Howling processing method and device, electronic equipment and storage medium

Abstract

The invention provides a howling processing method and device, electronic equipment and a storage medium, and relates to the technical field of audio data processing. The howling processing method comprises the following steps: acquiring to-be-processed audio data; performing howling detection on the to-be-processed audio data; if no howling occurs, processing the to-be-processed audio data based on a preset DRC algorithm; if the howling occurs, determining a frequency point of the howling; adjusting parameters in a preset DRC algorithm based on the frequency points; and processing the to-be-processed audio data based on the DRC algorithm after parameter adjustment to obtain audio data after howling suppression. Even if the audio data to be processed generate howling, the energy amplitude of the howling can be limited through the DRC, so that the subsequently broadcasted howling sound is not large, and the discomfort of the howling to a user is reduced. Meanwhile, the parameters of the DRC are adjusted through the frequency points of the howling, so that the howling can be further suppressed through the DRC after the parameters are adjusted.

Description

Technical Field

[0001] This application relates to the technical field of audio data processing, and more specifically, to a method, apparatus, electronic device, and storage medium for handling howling. Background Technology

[0002] Feedback is a high-frequency, sharp, abnormal sound phenomenon that can cause discomfort to the user's ears. Frequent feedback can potentially cause irreversible damage to the user's hearing. Currently, software algorithms are commonly used to detect feedback.

[0003] The typical approach to detecting feedback using software algorithms involves first caching a certain amount of audio data, and then performing feedback detection based on this cached data. However, because caching data before analysis and detection is required, there is a lag in feedback detection, meaning that a portion of the audio causing feedback will still be played. The broadcast feedback sound is usually loud and sharp, causing discomfort to the user's ears. Summary of the Invention

[0004] This application provides a method, apparatus, electronic device, and storage medium for handling howling, in order to solve the problem that the howling sound in the broadcast section is usually loud and sharp, which can cause discomfort to the user's ears.

[0005] In a first aspect, this application provides a method for handling feedback, comprising: acquiring audio data to be processed; performing feedback detection on the audio data to be processed; if no feedback occurs, processing the audio data to be processed based on a preset DRC (Dynamic Range Control) algorithm; if feedback occurs, determining the frequency point of the feedback; adjusting the parameters in the preset DRC algorithm based on the frequency point; and processing the audio data to be processed based on the DRC algorithm with adjusted parameters to obtain audio data with feedback suppressed.

[0006] In this embodiment, the audio data to be processed is handled by DRC. Even if feedback occurs in the audio data, DRC can limit the energy amplitude of the feedback, ensuring that the feedback sound in subsequent playback is not too loud, thereby reducing the discomfort caused by the feedback to the user. Simultaneously, by adjusting the parameters of DRC based on the frequency of the feedback, the feedback can be further suppressed through the adjusted DRC. Therefore, after playing the audio data with suppressed feedback, the feedback sound is further reduced or even eliminated.

[0007] In conjunction with the technical solution provided in the first aspect above, in some possible implementations, the step of detecting howling in the audio data to be processed includes: converting the audio data to be processed into frequency domain data; detecting whether the frequency domain data contains a single-frequency signal with energy greater than a preset energy threshold; wherein, if a single-frequency signal with energy greater than the preset energy threshold exists, it is determined that howling has occurred.

[0008] In this embodiment, since howling typically involves the accumulation of energy at the same frequency, the energy of the howling becomes increasingly larger. Based on this, this solution detects the frequency domain data of the audio data to be processed, and identifies howling as occurring when a single-frequency signal with energy exceeding a preset energy threshold is detected. This allows for accurate howling identification.

[0009] In conjunction with the technical solution provided in the first aspect above, in some possible implementations, before converting the audio data to be processed into frequency domain data, the method further includes: determining that the signal energy of the audio data to be processed is greater than a preset threshold; wherein, the audio data to be processed is time domain data.

[0010] In this embodiment of the application, by performing threshold detection on the signal energy of the audio signal (time domain data) to be processed, audio signals with low energy are filtered out, reducing the amount of data for subsequent frequency domain conversion and howling detection, improving howling detection efficiency, and thus reducing lag.

