Voice feedback suppression method, electronic device and storage medium

Abstract

The present invention discloses an acoustic feedback suppression method, an electronic device, and a storage medium. The method includes: obtaining an input signal and reducing the correlation between the input signal and a speaker feedback signal; reducing the energy proportion of the feedback signal in the input signal to obtain an output signal, where the feedback signal is a signal obtained by the speaker feedback signal passing through a feedback function. In the embodiments of the present invention, by reducing the correlation of the input signal, the achievement condition of howling is destroyed, and by combining with reducing the energy proportion of the feedback signal to increase the maximum gain of the system, it is possible to effectively prevent howling suppression, and at the same time increase the amplification gain upper limit of the assistive listening headphone system for the input signal to obtain a greater output gain.

Description

Technical Field

[0001] The present invention belongs to the technical field of headphone sound suppression, and particularly relates to a sound feedback suppression method, an electronic device, and a storage medium. Background Art

[0002] In the prior art, at least one sound feedback detection signal is played through a speaker of a mobile terminal and the sound feedback detection signal is recorded; the sound feedback detection signal is collected through a microphone of the mobile terminal and the collected sound feedback detection signal is recorded; the played sound feedback detection signal and the collected sound feedback detection signal are compared to obtain a sound feedback detection result; the pose information of the mobile terminal is obtained in real time, and the sound feedback detection result is updated based on the pose information for sound feedback suppression. The prior art is based on the test of traveling sound feedback, and sound feedback is suppressed in real time and dynamically according to the test result, so as to avoid the occurrence of howling after the pose of the mobile terminal changes.

[0003] In the prior art, another method for sound feedback suppression is also provided. Mainly, a linear prediction unit receives an external input sound source for howling suppression, and an adaptive filtering unit receives the signal processed by the linear prediction unit, models the acoustic environment, cancels the echo signal in the sound feedback, and eliminates the echo. It overcomes the biased estimation of the traditional subband adaptive filter for highly colored signals, can not only model the acoustic environment more accurately, but also effectively follow the changing acoustic environment. While effectively suppressing sound feedback, it reduces the impact on the original sound, and is mainly applied to occasions such as medical hearing aids and sound reinforcement systems.

[0004] The inventor found that: Howling mainly occurs because the output signal and the input signal of the assistive listening headphone form a loop. The gain and phase shift of the loop will cause howling, which is currently inevitable and a long-existing problem in this field. Using an adaptive filter to extract sound feedback has its own bottleneck. When the feedback reaches a certain level, the residual feedback signal cannot be completely eliminated, and after being amplified by the system multiple times, oscillations are formed, resulting in howling. The suppression effect on sound feedback is limited and will fail after the amplification gain reaches a certain level, and it will cause distortion to human voices when the assistive listening headphone device is used. Summary of the Invention

[0005] The embodiments of the present invention aim to solve at least one of the above technical problems.

[0006] In a first aspect, an embodiment of the present invention provides a sound feedback suppression method, including: obtaining an input signal, reducing the correlation between the input signal and the speaker feedback signal; reducing the energy ratio of the feedback signal in the input signal to obtain an output signal, where the feedback signal is a signal obtained by the speaker feedback signal passing through a feedback function.

[0007] In a second aspect, an embodiment of the present invention provides an electronic device, which includes: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and when the instructions are executed by the at least one processor, the at least one processor is enabled to execute any one of the above-mentioned acoustic feedback suppression methods of the present invention.

[0008] In a third aspect, an embodiment of the present invention provides a storage medium, in which one or more programs including execution instructions are stored, and the execution instructions can be read and executed by an electronic device (including but not limited to a computer, a server, or a network device, etc.) for executing any one of the above-mentioned acoustic feedback suppression methods of the present invention.

[0009] In a fourth aspect, an embodiment of the present invention further provides a computer program product, which includes a computer program stored on a storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer is enabled to execute any one of the above-mentioned acoustic feedback suppression methods.

