A Digital Wireless Audio Signal Noise Reduction Optimization Method Based on Matlab

Abstract

The present invention relates to the technical field of digital signal processing, and specifically relates to a digital wireless audio signal noise reduction optimization method based on Matlab, including: S1, obtaining real-time transmission data of the digital wireless audio signal; S2, performing noise recognition processing on the basis of the real-time transmission data of the digital wireless audio signal to obtain noise type data of the digital wireless audio signal; S3, based on Matlab, performing feature analysis processing on the basis of the real-time transmission data and the noise type data of the digital wireless audio signal to establish a noise feature database of the digital wireless audio signal; S4, using the real-time transmission data and the noise feature database of the digital wireless audio signal to establish a noise reduction model of the digital wireless audio signal based on SVM-LSTM; S5, obtaining a digital wireless audio signal noise reduction optimization result by using the noise reduction model of the digital wireless audio signal; compared with the prior art, the limitations of the existing filtering noise reduction technology are solved, and the accuracy and processing efficiency of noise reduction are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of digital signal processing, and particularly relates to a digital wireless audio signal noise reduction and optimization method based on Matlab. Background Art

[0002] With the development of wireless communication technology, the application of digital wireless audio signals is becoming more and more extensive, such as Bluetooth headsets, wireless microphones, in-vehicle audio systems, etc. However, during the transmission of wireless audio signals, due to various factors, such as electromagnetic interference, multipath propagation, etc., noise will inevitably be mixed into the signals. These noises will seriously affect the quality of audio signals and also affect the user's auditory experience, so noise reduction processing is required.

[0003] The existing noise reduction technologies mainly focus on filtering processing, including time-domain filtering, frequency-domain filtering, spectral subtraction, etc. Although these methods can reduce the influence of noise to a certain extent, they often aim at filtering specific types of noise and have poor adaptability to complex and variable noise environments. They cannot achieve comprehensive noise filtering and are prone to introducing additional noise, resulting in signal distortion, thus affecting the noise reduction effect. At the same time, the high complexity of the algorithms used will lead to signal processing delay, making it difficult to meet the requirements of communication. Summary of the Invention

[0004] Aiming at the deficiencies of the prior art, the present invention provides a digital wireless audio signal noise reduction and optimization method based on Matlab, which realizes effective noise reduction while maintaining low latency in a complex and variable noise environment.

[0005] A digital wireless audio signal noise reduction and optimization method based on Matlab includes:

[0006] S1. Obtain the real-time transmission data of the digital wireless audio signal;

[0007] S2. Perform noise recognition processing according to the real-time transmission data of the digital wireless audio signal to obtain the noise type data of the digital wireless audio signal;

[0008] S3. Based on Matlab, perform feature analysis processing according to the real-time transmission data and noise type data of the digital wireless audio signal to establish a noise feature database of the digital wireless audio signal;

[0009] S4. Use the real-time transmission data and noise feature database of the digital wireless audio signal to establish a noise reduction model of the digital wireless audio signal based on SVM-LSTM;

[0010] S5. Use the noise reduction model of the digital wireless audio signal to obtain the digital wireless audio signal noise reduction and optimization result.

[0011] Further, obtaining the real-time transmission data of the digital wireless audio signal includes:

[0012] S1-1. Obtaining the source data of the digital wireless audio signal;

[0013] S1-2. Respectively obtaining the corresponding sampling environment information data and sampling device information data according to the source data of the digital wireless audio signal;

[0014] S1-3. Using the source data of the digital wireless audio signal, the sampling environment information data and the sampling device information data as the transmission data of the digital wireless audio signal;

[0015] S1-4. Collecting the transmission data of the digital wireless audio signal corresponding to the current moment t as the real-time transmission data of the digital wireless audio signal;

[0016] Among them, the sampling environment information data includes the number of channels, sampling frequency, sampling time and frame structure data, and the sampling device information data includes the MAC address, sampling device voltage and sampling device current.

[0017] Further, performing noise recognition processing according to the real-time transmission data of the digital wireless audio signal to obtain the noise type data of the digital wireless audio signal includes:

[0018] S2-1. Obtaining the historical transmission data of the corresponding digital wireless audio signal according to the real-time transmission data of the digital wireless audio signal;

[0019] S2-2. Obtaining the noise comparison reference of the digital wireless audio signal according to the historical transmission data of the digital wireless audio signal;

[0020] S2-3. Performing noise recognition processing according to the noise comparison reference of the digital wireless audio signal to obtain the noise type data of the digital wireless audio signal.