[0011] In conjunction with the technical solution provided in the first aspect above, in some possible implementations, if the device performing the method is in an audio playback scenario, the step of detecting howling in the audio data to be processed includes: converting the audio data to be processed into frequency domain data; detecting whether the frequency domain data contains a single-frequency signal with energy greater than a preset energy threshold; if so, acquiring the currently playing audio data; determining whether the frequency point with the highest energy in the audio data is consistent with the frequency point of the single-frequency signal; if consistent, determining that no howling has occurred; if inconsistent, determining that howling has occurred.

[0012] In this embodiment of the application, since the device itself is playing audio, it is necessary to further determine whether the single-frequency signal is the audio being played, so as to prevent the high-pitched part of the played audio from being identified as howling and improve the accuracy of howling detection.

[0013] In conjunction with the technical solution provided in the first aspect above, in some possible implementations, before processing the audio data to be processed based on the DRC algorithm with adjusted parameters to obtain audio data with suppressed feedback, the method further includes: amplifying the audio data to be processed; correspondingly, processing the audio data to be processed based on a preset DRC algorithm includes: processing the amplified audio data to be processed based on the DRC algorithm; processing the audio data to be processed based on the DRC algorithm with adjusted parameters to obtain audio data with suppressed feedback includes: processing the amplified audio data to be processed based on the DRC algorithm with adjusted parameters to obtain audio data with suppressed feedback.

[0014] In this embodiment, the audio data to be processed is amplified, and then the amplified audio data to be processed is processed using the DRC algorithm, thereby ensuring that the energy amplitude of the final played audio data (the audio data to be processed after DRC algorithm processing) can be effectively limited by the DRC algorithm, thus protecting the user's hearing.

[0015] In conjunction with the technical solution provided in the first aspect above, in some possible implementations, the DRC algorithm is a WDRC (Wide Dynamic Range Compression) algorithm; based on the frequency point of the howling, the parameters of the DRC algorithm are adjusted, including: reducing the amplitude limiting threshold corresponding to the frequency point of the howling in the WDRC algorithm; increasing the compression ratio corresponding to the frequency point of the howling in the WDRC algorithm.

[0016] In this embodiment, the maximum energy of the howling can be reduced by lowering the limiting threshold corresponding to the frequency point of the howling. Furthermore, increasing the compression ratio corresponding to the frequency point of the howling in the WDRC algorithm can further reduce the energy of the howling, thereby suppressing the howling.

[0017] In conjunction with the technical solution provided in the first aspect above, in some possible implementations, adjusting the parameters of the DRC algorithm based on the frequency point of the howling also includes: reducing the attack time of the WDRC algorithm.

[0018] In this embodiment of the application, by reducing the attack time of the WDRC algorithm, the efficiency of the WDRC algorithm in reducing the energy of howling can be improved, thereby suppressing howling more quickly.

[0019] Secondly, this application provides a feedback processing device, comprising: an acquisition module and a processing module; the acquisition module is used to acquire audio data to be processed; the processing module is used to perform feedback detection on the audio data to be processed; if no feedback occurs, the audio data to be processed is processed based on a preset DRC algorithm; the processing module is further used to determine the frequency point of feedback if feedback occurs; adjust the parameters in the preset DRC algorithm based on the frequency point; and process the audio data to be processed based on the DRC algorithm with adjusted parameters to obtain audio data with feedback suppressed.

[0020] Thirdly, this application provides an electronic device, including: a memory and a processor, the memory and the processor being connected; the memory being used to store a program; the processor being used to invoke the program stored in the memory to execute the method described in the first aspect and / or in combination with any possible implementation of the first aspect.

[0021] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a computer, performs the methods described in the first aspect and / or in combination with any possible implementation of the first aspect. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a flowchart illustrating the first method for handling howling sounds according to an embodiment of this application; Figure 2 This is a schematic diagram illustrating a frequency domain signal according to an embodiment of this application; Figure 3 This is a flowchart illustrating a DRC algorithm according to an embodiment of this application; Figure 4 This is a flowchart illustrating a WDRC algorithm according to an embodiment of this application; Figure 5 This is a schematic flowchart illustrating a second method for handling howling sounds, as shown in an embodiment of this application. Figure 6 This is a structural block diagram of a howling processing device shown in an embodiment of this application; Figure 7 This is a structural block diagram of an electronic device shown in an embodiment of this application. Detailed Implementation

[0024] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0025] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, relational terms such as "first," "second," etc., in the description of this application are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus.

