Microphone audio signal correction method, system and device and storage medium

Abstract

The invention relates to the technical field of audio systems, in particular to a microphone audio signal correction method, system and device and a storage medium. The method comprises the steps of firstly obtaining an audio correction mode and a target parameter, and determining an overall audio correction parameter; then setting personalized correction parameters for each channel in combination with microphone channel information; performing audio correction processing according to the overall and personalized parameters; then, quality detection is carried out on the corrected audio, if a detection result is different from a target parameter and exceeds a threshold value, audio quality monitoring is triggered, parameter adjustment information is obtained, personalized correction parameters are dynamically updated according to the information, the audio can be processed more comprehensively by combining the overall and personalized parameters, meanwhile, the personalized parameters are adjusted in a self-adaptive mode, and the user experience is improved. The processing effect can be continuously optimized, the self-adaptive adjustment capability is improved, and the ideal noise reduction capability is kept.

Description

Technical Field

[0001] The present application relates to the technical field of audio systems, and in particular to a microphone audio signal correction method, system, device and storage medium. Background Art

[0002] With the continuous development of voice interaction technology, microphone arrays are widely used in various voice interaction devices. Microphone arrays can effectively capture target voice signals while suppressing interference such as environmental noise and echo, which is the key to achieving high-quality voice input. However, complex actual environments will bring severe challenges to the performance of microphone arrays, so it is necessary to perform appropriate correction processing on microphone audio signals.

[0003] The prior art usually uses an adaptive filtering algorithm based on noise spectrum estimation to perform noise suppression processing on microphone audio signals. This type of algorithm first estimates the ambient noise spectrum, then designs an adaptive filter based on the noise spectrum, filters each microphone channel, and suppresses noise interference. The prior art usually assumes that the noise is stationary, but the noise in the actual environment is often non-stationary. The prior art lacks adaptive adjustment capabilities and cannot dynamically optimize parameters according to environmental changes, resulting in the processing effect being difficult to guarantee in complex environments. This situation needs to be further improved. Summary of the invention

[0004] In order to solve the problem that the existing audio signal correction method lacks adaptive adjustment capability, the present application provides a microphone audio signal correction method, system, device and storage medium, which adopts the following technical solutions: In a first aspect, the present application provides a microphone audio signal calibration method, comprising the following steps: Acquire an audio correction mode and a target parameter, and acquire an overall audio correction parameter according to the audio correction mode and the target parameter; Acquire microphone channel information, and set personalized correction parameters for the microphone channel according to the microphone channel information and the overall audio correction parameters; Performing audio correction according to the personalized correction parameter and the overall audio correction parameter; Performing quality detection on the corrected audio to obtain audio detection parameters; comparing the audio detection parameters with the target parameters to obtain parameter difference values; If the parameter difference value exceeds a preset threshold, audio quality monitoring is triggered; and parameter adjustment information is obtained according to the audio quality monitoring result; The personalized correction parameters are updated according to the parameter adjustment information.

[0005] By adopting the above-mentioned technical scheme, the present application first obtains the audio correction mode and target parameters to determine the overall audio correction parameters; then combines the microphone channel information to set personalized correction parameters for each channel; performs audio correction processing according to the overall and personalized parameters; then, performs quality detection on the corrected audio. If the detection result differs from the target parameter and exceeds the threshold, audio quality monitoring is triggered, parameter adjustment information is obtained, and personalized correction parameters are dynamically updated based on the information. Combining the overall and personalized parameters, the audio can be processed more comprehensively. At the same time, the personalized parameters are adaptively adjusted to continuously optimize the processing effect, improve the adaptive adjustment capability, and maintain a more ideal noise reduction capability.

[0006] Optionally, the step of acquiring the audio correction mode and the target parameters, and acquiring the overall audio correction parameters according to the audio correction mode and the target parameters, specifically comprises the following steps: Extracting a target signal-to-noise ratio from the target parameters, and using the target signal-to-noise ratio as a main noise suppression target; Acquire noise estimation parameters, adaptive filter parameters, and pre-processing parameters according to the target signal-to-noise ratio and the audio correction mode; The target signal-to-noise ratio, noise estimation parameters, adaptive filter parameters and pre-processing parameters are associated to obtain the overall audio correction parameters.

[0007] By adopting the above technical solution, the present application first extracts the target signal-to-noise ratio from the target parameters as the main noise suppression target; then obtains the noise estimation parameters, adaptive filter parameters and pre-processing parameters according to the target signal-to-noise ratio and the audio correction mode; finally, the target signal-to-noise ratio, noise estimation parameters, filter parameters and pre-processing parameters are associated to obtain the overall audio correction parameters that meet the requirements.

[0008] Optionally, the pre-processing parameters include pre-emphasis filter parameters and de-pre-emphasis filter parameters, and the noise estimation parameters include noise spectrum estimation parameters and noise tracking factor parameters. The step of acquiring noise estimation parameters, adaptive filter parameters and pre-processing parameters according to the target signal-to-noise ratio and the audio correction mode specifically comprises the following steps: According to the target signal-to-noise ratio and the audio correction mode, acquiring the pre-emphasis filter parameters, the de-pre-emphasis filter parameters, the noise spectrum estimation parameters, the noise tracking factor parameters and the adaptive filter parameters; The noise estimation parameter is acquired according to the noise spectrum estimation parameter and the noise tracking factor parameter.