[0021] Further, obtaining the historical transmission data of the corresponding digital wireless audio signal according to the real-time transmission data of the digital wireless audio signal includes:

[0022] S2-1-1. Obtaining the sampling environment information data and sampling device information data corresponding to the t-n moment according to the real-time transmission data of the digital wireless audio signal;

[0023] S2-1-2. Determine whether the collected environment information data and the collected device information data at the t-n moment are consistent with the collected environment information data and the collected device information data at the t moment. If so, use the collected environment information data and the collected device information data at the t-n moment as the historical transmission data of the digital wireless audio signal. Otherwise, obtain the collected environment information data and the collected device information data that are consistent with the collected environment information data and the collected device information data at the t moment as the historical transmission data of the digital wireless audio signal;

[0024] Among them, t-n is any previous moment corresponding to the current moment, and n is a natural number greater than 1.

[0025] Further, obtaining the noise comparison benchmark of the digital wireless audio signal according to the historical transmission data of the digital wireless audio signal includes:

[0026] S2-2-1. Obtain the historical noise data of the corresponding digital wireless audio signal according to the historical transmission data of the digital wireless audio signal;

[0027] S2-2-2. Perform sampling environment division processing on the historical noise data of the digital wireless audio signal to respectively obtain the channel noise data, the frequency noise data, and the sampling time noise data as the sampling environment noise data;

[0028] S2-2-3. Perform sampling device division processing on the historical noise data of the digital wireless audio signal to obtain the sampling device noise data corresponding to different MAC addresses;

[0029] S2-2-4. Obtain the corresponding sampling environment information data and sampling device information data according to the sampling environment noise data and the sampling device noise data;

[0030] S2-2-5. Use the sampling environment information data and the sampling device information data as the noise comparison benchmark of the digital wireless audio signal.

[0031] Further, performing noise identification processing according to the noise comparison benchmark of the digital wireless audio signal to obtain the noise type data of the digital wireless audio signal includes:

[0032] S2-3-1. Respectively obtain the noise data corresponding to the change of the sampling environment, the noise data corresponding to the change of the sampling device, and the noise data corresponding to the change of the sampling time according to the noise comparison benchmark of the digital wireless audio signal;

[0033] S2-3-2. Establish the first mapping between the sampling environment and the noise according to the noise data corresponding to the change of the sampling environment, and establish the first trend of the noise changing with the sampling environment;

[0034] S2-3-3. Establish a second mapping between the sampling device and the noise based on the noise data that changes with the sampling device, and establish a second trend of the noise changing with the sampling device;

[0035] S2-3-4. Establish a third mapping based on the noise data that changes with the sampling time and the first mapping, and establish a third trend of the noise changing with the sampling time under the same sampling environment;

[0036] S2-3-5. Establish a fourth mapping based on the noise data that changes with the sampling time and the second mapping, and establish a fourth trend of the noise changing with the sampling time under the same sampling device;

[0037] S2-3-6. Determine whether the third trend shows periodic changes. If so, output the sampling environment corresponding to the third trend as fixed noise data; otherwise, output the sampling environment corresponding to the third trend as random noise data;

[0038] S2-3-7. Determine whether the fourth trend shows periodic changes. If so, output the sampling device corresponding to the fourth trend as fixed noise data; otherwise, output the sampling device corresponding to the fourth trend as random noise data;

[0039] S2-3-8. Use the fixed noise data or random noise data as the noise type data of the digital wireless audio signal;

[0040] Wherein, the first trend, the second trend, the third trend and the fourth trend are all the numerical trends of the noise data.

[0041] Further, based on the real-time transmission data and the noise type data of the digital wireless audio signal, perform feature analysis and processing based on Matlab to establish a noise feature database of the digital wireless audio signal, including:

[0042] S3-1. Based on the real-time transmission data of the digital wireless audio signal, perform resampling processing, normalization processing and segmentation and windowing processing in sequence based on Matlab to obtain preprocessing data corresponding to the real-time transmission of the digital wireless audio signal;

[0043] S3-2. Based on the preprocessing data of the real-time transmission of the digital wireless audio signal, perform feature extraction based on Matlab to obtain the time-domain features and frequency-domain features of the corresponding digital wireless audio signal respectively;

[0044] S3-3. Obtain noise data features based on the time-domain features and frequency-domain features of the digital wireless audio signal;

[0045] S3-4. Use the noise data features to establish a noise feature database of the digital wireless audio signal.