[0026] The technical solution of this application will now be described in detail with reference to the accompanying drawings.

[0027] Please see Figure 1 , Figure 1 This is a flowchart illustrating a howling processing method provided in an embodiment of this application. The following will be combined with... Figure 1 The steps involved are explained.

[0028] S100: Acquire audio data to be processed.

[0029] The audio data to be processed can be pre-acquired and stored in a storage medium, which can be directly retrieved when needed. Alternatively, the audio data to be processed can also be audio data acquired in real time by the audio acquisition module.

[0030] The audio acquisition module can be a device such as a microphone or a sound sensor; there are no restrictions on the specific type of audio acquisition module.

[0031] Optionally, when the audio data to be processed is acquired by an audio acquisition module such as a microphone, since the data acquired by the audio acquisition module is usually an analog signal, the specific way to obtain the audio data to be processed can be: first, acquire the analog signal acquired by the audio acquisition module, and then convert the analog signal into a digital signal to obtain the audio data to be processed.

[0032] S200: Performs feedback detection on the audio data to be processed.

[0033] Optionally, feedback detection can be performed on the acquired audio data of a preset length after each acquisition of such data.

[0034] For example, if the preset length is 5ms, then after acquiring the data from 0 to 5ms in the audio data to be processed, feedback detection is performed on this 5ms data. Then feedback detection is performed on the acquired data from 5 to 10ms. This process continues until feedback detection is performed on all data in the audio data to be processed. This example is for illustrative purposes only and should not be construed as a limitation of this application.

[0035] The specific value of the preset length can be set according to actual needs; there is no restriction on its specific length here.

[0036] In one implementation, the method for detecting feedback in the audio data to be processed can be as follows: First, the audio data to be processed is converted into frequency domain data. Then, it is detected whether a single-frequency signal with energy greater than a preset energy threshold exists in the frequency domain data. If a single-frequency signal with energy greater than the preset energy threshold exists, feedback is determined to have occurred.

[0037] The specific methods and principles for converting audio data to frequency domain data are well known to those skilled in the art, and will not be elaborated here for the sake of brevity.

[0038] The preset energy threshold can be set according to actual needs; its specific value is not limited here.

[0039] Optionally, the preset energy threshold can be determined by testing each type of device separately, determining the energy range of howling that occurs in that type of device, and then determining the corresponding energy threshold for that type of device based on this range.

[0040] A single-frequency signal refers to a signal in the frequency domain data whose frequency components are concentrated at a single center frequency and are not interfered with by other frequency components.

[0041] Alternatively, a single-frequency signal can also be a signal whose peak-to-average power ratio (PAPR) is greater than a preset power ratio threshold. In other words, a single-frequency signal is a signal whose PAPR is greater than the preset power ratio threshold.

[0042] To facilitate understanding of single-frequency signals, Figure 2 For example.

[0043] like Figure 2 As shown, a distinct high-energy signal appears between 1100 and 1200 on the horizontal axis, and this high-energy signal is significantly higher than the energy of other frequencies around it. This distinct high-energy signal is the single-frequency signal.

[0044] In one implementation, the specific method for detecting whether a single-frequency signal with energy greater than a preset energy threshold appears in the frequency domain data can be: detecting whether the maximum signal energy of the single-frequency signal in the frequency domain data is greater than the preset energy threshold.

[0045] In one implementation, if the device executing this method is in an audio playback scenario, the specific method for detecting howling in the audio data to be processed can be: converting the audio data to be processed into frequency domain data. Then detecting whether the frequency domain data contains a single-frequency signal with energy greater than a preset energy threshold.

