual time consumed by the device in each processing layer can be calculated. Using the microcontroller or dedicated audio processing chip built into the subwoofer, the recorded timestamp data is analyzed in real time to calculate the actual processing delay of each processing layer and compare it with the expected processing time in the pre-set layered compensation model to obtain the delay error of each layer. To improve the accuracy and real-time performance of the feedback, a periodic reporting mechanism can be adopted, such as per second or per audio frame cycle, to send the calculated layered delay error data to the main control device through a wireless communication module. After receiving the delay error feedback from each subwoofer device, the main control device summarizes and processes the feedback, uses a delay error analysis model to evaluate the synchronization status of the overall system, and generates a hierarchical delay error feedback report. The hierarchical delay error report details the delay error of each subwoofer device at each processing layer.

[0048] 105. Based on the layered delay error feedback, adjust the initial compensation duration of each layer of each subwoofer device to obtain the target compensation duration;

[0049] Based on hierarchical delay error feedback, the error of each layer is quantitatively evaluated. By comparing the difference between the actual processing delay and the expected compensation time, the required adjustment amount for each layer is calculated. The initial compensation time is dynamically corrected according to the adjustment amount. During the correction process, network fluctuation prediction, hardware performance change trend and historical adjustment records are considered. Weighted averaging or machine learning algorithms are used to optimize the adjustment strategy to ensure that each correction can quickly respond to the current error and maintain system stability. Finally, the target compensation time for each layer of each subwoofer device is generated.

[0050] The formula for calculating the target compensation duration is:

[0051] TC t =TC i +(ω1×ΔTC n +ω2×ΔTC h +ω3×ΔTC m )

[0052] Among them, TC t To compensate for the target duration, TC nTC is the adjustment amount obtained based on network fluctuation prediction. h TC is the adjustment amount obtained based on the trend of hardware performance changes. m The adjustment amount is obtained based on historical adjustment records, and ω1, ω2, and ω3 are the allocation weights, where ω1 + ω2 + ω3 = 1.

[0053] Let the initial compensation duration be TC. i The actual processing time is TC. a The expected compensation is TC e Then the delay error of the transport layer Er = TC a -TC e When the delay error is greater than the preset error, the target compensation time for the corresponding layer is calculated.

[0054] 106. Based on the compensation duration of each target, coordinate and control the audio output timing of multiple subwoofer devices to achieve multi-room synchronization.

[0055] Based on the compensation duration of each target, the audio playback commands of the subwoofer devices in each room are uniformly scheduled through a timestamp synchronization mechanism to ensure that each subwoofer device outputs audio according to the corrected timing. At the same time, the network status is dynamically monitored and the compensation strategy is adjusted in a timely manner to achieve synchronous playback of audio in multiple rooms.

[0056] When coordinating and controlling the audio output timing of multiple subwoofer devices, a multi-device synchronization optimization algorithm is used for calculation.

[0057] The multi-device synchronization optimization algorithm formula is as follows:

[0058] MDS = arg min∑|D i -D ref | 2

[0059] Where MDS represents the multi-device synchronization optimization quantity, D i D is the total delay of device i, which is the initial delay of the device plus the compensated delay. ref For reference delay, the median delay of all devices is taken.

[0060] Optimization constraints: |Di-Dj|≤MaxT, meaning the delay difference between devices does not exceed the maximum tolerance value, such as 5ms; |Ci|≤MaxA, meaning the compensation offset does not exceed the maximum adjustment value, such as 50ms.

[0061] The iterative update formula is: Ci(k+1)=Ci(k)+η×(D) ref-Di(k)); where Ci(k+1) is the compensation amount of device i after the (k+1)th iteration, Ci(k) is the compensation amount of device i after the kth iteration, η is the learning rate, which is a constant between 0 and 1 used to control the compensation in each iteration, and Di(k) is the total delay of device i after the kth iteration, that is, the initial delay of device i plus the compensation amount after the kth iteration.

[0062] In this embodiment of the invention, by acquiring the initial delay data of each room's subwoofer sub-devices and utilizing a layered compensation model, the initial compensation duration of each layer can be accurately calculated. Combined with real-time monitoring of the layered delay error feedback, the compensation parameters are dynamically adjusted, ultimately achieving high-precision timing synchronization of multi-room subwoofer devices. This effectively reduces audio transmission delay differences, improves the sound field consistency of the multi-room subwoofer system, enhances the user's immersive listening experience, adapts to dynamic delay changes in complex environments, and ensures the stability and synchronization of audio playback.

[0063] Please see Figure 2 Another embodiment of the subwoofer device delay synchronization method in this invention includes:

[0064] 201. Construct a hierarchical compensation model for the subwoofer device. The hierarchical compensation model includes a hardware layer compensation sub-model, a software processing layer compensation sub-model, and a transmission layer compensation sub-model.

[0065] The construction of the hardware layer compensation sub-model includes: collecting hardware delay benchmark data of different subwoofer models, including signal conversion delay, power amplifier response delay and physical transmission delay; generating a hardware delay lookup table based on the mapping relationship between device model and delay data; fitting the correlation function between hardware parameters and delay to form a fixed offset compensation rule.