[0010] By reducing the correlation of the input signal and destroying the conditions for howling to occur, and combining with reducing the energy ratio of the feedback signal to increase the maximum gain of the system, the embodiment of the present invention can effectively prevent howling, and at the same time increase the upper limit of the amplification gain of the assistive listening headphone system for the input signal to obtain a larger output gain. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0012] Figure 1 It is a flowchart of an embodiment of the acoustic feedback suppression method of the present invention;

[0013] Figure 2 It is a schematic diagram of howling generation of the acoustic feedback suppression method of the present invention;

[0014] Figure 3 It is a schematic diagram of an adaptive filter of the acoustic feedback suppression method of the present invention;

[0015] Figure 4 It is a schematic diagram of decorrelation of a pre-filter of the acoustic feedback suppression method of the present invention;

[0016] Figure 5 It is a step flowchart of the acoustic feedback suppression method of the present invention;

[0017] Figure 6 This is a schematic structural diagram of an embodiment of the electronic device of the present invention. Detailed implementation manners

[0018] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are only a part rather than all of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0019] It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments may be combined with each other.

[0020] The present invention may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The present invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including storage devices.

[0021] In the present invention, "module", "device", "system", etc. refer to relevant entities applied to a computer, such as hardware, a combination of hardware and software, software, or software in execution. Specifically, for example, an element may be, but is not limited to, a process running on a processor, a processor, an object, an executable element, an execution thread, a program, and / or a computer. Also, an application program or a script program running on a server, and the server may both be elements. One or more elements may be in a process and / or thread in execution, and the elements may be localized on one computer and / or distributed between two or more computers, and may be run by various computer-readable media. The elements may also communicate through local and / or remote processes according to signals having one or more data packets, for example, signals from data interacting with another element in a local system, a distributed system, and / or signals interacting with other systems through a network in the Internet.

[0022] Finally, it should also be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprising" and "including" not only include those elements, but also include other elements not explicitly listed, or also include elements inherent in such a process, method, article or device. Without further limitation, an element defined by the statement "including..." does not exclude the existence of additional identical elements in the process, method, article or device including the said element.

[0023] An embodiment of the present invention provides an acoustic feedback suppression method, which can be applied to an electronic device. The electronic device can be a computer, a server or other electronic products, etc., and the present invention does not make any limitation thereto.

[0024] Please refer to Figure 1 , which shows an acoustic feedback suppression method provided by an embodiment of the present invention.

[0025] As Figure 1 shown, in step 101, an input signal is acquired, and the correlation between the input signal and the speaker feedback signal is reduced;

[0026] In step 102, the energy proportion of the feedback signal in the input signal is reduced to obtain an output signal, where the feedback signal is a signal obtained by passing the speaker feedback signal through a feedback function.

[0027] In this embodiment, for step 101, the signal is collected by a speaker, and the correlation of the collected signal is reduced, mainly reducing the correlation between the collected input signal and the speaker feedback signal. Due to the high correlation between the input signal y(ω) and the speaker feedback signal u(ω), self-cancellation is likely to occur. Therefore, the input signal needs to be preprocessed to reduce its correlation. The way of decorrelation can be decorrelation by adding white noise according to the signal-to-noise ratio, or adding a pre-filter for decorrelation.

[0028] After that, for step 102, the energy proportion of the feedback signal in the input signal is reduced to obtain an output signal. By using an adaptive filter to reduce the proportion of the actual acoustic feedback signal energy that actually amplifies the signal in the input signal, the condition for achieving howling is destroyed. The feedback signal is a signal obtained by passing the speaker feedback signal through a feedback function, where the system frequency response is:

[0029]

[0030] Howling occurs when the feedback function G(ω) and the transfer function C(ω) are in the same phase and |G(ω)*C(ω)*K|>1, where K is the speaker gain.

[0031] The method of the embodiment of the present application can effectively prevent howling by reducing the correlation of the input signal, destroying the conditions for howling, and combining with reducing the energy ratio of the feedback signal to increase the maximum gain of the system. At the same time, it increases the upper limit of the amplification gain of the input signal by the assistive listening headphone system to obtain a larger output gain.

[0032] In some alternative embodiments, a pre-filter is used to whiten the input signal and the speaker feedback signal to reduce their correlation. The actual input signal y(ω) = voice signal v(ω) + feedback signal x(ω) + ambient noise n(ω), where the pre-filter is the estimated inverse H′ -1 (ω) of the voice model. The estimated inverse of the voice model is calculated using the input signal and the speaker feedback signal to obtain the whitened pure voice signal and the whitened speaker feedback signal.

[0033] The method of the embodiment of the present application whitens the input signal y(ω) and the output signal u(ω) by using the pre-filter H′ -1 (ω) to reduce their correlation and increase the maximum gain of the system.

