A method and device for audio synchronization of wireless headphones based on Polar code

Abstract

The present invention relates to an audio synchronization method and device for wireless headphones based on Polar codes, the method comprising: obtaining a target audio signal and extracting time domain features and frequency domain features of the target audio signal, and determining the sparsity of the target audio signal based thereon; based on the sparsity of the audio signal, compressing the target audio signal using different compressed sensing methods; encoding the compressed audio signal through Polar codes; embedding a synchronization code into the encoded audio signal based on the time domain features and frequency domain features; receiving an audio signal after the synchronization code is embedded, and decoding the audio signal and extracting the synchronization code; synchronizing multiple wireless headphones based on the comparison result of the extracted synchronization code and the embedded synchronization code. The present invention improves the efficiency and adaptability of compression and synchronous transmission by selecting a suitable compressed sensing method for different types of audio signals and combining it with Polar codes.

Description

Technical Field

[0001] The present invention belongs to the technical field of audio synchronization, and in particular relates to an audio synchronization method and device for wireless headphones based on Polar codes. Background Art

[0002] When wireless headphones transmit audio signals, they need to go through a series of processes such as encoding, modulation, wireless transmission, demodulation and decoding. In this process, signal quality and synchronization accuracy are crucial. However, due to problems such as interference and channel attenuation in the wireless environment, traditional wireless headphones face the following technical challenges:

[0003] 1. Audio quality: Traditional Bluetooth coding and modulation methods (such as SBC and AAC) cannot provide high-fidelity audio quality under limited bandwidth, and are especially susceptible to interference and channel attenuation in complex wireless environments. 2. Synchronization issues: Stereo headphones have very high requirements for audio synchronization between the left and right ears, but existing wireless transmission technologies often cannot guarantee millisecond-level synchronization accuracy, resulting in audio signal asynchrony. 3. Latency issues: In scenarios with high real-time requirements such as video conferencing, games, and video playback, the delay in audio transmission directly affects the user experience, and existing wireless technologies are difficult to meet high response requirements. Summary of the invention

[0004] In order to solve the audio quality and synchronization problems of headphones, a first aspect of the present invention provides an audio synchronization method for wireless headphones based on Polar codes, including: acquiring a target audio signal and extracting time domain features and frequency domain features of the target audio signal, and determining the sparsity of the target audio signal based on the time domain features and frequency domain features; compressing the target audio signal using different compressed sensing methods based on the sparsity of the audio signal; encoding the compressed audio signal through Polar codes; embedding a synchronization code into the encoded audio signal based on the time domain features and frequency domain features; receiving the audio signal after the synchronization code is embedded, and decoding the audio signal and extracting the synchronization code; synchronizing multiple wireless headphones based on the comparison result of the extracted synchronization code and the embedded synchronization code.

[0005] In some embodiments of the present invention, determining the sparsity of the target audio signal based on the time domain features and the frequency domain features includes: if the short-time energy standard deviation and the spectrum bandwidth are greater than preset values, determining that the target audio signal is a sparse signal.

[0006] In some embodiments of the present invention, based on the sparsity of the audio signal, using different compressed sensing to compress the target audio signal includes: for a sparse signal, compressing the audio signal by presetting a sparse basis and a measurement matrix; for a non-sparse signal, compressing the audio signal by presetting a measurement matrix and a regularization method.

[0007] In some embodiments of the present invention, encoding the compressed audio signal by using Polar code includes: constructing a generator matrix based on Kronecker powers of a preset kernel matrix; and encoding the compressed audio signal by using the generator matrix.

[0008] Furthermore, embedding a synchronization code into the encoded audio signal based on the time domain characteristics and frequency domain characteristics includes: based on the short-time energy standard deviation and spectrum bandwidth of the target audio signal as basic data, generating a synchronization code from the basic data and the arrival time of the audio data through an adaptive linear prediction method.

[0009] In some embodiments of the present invention, synchronizing multiple wireless headsets based on the comparison result of the extracted synchronization code and the embedded synchronization code includes: comparing the synchronization code extracted by each wireless headset with the embedded synchronization code respectively: if the distortion degree of the synchronization code and the embedded synchronization code signal is greater than a threshold, synchronizing the multiple wireless headsets.