[0046] If a single-frequency signal with energy exceeding a preset energy threshold is detected, the currently playing audio data is acquired. It is then determined whether the frequency point with the highest energy in the audio data matches the frequency point of the single-frequency signal. If they match, it is confirmed that no feedback (howling) has occurred. If they do not match, it is confirmed that feedback (howling) has occurred.

[0047] If no single-frequency signal with energy exceeding the preset energy threshold is detected, it is confirmed that no howling has occurred.

[0048] Since the device itself is playing audio, it is necessary to further determine whether the single-frequency signal is the audio being played, in order to prevent the high-pitched parts of the played audio from being identified as feedback and to improve the accuracy of feedback detection.

[0049] Optionally, when the feedback detection is performed on a portion of the audio data to be processed (hereinafter referred to as the detection segment), the currently playing audio data can also be obtained by retrieving data (hereinafter referred to as the audio segment) from the currently playing audio data that has the same length (duration) as the audio data to be processed for feedback detection. Furthermore, the time for feedback detection of the detection segment overlaps with the time for playback of the audio segment.

[0050] In one implementation, before converting the audio data to be processed into frequency domain data, it can be determined that the signal energy of the audio data to be processed is greater than a preset threshold. Here, the audio data to be processed is time domain data.

[0051] By performing threshold detection on the signal energy of the audio signal (time domain data) to be processed, low-energy audio signals are filtered out. Only signals with energy greater than the preset threshold can enter the subsequent howling detection step (i.e., S200), reducing the amount of data required for subsequent frequency domain conversion and howling detection, improving howling detection efficiency, and thus reducing lag.

[0052] The specific value of the preset threshold can be set according to actual needs; there is no restriction on the specific value of the preset threshold here.

[0053] Optionally, the preset threshold can be obtained by debugging the actual structure and device parameters of the device (the device executing this method) during the development phase.

[0054] For example, multiple initial thresholds can be preset, each initial threshold can be tested, and the one with the best performance can be selected as the final preset threshold. The best performance can be comprehensively evaluated by factors such as howling detection accuracy and data computation.

[0055] The test initial threshold is also the initial threshold applied to the howling processing method provided in this application, and the howling processing method with the initial threshold applied is tested through multiple preset samples.

[0056] Optionally, the specific method for determining whether the signal energy of the audio data to be processed is greater than the preset threshold can be: judging whether the signal energy of each signal point in the acquired audio data to be processed is greater than the preset threshold.

[0057] Optionally, after determining that the signal energy of the audio data to be processed is greater than a preset threshold, the signal point that is greater than the preset threshold is taken as the center, and the signals before and after the center for a preset duration are taken as the signals processed by S200.

[0058] For example, if the signal with a signal energy greater than a preset threshold in the audio data to be processed is the signal at 100ms, and the preset duration is 3ms, then the data from 97ms to 103ms in the audio data to be processed will be used for howling detection via S200.

[0059] The examples provided here are for illustrative purposes only and should not be construed as limiting the scope of this application. The specific value of the preset duration can be set according to actual needs. This is just one way to implement the preset duration.

[0060] S300: If no feedback occurs, the audio data to be processed is processed based on the preset DRC algorithm.

[0061] By using the DRC algorithm to process the audio data, the playback of the processed data can be restricted to a certain range, thereby improving the user experience.

[0062] S400: If a whistling sound occurs, determine the frequency of the whistling sound.

[0063] Optionally, the frequency point of the howling is: the frequency of the signal point with the largest energy amplitude (i.e., signal strength) corresponding to the howling.

[0064] For example, when a single-frequency signal with energy greater than a preset energy threshold appears, the center frequency of the single-frequency signal can be determined as the frequency of the howling.

[0065] S500: Adjusts the parameters in the preset DRC algorithm based on the frequency point.

[0066] In one implementation, adjusting the parameters in the preset DRC algorithm can be achieved by: shortening the attack time of the DRC algorithm, and / or lowering the amplitude limiting threshold of the DRC algorithm. This limits the output amplitude of the frequency band corresponding to the howling frequency point in the shortest possible time.

[0067] Optionally, before adjusting the parameters of the DRC algorithm, the energy amplitude of the howling can be obtained, and then the limiting threshold corresponding to the frequency point of the howling can be adjusted according to the energy amplitude of the howling. The larger the energy amplitude of the howling, the lower the limiting threshold corresponding to the frequency point of the howling after adjustment.