[0066] The specific data collected includes signal conversion delay (the time taken to convert a digital signal to an analog signal), power amplifier response delay (the response time of a power amplifier processing a signal), and physical transmission delay (the transmission time of an audio signal on the internal circuit board of the device). These data can be measured multiple times under different operating temperatures and voltages to cover the possible operating range of the device. After data acquisition, a mapping relationship is established between the measurement results and the device model. A hardware delay lookup table is generated through statistical analysis, storing various delay parameters according to device model. Based on the lookup table, the mathematical relationship between hardware parameters and delay can be further analyzed. Regression analysis is used to fit a function model that describes the relationship between parameters and delay. For example, a linear relationship between circuit board length and transmission delay can be established using the least squares method, or a nonlinear relationship between power amplifier efficiency and response delay can be analyzed. The final fixed offset compensation rule solidifies the relationship between hardware model, operating parameters, and expected delay in the model.

[0067] The construction of the software processing layer compensation sub-model includes: code-level analysis of the audio processing algorithm, marking key processing nodes and their corresponding theoretical clock cycles; simulating various feature combinations of input audio data, and statistically analyzing the actual processing delay under each combination; and establishing a multi-dimensional lookup table or neural network prediction model based on the correspondence between feature combinations and delays.

[0068] The audio processing algorithms running in the subwoofer device are analyzed at the code level. Key processing nodes are identified through reverse engineering or source code analysis, including but not limited to core modules such as digital filtering, dynamic range control, and frequency band separation. The theoretical number of clock cycles required for each node to complete processing is calculated based on the processor architecture and clock frequency. This step requires careful consideration of the impact of underlying factors such as processor pipeline efficiency and cache hit rate on actual execution time. After completing the algorithm analysis, simulation tests are conducted using audio input data combinations covering various typical scenarios. These combinations require systematic changes to the sampling rate, bit depth, and dynamic range. Key characteristic parameters such as spectral complexity are used to accurately measure the actual latency from data input to processing completion for each combination of features using performance analysis tools, establishing a latency database containing thousands of test results. Based on this test data, data mining techniques are employed to analyze the correlation between different audio features and processing latency. For strong linear relationships, a multi-dimensional lookup table approach can be used for rapid matching, directly outputting the estimated latency value using the audio feature parameters as an index. For complex nonlinear relationships, a neural network model needs to be trained, using the audio feature parameters as the input layer, and outputting the predicted latency value after nonlinear transformation through multiple hidden layers. The final prediction model needs continuous verification and iterative optimization in a real-world operating environment to ensure that it accurately reflects the dynamic changes in software processing latency, providing reliable latency prediction data for the hierarchical compensation system.

[0069] The system can automatically select between multidimensional lookup tables and neural network prediction models based on audio feature dimensions and sampling rate. Specifically, when reverse engineering or analyzing the source code of audio processing algorithms, the system first obtains the device's firmware image or directly accesses the algorithm's source code. Disassemblers or code analysis software are then used to systematically analyze the binary instructions or source code. During this analysis, key function calls and loop structures in the algorithm flow are identified, especially modules involving large amounts of data processing, such as the implementation of FIR / IIR filters in digital filtering, compression and limiting algorithms in dynamic range control, and multiphase filter banks in frequency band separation. For each identified key module, its input / output buffer management mechanism and data processing blocks are analyzed. Factors affecting execution efficiency, such as size settings and loop unrolling optimization strategies, are considered. The typical instruction types and execution cycle counts of each module are statistically analyzed in conjunction with the target processor's instruction set architecture, such as the intensive use of multiplication-accumulation instructions in digital filtering. For modules optimized for parallel computing, the additional overhead caused by thread scheduling strategies and data synchronization mechanisms also needs to be analyzed. After completing the static analysis, dynamic debugging tools are needed to set breakpoints at key function entry and exit points to actually measure the execution time distribution of each module and cross-validate it with theoretical clock cycle estimates. This process requires iterative iteration until a complete algorithm processing flowchart is established, and the theoretical time consumption and actual measured values ​​of each node are accurately labeled.

[0070] The construction of the transport layer compensation sub-model includes: deploying test nodes in a typical network environment to measure transmission delay under different bandwidths, packet loss rates, and topologies; extracting network state feature parameters, including round-trip time, jitter variance, and protocol overhead; and training a dynamic prediction model, which takes network state features as input and outputs the delay compensation amount.