[0010] According to a second aspect of the present invention, there is provided an audio synchronization device for wireless headphones based on Polar codes, comprising: an acquisition module for acquiring a target audio signal and extracting time domain features and frequency domain features of the target audio signal, and determining the sparsity of the target audio signal based on the time domain features and frequency domain features; a compression module for compressing the target audio signal by using different compression sensing methods based on the sparsity of the audio signal; an embedding module for encoding the compressed audio signal through Polar codes; embedding a synchronization code into the encoded audio signal based on the time domain features and frequency domain features; a synchronization module for receiving the audio signal after the synchronization code is embedded, decoding the audio signal and extracting the synchronization code; and synchronizing multiple wireless headphones based on a comparison result of the extracted synchronization code and the embedded synchronization code.

[0011] The third aspect of the present invention provides an electronic device, comprising: one or more processors; a storage device for storing one or more programs, when the one or more programs are executed by the one or more processors, the one or more processors implement the audio synchronization method of wireless headphones based on Polar codes provided in the first aspect of the present invention.

[0012] A fourth aspect of the present invention provides a computer-readable medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the audio synchronization method for wireless headphones based on Polar codes provided in the first aspect of the present invention is implemented.

[0013] The beneficial effects of the present invention are:

[0014] The present invention relates to an audio synchronization method and device for wireless headphones based on Polar codes, and the method includes: obtaining a target audio signal and extracting the time domain features and frequency domain features of the target audio signal, and determining the sparsity of the target audio signal based on the time domain features and frequency domain features of the target audio signal; compressing the target audio signal using different compression sensing methods based on the sparsity of the audio signal; encoding the compressed audio signal through Polar codes; embedding a synchronization code into the encoded audio signal based on the time domain features and frequency domain features; receiving the audio signal after the synchronization code is embedded, and decoding the audio signal and extracting the synchronization code; synchronizing multiple wireless headphones based on the comparison result of the extracted synchronization code and the embedded synchronization code. It can be seen that the present invention classifies the audio signal through the traditional audio signal processing method, and then selects different compression modes according to different classifications, thereby improving the transmission efficiency; then through Polar coding, the stability and adaptability of the transmission are guaranteed, and finally the audio synchronization of the wireless headphones is realized by verifying the synchronization code based on the time and frequency domain features. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A schematic diagram of a basic flow chart of an audio synchronization method for wireless headphones based on Polar codes in some embodiments of the present invention;

[0016] Figure 2 It is a schematic diagram of a specific flow of an audio synchronization method for wireless headphones based on Polar codes in some embodiments of the present invention;

[0017] Figure 3 It is a schematic diagram of the structure of an audio synchronization device for wireless headphones based on Polar codes in some embodiments of the present invention;

[0018] Figure 4 It is a schematic diagram of the structure of an electronic device in some embodiments of the present invention. DETAILED DESCRIPTION

[0019] The principles and features of the present invention are described below in conjunction with the accompanying drawings. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention.

[0020] refer to Figure 1 and Figure 2 In a first aspect of the present invention, a method for audio synchronization of a wireless headset based on Polar code is provided, comprising:

[0021] S100. Acquire a target audio signal and extract time domain features and frequency domain features of the target audio signal, and determine the sparsity of the target audio signal based on the time domain features and frequency domain features;

[0022] S200. Based on the sparsity of the audio signal, compress the target audio signal using different compression sensing methods on the audio signal;

[0023] S300. Encoding the compressed audio signal by Polar code; embedding a synchronization code into the encoded audio signal based on the time domain characteristics and frequency domain characteristics;

[0024] S400. Receive an audio signal with an embedded synchronization code, decode the audio signal and extract the synchronization code; synchronize multiple wireless headsets based on a comparison result between the extracted synchronization code and the embedded synchronization code.

[0025] It can be understood that the target audio signal is at least one or more of a speech signal, a music signal, and an ambient sound. The target audio signal comes from a sampled or processed audio signal of a live environment, or an audio part of a video signal, etc. Regardless of the form of the audio signal, it does not affect the extraction of the audio signal by the existing audio processing technology.

[0026] In step S100 of some embodiments of the present invention, a target audio signal is acquired and time domain features and frequency domain features of the target audio signal are extracted.