[0009] By adopting the above technical solution, the present application first obtains the pre-emphasis filter parameters, de-pre-emphasis filter parameters, noise spectrum estimation parameters, noise tracking factor parameters and adaptive filter parameters according to the target signal-to-noise ratio and the audio correction mode, and then combines the noise spectrum estimation parameters and the noise tracking factor parameters to obtain the final noise estimation parameters; the pre-processing and noise estimation links are subdivided, and the parameters of each sub-link can be finely controlled.

[0010] Optionally, the personalized correction parameters include channel noise suppression parameters and channel feedback suppression parameters, and the acquiring of microphone channel information and setting of personalized correction parameters for the microphone channel according to the microphone channel information and the overall audio correction parameters specifically include the following steps: Obtain microphone channel position information and channel noise characteristic information; Acquire channel pre-processing parameters for the microphone channel according to the pre-processing parameters, the channel position information and the channel noise characteristic information; The channel noise suppression parameter and the channel feedback suppression parameter are obtained for the microphone channel according to the noise estimation parameter, the adaptive filter parameter, the channel position information and the channel noise characteristic information.

[0011] By adopting the above-mentioned technical scheme, since different microphone channels have different noise characteristics and feedback conditions due to differences in position and environment, the present application obtains corresponding channel pre-processing parameters, channel noise suppression parameters and channel feedback suppression parameters for each channel based on the position information and noise characteristic information of the microphone channel, combined with the pre-processing parameters, noise estimation parameters and adaptive filter parameters in the overall audio correction parameters, as personalized correction parameters for the channel, which can more accurately reflect the actual status of each microphone channel and form a good coordination with the overall strategy, thereby achieving high-quality noise reduction in complex environments.

[0012] Optionally, obtaining parameter adjustment information according to the audio quality monitoring result specifically includes the following steps: Acquiring audio quality change information according to the audio quality monitoring result; Acquire quality abnormality trigger information, and trigger an environmental detection instruction according to the quality abnormality trigger information; Acquire environment detection result information, and acquire current audio processing state information according to the environment detection result information and the audio quality change information; Parameter adjustment information is obtained according to the current audio processing state information and the overall audio correction parameter.

[0013] By adopting the above-mentioned technical solution, when audio quality monitoring finds that the quality indicators have changed, it is necessary to analyze the reasons for the changes and make corresponding adjustments. This application obtains the current audio processing status information based on the environmental detection result information and the previously obtained audio quality change information. When the audio quality is abnormal, it can actively diagnose the environment, analyze the status, and make targeted parameter adjustments, thereby improving the timeliness and pertinence of the adjustments.

[0014] Optionally, updating the personalized correction parameter according to the parameter adjustment information specifically includes the following steps: According to the parameter adjustment information, obtaining personalized parameter adjustment information, wherein the personalized parameter adjustment information includes an adjusted channel noise suppression parameter and an adjusted channel feedback suppression parameter; Comparing the adjusted channel noise suppression parameter and the adjusted channel feedback suppression parameter with a preset parameter threshold, and if they are within the threshold range, updating the personalized correction parameter according to the personalized parameter adjustment information; If it exceeds the threshold range, a parameter secondary adjustment instruction is triggered, and secondary adjustment parameter information is obtained according to the parameter secondary adjustment instruction, and the personalized correction parameter is updated according to the secondary adjustment parameter information.

[0015] By adopting the above technical solution, the present application first obtains the adjusted personalized parameters according to the parameter adjustment information, and then compares it with the preset threshold value. The update operation is performed only within the threshold range; if the adjusted parameters exceed the expected range, a secondary adjustment procedure will be triggered, and the parameter value will be re-determined according to the secondary adjustment information before updating. This avoids parameter abnormalities, ensures that the adjustment is within a controllable range, and improves the stability and processing quality of the overall system.

[0016] In a second aspect, the present application provides a microphone audio signal correction system, comprising: An audio correction mode acquisition module, used to acquire an audio correction mode; A target parameter acquisition module is used to obtain target parameters; An overall parameter generation module, used for acquiring overall audio correction parameters according to the audio correction mode and the target parameters; A channel parameter setting module, used to obtain microphone channel information, and set personalized correction parameters for each microphone channel according to the microphone channel information and the overall audio correction parameters; An audio correction module, used for performing audio correction according to the personalized correction parameters and the overall audio correction parameters; A quality detection module is used to perform quality detection on the corrected audio and obtain audio detection parameters; A difference acquisition module, used for comparing the audio detection parameter with the target parameter to obtain a parameter difference value; An adaptive adjustment trigger module, used to trigger audio quality monitoring when the parameter difference value exceeds a preset threshold; A parameter adjustment module, used for obtaining parameter adjustment information according to the adaptive adjustment mechanism; A parameter updating module is used to update the personalized correction parameters according to the parameter adjustment information.