[0046] Furthermore, obtaining noise data features according to the time domain features and frequency domain features of the digital wireless audio signal includes:

[0047] S3-3-1. Obtain the historical average frequency corresponding to the digital wireless audio signal;

[0048] S3-3-2 performing frequency segmentation according to the time domain characteristics and frequency domain characteristics of the digital wireless audio signal to obtain a primary region and a secondary region of the digital wireless audio signal respectively;

[0049] S3-3-2-1. Obtain a corresponding frequency image based on the time domain characteristics and frequency domain characteristics of the digital wireless audio signal;

[0050] S3-3-2-2. Perform average frequency segmentation processing on the frequency image of the digital wireless audio signal to obtain corresponding primary and secondary regions;

[0051] S3-3-3. Comparing and analyzing the noise type data of the digital wireless audio signal based on the primary area and the secondary area of the digital wireless audio signal to obtain random noise data;

[0052] S3-3-3-1. Obtain corresponding amplitude features according to the primary area and the secondary area of the digital wireless audio signal;

[0053] S3-3-3-2. Acquire corresponding sampling environment data and sampling equipment data according to the amplitude characteristics;

[0054] S3-3-3-3. Obtain corresponding random noise data based on the noise type data of the digital wireless audio signal according to the sampling environment data and the sampling device data;

[0055] S3-3-4. Acquire, based on the random noise data, signal strength characteristics, amplitude characteristics, and phase characteristics corresponding to the random noise data as noise data characteristics;

[0056] Among them, the average frequency segmentation is to take the absolute value of the historical average frequency, and perform segmentation processing based on the absolute value of the historical average frequency. The main area is the image area with a positive value lower than the average frequency and a negative value higher than the average frequency, and the secondary area is the image area with a positive value higher than the average frequency and a negative value lower than the average frequency.

[0057] Furthermore, establishing a noise reduction model for digital wireless audio signals based on SVM-LSTM using the real-time transmission data of the digital wireless audio signals and the noise feature database includes:

[0058] S4-1. Use the real-time transmission data of the digital wireless audio signal and the historical noise feature data in the noise feature database as the training set, use the noise type data as the validation set, and establish an initial classification model based on SVM;

[0059] S4-2. Input the real-time transmission data of the digital wireless audio signal into the initial classification model to obtain an initial data output result;

[0060] S4-3. Determine whether the initial data output result corresponds to the validation set. If so, execute S4-4; otherwise, use the initial output result as the updated training set and return to S4-1;

[0061] S4-4. Obtain the data features of the real-time transmission data of the digital wireless audio signal;

[0062] S4-5. Compare the data features of the real-time transmission of the digital wireless audio signal with the noise feature database to obtain the denoised data features of the corresponding digital wireless audio signal;

[0063] S4-6. Use the output result of the initial data as the input and the denoised data of the digital wireless audio signal corresponding to the denoised data features of the digital wireless audio signal as the output, and establish a noise reduction training model based on LSTM;

[0064] S4-7. Obtain the initial feature output result of the noise reduction training model, and determine whether the initial feature output result corresponds to the denoised data of the digital wireless audio signal. If so, execute S4-8; otherwise, use the data features of the digital wireless audio data as the input and return to S4-6;

[0065] S4-8. Respectively obtain the denoised data of the digital wireless audio signal at time t and time t+1 and input them into the noise reduction training model to obtain the corresponding model output results;

[0066] S4-9. Determine whether the change trends of the model output results corresponding to time t and time t+1 are consistent. If so, output the initial training model as the noise reduction optimization function model of the digital wireless audio signal; otherwise, obtain the abnormal values with inconsistent change trends as the updated training set and return to S4-1.

[0067] Further, using the noise reduction model of the digital wireless audio signal to obtain the noise reduction optimization result of the digital wireless audio signal includes:

[0068] S5-1. Use the noise reduction model of the digital wireless audio signal to obtain the real-time output result of the denoised data of the corresponding digital wireless audio signal;

[0069] S5-2. Obtain the channel data corresponding to the real-time transmission of the digital wireless audio signal according to the real-time output result of the noise reduction data of the digital wireless audio signal;

[0070] S5-3. Obtain the multi-channel data corresponding to the real-time transmission of the noise reduction data of the digital wireless audio signal according to the channel data corresponding to the real-time transmission of the digital wireless audio signal;

[0071] S5-4. Obtain the corresponding first-channel output data and second-channel output data according to the multi-channel data corresponding to the real-time transmission of the noise reduction data of the digital wireless audio signal;

[0072] S5-5. Determine whether the first-channel output data and the second-channel output data are synchronized. If so, output the first-channel output data and the second-channel output data as the initial noise reduction result of the digital wireless audio signal, and directly execute S5-7. Otherwise, execute S5-6;

[0073] S5-6. Determine whether there is a delay relationship between the second-channel output data and the first-channel output data. If so, use the second-channel output data and the first-channel output data as an updated training set, and return to S4-1. Otherwise, use the first-channel output data and the second-channel output data as the initial noise reduction result of the digital wireless audio signal, and execute S5-7;

[0074] S5-7. Obtain the corresponding signal-to-noise ratio according to the initial noise reduction result of the digital wireless audio signal;

[0075] S5-8. Determine whether the signal-to-noise ratio is lower than the standard signal-to-noise ratio of the historical noise reduction result of the corresponding digital wireless audio signal. If so, output the initial noise reduction result of the digital wireless audio signal as the noise reduction optimization result of the digital wireless audio signal. Otherwise, obtain the multi-channel data corresponding to the real-time transmission of the noise reduction data of the digital wireless audio signal corresponding to the initial noise reduction result.