[0071] Multiple test nodes were deployed in representative real-world network environments to construct test scenarios with different topologies, including home Wi-Fi, enterprise wired networks, and hybrid networks. Various network conditions were simulated in these environments using network testing equipment or customized measurement programs, including different bandwidth configurations, packet loss rate gradients, and changes in network topologies such as star and mesh. End-to-end transmission delay data was recorded under each condition. After collecting a large amount of measured data, key feature parameters that accurately reflect network status were extracted. Round-trip time reflects basic network latency, jitter variance characterizes network stability, and protocol overhead quantifies the processing latency of transmission protocols such as TCP / UDP. These feature parameters underwent standardization and correlation analysis to remove redundant information and retain the most predictive core indicators. Based on the filtered feature parameter set, a dynamic prediction model was trained using machine learning methods. Network status features were used as input vectors, and a mapping relationship between network status features and measured latency was established through supervised learning algorithms. During model training, cross-validation was used to optimize hyperparameters, and the model was periodically updated with newly collected data to ensure it could adapt to dynamic changes in the network environment. The final prediction model can accurately output the required latency compensation based on real-time monitored network status features.

[0072] 202. Obtain the initial delay data of the subwoofer devices in each room;

[0073] Send test audio signals to subwoofer devices in each room; record the time when each subwoofer device receives the test audio signal and generates the initial audio response; compare the time when the test audio signal is sent with the time when each subwoofer device generates the initial audio response to obtain the initial delay data of each subwoofer device.

[0074] 203. Based on the initial delay data, adjust the preset hierarchical compensation model to generate the target hierarchical compensation model corresponding to each subwoofer device.

[0075] The adjustment of the preset hierarchical compensation model based on the initial latency data includes: decomposing the initial latency data into hardware, software processing, and transmission layers to obtain the initial latency components of each layer; for each layer's latency component, using corresponding adjustment strategies to correct the preset model parameters: for the hardware layer: matching the preset baseline latency table based on the device model, calculating the offset between the measured value and the baseline value, and updating the fixed compensation parameters; for the software processing layer: dynamically retrieving the preset latency mapping table based on the audio data characteristics, and optimizing the lookup step size or neural network weights; for the transmission layer: combining real-time network status data to calibrate the bandwidth-latency correlation coefficient of the dynamic prediction model.

[0076] The hardware layer adjustment strategy specifically includes: if the measured hardware latency exceeds the theoretical range of the preset model, the device is marked as abnormal and recalibration is triggered; if the measured value is within the theoretical range, the weighted average method is used to integrate the new data into the historical dataset to generate an updated baseline latency table.

[0077] The software processing layer adjustment strategy specifically includes: establishing a separate sub-mapping table for frequently occurring audio feature combinations to reduce lookup latency; and using an online learning algorithm to fine-tune the hidden layer node parameters for the neural network prediction model.

[0078] The adjustment strategies at the transport layer specifically include: switching to anti-jitter compensation mode when the network packet loss rate exceeds the threshold, increasing the redundancy of the compensation time; periodically verifying the accuracy of the prediction model through probe data, and retraining the model if the error continues to exceed the limit.

[0079] 204. Calculate the initial compensation time of each subwoofer device at the hardware layer, software processing layer, and transmission layer based on the hierarchical compensation model of each target;

[0080] Obtain the current delay-related parameter data of each subwoofer device, and input the current delay-related parameter data into the corresponding target hierarchical compensation model; use the target hierarchical compensation model to calculate the preliminary compensation duration of the hardware layer, software processing layer and transmission layer respectively; summarize and verify the preliminary compensation duration of each layer to ensure that the sum of the compensation duration of each layer meets the overall delay requirements.

[0081] The specific execution process of calculating the preliminary compensation time of the hardware layer, software processing layer, and transmission layer using the target hierarchical compensation model is as follows: using the hardware layer compensation sub-model, the preliminary compensation time of the hardware layer is calculated based on the current state and historical data of the hardware device; using the software processing layer compensation sub-model, the preliminary compensation time of the software processing layer is calculated based on the complexity of the input audio data and the software operating environment; using the transmission layer compensation sub-model, the preliminary compensation time of the transmission layer is calculated based on the real-time monitored transmission network conditions.

[0082] The system collects dynamic status parameters of the subwoofer device in real time at the hardware, software processing, and transmission layers, and obtains current latency-related parameter data, including but not limited to: real-time physical status indicators such as CPU temperature, memory usage, and core frequency; processing environment parameters such as audio stream complexity characteristics and thread scheduling latency; and real-time network quality data such as network RTT, jitter variance, and packet loss rate.

[0083] For example, key device status parameters are acquired in real time, including CPU temperature, memory usage, disk I / O load, and the operating frequency of core hardware components. Latency records, performance degradation trends, and fault maintenance logs for the hardware device in similar past usage scenarios are retrieved from a historical database. This real-time and historical data is input into the hardware-layer compensation sub-model. The hardware latency prediction engine, built on machine learning algorithms, begins working within the model. This engine analyzes the correlation between current hardware status parameters and historical latency anomalies. For instance, when CPU temperature exceeds a threshold and memory usage remains high, latency typically increases by a preset duration, such as 2 milliseconds. Through feature-weighted calculations, the impact of each current status parameter on latency is considered, along with the average compensation duration required under similar historical conditions, ultimately outputting the preliminary compensation duration for the hardware layer.

[0084] The calculation formula is:

[0085]

[0086] Where ΔT is the initial compensation duration of the hardware layer, and S i For the i-th real-time status parameter, such as CPU temperature, memory usage, etc., H i Let ∑ω be the corresponding historical mean delay. i =1, f(S) i H i ) is the state-delay correlation function, and ε is the noise correction term, such as aging compensation.