[0017] Optionally, the parameter updating module includes: A personalized parameter adjustment unit, configured to obtain personalized parameter adjustment information according to the parameter adjustment information, wherein the personalized parameter adjustment information includes an adjusted channel noise suppression parameter and an adjusted channel feedback suppression parameter; A parameter threshold comparison unit, used for comparing the adjusted channel noise suppression parameter and the adjusted channel feedback suppression parameter with a preset parameter threshold; a parameter updating unit, configured to update the personalized correction parameter according to the personalized parameter adjustment information when the adjusted parameter is within a threshold range; A secondary adjustment trigger unit, used for triggering a parameter secondary adjustment instruction when the adjusted parameter exceeds a threshold range; A secondary adjustment parameter acquisition unit, used to acquire secondary adjustment parameter information according to the parameter secondary adjustment instruction; The parameter updating unit is further configured to update the personalized correction parameter according to the secondary adjustment parameter information.

[0018] In a third aspect, the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned microphone audio signal correction method when executing the computer program.

[0019] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the above-mentioned microphone audio signal correction method are implemented.

[0020] In summary, the present application includes at least one of the following beneficial technical effects: 1. This application first obtains the audio correction mode and target parameters to determine the overall audio correction parameters; then combines the microphone channel information to set personalized correction parameters for each channel; performs audio correction processing according to the overall and personalized parameters; then, performs quality detection on the corrected audio. If the detection result differs from the target parameter and exceeds the threshold, the audio quality monitoring is triggered, the parameter adjustment information is obtained, and the personalized correction parameters are dynamically updated according to the information. By combining the overall and personalized parameters, the audio can be processed more comprehensively. At the same time, the personalized parameters are adaptively adjusted, which can continuously optimize the processing effect, improve the adaptive adjustment capability, and maintain a relatively ideal noise reduction capability; 2. The present application first obtains the pre-emphasis filter parameters, the de-pre-emphasis filter parameters, the noise spectrum estimation parameters, the noise tracking factor parameters and the adaptive filter parameters according to the target signal-to-noise ratio and the audio correction mode, and then combines the noise spectrum estimation parameters and the noise tracking factor parameters to obtain the final noise estimation parameters; the pre-processing and noise estimation links are subdivided, and the parameters of each sub-link can be finely controlled; 3. This application obtains corresponding channel pre-processing parameters, channel noise suppression parameters and channel feedback suppression parameters for each channel based on the position information and noise characteristic information of the microphone channel, combined with the pre-processing parameters, noise estimation parameters and adaptive filter parameters in the overall audio correction parameters, as personalized correction parameters for the channel, which can more accurately reflect the actual status of each microphone channel and form a good coordination with the overall strategy, thereby achieving high-quality noise reduction in complex environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a flowchart of a microphone audio signal correction method according to an embodiment of the present application; Figure 2 It is a flowchart of step S10 in a microphone audio signal correction method according to an embodiment of the present application; Figure 3 It is a flowchart of step S22 in a microphone audio signal correction method according to an embodiment of the present application; Figure 4 It is a flowchart of step S30 in a microphone audio signal correction method according to an embodiment of the present application; Figure 5 It is a flowchart of step S40 in a microphone audio signal correction method according to an embodiment of the present application; Figure 6 It is a flowchart of step S60 in a microphone audio signal correction method according to an embodiment of the present application; Figure 7 It is a module schematic diagram of a microphone audio signal correction system according to an embodiment of the present application; Figure 8It is a diagram of the internal structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0022] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification and appended claims of the present application, the singular expressions "one", "a kind of", "said", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more listed items.

[0023] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0024] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0025] In a first aspect, the present application provides a microphone audio signal correction method, referring to Figure 1 , including the following steps: S10: Obtain an audio correction mode and target parameters, and obtain overall audio correction parameters according to the audio correction mode and target parameters.

[0026] In this embodiment, the audio correction mode refers to the correction strategy for different preset scenarios, such as conference mode, mobile phone mode, headphone mode, etc. The target parameter is the expected audio quality indicator, such as target signal-to-noise ratio, target speech fidelity, etc. The overall audio correction parameter is a system-level parameter set used to guide the subsequent correction operations of all channels.

[0027] Specifically, the system provides multiple audio correction mode options for users to choose from, or automatically determines the applicable mode based on the current scene analysis. Then, key indicators are extracted from the target parameters as the main correction targets, such as the target signal-to-noise ratio as the main noise suppression target. According to the selected mode and target indicators, the parameter lookup table is queried to obtain the corresponding noise estimation parameters, adaptive filter parameters, pre-processing parameters, etc., and the overall audio correction parameter set is generated based on the combination of these parameters.

[0028] S20: Acquire microphone channel information, and set personalized correction parameters for the microphone channel according to the microphone channel information and the overall audio correction parameters.

[0029] In this embodiment, the microphone channel information includes the position information of each microphone channel and the noise characteristic information of the channel; the personalized correction parameter refers to a set of correction parameters for each specific channel, which is used to guide the noise reduction, feedback suppression and other operations of the channel.

[0030] Specifically, by acquiring the microphone channel information, and then matching appropriate personalized correction parameters for each channel according to the microphone channel information and the overall audio correction parameters, the personalized parameters of different channels will be different.

[0031] S30: Perform audio correction according to the personalized correction parameters and the overall audio correction parameters.

[0032] In this embodiment, audio correction is a processing process performed on the original audio signal received from the microphone, including pre-processing, noise reduction, feedback suppression, etc.

[0033] Specifically, for the original audio signal of each channel, the corresponding personalized pre-processing parameters are first used to perform pre-processing operations such as pre-emphasis filtering and de-pre-emphasis filtering, and then noise detection and noise suppression are performed. Finally, the audio signal is feedback suppressed to eliminate howling and other problems. After all channels complete the above corrections, the final optimized audio output is obtained.