[0076] Compared with the closest prior art, the beneficial effects of the present invention are:

[0077] The present invention provides a method for optimizing the noise reduction of digital wireless audio signals based on Matlab. By comparing and analyzing the real-time transmission data of digital wireless audio signals, using the noise data under the same acquisition environment and acquisition equipment as a benchmark, the data characteristics of digital wireless audio signals and the noise data characteristics are obtained based on Matlab. A noise reduction model is constructed by combining a support vector machine and a long short-term memory network, which solves the limitations of existing filtering and noise reduction technologies, reduces the dependence on specific noise types, can cope with the changes in complex noise environments, can flexibly identify different types of noises, and effectively reduces the noise of digital wireless audio signals. Compared with the existing technology, the accuracy of noise recognition and the processing efficiency are improved, the signal distortion caused by excessive noise reduction is reduced, and the quality of audio signals is significantly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 is a flowchart of a method for optimizing the noise reduction of digital wireless audio signals based on Matlab according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0079] The following further details the specific embodiments of the present invention with reference to the accompanying drawings.

[0080] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0081] Embodiment 1: The present invention provides a method for optimizing the noise reduction of digital wireless audio signals based on Matlab, as Figure 1 shown, including:

[0082] S1. Obtain the real-time transmission data of digital wireless audio signals;

[0083] S2. Perform noise recognition processing on the real-time transmission data of the digital wireless audio signals to obtain the noise type data of the digital wireless audio signals;

[0084] S3. Based on the real-time transmission data of the digital wireless audio signals and the noise type data, perform feature analysis processing based on Matlab to establish a noise feature database of the digital wireless audio signals;

[0085] S4. Use the real-time transmission data of the digital wireless audio signals and the noise feature database to establish a noise reduction model of the digital wireless audio signals based on SVM-LSTM;

[0086] S5. Obtain the optimized result of digital wireless audio signal noise reduction using the noise reduction model of the digital wireless audio signal.

[0087] S1 specifically includes:

[0088] S1-1. Obtain the source data of the digital wireless audio signal;

[0089] S1-2. Obtain the corresponding sampling environment information data and sampling device information data according to the source data of the digital wireless audio signal;

[0090] S1-3. Use the source data of the digital wireless audio signal, sampling environment information data and sampling device information data as the transmission data of the digital wireless audio signal;

[0091] S1-4. Collect the transmission data of the digital wireless audio signal corresponding to the current moment t as the real-time transmission data of the digital wireless audio signal;

[0092] Among them, the sampling environment information data includes the number of channels, sampling frequency, sampling time and frame structure data, and the sampling device information data includes the MAC address, sampling device voltage and sampling device current.

[0093] S2 specifically includes:

[0094] S2-1. Obtain the historical transmission data of the corresponding digital wireless audio signal according to the real-time transmission data of the digital wireless audio signal;

[0095] S2-2. Obtain the noise comparison benchmark of the digital wireless audio signal according to the historical transmission data of the digital wireless audio signal;

[0096] S2-3. Perform noise identification processing according to the noise comparison benchmark of the digital wireless audio signal to obtain the noise type data of the digital wireless audio signal.

[0097] S2-1 specifically includes:

[0098] S2-1-1. Obtain the sampling environment information data and sampling device information data at the t-n moment according to the real-time transmission data of the digital wireless audio signal;

[0099] S2-1-2. Determine whether the collected environmental information data and the collected device information data at the t-n moment are consistent with those at the t moment. If so, use the collected environmental information data and the collected device information data at the t-n moment as the historical transmission data of the digital wireless audio signal. Otherwise, obtain the collected environmental information data and the collected device information data that are consistent with those at the t moment as the historical transmission data of the digital wireless audio signal;

[0100] Wherein, t-n is any previous moment corresponding to the current moment, and n is a natural number greater than 1.

[0101] S2-2 specifically includes:

[0102] S2-2-1. Obtain the historical noise data of the corresponding digital wireless audio signal according to the historical transmission data of the digital wireless audio signal;

[0103] S2-2-2. Perform sampling environment division processing according to the historical noise data of the digital wireless audio signal to obtain the channel noise data, the frequency noise data, and the sampling time noise data respectively as the sampling environment noise data;

[0104] S2-2-3. Perform sampling device division processing according to the historical noise data of the digital wireless audio signal to obtain the sampling device noise data corresponding to different MAC addresses;

[0105] S2-2-4. Obtain the corresponding sampling environment information data and sampling device information data according to the sampling environment noise data and the sampling device noise data;

[0106] S2-2-5. Use the sampling environment information data and the sampling device information data as the noise comparison benchmark of the digital wireless audio signal.