[0034] In some alternative embodiments, the correlation between the estimated whitened pure voice signal and the whitened speaker feedback signal is calculated. The estimated pure voice signal e(ω) is obtained by subtracting the estimated feedback function G′(ω) of the previous frame multiplied by the speaker feedback signal u(ω) from the input signal y(ω). The estimated whitened pure voice signal e -1 (ω) is obtained by multiplying the estimated pure voice signal e(ω) by the pre-filter H’ p (ω), where the superscript P represents the signal after whitening; the speaker feedback signal u(ω) is multiplied by the pre-filter H’ -1 (ω) to obtain the whitened speaker feedback signal u p (ω). The estimated pure voice signal is obtained by subtracting the estimated feedback signal from the input signal. The estimated feedback signal is obtained from the speaker feedback signal through the estimated feedback function. The correlation between the two is calculated, and the white noise r(ω) added to the output signal u(ω) is calculated from the correlation coefficient. The pre-estimated signal-to-noise ratio is determined based on the calculated correlation, and the intensity of the required added white noise signal is calculated based on the pre-estimated signal-to-noise ratio.

[0035] It should be noted that in the present application, the input signal y(ω) and the output signal u(ω) are whitened by using the pre-filter H′ -1 (ω) to reduce their correlation and increase the maximum gain of the system. At the same time, the pre-estimated signal-to-noise ratio is used to calculate the intensity of the required added white noise signal r(ω).

[0036] In some alternative embodiments, the estimation of the pure speech signal and the pre-filter are calculated to obtain the whitened pure speech signal. The estimated pure speech signal e(ω) is multiplied by the pre-filter H’ -1 (ω) to obtain the whitened pure speech signal e p (ω). Then, the loudspeaker feedback signal and the pre-filter are calculated to obtain the whitened loudspeaker feedback signal. The loudspeaker feedback signal u(ω) is multiplied by the pre-filter H’ -1 (ω) to obtain the whitened loudspeaker feedback signal u p (ω). For example, e(ω) and the pre-filter H’ -1 (ω) are multiplied to obtain e p (ω); u(ω) and the pre-filter H’ -1 (ω) are multiplied to obtain u p (ω).

[0037] In some alternative embodiments, the estimation of the pure speech signal is obtained by calculating the input signal, the feedback function estimated from the previous frame, and the feedback signal. The estimated pure speech signal e(ω) is obtained by subtracting the product of the feedback function G′(ω) estimated from the previous frame and the loudspeaker feedback signal u(ω) from the input signal y(ω). The input signal is a pure input signal that only contains the speech signal, the feedback signal, and the environmental noise signal.

[0038] In some alternative embodiments, the estimation of the feedback function is obtained by calculating using the whitened signal after decorrelation. Based on the whitened loudspeaker feedback signal and the whitened pure speech signal after decorrelation, the estimation of the feedback function is obtained. For example, the transfer function is calculated using the decorrelated e p (ω) and u p (ω): u p (ω) / e p (ω) = G′(ω), to obtain the estimation of the current hearing aid feedback function G(ω).

[0039] In some alternative embodiments, the estimation of the whitened pure speech signal and (e p (ω)) / (e p (ω)) 2 are calculated to obtain R(ω). Then, R(ω) and the preset white noise source are calculated to obtain the white noise r(ω). The calculation formula is u p (ω)*(e p (ω)) / (e p (ω)) 2 = R(ω); R(ω)*n(ω) = r(ω), where n(ω) is the set white noise source.

[0040] In some alternative embodiments, the input signal y(ω), the feedback function G′(ω) estimated from the previous frame, and the speaker feedback signal u(ω) are calculated to obtain the amplified signal E(ω). By calculating the transfer function C(ω) for the amplified signal E(ω), the speaker gain K, and the white noise r(ω), the output signal is obtained, where the calculation formula is y(ω) - G′(ω) * u(ω) = E(ω), and E(ω) * C(ω) * K + r(ω) = output signal.

[0041] Please refer to Figure 2 , which shows the howling generation schematic diagram of the acoustic feedback suppression method of the present invention.

[0042] As Figure 2 shown, v(ω) is the near-end speech; n(ω) is the environmental noise which is not considered; u(ω) is the speaker feedback signal; y(ω) is the signal collected by the speaker and also the input signal; C(ω) is the transfer function, K is the speaker gain; G(ω) is the feedback function, and x(ω) is the feedback signal.

[0043] The system frequency response is:

[0044] Therefore: When G(ω) and C(ω) are in the same phase and |G(ω) * C(ω) * K| > 1, howling occurs.