[0027] Specifically, in the process of extracting the time domain features and frequency domain features of the target audio signal, the target audio signal needs to be preprocessed, including: denoising, using filtering technology to remove background noise; signal segmentation: dividing the long audio signal into short time frames (such as 20 milliseconds). Normalization: Normalize the audio signal so that the signal amplitude is within a standard range. Time domain features include zero crossing rate (ZCR), short-time energy, etc. Frequency domain features include Mel frequency cepstral coefficients (MFCC), spectrum centroid, spectrum bandwidth, etc.

[0028] It can be understood that for speech signals, the ZCR is high and the centroid of the spectrum is in the mid-frequency region. For music signals, the spectrum is relatively dispersed and the short-time energy fluctuates greatly. For ambient sound, the ZCR and short-time energy change slightly and the centroid of the spectrum is in the low-frequency region. Therefore, different speech signals can be distinguished by short-time energy and ZCR.

[0029] Therefore, determining the sparsity of the target audio signal based on the time domain features and the frequency domain features includes: if the short-time energy standard deviation and the spectrum bandwidth are greater than preset values, determining that the target audio signal is a sparse signal.

[0030] Specifically, ZCR is expressed as:

[0031] Where 1(·) represents the indicator function, N is the number of samples, and x[n] is the audio signal.

[0032] The short-time energy is expressed as:

[0033] Where E represents short-time energy, N is the number of samples, and x[n] is the audio signal.

[0034] The spectrum centroid is expressed as:

[0035] X[k] is the audio signal.

[0036] Accordingly, the spectrum bandwidth is expressed as:

[0037]

[0038] Without loss of generality, the degree of spectral dispersion can be quantified by spectral bandwidth and spectral entropy. Short-time energy fluctuations can be quantified by calculating the standard deviation of short-time energy and the rate of change of short-time energy. The standard deviation of short-time energy measures the degree of fluctuation of short-time energy. The larger the standard deviation, the greater the fluctuation of short-time energy.

[0039] The short-time energy standard deviation is expressed as: Where: E[n] represents the short-time energy of the nth frame, is the average value of short-time energy, and the calculation formula is:

[0040]

[0041] On the other hand, the rate of change of short-time energy measures the rate at which short-time energy changes over time. The greater the rate of change, the more drastic the fluctuation of short-time energy.

[0042] Short-time energy change rate formula:

[0043]

[0044] Conditions for judging the degree of spectrum dispersion: Large spectrum bandwidth: When the spectrum bandwidth value exceeds a certain threshold (such as the typical spectrum bandwidth threshold of a music signal), the spectrum is judged to be relatively dispersed. High spectrum entropy: When the spectrum entropy value is close to the maximum value (log 2 N), the spectrum is judged to be relatively dispersed. Short-time energy fluctuation, large short-time energy standard deviation: When the short-time energy standard deviation value exceeds a certain threshold (such as the typical standard deviation threshold of a music signal), it is judged that the short-time energy fluctuation is large. High short-time energy change rate: When the short-time energy change rate value exceeds a certain threshold (such as the typical change rate threshold of a music signal), it is judged that the short-time energy fluctuation is large.

[0045] In a specific judgment example, spectrum bandwidth: calculate the spectrum bandwidth of the audio signal, and determine whether it exceeds the set threshold, such as 800Hz. If it exceeds, it means that the spectrum is relatively dispersed. Spectral entropy: calculate the spectrum entropy of the audio signal. Determine whether it is close to the maximum value (for example, 0.9log2N). If it is close, it means that the spectrum is relatively dispersed. Short-time energy standard deviation: calculate the short-time energy standard deviation of the audio signal. Determine whether it exceeds the set threshold, such as 0.05. If it exceeds, it means that the short-time energy fluctuation is large. Short-time energy change rate: calculate the short-time energy change rate of the audio signal. Determine whether it exceeds the set threshold, such as 0.1. If it exceeds, it means that the short-time energy fluctuation is large. Through the above quantitative indicators and judgment criteria, the degree of spectrum dispersion and short-time energy fluctuation of the audio signal can be effectively judged, so as to better classify the audio signal and use it in compressed sensing classification.