[0087] The input audio data is processed using audio feature analysis algorithms to extract complexity-related indicators, such as the frequency distribution range, dynamic range, harmonic richness, and transient frequency of the signal, thus quantifying the audio complexity score. Software operating environment information, including CPU core utilization, real-time memory usage, thread concurrency, and cache hit rate, is obtained through system monitoring tools. These audio complexity scores and software operating environment parameters are then input into the software processing layer compensation sub-model. This model, built on a deep learning network, performs feature fusion and learning on the input data, analyzes the impact of different combinations of audio complexity and software operating environment on software processing latency, and predicts the initial compensation time required by the software processing layer under the current audio complexity and software operating environment conditions by continuously iterating and optimizing the network parameters.

[0088] The system acquires key metrics such as bandwidth utilization, packet loss rate, and latency jitter of the transmission network in real time, while also recording the arrival time interval and sequence integrity information of data packets. This real-time monitored transmission network data is input into the transport layer compensation sub-model. This model, built on a dynamic time series prediction algorithm, can quickly analyze the current network bandwidth fluctuations, packet loss burst patterns, and latency jitter distribution characteristics. Referring to compensation duration examples from historical network fluctuation data, the algorithm adaptively adjusts parameters to predict the initial compensation duration required by the transport layer under the current transmission network conditions.

[0089] 205. Monitor the actual processing delay of each subwoofer device in real time and generate layered delay error feedback;

[0090] Regularly send monitoring audio signals to each subwoofer device; record the actual processing delay of each subwoofer device after receiving the monitoring audio signals; analyze the actual processing delay, and generate layered delay error feedback according to the hardware layer, software processing layer and transmission layer.

[0091] The specific execution process for analyzing actual processing latency and generating layered latency error feedback, categorized into hardware, software processing, and transmission layers, is as follows: The actual processing latency data is compared with historical latency data to analyze latency change trends; based on these trends and considering the performance characteristics of the hardware, software processing, and transmission layers, the actual processing latency is assigned to a specific layer; based on the latency data of each layer after the layer assignment determination, the difference between the actual latency and the expected latency is calculated as the layered latency error, and this error information is fed back in a layered manner.

[0092] An analytical approach combining sliding window and trend fitting can be employed. First, a suitable sliding window length is set, such as 10 seconds. The windows are slid sequentially over time, and the average, maximum, minimum, and variance of the actual processing delay data within each window are calculated. Simultaneously, historical delay data with the same time span and similar system operating conditions is retrieved from a historical database, and the corresponding statistics are calculated. Next, the statistics of the actual delay and historical delay are compared window by window to observe the numerical differences and trends. Then, trend fitting methods such as linear regression or moving average are used to fit the statistical sequences of the actual and historical delays, respectively, resulting in two trend lines. By comparing the slope, intercept, and fluctuation of the two trend lines, it is possible to analyze whether the actual delay, compared to the historical delay, exhibits an upward, downward, stable, or periodic fluctuation trend, and the strength and significance of this trend are quantified.

[0093] A hierarchical attribution method based on feature association analysis and weighted scoring can be adopted. First, based on the performance characteristics of the hardware layer, software processing layer, and transmission layer, feature parameters closely related to latency changes are extracted. Hardware layer performance characteristics include CPU frequency fluctuation range, memory read / write rate changes, and hardware resource utilization threshold exceedances. Software processing layer performance characteristics include algorithm complexity indicators, abnormal thread concurrency, and the magnitude of software cache hit rate decline. Transmission layer performance characteristics include the magnitude of network bandwidth drop, packet loss rate increase rate, and latency jitter exceeding limits. Based on the correlation between the feature parameters of each layer and the latency change trend in historical data, corresponding weight coefficients are assigned to the feature parameters of different layers. The actual processing latency change trend is matched with the feature parameters of each layer to calculate the contribution of each layer's feature parameters to the current latency change, i.e., the deviation between the current value and the normal value of each layer's feature parameter is multiplied by the corresponding weight coefficient. The layer with the largest contribution is the main attribution layer for the actual processing latency. If multiple layers have similar and high contributions, the latency is determined to be jointly affected by these layers, thus achieving hierarchical attribution.

[0094] For each layer, the expected latency value of that layer under the current operating conditions is extracted from the pre-defined performance benchmark library. The actual latency data of each layer is subtracted from the expected latency value one by one to obtain the latency difference of each layer. This difference is the layer latency error. An error feedback template containing a three-layer structure of hardware, software and transmission is constructed. The calculated latency error of each layer is accurately filled into the corresponding position of the template according to its layer.

[0095] 206. Based on the layered delay error feedback, the initial compensation duration of each layer of each subwoofer device is adjusted to obtain the target compensation duration;

[0096] The layered delay error feedback is analyzed to extract the delay error values ​​of the hardware layer, software processing layer, and transmission layer. The delay error values ​​of each layer are compared with preset error thresholds to determine whether the compensation duration needs to be adjusted. If the delay error value exceeds the error threshold, the initial compensation duration of the corresponding layer is increased or decreased according to the direction and magnitude of the delay error and the preset adjustment rules to obtain the target compensation duration of each layer.