[0107] S2-3 specifically includes:

[0108] S2-3-1. Obtain the noise data corresponding to the change of the sampling environment, the noise data corresponding to the change of the sampling device, and the noise data corresponding to the change of the sampling time respectively according to the noise comparison benchmark of the digital wireless audio signal;

[0109] S2-3-2. Establish a first mapping between the sampling environment and the noise according to the noise data corresponding to the change of the sampling environment, and establish a first trend of the noise changing with the sampling environment;

[0110] S2-3-3. Establish a second mapping between the sampling device and the noise according to the noise data corresponding to the change of the sampling device, and establish a second trend of the noise changing with the sampling device;

[0111] S2-3-4. Establish a third mapping based on the noise data that changes with the sampling time and the first mapping, and establish a third trend of the noise changing with the sampling time in the same sampling environment;

[0112] S2-3-5. Establish a fourth mapping based on the noise data that changes with the sampling time and the second mapping, and establish a fourth trend of the noise changing with the sampling time under the same sampling device;

[0113] S2-3-6. Determine whether the third trend changes periodically. If so, output the sampling environment corresponding to the third trend as fixed noise data; otherwise, output the sampling environment corresponding to the third trend as random noise data;

[0114] S2-3-7. Determine whether the fourth trend changes periodically. If so, output the sampling device corresponding to the fourth trend as fixed noise data; otherwise, output the sampling device corresponding to the fourth trend as random noise data;

[0115] S2-3-8. Use the fixed noise data or random noise data as the noise type data of the digital wireless audio signal;

[0116] Among them, the first trend, the second trend, the third trend and the fourth trend are all the numerical trends of the noise data.

[0117] S3 specifically includes:

[0118] S3-1. Based on the real-time transmission data of the digital wireless audio signal, perform resampling processing, normalization processing and segmentation windowing processing in sequence using Matlab to obtain the preprocessing data corresponding to the real-time transmission of the digital wireless audio signal;

[0119] S3-2. Based on the preprocessing data corresponding to the real-time transmission of the digital wireless audio signal, perform feature extraction using Matlab to obtain the time-domain features and frequency-domain features of the corresponding digital wireless audio signal respectively;

[0120] S3-3. Obtain the noise data features according to the time-domain features and frequency-domain features of the digital wireless audio signal;

[0121] S3-4. Use the noise data features to establish a noise feature database of the digital wireless audio signal.

[0122] S3-3 specifically includes:

[0123] S3-3-1. Obtain the corresponding historical average frequency of the digital wireless audio signal;

[0124] S3-3-2. Perform frequency segmentation according to the time-domain features and frequency-domain features of the digital wireless audio signal to obtain the main area and the secondary area of the digital wireless audio signal respectively;

[0125] S3-3-2-1. Obtain the corresponding frequency image according to the time-domain characteristics and frequency-domain characteristics of the digital wireless audio signal;

[0126] S3-3-2-2. Perform average frequency segmentation processing on the frequency image of the digital wireless audio signal to obtain the corresponding main region and secondary region;

[0127] S3-3-3. Compare and analyze based on the noise type data of the digital wireless audio signal according to the main region and secondary region of the digital wireless audio signal to obtain random noise data;

[0128] S3-3-3-1. Obtain the corresponding amplitude characteristics according to the main region and secondary region of the digital wireless audio signal respectively;

[0129] S3-3-3-2. Obtain the corresponding sampling environment data and sampling device data according to the amplitude characteristics;

[0130] S3-3-3-3. Obtain the corresponding random noise data based on the sampling environment data and sampling device data according to the noise type data of the digital wireless audio signal;

[0131] S3-3-4. Obtain the signal intensity characteristics, amplitude characteristics and phase characteristics of the corresponding random noise data as noise data characteristics;

[0132] Wherein, the average frequency segmentation is to take the absolute value of the historical average frequency, and perform segmentation processing based on the absolute value of the historical average frequency. The main region is the image region below the positive value of the average frequency and above the negative value of the average frequency, and the secondary region is the image region above the positive value of the average frequency and below the negative value of the average frequency.