[0068] To facilitate understanding of the specific working principle of DRC, the following will combine... Figure 3 Please provide an explanation.

[0069] like Figure 3 As shown, x[n] is the acquired audio data to be processed, which is a linear value. The dB conversion module converts x[n] to a dB value x. dB [n]. Then the first calculation module calculates based on x. dB [n] calculates x SC [n], whose computational logic can be expressed as: Where G represents the desired gain, TK represents the input level (dB), TK represents the limiting threshold, also known as the compression inflection point, and CR represents the compression ratio.

[0070] Then calculate x dB [n] and x SC The difference between [n] yields the actual gain value g. c [n]. Then for g c [n] is used for gain smoothing to obtain the actual output gain g. s [n]. Where g s [n] will gradually change to g within a preset time period. c [n]. For example, if g c If [n] is -10dB, then g s [n] will gradually decrease from 0dB to -10dB over time.

[0071] Then in g s A compensation gain value is superimposed on [n] to obtain g. m [n]. Finally, g m [n] is converted to a linear value g. lin [n]. Finally, x[n] and g linMultiplying [n] together yields the final output y[n] of the DRC algorithm.

[0072] The specific principles and execution logic of DRC are well known to those skilled in the art, and will not be elaborated here for the sake of brevity.

[0073] S600: Based on the DRC algorithm with adjusted parameters, it processes the audio data to be processed to obtain the audio data after suppressing feedback.

[0074] In one implementation, before processing the audio data to be processed using the DRC algorithm with adjusted parameters to obtain audio data with feedback eliminated, the audio data to be processed can be amplified.

[0075] Accordingly, the method for processing the audio data to be processed based on the preset DRC algorithm is as follows: the amplified audio data to be processed is processed based on the DRC algorithm.

[0076] The specific method for processing the audio data to be processed based on the DRC algorithm with adjusted parameters to obtain the audio data after suppressing feedback is as follows: The amplified audio data to be processed is processed based on the DRC algorithm with adjusted parameters to obtain the audio data after suppressing feedback.

[0077] In one implementation, the DRC algorithm described above can be the WDRC algorithm.

[0078] Optionally, based on the frequency point of the howling, the specific way to adjust the parameters of the DRC algorithm can be: lowering the limiting threshold corresponding to the frequency point of the howling in the WDRC algorithm, and increasing the compression ratio corresponding to the frequency point of the howling in the WDRC algorithm.

[0079] By lowering the amplitude limiting threshold corresponding to the frequency point of the howling, the maximum energy of the howling can be reduced. Increasing the compression ratio corresponding to the frequency point in the WDRC algorithm can further reduce the energy of the howling, thereby suppressing the howling.

[0080] Optionally, before adjusting the parameters of the WDRC algorithm, the energy amplitude of the howling can be obtained, and then the limiting threshold corresponding to the frequency point of the howling can be adjusted according to the energy amplitude of the howling. The larger the energy amplitude of the howling, the lower the limiting threshold corresponding to the frequency point of the howling after adjustment.

[0081] Optionally, adjusting the parameters of the WDRC algorithm can reduce the attack time of the WDRC algorithm.

[0082] By reducing the attack time of the WDRC algorithm, the efficiency of the WDRC algorithm in reducing the energy of howling can be improved, thereby suppressing howling more quickly.

[0083] To make it easier to understand, we will take the frequency of the howling sound as 2kHz as an example.

[0084] The parameters of the WDRC algorithm are adjusted as follows: the clipping threshold in the frequency band near 2kHz is lowered. Simultaneously, the attack time is reduced to allow the adjusted clipping threshold to take effect more quickly.

[0085] The WDRC algorithm divides the frequency into multiple frequency bands, and the parameters (amplitude limiting threshold, compression ratio, attack time, etc.) corresponding to different frequency bands can be different.

[0086] For example, the WDRC algorithm divides the frequency band into [X1,X2], X1<X、X2> The three frequency bands are X1 and X2, and the signals in these three bands are processed independently.