[0097] The process of increasing or decreasing the initial compensation duration of the corresponding layer according to the preset adjustment rules is as follows: For the hardware layer, if the latency error is positive, the initial compensation duration is increased; if the latency error is negative, the initial compensation duration is decreased. For the software processing layer, the specific magnitude of the increase or decrease in compensation duration is determined based on the characteristics of the software algorithm and historical adjustment data. For the transmission layer, the magnitude of the increase or decrease in compensation duration is dynamically adjusted in conjunction with real-time monitoring data of network conditions to adapt to changes in network latency.

[0098] For example, in the first audio processing system, after hierarchical delay error feedback analysis, the delay error value of the hardware layer is +15 milliseconds, the software processing layer is -8 milliseconds, and the transmission layer is +20 milliseconds. The preset error threshold is ±10 milliseconds. Since the delay error values ​​of the hardware layer and the transmission layer exceed the threshold, the compensation duration needs to be adjusted. For the hardware layer, since its delay error is positive, the initial compensation duration is increased by 15 milliseconds according to the rules. The software processing layer has a negative delay error, and based on the characteristics of the algorithm of this layer and historical adjustment data, the initial compensation duration is reduced by 8 milliseconds. The characteristics of the algorithm of this layer are, for example, that the audio encoding complexity has a large impact on the delay, and historical adjustment data shows that adjusting by 5-10 milliseconds under similar errors in the past can restore stability. The transmission layer has a positive delay error, and based on the real-time monitoring of the decrease in network bandwidth and the increase in packet loss rate, the initial compensation duration is dynamically increased by 25 milliseconds. Finally, the target compensation durations for the hardware layer, software processing layer, and transmission layer are the original initial compensation duration +1 millisecond, the original initial compensation duration -8 milliseconds, and the original initial compensation duration +25 milliseconds, respectively.

[0099] 207. Based on the compensation duration of each target, coordinate and control the audio output timing of multiple subwoofer devices to achieve multi-room synchronization.

[0100] In this embodiment of the invention, by subdividing the initial latency data into three key factors—hardware latency, software processing latency, and transmission latency—and establishing a targeted hierarchical compensation model, it is possible to more accurately identify and compensate for latency errors from different sources. During audio playback, the compensation parameters of each layer are dynamically optimized by combining real-time monitoring of hierarchical latency error feedback, significantly improving the synchronization accuracy of multi-room subwoofer systems. This effectively solves the problem of inaccurate compensation caused by the difficulty in distinguishing latency sources in traditional methods. This hierarchical compensation mechanism not only achieves effective synchronization of subwoofers across rooms but also adapts to changes in different hardware configurations, software algorithms, and network environments, greatly improving the stability and sound field consistency of distributed bass systems and providing users with an immersive, high-quality listening experience.

[0101] The above describes the subwoofer device delay synchronization method in the embodiments of the present invention. The following describes the subwoofer device delay synchronization device in the embodiments of the present invention. Please refer to [link / reference]. Figure 3 One embodiment of the subwoofer device delay synchronization device in this invention includes:

[0102] The acquisition module 301 is used to acquire the initial delay data of the subwoofer sub-devices in each room;

[0103] The generation module 302 is used to adjust the preset layered compensation model according to each initial delay data, and generate the target layered compensation model corresponding to each subwoofer device.

[0104] Calculation module 303 is used to calculate the initial compensation time of each subwoofer device at the hardware layer, software processing layer and transmission layer based on the hierarchical compensation model of each target;

[0105] The processing module 304 is used to monitor the actual processing delay of each subwoofer device in real time during audio playback and generate layered delay error feedback.

[0106] The adjustment module 305 is used to adjust the initial compensation time of each layer of each subwoofer device according to the layer delay error feedback, so as to obtain the target compensation time.

[0107] Synchronization module 306 is used to coordinate and control the audio output timing of multiple subwoofer devices to achieve multi-room synchronization based on the compensation duration of each target.

[0108] In this embodiment of the invention, by acquiring the initial delay data of each room's subwoofer sub-devices and utilizing a layered compensation model, the initial compensation duration of each layer can be accurately calculated. Combined with real-time monitoring of the layered delay error feedback, the compensation parameters are dynamically adjusted, ultimately achieving high-precision timing synchronization of multi-room subwoofer devices. This effectively reduces audio transmission delay differences, improves the sound field consistency of the multi-room subwoofer system, enhances the user's immersive listening experience, adapts to dynamic delay changes in complex environments, and ensures the stability and synchronization of audio playback.

[0109] Please see Figure 4 Another embodiment of the subwoofer device delay synchronization device in this invention includes:

[0110] The acquisition module 301 is used to acquire the initial delay data of the subwoofer sub-devices in each room;

[0111] The generation module 302 is used to adjust the preset layered compensation model according to each initial delay data, and generate the target layered compensation model corresponding to each subwoofer device.