[0133] S4 specifically includes:

[0134] S4-1. Use the real-time transmission data of the digital wireless audio signal and the historical noise characteristic data in the noise characteristic database as the training set, and use the noise type data as the verification set to establish an initial classification model based on SVM;

[0135] S4-2. Input the real-time transmission data of the digital wireless audio signal into the initial classification model to obtain an initial data output result;

[0136] S4-3. Judge whether the initial data output result corresponds to the verification set. If so, execute S4-4; otherwise, use the initial output result as the updated training set and return to S4-1;

[0137] S4-4. Obtain the data characteristics of the real-time transmission data of the digital wireless audio signal;

[0138] S4-5. Compare and process the data characteristics of the real-time transmission of the digital wireless audio signal with the noise characteristic database to obtain the denoised data characteristics of the corresponding digital wireless audio signal;

[0139] S4-6. Using the output result of the initial data as the input and the denoised data corresponding to the denoised data characteristics of the digital wireless audio signal as the output, establish a noise reduction training model based on LSTM;

[0140] S4-7. Obtain the initial feature output result of the noise reduction training model, and determine whether the initial feature output result corresponds to the denoised data of the digital wireless audio signal. If so, execute S4-8; otherwise, use the data characteristics of the digital wireless audio data as the input and return to S4-6;

[0141] S4-8. Respectively obtain the denoised data of the digital wireless audio signal at time t and time t + 1 and input them into the noise reduction training model to obtain the corresponding model output results;

[0142] S4-9. Determine whether the change trends of the model output results corresponding to time t and time t + 1 are consistent. If so, output the initial training model as the noise reduction optimization function model of the digital wireless audio signal; otherwise, obtain the abnormal values with inconsistent change trends as the updated training set and return to S4-1.

[0143] S5 specifically includes:

[0144] S5-1. Use the noise reduction model of the digital wireless audio signal to obtain the real-time output result of the denoised data of the corresponding digital wireless audio signal;

[0145] S5-2. Obtain the channel data of the real-time transmission of the corresponding digital wireless audio signal according to the real-time output result of the denoised data of the digital wireless audio signal;

[0146] S5-3. Obtain the multi-channel data of the real-time transmission of the denoised data of the corresponding digital wireless audio signal according to the channel data of the real-time transmission of the digital wireless audio signal;

[0147] S5-4. Obtain the corresponding first-channel output data and second-channel output data according to the multi-channel data of the real-time transmission of the denoised data of the digital wireless audio signal;

[0148] S5-5. Determine whether the output data of the first channel and the output data of the second channel are synchronized. If so, output the output data of the first channel and the output data of the second channel as the initial noise reduction result of the digital wireless audio signal, and directly execute S5-7; otherwise, execute S5-6;

[0149] S5-6. Determine whether there is a delay relationship between the output data of the second channel and the output data of the first channel. If so, use the output data of the second channel and the output data of the first channel as an updated training set, and return to S4-1; otherwise, use the output data of the first channel and the output data of the second channel as the initial noise reduction result of the digital wireless audio signal, and execute S5-7;

[0150] S5-7. Obtain the corresponding signal-to-noise ratio according to the initial noise reduction result of the digital wireless audio signal;

[0151] S5-8. Determine whether the signal-to-noise ratio is lower than the standard signal-to-noise ratio of the historical noise reduction result of the corresponding digital wireless audio signal. If so, output the initial noise reduction result of the digital wireless audio signal as the noise reduction optimization result of the digital wireless audio signal; otherwise, obtain the multi-channel data of the real-time transmission of the digital wireless audio signal noise reduction data corresponding to the initial noise reduction result.

[0152] Those skilled in the art should understand that the embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0153] The present invention is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the processes and / or blocks in the flowchart and / or block diagram can also be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0154] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce a manufacture including an instruction device that implements the functions specified in one or more of the processes Figure 1 one or more processes and / or blocks Figure 1 specified in the block or blocks.

[0155] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in one or more of the processes Figure 1 one or more processes and / or blocks Figure 1 specified in the block or blocks.

[0156] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications or equivalent replacements can still be made to the specific embodiments of the present invention. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention shall be covered by the protection scope of the claims of the present invention.

Claims

1. A digital wireless audio signal noise reduction optimization method based on Matlab, characterized in that, Including: S1. Obtain the real-time transmission data of the digital wireless audio signal; S2. Perform noise recognition processing according to the real-time transmission data of the digital wireless audio signal to obtain the noise type data of the digital wireless audio signal; S2-1. Obtain the historical transmission data of the corresponding digital wireless audio signal according to the real-time transmission data of the digital wireless audio signal; S2-2. Obtain the noise comparison benchmark of the digital wireless audio signal according to the historical transmission data of the digital wireless audio signal; S2-3. Perform noise recognition processing according to the noise comparison benchmark of the digital wireless audio signal to obtain the noise type data of the digital wireless audio signal; S3. Based on Matlab, perform feature analysis processing according to the real-time transmission data and noise type data of the digital wireless audio signal to establish a noise feature database of the digital wireless audio signal; S3-1. Based on Matlab, perform resampling processing, normalization processing, and segmentation and windowing processing in sequence according to the real-time transmission data of the digital wireless audio signal to obtain the preprocessed data of the real-time transmission of the corresponding digital wireless audio signal; S3-2. Based on Matlab, perform feature extraction according to the preprocessed data of the real-time transmission of the digital wireless audio signal to obtain the time-domain feature and frequency-domain feature of the corresponding digital wireless audio signal respectively; S3-3. Obtain the noise data feature according to the time-domain feature and frequency-domain feature of the digital wireless audio signal; S3-4. Use the noise data feature to establish a noise feature database of the digital wireless audio signal; S4. Based on SVM-LSTM, establish a noise reduction model of the digital wireless audio signal by using the real-time transmission data and noise feature database of the digital wireless audio signal; S5. Obtain the noise reduction optimization result of the digital wireless audio signal by using the noise reduction model of the digital wireless audio signal.