[0034] S40, performing quality detection on the corrected audio to obtain audio detection parameters; comparing the audio detection parameters with target parameters to obtain parameter difference values.

[0035] In this embodiment, quality detection refers to analyzing and evaluating the audio output after correction processing to obtain detection parameters reflecting audio quality, such as actual signal-to-noise ratio, speech fidelity score, etc. These detection parameters are then compared with pre-set target parameters to calculate the difference between the two.

[0036] Specifically, an audio quality assessment algorithm is used to perform spectrum analysis, distortion detection, speech clarity scoring, etc. on the corrected audio to obtain quality parameters such as actual signal-to-noise ratio and speech fidelity score. These parameters are compared one by one with the target signal-to-noise ratio, target speech fidelity and other target parameters set in step S10, and the corresponding difference values ​​are calculated to evaluate whether the current correction effect meets the standard.

[0037] S50. If the parameter difference value exceeds a preset threshold, audio quality monitoring is triggered; and parameter adjustment information is obtained according to the audio quality monitoring result.

[0038] If the parameter difference exceeds the threshold, it means that the current correction effect is significantly different from the expected one. At this time, it is necessary to start the audio quality monitoring mechanism and conduct an in-depth analysis of the reasons for the quality degradation. Based on the monitoring and analysis results, the parameter information that needs to be adjusted is obtained, which provides a basis for the next parameter update.

[0039] Specifically, this application sets a difference threshold range, such as a signal-to-noise ratio difference within 3dB and a speech fidelity score difference within 0.2 points, which is considered acceptable. If the difference value is detected to be beyond the threshold range, the audio quality is considered poor, and the system automatically triggers the audio quality monitoring process, including: detecting the current environmental noise situation, checking the microphone array status, analyzing whether the voice pattern has changed, etc., and querying the problem-parameter mapping table according to the type of problem found in the monitoring, obtaining the parameter items and adjustment methods that need to be adjusted, and outputting them as parameter adjustment information.

[0040] S60: Update the personalized correction parameters according to the parameter adjustment information.

[0041] Specifically, the parameter items that need to be adjusted are parsed from the parameter adjustment information, such as the need to increase the noise suppression strength of a certain channel, increase the feedback suppression coefficient of a certain channel, etc. Then, according to the adjustment method, the original personalized noise suppression parameters, feedback suppression parameters, etc. are adjusted accordingly to obtain an updated personalized correction parameter set.

[0042] In one embodiment, referring to Figure 2 In step S10, the audio correction mode and target parameters are obtained, and the overall audio correction parameters are obtained according to the audio correction mode and target parameters, which specifically includes the following steps: S21. Extracting a target signal-to-noise ratio from the target parameters, and taking the target signal-to-noise ratio as a main noise suppression target.

[0043] The target signal-to-noise ratio refers to the signal-to-noise ratio level that the final audio output should achieve. In this embodiment, the target signal-to-noise ratio is used as the main noise suppression target and the main optimization direction of the correction.

[0044] Specifically, the target signal-to-noise ratio parameter is extracted from the target parameter set by the user or the system default. If the user does not set it specifically, the corresponding recommended target signal-to-noise ratio value can be found according to the current audio correction mode (such as conference mode) and used as the system default value.

[0045] S22. Acquire noise estimation parameters, adaptive filter parameters, and pre-processing parameters according to the target signal-to-noise ratio and the audio correction mode.

[0046] In this embodiment, effective noise reduction and anti-echo are achieved specifically through noise estimation parameters, adaptive filter parameters and pre-processing parameters. Different target signal-to-noise ratios and correction modes have different corresponding setting requirements for noise estimation parameters, adaptive filter parameters and pre-processing parameters.

[0047] Specifically, this embodiment pre-establishes a lookup table, and stores corresponding noise estimation algorithm type, algorithm parameters, adaptive filter type, filter length, pre-processing filter type and other parameter configuration schemes according to different combinations of target signal-to-noise ratio and audio mode. After determining the target signal-to-noise ratio and the current correction mode, the lookup table is searched to obtain the matching noise estimation parameter set, adaptive filter parameter set and pre-processing parameter set.

[0048] S23, obtaining overall audio correction parameters according to the association of the target signal-to-noise ratio, the noise estimation parameters, the adaptive filter parameters and the pre-processing parameters.

[0049] Specifically, according to the target signal-to-noise ratio, a noise suppression strength adjustment coefficient is set, and then the noise suppression strength adjustment coefficient is combined with the noise estimation parameter to obtain the desired noise detection threshold, smoothing factor and other specific noise estimation sub-parameters, and then the adjustment coefficient is simultaneously applied to the adaptive filter parameters to obtain specific sub-parameters such as filter length and adaptive step size. Finally, the pre-processing parameters are fused with the previous parameter set to generate a comprehensive overall audio correction parameter set containing various sub-parameter items.

[0050] In one embodiment, referring to Figure 3 In step S22, the pre-processing parameters include pre-emphasis filter parameters and de-pre-emphasis filter parameters, and the noise estimation parameters include noise spectrum estimation parameters and noise tracking factor parameters. According to the target signal-to-noise ratio and the audio correction mode, noise estimation parameters, adaptive filter parameters and pre-processing parameters are obtained, which specifically includes the following steps: S221. According to the target signal-to-noise ratio and the audio correction mode, obtain pre-emphasis filter parameters, de-pre-emphasis filter parameters, noise spectrum estimation parameters, noise tracking factor parameters and adaptive filter parameters.