[0112] Calculation module 303 is used to calculate the initial compensation time of each subwoofer device at the hardware layer, software processing layer and transmission layer based on the hierarchical compensation model of each target;

[0113] The processing module 304 is used to monitor the actual processing delay of each subwoofer device in real time during audio playback and generate layered delay error feedback.

[0114] The adjustment module 305 is used to adjust the initial compensation time of each layer of each subwoofer device according to the layer delay error feedback, so as to obtain the target compensation time.

[0115] Synchronization module 306 is used to coordinate and control the audio output timing of multiple subwoofer devices to achieve multi-room synchronization based on the compensation duration of each target.

[0116] Optionally, the acquisition module 301 can be specifically used for:

[0117] Send test audio signals to subwoofer devices in each room; record the time when each subwoofer device receives the test audio signal and generates the initial audio response; compare the time when the test audio signal is sent with the time when each subwoofer device generates the initial audio response to obtain the initial delay data of each subwoofer device.

[0118] Optionally, the subwoofer device delay synchronization device also includes:

[0119] Module 307 is used to construct a layered compensation model for the subwoofer device. The layered compensation model includes a hardware layer compensation sub-model, a software processing layer compensation sub-model, and a transmission layer compensation sub-model.

[0120] Optionally, builder module 307 can be specifically used for:

[0121] Hardware delay baseline data for different subwoofer models were collected, including signal conversion delay, power amplifier response delay, and physical transmission delay. Based on the mapping relationship between device models and delay data, a hardware delay comparison table was generated. A correlation function between hardware parameters and delay was fitted to form a fixed offset compensation rule.

[0122] Optionally, building module 307 can also be specifically used for:

[0123] The audio processing algorithm is analyzed at the code level, and key processing nodes and their corresponding theoretical clock cycles are marked. Various feature combinations of input audio data are simulated, and the actual processing delay under each combination is statistically analyzed. Based on the correspondence between feature combinations and delays, a multidimensional lookup table or neural network prediction model is established.

[0124] Optionally, building module 307 can also be specifically used for:

[0125] Deploy test nodes in typical network environments to measure transmission delays under different bandwidths, packet loss rates, and topologies; extract network state characteristic parameters, including round-trip time, jitter variance, and protocol overhead; train a dynamic prediction model, which takes network state characteristics as input and outputs delay compensation.

[0126] Optionally, the computing module 303 includes:

[0127] The input unit 3031 is used to acquire the current delay-related parameter data of each subwoofer device and input the current delay-related parameter data into the corresponding target hierarchical compensation model;

[0128] The computing unit 3032 is used to calculate the preliminary compensation time of the hardware layer, software processing layer and transmission layer respectively using the hierarchical compensation model.

[0129] The verification unit 3033 is used to summarize and verify the preliminary compensation duration of each layer to ensure that the sum of the compensation durations of each layer meets the overall delay requirements.

[0130] Optionally, the computing unit 3032 can be specifically used for:

[0131] Using the hardware layer compensation sub-model, the initial compensation duration of the hardware layer is calculated based on the current state and historical data of the hardware device; using the software processing layer compensation sub-model, the initial compensation duration of the software processing layer is calculated based on the complexity of the input audio data and the software operating environment; using the transmission layer compensation sub-model, the initial compensation duration of the transmission layer is calculated based on the real-time monitored transmission network conditions.

[0132] Optionally, the processing module 304 includes:

[0133] The transmitting unit 3041 is used to periodically send monitoring audio signals to each subwoofer device;

[0134] Recording unit 3042 is used to record the actual processing delay of each subwoofer device after receiving the monitored audio signal;

[0135] Analysis unit 3043 is used to perform analysis based on actual processing delay, and to generate layered delay error feedback by dividing the data into hardware layer, software processing layer and transmission layer.

[0136] Optionally, analysis unit 3043 is specifically used for:

[0137] The actual processing delay data is compared with historical delay data to analyze the delay change trend. Based on the delay change trend, and combined with the performance characteristics of the hardware layer, software processing layer, and transmission layer, the actual processing delay is classified into layers. Based on the delay data of each layer after classification, the difference between the actual delay and the expected delay is calculated as the layered delay error, and the error information is fed back in a layered manner.

[0138] Optionally, the adjustment module 305 includes:

[0139] Extraction unit 3051 is used to analyze the layered delay error feedback and extract the delay error values ​​of the hardware layer, software processing layer and transmission layer respectively.

[0140] The judgment unit 3052 is used to compare the delay error values ​​of each layer with the preset error threshold to determine whether the compensation time adjustment is required.

[0141] The adjustment unit 3053 is used to increase or decrease the initial compensation time of the corresponding layer according to the direction and magnitude of the delay error and a preset adjustment rule if the delay error value exceeds the error threshold, so as to obtain the target compensation time of each layer.