2. The digital wireless audio signal noise reduction optimization method based on Matlab according to claim 1, characterized in that, Obtaining the real-time transmission data of the digital wireless audio signal includes: S1-1. Obtain the source data of the digital wireless audio signal; S1-2. Respectively obtain the corresponding sampling environment information data and sampling device information data according to the source data of the digital wireless audio signal; S1-3. Use the source data, sampling environment information data, and sampling device information data of the digital wireless audio signal as the transmission data of the digital wireless audio signal; S1-4. Collect the transmission data of the digital wireless audio signal corresponding to the current moment t as the real-time transmission data of the digital wireless audio signal; Among them, the sampling environment information data includes the number of channels, sampling frequency, sampling time, and frame structure data, and the sampling device information data includes the MAC address, sampling device voltage, and sampling device current.

3. A digital wireless audio signal noise reduction optimization method based on Matlab according to claim 1, characterized in that, Obtaining the historical transmission data of the corresponding digital wireless audio signal according to the real-time transmission data of the digital wireless audio signal includes: S2-1-1. Obtain the acquisition environment information data and acquisition device information data corresponding to the t-n moment according to the real-time transmission data of the digital wireless audio signal; S2-1-2. Determine whether the collected environmental information data and the collected device information data at the t-n moment are consistent with the collected environmental information data and the collected device information data at the t moment. If so, use the collected environmental information data and the collected device information data at the t-n moment as the historical transmission data of the digital wireless audio signal. Otherwise, obtain the collected environmental information data and the collected device information data that are consistent with the collected environmental information data and the collected device information data at the t moment as the historical transmission data of the digital wireless audio signal; Among them, t-n is any previous moment corresponding to the current moment, and n is a natural number greater than 1.

4. A noise reduction optimization method for digital wireless audio signals based on Matlab according to claim 1, characterized in that, Obtaining the noise comparison reference of the digital wireless audio signal according to the historical transmission data of the digital wireless audio signal includes: S2-2-1. Obtain the historical noise data corresponding to the digital wireless audio signal according to the historical transmission data of the digital wireless audio signal; S2-2-2. Perform sampling environment division processing on the historical noise data of the digital wireless audio signal to respectively obtain channel noise data, frequency noise data, and sampling time noise data as sampling environment noise data; S2-2-3. Perform sampling device division processing on the historical noise data of the digital wireless audio signal to obtain sampling device noise data corresponding to different MAC addresses; S2-2-4. Obtain the corresponding sampling environment information data and sampling device information data according to the sampling environment noise data and the sampling device noise data; S2-2-5. Use the sampling environment information data and the sampling device information data as the noise comparison reference of the digital wireless audio signal.

5. A digital wireless audio signal noise reduction optimization method based on Matlab according to claim 1, characterized in that Performing noise identification processing according to the noise comparison reference of the digital wireless audio signal to obtain the noise type data of the digital wireless audio signal includes: S2-3-1. Respectively obtain the noise data corresponding to the change of the sampling environment, the noise data corresponding to the change of the sampling device, and the noise data corresponding to the change of the sampling time according to the noise comparison reference of the digital wireless audio signal; S2-3-2. Establish a first mapping between the sampling environment and the noise according to the noise data corresponding to the change of the sampling environment, and establish a first trend of the noise changing with the sampling environment; S2-3-3. Establish a second mapping between the sampling device and the noise according to the noise data corresponding to the change of the sampling device, and establish a second trend of the noise changing with the sampling device; S2-3-4. Establish a third mapping according to the noise data corresponding to the change of the sampling time and the first mapping, and establish a third trend of the noise changing with the sampling time under the same sampling environment; S2-3-5. Establish a fourth mapping according to the noise data corresponding to the change of the sampling time and the second mapping, and establish a fourth trend of the noise changing with the sampling time under the same sampling device; S2-3-6. Determine whether the third trend changes periodically. If so, output the sampling environment corresponding to the third trend as fixed noise data. Otherwise, output the sampling environment corresponding to the third trend as random noise data; S2-3-7. Determine whether the fourth trend changes periodically. If so, output the sampling device corresponding to the fourth trend as fixed noise data; otherwise, output the sampling device corresponding to the fourth trend as random noise data; S2-3-8. Use the fixed noise data or random noise data as the noise type data of the digital wireless audio signal; Among them, the first trend, the second trend, the third trend, and the fourth trend are all the numerical trends of the noise data.