[0087] In one implementation, when the device executing this method is a headset, when feedback occurs, the energy output of the headset's speaker far exceeds the energy under normal operating conditions. This solution utilizes the limiting function of the WDRC algorithm to limit the ambient sound mode output of the headset to a safe range, thus ensuring the normal use of the ambient sound mode and reducing the amplitude of feedback when it occurs. By controlling the large output energy during feedback within a suitable range within milliseconds, the discomfort caused by sudden large signals is avoided. Furthermore, by using multi-band WDRC, the parameters for compressing the frequency bands prone to feedback can be controlled individually, thus controlling the feedback sound while preserving the ambient sound effect to a certain extent.

[0088] To facilitate understanding of the WDRC algorithm, the following will use... Figure 4 Let's take an example to illustrate.

[0089] like Figure 4 As shown, the WDRC algorithm first performs signal strength detection on the audio data, comparing the signal strength with a limiting threshold within the WDRC algorithm. If the signal strength exceeds the limiting threshold, the gain is calculated. Then, gain smoothing is performed, and finally, the gain is output. If the signal strength of the audio data is less than or equal to the amplitude limiting threshold in the WDRC algorithm, the audio data is output directly.

[0090] Gain smoothing refers to a technique in audio processing or control systems used to smoothly adjust gain changes, aiming to avoid the negative impact of sudden gain changes on sound quality or system stability. When the current signal strength is greater than the limiting threshold, the actual output signal strength calculated by the compression ratio within the WDRC algorithm needs to gradually transition from the current signal strength to the target signal strength. Gain smoothing is represented on the time axis as a process of slowly decreasing / increasing the output signal strength, eventually decreasing to the calculated target signal strength. The final output gain is the signal after gain smoothing.

[0091] First, the level of the input signal is calculated, and the calculation formula can be expressed as: .

[0092] Then, the output gain is calculated based on the limiting threshold and compression ratio. The calculation formula can be expressed as: .

[0093] Where G represents the desired gain, TK represents the input level (dB), TK represents the limiting threshold, also known as the compression inflection point, and CR represents the compression ratio.

[0094] To facilitate understanding of the above-described howling suppression method, examples will be provided below. It should be noted that the examples given here are merely one implementation of the howling suppression method provided in this application.

[0095] like Figure 5 As shown, the initial audio data is first acquired through a microphone. Then, the acquired initial audio data is converted into analog data through analog-to-digital conversion to obtain the audio data to be processed.

[0096] The signal energy of the audio data to be processed is compared with a preset feedback threshold. If the signal energy of the audio data to be processed is less than the preset threshold, no further feedback detection is performed.

[0097] If the signal energy of the audio data to be processed is greater than or equal to a preset threshold, an interrupt signal is triggered (i.e., Figure 5 The hardware signal interruption shown converts the audio data to be processed into frequency domain data. Then, it checks whether a single-frequency signal with energy greater than a preset energy threshold appears in the frequency domain data.

[0098] If a single-frequency signal with energy exceeding a preset energy threshold is detected, the currently playing audio data is acquired. It is then determined whether the frequency point with the highest energy in the audio data matches the frequency point of the single-frequency signal.

[0099] If the frequency point with the highest energy in the audio data matches the frequency point of the single-frequency signal, it is confirmed that there is no howling.

[0100] If the frequency point with the highest energy in the audio data does not match the frequency point of the single-frequency signal, then a howling sound is confirmed.

[0101] If feedback is detected, the frequency point of the feedback is determined. Then, the limiting threshold corresponding to the frequency point in the WDRC algorithm is lowered, the compression ratio corresponding to the frequency point in the WDRC algorithm is increased, and the attack time of the WDRC algorithm is reduced. The audio data to be processed is then processed based on the parameter-adjusted WDRC algorithm.

[0102] in, Figure 5 The specific implementation methods of each step shown have been clearly described above, and will not be repeated here for the sake of brevity.

[0103] Based on the same technical concept, this application also provides a howling processing device. For example... Figure 6 As shown, the howling processing device 100 includes an acquisition module 110 and a processing module 120.