[0142] Optionally, the adjustment unit 3053 is specifically used for:

[0143] For the hardware layer, if the latency error is positive, the initial compensation duration is increased; if the latency error is negative, the initial compensation duration is decreased. For the software processing layer, the specific range of increase or decrease in compensation duration is determined based on the characteristics of the software algorithm and historical adjustment data. For the transmission layer, the range of increase or decrease in compensation duration is dynamically adjusted based on real-time monitoring data of network conditions to adapt to changes in network latency.

[0144] In this embodiment of the invention, by subdividing the initial latency data into three key factors—hardware latency, software processing latency, and transmission latency—and establishing a targeted hierarchical compensation model, it is possible to more accurately identify and compensate for latency errors from different sources. During audio playback, the compensation parameters of each layer are dynamically optimized by combining real-time monitoring of hierarchical latency error feedback, significantly improving the synchronization accuracy of multi-room subwoofer systems. This effectively solves the problem of inaccurate compensation caused by the difficulty in distinguishing latency sources in traditional methods. This hierarchical compensation mechanism not only achieves effective synchronization of subwoofers across rooms but also adapts to changes in different hardware configurations, software algorithms, and network environments, greatly improving the stability and sound field consistency of distributed bass systems and providing users with an immersive, high-quality listening experience.

[0145] above Figure 3 and Figure 4 The subwoofer device delay synchronization device in this embodiment of the invention will be described in detail from the perspective of modular functional entities. The electronic device in this embodiment of the invention will be described in detail from the perspective of hardware processing.

[0146] See Figure 5 As shown, the electronic device includes a processor 500 and a memory 501. The memory 501 stores machine-executable instructions that can be executed by the processor 500. The processor 500 executes the machine-executable instructions to implement the above-described subwoofer device delay synchronization method.

[0147] Furthermore, Figure 5 The electronic device shown also includes a bus 502 and a communication interface 503. The processor 500, the communication interface 503 and the memory 501 are connected via the bus 502.

[0148] The memory 501 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 503 (which can be wired or wireless), such as the Internet, wide area network, local area network, metropolitan area network, etc. The bus 502 may be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 5 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0149] The processor 500 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of the processor 500 or by instructions in software form. The processor 500 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this disclosure. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this disclosure can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules may reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The storage medium is located in memory 501. The processor 500 reads the information in memory 501 and, in conjunction with its hardware, completes the method steps of the aforementioned embodiment.

[0150] The present invention also provides an electronic device, the computer device including a memory and a processor, the memory storing computer-readable instructions, which, when executed by the processor, cause the processor to perform the steps of the subwoofer device delay synchronization method in the above embodiments.

[0151] The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium, wherein the computer-readable storage medium stores instructions that, when the instructions are executed on a computer, cause the computer to perform the steps of the subwoofer device delay synchronization method.

[0152] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0153] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0154] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for delaying synchronization of a subwoofer device, characterized in that, The subwoofer device delay synchronization method includes: Obtain the initial delay data of the subwoofer devices in each room; Based on the initial delay data, the preset hierarchical compensation model is adjusted to generate the target hierarchical compensation model corresponding to each subwoofer sub-device. The hierarchical compensation model includes a hardware layer compensation sub-model, a software processing layer compensation sub-model, and a transmission layer compensation sub-model. The initial compensation time of each subwoofer device at the hardware layer, software processing layer and transmission layer is calculated based on the hierarchical compensation model of each target. During audio playback, the actual processing delay of each subwoofer device is monitored in real time and layered delay error feedback is generated; Based on the layered delay error feedback, the initial compensation duration of each layer of each subwoofer device is adjusted to obtain the target compensation duration. Based on the compensation duration of each target, the audio output timing of multiple subwoofer devices is coordinated and controlled to achieve multi-room synchronization.

2. The subwoofer device delay synchronization method according to claim 1, characterized in that, The acquisition of initial delay data for each room's subwoofer sub-devices includes: Send test audio signals to the subwoofers in each room; Record the time point at which each subwoofer receives the test audio signal and generates the initial audio response; By comparing the transmission time of the test audio signal with the time when each subwoofer device generates its initial audio response, the initial delay data of the subwoofer device in each room is obtained.

3. The subwoofer device delay synchronization method according to claim 1, characterized in that, The construction of the hardware layer compensation sub-model includes: Hardware delay baseline data of different models of subwoofers were collected, including signal conversion delay, power amplifier response delay and physical transmission delay. A hardware latency lookup table is generated based on the mapping relationship between device model and latency data; A fixed offset compensation rule is formed by fitting the correlation function between hardware parameters and latency.

4. The subwoofer device delay synchronization method according to claim 1, characterized in that, The construction of the software processing layer compensation sub-model includes: The audio processing algorithm is analyzed at the code level, and key processing nodes and their corresponding theoretical clock cycles are marked. Simulate multiple combinations of features in input audio data and statistically analyze the actual processing latency under each combination. Based on the correspondence between feature combinations and delays, a multidimensional lookup table or neural network prediction model is established.

5. The subwoofer device delay synchronization method according to claim 1, characterized in that, The construction of the transport layer compensation sub-model includes: Deploy test nodes in a typical network environment to measure transmission latency under different bandwidths, packet loss rates, and topologies. Extract network state characteristic parameters, including round-trip time, jitter variance, and protocol overhead; A dynamic prediction model is trained, which takes network state features as input and outputs a delay compensation amount.