6. A digital wireless audio signal noise reduction optimization method based on Matlab according to claim 1, characterized in that Obtaining the noise data characteristics according to the time domain characteristics and frequency domain characteristics of the digital wireless audio signal includes: S3-3-1. Obtain the corresponding historical average frequency of the digital wireless audio signal; S3-3-2. Perform frequency segmentation according to the time domain characteristics and frequency domain characteristics of the digital wireless audio signal to obtain the main area and the secondary area of the digital wireless audio signal respectively; S3-3-2-1. Obtain the corresponding frequency image according to the time domain characteristics and frequency domain characteristics of the digital wireless audio signal; S3-3-2-2. Perform average frequency segmentation processing on the frequency image of the digital wireless audio signal to obtain the corresponding main area and secondary area; S3-3-3. Compare and analyze the main area and the secondary area of the digital wireless audio signal based on the noise type data of the digital wireless audio signal to obtain random noise data; S3-3-3-1. Obtain the corresponding amplitude characteristics according to the main area and the secondary area of the digital wireless audio signal respectively; S3- ​ ​ ​ 7. A noise reduction optimization method for digital wireless audio signals based on Matlab according to claim 1, characterized in that ​ ​ ​ ​ ​ S4-5. Compare and process the data characteristics of the real-time transmission of the digital wireless audio signal with the noise characteristics database to obtain the denoised data characteristics of the corresponding digital wireless audio signal; S4-6. Using the initial data output result as the input and the denoised data corresponding to the denoised data characteristics of the digital wireless audio signal as the output, establish a noise reduction training model based on LSTM; S4-7. Obtain the initial feature output result of the noise reduction training model, and determine whether the initial feature output result corresponds to the denoised data of the digital wireless audio signal. If so, execute S4-8; otherwise, use the denoised data characteristics of the digital wireless audio signal as the input and return to S4-6; S4-8. Respectively obtain the denoised data of the digital wireless audio signal at time t and time t+1 and input them into the noise reduction training model to obtain the corresponding model output results; S4-9. Determine whether the change trends of the model output results corresponding to time t and time t+1 are consistent. If so, output the noise reduction training model as the noise reduction model of the digital wireless audio signal; otherwise, obtain the outliers with inconsistent change trends as the updated training set and return to S4-1.

8. A digital wireless audio signal noise reduction optimization method based on Matlab according to claim 7, characterized in that Obtaining the digital wireless audio signal noise reduction optimization result by using the noise reduction model of the digital wireless audio signal includes: S5-1. Use the noise reduction model of the digital wireless audio signal to obtain the real-time output result of the denoised data of the corresponding digital wireless audio signal; S5-2. Obtain the channel data of the real-time transmission of the corresponding digital wireless audio signal according to the real-time output result of the denoised data of the digital wireless audio signal; S5-3. Obtain the multi-channel data of the real-time transmission of the denoised data of the corresponding digital wireless audio signal according to the channel data of the real-time transmission of the digital wireless audio signal; S5-4. Obtain the corresponding first-channel output data and second-channel output data according to the multi-channel data of the real-time transmission of the denoised data of the digital wireless audio signal; S5-5. Determine whether the first-channel output data and the second-channel output data are synchronized. If so, output the first-channel output data and the second-channel output data as the initial noise reduction result of the digital wireless audio signal and directly execute S5-7; otherwise, execute S5-6; S5-6. Determine whether there is a delay relationship between the second-channel output data and the first-channel output data. If so, use the second-channel output data and the first-channel output data as the updated training set and return to S4-1; otherwise, use the first-channel output data and the second-channel output data as the initial noise reduction result of the digital wireless audio signal and execute S5-7; S5-7. Obtain the corresponding signal-to-noise ratio according to the initial noise reduction result of the digital wireless audio signal; S5-8. Determine whether the signal-to-noise ratio is lower than the historical noise reduction result standard signal-to-noise ratio of the corresponding digital wireless audio signal. If so, output the initial noise reduction result of the digital wireless audio signal as the noise reduction optimization result of the digital wireless audio signal. Otherwise, obtain the multi-channel data of the real-time transmission of the digital wireless audio signal noise reduction data corresponding to the initial noise reduction result.

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