[0104] The acquisition module 110 is used to acquire the audio data to be processed.

[0105] The processing module 120 is used to perform feedback detection on the audio data to be processed; if no feedback occurs, the audio data to be processed is processed based on a preset DRC algorithm.

[0106] The processing module 120 is also used to determine the frequency point of the feedback if feedback occurs; adjust the parameters in the preset DRC algorithm based on the frequency point; and process the audio data to be processed based on the DRC algorithm after adjusting the parameters to obtain the audio data after suppressing feedback.

[0107] The processing module 120 is specifically used to convert the audio data to be processed into frequency domain data; detect whether the frequency domain data contains a single frequency signal with energy greater than a preset energy threshold; wherein, if there is a single frequency signal with energy greater than the preset energy threshold, it is determined that a howling has occurred.

[0108] Before converting the audio data to be processed into frequency domain data, the processing module 120 is further configured to determine that the signal energy of the audio data to be processed is greater than a preset threshold; wherein, the audio data to be processed is time domain data.

[0109] If the device executing the method is in an audio playback scenario, the processing module 120 is specifically used to convert the audio data to be processed into frequency domain data; detect whether the frequency domain data contains a single-frequency signal with energy greater than a preset energy threshold; if so, acquire the currently playing audio data; determine whether the frequency point with the highest energy in the audio data is consistent with the frequency point of the single-frequency signal; if consistent, determine that no feedback has occurred; if inconsistent, determine that feedback has occurred.

[0110] Before processing the audio data to be processed based on the DRC algorithm with adjusted parameters to obtain audio data with feedback eliminated, the processing module 120 is also used to amplify the audio data to be processed.

[0111] Correspondingly, the processing module 120 is specifically used to process the amplified audio data to be processed based on the DRC algorithm; and to process the amplified audio data to be processed based on the DRC algorithm with adjusted parameters to obtain audio data after suppressing feedback.

[0112] In one implementation, the DRC algorithm is the WDRC algorithm; the processing module 120 is specifically used to reduce the limiting threshold corresponding to the frequency point in the WDRC algorithm; and to increase the compression ratio corresponding to the frequency point in the WDRC algorithm.

[0113] The processing module 120 is also used to reduce the attack time of the WDRC algorithm.

[0114] The howling processing device 100 provided in this application embodiment has the same implementation principle and technical effect as the aforementioned howling processing method embodiment. For the sake of brevity, any parts not mentioned in the device embodiment can be referred to the corresponding content in the aforementioned howling processing method embodiment.

[0115] Please see Figure 7 This is an electronic device 200 provided in an embodiment of this application. The electronic device 200 includes: a processor 210 and a memory 220.

[0116] The memory 220 and processor 210 are electrically connected directly or indirectly to each other to achieve data transmission or interaction. For example, these components can be electrically connected to each other through one or more communication buses or signal lines. The memory 220 is used to store computer programs, such as those containing... Figure 6The software functional module shown is the feedback processing device 100. The feedback processing device 100 includes at least one software functional module that can be stored as software or firmware in the memory 220 or embedded in the operating system (OS) of the electronic device 200. The processor 210 is used to execute executable modules stored in the memory 220, such as the software functional module or computer program included in the feedback processing device 100. In this case, the processor 210 is used to acquire audio data to be processed; perform feedback detection on the audio data to be processed; if no feedback occurs, process the audio data to be processed based on a preset DRC algorithm; if feedback occurs, determine the frequency point of the feedback; adjust the parameters in the preset DRC algorithm based on the frequency point; and process the audio data to be processed based on the adjusted DRC algorithm to obtain audio data with feedback suppressed.

[0117] The memory 220 can be, but is not limited to, RAM (Random Access Memory), ROM (Read Only Memory), PROM (Programmable Read-Only Memory), EPROM (Erasable Programmable Read-Only Memory), EEPROM (Electric Erasable Programmable Read-Only Memory), etc.

[0118] Processor 210 may be an integrated circuit chip with signal processing capabilities. The aforementioned processor can be a general-purpose processor, including a CPU (Central Processing Unit), NP (Network Processor), etc.; it can also be a DSP (Digital Signal Processor), ASIC (Application Specific Integrated Circuit), FPGA (Field Programmable Gate Array), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor, or processor 210 can be any conventional processor.