[0046] Optionally, audio signals can be classified through machine learning to distinguish between speech, music, and ambient sound. In particular, in order to adapt to the computing power and power consumption of wireless headphones, machine learning methods are deployed, including but not limited to: support vector machine (SVM), convolutional neural network (CNN), random forest (Random Forest) or other lightweight machine learning algorithms. Generally, machine learning algorithms include a training phase and a testing phase. The training phase uses labeled audio data to train the classification model; the testing phase uses the trained model to classify the preprocessed audio signal.

[0047] In step S200 of some embodiments of the present invention, compressing the target audio signal by using different compression sensing methods on the audio signal based on the sparsity of the audio signal includes:

[0048] S201. For a sparse signal, compressing the audio signal by presetting a sparse basis and a measurement matrix;

[0049] Specifically, for sparse signals (such as speech signals), sparse representation is used for efficient compression. Sparse representation:

[0050] x=Ψs,

[0051] Among them, Ψ is a sparse basis and s is a sparse coefficient vector.

[0052] Then perform compressed sensing on the sparse signal:

[0053] y=Φx=ΦΨs,

[0054] Where Φ is the measurement matrix and y is the compressed signal.

[0055] Next, sparse reconstruction is performed based on the compressed signal:

[0056]

[0057] The sparse coefficient s is recovered by solving this optimization problem, and then the original signal x is restored by x=Ψs.

[0058] S202. For a non-sparse signal, compress the audio signal by using a preset measurement matrix and a regularization method.

[0059] Specifically, for non-sparse signals (such as music signals), an optimized compressed sensing algorithm is used for processing.

[0060] Optimized measurement matrix: Using the designed measurement matrix Φ opt Compression is performed. The measurement matrix is, for example, a Gaussian random matrix;

[0061] y=Φ opt x,

[0062] Optimized sparse reconstruction:

[0063]

[0064] Here, λ is a regularization parameter that controls the balance between sparsity and reconstruction error.

[0065] It can be understood that the audio data after compression sensing is encoded with Polar code to improve the reliability and anti-interference ability of data transmission.

[0066] Therefore, in step S300 of some embodiments of the present invention, encoding the compressed audio signal by using Polar code includes: constructing a generator matrix based on Kronecker powers of a preset kernel matrix; and encoding the compressed audio signal by using the generator matrix.

[0067] Specifically, the Polar code uses the generator matrix G N , which is constructed based on the kernel matrix The Kronecker power of .

[0068]

[0069] Coding process: Encode the compressed sensing data y through the generator matrix.

[0070] u=y·GN.

[0071] The corresponding decoding process is performed by using a successive elimination (SC) algorithm or its improved algorithm (such as SC-List, SC-Flip):

[0072] The SC decoding process is expressed as:

[0073]

[0074] in, is the log-likelihood ratio (LLR) of the ith bit.

[0075] Furthermore, embedding a synchronization code into the encoded audio signal based on the time domain characteristics and frequency domain characteristics includes: based on the short-time energy standard deviation and spectrum bandwidth of the target audio signal as basic data, generating a synchronization code from the basic data and the arrival time of the audio data through an adaptive linear prediction method.

[0076] Specifically, a synchronization code is embedded in the audio signal after compression sensing, and multi-device synchronization is achieved through spectrum watermarking technology. Watermark generation: Generate a watermark signal w that is compatible with the audio signal spectrum, w = generate_watermark(N); Watermark embedding: Embed the watermark signal into the audio signal. z = x^+α·w, where α is the watermark embedding strength.

[0077] Adaptive linear prediction is expressed as:

[0078]

[0079] in: is the predicted value, a i is the linear prediction coefficient; y(ti) is the past output value, b is the input gain, and x(t) is the current input. Update rule: Use the LMS (least mean square error) algorithm to update the prediction coefficient: a i (t+1)=a i (t)+μe(t)y(ti),

[0080] Where: e(t) = y(t) - y^(t) is the prediction error; μ is the step size parameter that controls the update speed.