[0051] Specifically, according to different combinations of target signal-to-noise ratio and audio mode, corresponding parameter configuration schemes such as pre-emphasis filter type and order, de-pre-emphasis filter type and order, noise spectrum estimation algorithm type and smoothing factor, noise tracking rate factor, adaptive filter type and length are stored.

[0052] In the above-mentioned lookup table, a parameter configuration scheme matching the input target signal-to-noise ratio and audio mode is retrieved, from which the pre-emphasis filter type and its order, the de-pre-emphasis filter type and its order are read out respectively as pre-emphasis / de-pre-emphasis filter parameters; at the same time, the noise spectrum estimation algorithm type and its smoothing factor are read out as noise spectrum estimation parameters; the rate factor of noise tracking is read out as a noise tracking factor parameter; and the adaptive filter type and its length are read out as adaptive filter parameters.

[0053] S222. Obtain noise estimation parameters according to noise spectrum estimation parameters and noise tracking factor parameters.

[0054] Specifically, a final noise estimation parameter set is constructed based on the noise spectrum estimation parameters and the noise tracking factor parameters.

[0055] In one embodiment, referring to Figure 4 In step S30, the personalized correction parameters include channel noise suppression parameters and channel feedback suppression parameters, and the microphone channel information is obtained. According to the microphone channel information and the overall audio correction parameters, the personalized correction parameters are set for the microphone channel, which specifically includes the following steps: S31. Obtain microphone channel position information and channel noise characteristic information.

[0056] In this embodiment, the microphone channel position information refers to the specific geometric position of the microphone in the array, and the channel noise characteristic information describes the type, spectrum distribution, and time duration characteristics of the noise to which the channel is subjected.

[0057] Specifically, the three-dimensional coordinate position of each microphone channel in the microphone array is automatically obtained. At the same time, the background noise of each channel is detected by the noise monitoring unit, and its spectrum power, duration, change rate, etc. are analyzed to form the noise characteristic data of the channel.

[0058] S32. Acquire channel pre-processing parameters for the microphone channel according to the pre-processing parameters, channel position information, and channel noise characteristic information.

[0059] In this embodiment, the channel pre-processing parameters are used to perform pre-processing such as pre-emphasis and de-pre-emphasis on the original audio signal of the channel to improve the subsequent noise reduction effect. Different channels have different locations and noise characteristics, and the pre-processing parameters required will also be different.

[0060] Specifically, the present application presets a lookup table, divides all possible situations into several gears according to the channel position and noise type (such as low-frequency noise, high-frequency noise), and stores the corresponding pre-emphasis filter type, order, de-emphasis filter type, order and other pre-processing parameter configurations for each gear; after obtaining the channel position and noise information, search the matching gear in the lookup table, read out the corresponding pre-processing parameter set, and use it as the personalized pre-processing parameter of the channel. Optionally, the farther away from the sound source, the higher the gear setting, and the higher the noise frequency, the higher the gear setting.

[0061] S33. Obtain channel noise suppression parameters and channel feedback suppression parameters for the microphone channel according to the noise estimation parameters, the adaptive filter parameters, the channel position information, and the channel noise characteristic information.

[0062] In this embodiment, the channel noise suppression parameter is used to guide the noise detection and suppression operation of the channel, and the channel feedback suppression parameter is used to guide anti-howling and echo suppression.

[0063] Similarly, a lookup table can be preset to store the corresponding noise suppression sub-parameters such as noise detection threshold and smoothing length, as well as the configuration scheme of feedback suppression sub-parameters such as adaptive filter length and adaptive step size for each situation according to different combinations of factors such as channel position and noise type. After obtaining the channel position and noise information, the matching scheme is retrieved in the lookup table, and the corresponding noise suppression parameter set and feedback suppression parameter set are read out. At the same time, these parameters are respectively fused with the noise estimation parameters and adaptive filter parameters in the overall parameters to form the final noise suppression and feedback suppression parameters of the channel.

[0064] In one embodiment, referring to Figure 5 In step S40, parameter adjustment information is obtained according to the audio quality monitoring result, which specifically includes the following steps: S41. Obtain audio quality change information according to the audio quality monitoring result.

[0065] In this embodiment, the audio quality change information reflects the change trend of the current audio quality relative to the expected target, such as continuous quality decline, sudden deterioration or fluctuation.

[0066] Specifically, this embodiment continuously tracks key indicators in the audio quality monitoring results, such as real-time signal-to-noise ratio, speech fidelity score, etc., and compares them with previous historical values. If a continuous downward trend is detected in these indicators, it is determined that the audio quality continues to deteriorate; if a large quality distortion suddenly occurs, it is determined that the audio quality suddenly deteriorates; if the indicator value fluctuates greatly, it is determined that the audio quality is unstable, etc.

[0067] S42: Acquire quality abnormality trigger information, and trigger an environmental detection instruction according to the quality abnormality trigger information.