[0119] Among them, the aforementioned electronic devices 200 include, but are not limited to, personal computers, servers, headphones, Bluetooth speakers, etc.

[0120] This application also provides a computer-readable storage medium (hereinafter referred to as the storage medium) storing a computer program. When the computer program is run by a computer, such as the electronic device 200 described above, it executes the above-described howling processing method. The computer-readable storage medium includes various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory, a random access memory, a magnetic disk, or an optical disk.

[0121] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for handling howling, characterized in that, include: Acquire the audio data to be processed; Perform feedback detection on the audio data to be processed; If no feedback occurs, the audio data to be processed is processed based on the preset DRC algorithm; If a whistling sound occurs, determine the frequency of the whistling sound; Based on the frequency point, the parameters in the preset DRC algorithm are adjusted; The DRC algorithm with adjusted parameters is used to process the audio data to be processed, resulting in audio data with suppressed feedback.

2. The method according to claim 1, characterized in that, The step of detecting howling in the audio data to be processed includes: Convert the audio data to be processed into frequency domain data; The system detects whether a single-frequency signal with energy greater than a preset energy threshold exists in the frequency domain data; if a single-frequency signal with energy greater than the preset energy threshold exists, it is determined that a howling sound has occurred.

3. The method according to claim 2, characterized in that, Before converting the audio data to be processed into frequency domain data, the method further includes: The signal energy of the audio data to be processed is determined to be greater than a preset threshold; wherein the audio data to be processed is time-domain data.

4. The method according to claim 1, characterized in that, If the device executing the method is in an audio playback scenario, the step of detecting howling in the audio data to be processed includes: Convert the audio data to be processed into frequency domain data; Detect whether the frequency domain data contains a single-frequency signal with energy greater than a preset energy threshold; If this occurs, retrieve the currently playing audio data; Determine whether the frequency point with the highest energy in the audio data is consistent with the frequency point of the single-frequency signal; If they match, it confirms that no whistling has occurred; If there is a discrepancy, a howling sound is confirmed.

5. The method according to claim 1, characterized in that, Before processing the audio data to be processed using the DRC algorithm with adjusted parameters to obtain audio data with feedback eliminated, the method further includes: The audio data to be processed is amplified; Accordingly, the audio data to be processed is processed based on a preset DRC algorithm, including: The amplified audio data to be processed is processed based on the DRC algorithm. The audio data to be processed is processed based on the DRC algorithm with adjusted parameters to obtain audio data after suppressing feedback, including: The amplified audio data to be processed is then processed using the DRC algorithm with adjusted parameters to obtain audio data after suppressing feedback.

6. The method according to any one of claims 1-5, characterized in that, The DRC algorithm is the WDRC algorithm; Based on the frequency of the howling, the parameters of the DRC algorithm are adjusted, including: In the WDRC algorithm, the amplitude limiting threshold corresponding to the frequency point of the howling is reduced; Increase the compression ratio corresponding to the frequency point of the whistling sound in the WDRC algorithm.

7. The method according to claim 6, characterized in that, Based on the frequency of the howling, the parameters of the DRC algorithm are adjusted, which also includes: Reduce the attack time of the WDRC algorithm.

8. A whistling suppression device, characterized in that, include: The acquisition module is used to acquire the audio data to be processed; The processing module is used to perform feedback detection on the audio data to be processed; If no feedback occurs, the audio data to be processed is processed based on the preset DRC algorithm; The processing module is also used to determine the frequency of the whistling sound if it occurs. Based on the frequency point, the parameters in the preset DRC algorithm are adjusted; based on the DRC algorithm with adjusted parameters, the audio data to be processed is processed to obtain the audio data after suppressing feedback.

9. An electronic device, characterized in that, include: A memory and a processor, wherein the memory and the processor are connected; The memory is used to store programs; The processor is configured to invoke a program stored in the memory to execute the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, It stores a computer program, which, when executed by a computer, performs the method as described in any one of claims 1-7.

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