[0081] Therefore, the synchronization code structure includes: short-time energy standard deviation: Std(E); spectrum bandwidth: SpectralBandwidth; arrival time: T arrival ; Adaptive prediction result: y^(t);

[0082] Therefore, the specific steps of synchronization code generation are: combining the above data to generate synchronization code, which can be done by simple connection or more complex encoding:

[0083]

[0084] It can be seen that by calculating the short-time energy standard deviation and spectrum bandwidth, combining the arrival time of audio data, and generating synchronization codes through adaptive linear prediction, accurate audio synchronization between wireless headphones can be achieved. This method combines the statistical characteristics of audio signals with adaptive prediction technology to improve the accuracy and robustness of synchronization.

[0085] In step S400 of some embodiments of the present invention, synchronizing multiple wireless headsets based on the comparison result of the extracted synchronization code and the embedded synchronization code includes: comparing the synchronization code extracted by each wireless headset with the embedded synchronization code respectively: if the distortion degree of the synchronization code and the embedded synchronization code signal is greater than a threshold, synchronizing the multiple wireless headsets.

[0086] Specifically, the receiving end extracts the watermark signal and performs audio synchronization correction. Watermark extraction: Extract the watermark signal from the received audio signal:

[0087] w′=extract(z),

[0088] Then, synchronization correction is performed by comparing the extracted watermark signal w′ with the original watermark signal w. When the watermark signal w′ is equal to the original watermark signal w, the wireless headset is synchronized.

[0089] In particular, in order to classify different types of audio signals (speech, music, ambient sound), different measurement matrices are used to compress various types of audio signals and generate different synchronization codes; the compressed sensing process is expressed as:

[0090] y voice =Φ voice x voice ,y music =Φ music x music ,

[0091] Combined with Polar code technology, high reliability and low latency of data transmission are ensured. Polar code encoding and decoding are performed on compressed multi-type audio data. The encoding process is expressed as:

[0092] u voicc =y coicc ·G N ,u music =y music ·G N ,

[0093] Then, synchronization correction and optimization: Spectrum watermarking technology is used to perform synchronization correction on various types of audio signals. Multi-device synchronization is achieved by embedding synchronization codes in various types of audio signals. The synchronization code is expressed as:

[0094]

[0095] Example 2

[0096] refer to Figure 3 In a second aspect of the present invention, there is provided an audio synchronization device 1 for wireless headphones based on Polar codes, comprising:

[0097] An acquisition module 11 is used to acquire a target audio signal and extract time domain features and frequency domain features of the target audio signal, and determine the sparsity of the target audio signal based on the time domain features and frequency domain features;

[0098] A compression module 12, configured to compress a target audio signal by using different compression sensing methods on the audio signal based on the sparsity of the audio signal;

[0099] The embedding module 13 is used to encode the compressed audio signal by using the Polar code; based on the time domain characteristics and the frequency domain characteristics, embed the synchronization code into the encoded audio signal;

[0100] The synchronization module 14 is used to receive the audio signal after the synchronization code is embedded, decode the audio signal and extract the synchronization code; based on the comparison result of the extracted synchronization code and the embedded synchronization code, synchronize the multiple wireless headphones.

[0101] Furthermore, the compression module 12 includes: a first compression unit, used to compress the audio signal for a sparse signal by presetting a sparse basis and a measurement matrix; and a second compression unit, used to compress the audio signal for a non-sparse signal by presetting a measurement matrix and a regularization method.

[0102] Example 3

[0103] refer to Figure 4 According to a third aspect of the present invention, an electronic device is provided, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the audio synchronization method of wireless headphones based on Polar codes according to the first aspect of the present invention.

[0104] The electronic device 500 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage device 508 into a random access memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the electronic device 500 are also stored. The processing device 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0105] Typically, the following devices may be connected to the I / O interface 505: an input device 506 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 507 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 508 including, for example, a hard disk, etc.; and a communication device 509. The communication device 509 may allow the electronic device 500 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 4 The electronic device 500 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead. Figure 4 Each block shown in the figure may represent one device, or may represent multiple devices as required.

[0106] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through a communication device 509, or installed from a storage device 508, or installed from a ROM 502. When the computer program is executed by the processing device 501, the above functions defined in the method of the embodiment of the present disclosure are executed. It should be noted that the computer-readable medium described in the embodiment of the present disclosure can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection with one or more conductors, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In an embodiment of the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, an apparatus, or a device. In an embodiment of the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in combination with an instruction execution system, an apparatus, or a device. The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.