6. The subwoofer device delay synchronization method according to claim 1, characterized in that, The calculation of the initial compensation time for each subwoofer sub-device at the hardware, software processing, and transmission layers based on the hierarchical compensation model for each target includes: Obtain the current delay-related parameter data of each subwoofer device, and input the current delay-related parameter data into the corresponding hierarchical compensation model; Using the aforementioned hierarchical compensation model, the preliminary compensation durations for the hardware layer, software processing layer, and transmission layer are calculated respectively. The initial compensation durations for each layer are summarized and verified to ensure that the sum of the compensation durations for each layer meets the overall delay requirements.

7. The subwoofer device delay synchronization method according to claim 6, characterized in that, The step of using the layered compensation model to calculate the preliminary compensation time for the hardware layer, software processing layer, and transmission layer respectively includes: Using the hardware layer compensation sub-model, the initial compensation duration of the hardware layer is calculated based on the current state and historical data of the hardware device. Using the software processing layer compensation sub-model, the initial compensation duration of the software processing layer is calculated based on the complexity of the input audio data and the software operating environment. Using the transport layer compensation sub-model, the initial compensation duration of the transport layer is calculated based on the real-time monitored transport network conditions.

8. The subwoofer device delay synchronization method according to claim 1, characterized in that, The real-time monitoring of the actual processing delay of each subwoofer device and the generation of layered delay error feedback include: Regularly send monitoring audio signals to each subwoofer device; Record the actual processing delay of each subwoofer device after receiving the monitored audio signal; The actual processing delay is analyzed, and the layers are divided into hardware layer, software processing layer and transmission layer to generate layered delay error feedback.

9. The subwoofer device delay synchronization method according to claim 8, characterized in that, The analysis utilizing the actual processing delay, categorized into hardware, software processing, and transmission layers, generates layered delay error feedback, including: The actual processing delay data is compared with historical delay data to analyze the trend of delay changes; Based on the aforementioned latency change trend, and combined with the performance characteristics of the hardware layer, software processing layer, and transmission layer, the actual processing latency is classified and assigned accordingly. Based on the delay data of each layer after the hierarchical attribution determination, the difference between the delay data and the expected delay is calculated as the hierarchical delay error, and the error information is fed back in a hierarchical form.

10. The subwoofer device delay synchronization method according to claim 1, characterized in that, The step of adjusting the initial compensation duration of each layer of each subwoofer device based on the layered delay error feedback to obtain the target compensation duration includes: The layered delay error feedback is analyzed to extract the delay error values ​​of the hardware layer, software processing layer, and transmission layer. The delay error values ​​of each layer are compared with the preset error threshold to determine whether the compensation duration needs to be adjusted. If the delay error value exceeds the error threshold, the initial compensation time of the corresponding layer is increased or decreased according to the direction and magnitude of the delay error and the preset adjustment rules, so as to obtain the target compensation time of each layer.

11. The subwoofer device delay synchronization method according to claim 10, characterized in that, The step of increasing or decreasing the initial compensation duration of the corresponding layer according to the preset adjustment rules includes: For the hardware layer, if the latency error is positive, the initial compensation duration is increased; if the latency error is negative, the initial compensation duration is decreased. For the software processing layer, the specific range of increase or decrease in compensation time is determined based on the characteristics of the software algorithm and historical adjustment data. For the transport layer, the compensation duration is dynamically adjusted based on real-time network condition monitoring data to adapt to changes in network latency.

12. A time-delay synchronization device for a subwoofer, characterized in that, The subwoofer device delay synchronization device includes: The acquisition module is used to acquire the initial delay data of the subwoofer devices in each room; The generation module is used to adjust the preset hierarchical compensation model according to each initial delay data, and generate the target hierarchical compensation model corresponding to each subwoofer sub-device. The hierarchical compensation model includes a hardware layer compensation sub-model, a software processing layer compensation sub-model, and a transmission layer compensation sub-model. The calculation module is used to calculate the initial compensation time of each subwoofer device at the hardware layer, software processing layer and transmission layer based on the hierarchical compensation model of each target. The processing module is used to monitor the actual processing delay of each subwoofer device in real time during audio playback and generate layered delay error feedback. The adjustment module is used to adjust the initial compensation time of each layer of each subwoofer device according to the layered delay error feedback, so as to obtain the target compensation time. The synchronization module is used to coordinate and control the audio output timing of multiple subwoofer devices based on the compensation duration of each target to achieve multi-room synchronization.

13. An electronic device, characterized in that, The electronic device includes: a memory and at least one processor, wherein the memory stores instructions; The at least one processor invokes the instructions in the memory to cause the electronic device to perform the subwoofer device delay synchronization method as described in any one of claims 1-11.

14. A computer-readable storage medium storing instructions thereon, characterized in that, When the instruction is executed by the processor, it implements the subwoofer device delay synchronization method as described in any one of claims 1-11.

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