[0068] In this embodiment, the quality abnormality trigger information refers to some criteria conditions pre-set in the system, which are used to determine whether the current audio quality is abnormal enough to require detection and diagnosis of the environment. Once the audio quality change information is detected to match these conditions, the system will automatically trigger the relevant instructions for environmental detection.

[0069] Specifically, set quality abnormality trigger conditions such as "quality continues to deteriorate for more than 5 minutes", "quality suddenly deteriorates by more than 5dB", "quality fluctuations exceed 3dB and last for more than 2 minutes". These conditions can be set in advance based on experience, or they can be adjusted through self-learning during system operation. When the monitored audio quality change information, such as the real-time signal-to-noise ratio drop, the voice fidelity score drop, and other indicator values ​​meet these conditions, the system will determine that the audio quality is abnormal and immediately trigger the environment detection command.

[0070] S43: Obtain environment detection result information, and obtain current audio processing state information based on the environment detection result information and the audio quality change information.

[0071] In this embodiment, the current audio processing state information reflects the specific reasons for the degradation of audio quality, such as changes in environmental noise, microphone failure, or voice mode switching.

[0072] Specifically, the system detects whether the noise exceeds the system's adaptability through environmental detection, and checks whether the operating status of each microphone channel in the microphone array is normal. The system analyzes these detection results together with the previously acquired audio quality change information (such as continuous quality degradation, sudden deterioration, or unstable fluctuations) to determine the current audio processing status, such as being affected by a certain type of sudden noise, due to the failure of a microphone channel, or the voice mode switching from a conference to a video call.

[0073] S44: Obtain parameter adjustment information according to the current audio processing state information and the overall audio correction parameters.

[0074] Specifically, according to the current processing status information obtained in the previous step, find the parameter adjustment strategy that matches it. For example, when encountering a certain type of low-frequency noise, increase the smoothing length in the noise suppression parameters of certain channels, lower the detection threshold, etc.; when encountering a microphone channel failure, increase the weights of other channels, and appropriately adjust the adaptive filter parameters, etc.

[0075] In one embodiment, referring to Figure 6 In step S60, the personalized correction parameters are updated according to the parameter adjustment information, which specifically includes the following steps: S61. Obtain personalized parameter adjustment information according to the parameter adjustment information.

[0076] The personalized parameter adjustment information includes the adjusted channel noise suppression parameter and the adjusted channel feedback suppression parameter.

[0077] Specifically, by traversing all adjustment items contained in the parameter adjustment information, the channel noise suppression sub-parameters (such as smoothing length, detection threshold, etc.) and feedback suppression sub-parameters (such as adaptive filter length, adaptive step size, etc.) involved are classified according to channels to form a personalized adjustment subset for each channel.

[0078] S62: Compare the adjusted channel noise suppression parameter and the adjusted channel feedback suppression parameter with a preset parameter threshold, and if they are within the threshold range, update the personalized correction parameter according to the personalized parameter adjustment information.

[0079] In this embodiment, in order to prevent excessive adjustment of personalized parameters from affecting system stability, the adjustment range of each channel is limited, and the actual update is performed only when the adjusted parameter value is within a reasonable threshold range.

[0080] Specifically, a change threshold range can be set in advance for each channel noise suppression and feedback suppression sub-parameter, such as noise smoothing length in [5, 50], adaptive filter length in [64, 512], etc. After obtaining the personalized adjustment information of the channel, the adjusted parameter value is compared with the corresponding threshold range. If the adjusted value is still within the threshold range, the personalized correction parameter of the channel is directly updated according to the adjustment information; if the adjusted value exceeds the threshold range, the update is not performed temporarily.

[0081] S63: If the threshold value is exceeded, a parameter secondary adjustment instruction is triggered, and secondary adjustment parameter information is obtained according to the parameter secondary adjustment instruction, and personalized correction parameters are updated according to the secondary adjustment parameter information.

[0082] Specifically, after detecting that the adjustment range of a certain channel exceeds the threshold, the secondary adjustment instruction of the channel parameter is automatically triggered; the secondary adjustment strategy can be to apply a reduction coefficient to the initial adjustment range to reduce the adjustment range to an acceptable range. For example, if the noise smoothing length of a certain channel is initially adjusted from 20 to 60, which exceeds the range of [5, 50], the secondary adjustment can reduce 60 to 40, which falls within the threshold range. After obtaining the reduced secondary adjustment parameter information, the information is used to replace the original personalized parameter adjustment information, and finally the actual update of the personalized correction parameters of the channel is completed, thereby taking into account both the effective adjustment of the parameters and the stability of the system.

[0083] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0084] In a second aspect, the present application provides a microphone audio signal correction system. The microphone audio signal correction system of the present application is described below in combination with the above-mentioned microphone audio signal correction method.

[0085] Reference Figure 7 , a microphone audio signal correction system, comprising: An audio correction mode acquisition module, used to acquire an audio correction mode; A target parameter acquisition module is used to obtain target parameters; An overall parameter generation module, used to obtain overall audio correction parameters according to the audio correction mode and target parameters; A channel parameter setting module is used to obtain microphone channel information and set personalized correction parameters for each microphone channel according to the microphone channel information and the overall audio correction parameters; An audio correction module, used for performing audio correction according to personalized correction parameters and overall audio correction parameters; A quality detection module is used to perform quality detection on the corrected audio and obtain audio detection parameters; A difference acquisition module is used to compare the audio detection parameters with the target parameters to obtain the parameter difference value; An adaptive adjustment trigger module is used to trigger audio quality monitoring when the parameter difference value exceeds a preset threshold; A parameter adjustment module, used for obtaining parameter adjustment information according to an adaptive adjustment mechanism; The parameter updating module is used to update the personalized correction parameters according to the parameter adjustment information.