[0107] The computer-readable medium may be included in the electronic device, or may exist independently without being installed in the electronic device. The computer-readable medium carries one or more computer programs. When the one or more programs are executed by the electronic device, the electronic device:

[0108] Computer program code for performing the operations of embodiments of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, Python, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on a user's computer, partially on a user's computer, as a separate software package, partially on a user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0109] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0110] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. An audio synchronization method for wireless headphones based on Polar codes, characterized in that: include: Acquire a target audio signal and extract time domain features and frequency domain features of the target audio signal, and determine the sparsity of the target audio signal based on the time domain features and the frequency domain features; Based on the sparsity of the audio signal, different compression sensing methods are used to compress the target audio signal; Encoding the compressed audio signal by using Polar code; embedding a synchronization code into the encoded audio signal based on the time domain characteristics and the frequency domain characteristics; Receiving an audio signal after embedding a synchronization code, decoding the audio signal and extracting the synchronization code; synchronizing a plurality of wireless headsets based on a comparison result of the extracted synchronization code and the embedded synchronization code; Based on the sparsity of the audio signal, using different compressed sensing methods to compress the target audio signal includes: for a sparse signal, compressing the audio signal by presetting a sparse basis and a measurement matrix; for a non-sparse signal, compressing the audio signal by presetting a measurement matrix and a regularization method; The embedding of synchronization code into the encoded audio signal based on the time domain features and frequency domain features includes: based on the short-time energy standard deviation and spectrum bandwidth of the target audio signal as basic data, generating a synchronization code from the basic data and the arrival time of the audio data by an adaptive linear prediction method.

2. The audio synchronization method of wireless headset based on Polar code according to claim 1, characterized in that: Based on the time domain features and frequency domain features, Determining the sparsity of the target audio signal includes: if the short-time energy standard deviation and the spectrum bandwidth are greater than preset values, determining that the target audio signal is a sparse signal.

3. The audio synchronization method of wireless headset based on Polar code according to claim 1, characterized in that: The encoding of the compressed audio signal by using the Polar code includes: constructing a generator matrix based on the Kronecker power of a preset kernel matrix; and encoding the compressed audio signal by using the generator matrix.

4. The audio synchronization method of wireless headset based on Polar code according to claim 1, characterized in that: The synchronizing of multiple wireless headsets based on the comparison result of the extracted synchronization code and the embedded synchronization code includes: comparing the synchronization code extracted by each wireless headset with the embedded synchronization code respectively; if the distortion degree of the synchronization code and the embedded synchronization code signal is greater than a threshold, synchronizing the multiple wireless headsets.

5. An audio synchronization device for wireless headphones based on Polar code, characterized in that: include: An acquisition module, used to acquire a target audio signal and extract time domain features and frequency domain features of the target audio signal, and determine the sparsity of the target audio signal based on the time domain features and frequency domain features; A compression module, used for compressing a target audio signal by using different compression sensing methods on the audio signal based on the sparsity of the audio signal; An embedding module, used to encode the compressed audio signal by using Polar code; and embed a synchronization code into the encoded audio signal based on the time domain characteristics and frequency domain characteristics; A synchronization module, used for receiving an audio signal embedded with a synchronization code, decoding the audio signal and extracting the synchronization code; synchronizing the plurality of wireless headsets based on a comparison result of the extracted synchronization code and the embedded synchronization code; The compression module comprises: a first compression unit, for compressing the audio signal by presetting a sparse basis and a measurement matrix for a sparse signal; a second compression unit, for compressing the audio signal by presetting a measurement matrix and a regularization method for a non-sparse signal; The embedding of synchronization code into the encoded audio signal based on the time domain features and frequency domain features includes: based on the short-time energy standard deviation and spectrum bandwidth of the target audio signal as basic data, generating a synchronization code from the basic data and the arrival time of the audio data by an adaptive linear prediction method.

6. An electronic device comprising: one or more processors; A storage device for storing one or more programs, which, when executed by the one or more processors, enables the one or more processors to implement the audio synchronization method for wireless headphones based on Polar codes as described in any one of claims 1 to 4.

7. A computer readable medium having a computer program stored thereon, wherein: When the computer program is executed by a processor, the audio synchronization method of a wireless headset based on Polar code is implemented as described in any one of claims 1 to 4.

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