[0086] In an optional embodiment, the overall parameter generation module includes: A target extraction unit, used for extracting a target signal-to-noise ratio from target parameters, and taking the target signal-to-noise ratio as a main noise suppression target; A correction parameter acquisition unit, used to acquire noise estimation parameters, adaptive filter parameters and pre-processing parameters according to a target signal-to-noise ratio and an audio correction mode; The overall parameter generation unit is used to obtain overall audio correction parameters according to the target signal-to-noise ratio, noise estimation parameters, adaptive filter parameters and pre-processing parameters.

[0087] In an optional embodiment, the pre-processing parameters include pre-emphasis filter parameters and de-pre-emphasis filter parameters, and the noise estimation parameters include noise spectrum estimation parameters and noise tracking factor parameters; The correction parameter acquisition unit includes: A preprocessing parameter acquisition unit, used to acquire pre-emphasis filter parameters and de-pre-emphasis filter parameters according to a target signal-to-noise ratio and an audio correction mode; A noise estimation parameter acquisition unit, used to acquire noise spectrum estimation parameters, noise tracking factor parameters, and adaptive filter parameters according to a target signal-to-noise ratio and an audio correction mode; The noise estimation generating unit is used to obtain noise estimation parameters according to the noise spectrum estimation parameters and the noise tracking factor parameters.

[0088] In an optional embodiment, the personalized correction parameters include channel noise suppression parameters and channel feedback suppression parameters; The channel parameter setting module includes: A channel information acquisition unit, used to acquire microphone channel position information and channel noise characteristic information; A channel pre-processing parameter acquisition unit, used to acquire a channel pre-processing parameter for each microphone channel according to the pre-processing parameter, channel position information and channel noise characteristic information; The channel noise reduction feedback parameter acquisition unit is used to acquire channel noise suppression parameters and channel feedback suppression parameters for each microphone channel according to the noise estimation parameters, the adaptive filter parameters, the channel position information and the channel noise characteristic information.

[0089] In an optional embodiment, the parameter adjustment module includes: An audio quality change acquisition unit, used to acquire audio quality change information according to the audio quality monitoring result; A quality convergence trigger unit, used to obtain quality anomaly trigger information; An environmental detection trigger unit, used to trigger an environmental detection instruction according to quality abnormality trigger information; An environmental detection result acquisition unit, used to acquire environmental detection result information; An audio state acquisition unit, used to acquire current audio processing state information based on the environment detection result information and the audio quality change information; The parameter adjustment information acquisition unit is used to acquire parameter adjustment information according to current audio processing state information and overall audio correction parameters.

[0090] In an optional embodiment, the parameter updating module includes: A personalized parameter adjustment unit, configured to obtain personalized parameter adjustment information according to the parameter adjustment information, wherein the personalized parameter adjustment information includes an adjusted channel noise suppression parameter and an adjusted channel feedback suppression parameter; A parameter threshold comparison unit, used for comparing the adjusted channel noise suppression parameter and the adjusted channel feedback suppression parameter with a preset parameter threshold; A parameter updating unit, configured to update the personalized correction parameter according to the personalized parameter adjustment information when the adjusted parameter is within a threshold range; A secondary adjustment trigger unit, used to trigger a parameter secondary adjustment instruction when the adjusted parameter exceeds a threshold range; A secondary adjustment parameter acquisition unit, used for acquiring secondary adjustment parameter information according to the parameter secondary adjustment instruction; The parameter updating unit is further used to update the personalized correction parameters according to the secondary adjustment parameter information.

[0091] In one embodiment, the present application provides an electronic device, which may be a server, and its internal structure diagram may be as follows: Figure 8 As shown. The electronic device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the electronic device is used to store data. The network interface of the electronic device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a microphone audio signal correction method is implemented.

[0092] Those skilled in the art will understand that Figure 8 The structure shown in the figure is merely a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the electronic device to which the scheme of the present application is applied. The specific electronic device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0093] In one embodiment, an electronic device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.

[0094] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the above-mentioned computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), tape, floppy disk, flash memory or optical memory, etc. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0095] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A microphone audio signal correction method, characterized in that: The steps include: Acquire an audio correction mode and a target parameter, and acquire an overall audio correction parameter according to the audio correction mode and the target parameter; Acquire microphone channel information, and set personalized correction parameters for the microphone channel according to the microphone channel information and the overall audio correction parameters; Performing audio correction according to the personalized correction parameter and the overall audio correction parameter; Performing quality detection on the corrected audio to obtain audio detection parameters; comparing the audio detection parameters with the target parameters to obtain parameter difference values; If the parameter difference value exceeds a preset threshold, audio quality monitoring is triggered; and parameter adjustment information is obtained according to the audio quality monitoring result; The personalized correction parameters are updated according to the parameter adjustment information.

2. The microphone audio signal correction method according to claim 1, characterized in that: The step of obtaining the audio correction mode and the target parameters, and obtaining the overall audio correction parameters according to the audio correction mode and the target parameters, specifically includes the following steps: Extracting a target signal-to-noise ratio from the target parameters, and using the target signal-to-noise ratio as a main noise suppression target; Acquire noise estimation parameters, adaptive filter parameters, and pre-processing parameters according to the target signal-to-noise ratio and the audio correction mode; The overall audio correction parameters are obtained according to the association of the target signal-to-noise ratio, the noise estimation parameters, the adaptive filter parameters and the pre-processing parameters.

3. The microphone audio signal correction method according to claim 2, characterized in that: The pre-processing parameters include pre-emphasis filter parameters and de-pre-emphasis filter parameters, and the noise estimation parameters include noise spectrum estimation parameters and noise tracking factor parameters. The step of acquiring noise estimation parameters, adaptive filter parameters and pre-processing parameters according to the target signal-to-noise ratio and the audio correction mode specifically comprises the following steps: According to the target signal-to-noise ratio and the audio correction mode, acquiring the pre-emphasis filter parameters, the de-pre-emphasis filter parameters, the noise spectrum estimation parameters, the noise tracking factor parameters and the adaptive filter parameters; The noise estimation parameter is acquired according to the noise spectrum estimation parameter and the noise tracking factor parameter.

4. The microphone audio signal correction method according to claim 2, characterized in that: The personalized correction parameters include channel noise suppression parameters and channel feedback suppression parameters, and the acquiring of microphone channel information and setting of personalized correction parameters for the microphone channel according to the microphone channel information and the overall audio correction parameters specifically include the following steps: Obtain microphone channel position information and channel noise characteristic information; Acquire channel pre-processing parameters for the microphone channel according to the pre-processing parameters, the channel position information and the channel noise characteristic information; The channel noise suppression parameter and the channel feedback suppression parameter are obtained for the microphone channel according to the noise estimation parameter, the adaptive filter parameter, the channel position information and the channel noise characteristic information.

5. The microphone audio signal correction method according to claim 1, characterized in that: The step of obtaining parameter adjustment information according to the audio quality monitoring result specifically includes the following steps: Acquiring audio quality change information according to the audio quality monitoring result; Acquire quality abnormality trigger information, and trigger an environmental detection instruction according to the quality abnormality trigger information; Acquire environment detection result information, and acquire current audio processing state information according to the environment detection result information and the audio quality change information; Parameter adjustment information is obtained according to the current audio processing state information and the overall audio correction parameter.

6. The microphone audio signal correction method according to claim 1, characterized in that: The updating of the personalized correction parameters according to the parameter adjustment information specifically includes the following steps: According to the parameter adjustment information, obtaining personalized parameter adjustment information, wherein the personalized parameter adjustment information includes an adjusted channel noise suppression parameter and an adjusted channel feedback suppression parameter; Comparing the adjusted channel noise suppression parameter and the adjusted channel feedback suppression parameter with a preset parameter threshold, and if they are within the threshold range, updating the personalized correction parameter according to the personalized parameter adjustment information; If it exceeds the threshold range, a parameter secondary adjustment instruction is triggered, and secondary adjustment parameter information is obtained according to the parameter secondary adjustment instruction, and the personalized correction parameter is updated according to the secondary adjustment parameter information.

7. A microphone audio signal correction system, characterized in that: include: An audio correction mode acquisition module, used to acquire an audio correction mode; A target parameter acquisition module is used to obtain target parameters; An overall parameter generation module, used for acquiring overall audio correction parameters according to the audio correction mode and the target parameters; A channel parameter setting module, used to obtain microphone channel information, and set personalized correction parameters for each microphone channel according to the microphone channel information and the overall audio correction parameters; An audio correction module, used for performing audio correction according to the personalized correction parameters and the overall audio correction parameters; A quality detection module is used to perform quality detection on the corrected audio and obtain audio detection parameters; A difference acquisition module, used for comparing the audio detection parameter with the target parameter to obtain a parameter difference value; An adaptive adjustment trigger module, used to trigger audio quality monitoring when the parameter difference value exceeds a preset threshold; A parameter adjustment module, used for obtaining parameter adjustment information according to the adaptive adjustment mechanism; A parameter updating module is used to update the personalized correction parameters according to the parameter adjustment information.

8. The microphone audio signal correction system according to claim 7, characterized in that: The parameter updating module comprises: A personalized parameter adjustment unit, configured to obtain personalized parameter adjustment information according to the parameter adjustment information, wherein the personalized parameter adjustment information includes an adjusted channel noise suppression parameter and an adjusted channel feedback suppression parameter; A parameter threshold comparison unit, used for comparing the adjusted channel noise suppression parameter and the adjusted channel feedback suppression parameter with a preset parameter threshold; a parameter updating unit, configured to update the personalized correction parameter according to the personalized parameter adjustment information when the adjusted parameter is within a threshold range; A secondary adjustment trigger unit, used for triggering a parameter secondary adjustment instruction when the adjusted parameter exceeds a threshold range; A secondary adjustment parameter acquisition unit, used to acquire secondary adjustment parameter information according to the parameter secondary adjustment instruction; The parameter updating unit is further configured to update the personalized correction parameter according to the secondary adjustment parameter information.

9. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the microphone audio signal correction method according to any one of claims 1 to 6 when executing the computer program.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the microphone audio signal correction method according to any one of claims 1 to 6 are implemented.

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