[0045] Please refer to Figure 3 , which shows the schematic diagram of the adaptive filter of the acoustic feedback suppression method of the present invention.

[0046] As Figure 3 shown, v(ω) is the near-end speech; n(ω) is the environmental noise which is not considered; u(ω) is the speaker feedback signal; y(ω) is the signal collected by the speaker and also the input signal; C(ω) is the transfer function, K is the speaker gain; G(ω) is the feedback function, and x(ω) is the feedback signal; G′ is the estimation of G, and X′ is the estimation of X. The advantage of using the adaptive filter method is that it can reduce the proportion δ = x(ω) – x^(ω) of the actual acoustic feedback signal energy in the amplified signal E(ω), thus destroying the conditions for howling to occur. However, the problem with such a design is that due to the high correlation between y(ω) and u(ω), self-cancellation is likely to occur. Therefore, it is necessary to preprocess the input signal to reduce its correlation.

[0047] Please refer to Figure 4 , which shows the pre-filter decorrelation schematic diagram of the acoustic feedback suppression method of the present invention.

[0048] As Figure 4As shown, v(ω) is the proximal speech; n(ω) is the environmental noise, which is not considered; u(ω) is the speaker feedback signal; y(ω) is the microphone acquisition signal; C(ω) is the transfer function, and K is the speaker gain; G(ω) is the feedback function, and x(ω) is the feedback signal; G′(ω) is the estimate of G(ω), and x′(ω) is the estimate of x(ω).

[0049] w(ω) is the assumed white noise signal source; H(ω) is the assumed language model; H′ -1 (ω) is the inverse of the estimate of the speech model H; e(ω) is the estimate of the pure input speech v(ω) obtained by subtracting the feedback estimate x′(ω) from y(ω); e p (ω) is the whitened signal after e(ω) passes through H′ -1 (ω); u p (ω) is the whitened signal after u(ω) passes through H′ -1 (ω); u p and e p update G′(ω), and calculate the correlation between the two at the same time. The white noise r(ω) added to the output signal u(ω) is calculated from the correlation coefficient; the signals are whitened by using the pre-filter H′ -1 (ω) for the input signal y(ω) and the output signal u(ω) to reduce their correlation and increase the maximum gain of the system. At the same time, the pre-estimated signal-to-noise ratio is used to calculate the required intensity of the added white noise signal r(ω).

[0050] Please refer to Figure 5 , which shows the step flowchart of the acoustic feedback suppression method of the present invention.

[0051] As Figure 5 shown, step 1: The actual input signal is y(ω) = v(ω) + x(ω) + n(ω) (speech + feedback sound + environmental noise)

[0052] Step 2: Subtract the G′(ω)*u(ω) estimated in the previous frame from y(ω) to obtain e(ω);

[0053] Multiply e(ω) by the pre-filter H’ -1 (ω) to obtain e p (ω); Multiply u(ω) by the pre-filter H’ -1 (ω) to obtain u p (ω);

[0054] Step 3: Use the decorrelated e p (ω) and u p (ω) to calculate the transfer function: u p (ω) / e p (ω) = G′(ω) to obtain the estimate of the current hearing aid feedback function G(ω).

[0055] Step 4: R(ω) = u p (ω)*conj(e p (ω)) / (e p (ω)) 2 ;

[0056] r(ω) = R(ω)*n(ω); n(ω) is a set white noise source

[0057] Step 5: E(ω) = y(ω) - G′(ω)*u(ω);

[0058] Step 6: u(ω) = E(ω)*C(ω)*K + r(ω); obtaining the output signal.

[0059] Step 7: Repeat the above operations for the new frame of data.

[0060] It should be noted that, for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of actions combined. However, those skilled in the art should know that the present invention is not limited by the described action sequence, because according to the present invention, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention. In the above embodiments, the descriptions of each embodiment have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0061] In some embodiments, the embodiments of the present invention provide a non - volatile computer - readable storage medium, in which one or more programs including execution instructions are stored, and the execution instructions can be read and executed by an electronic device (including but not limited to a computer, a server, or a network device, etc.) to execute any one of the above - mentioned acoustic feedback suppression methods of the present invention.

[0062] In some embodiments, the embodiments of the present invention further provide a computer program product, the computer program product includes a computer program stored on a non - volatile computer - readable storage medium, the computer program includes program instructions, and when the program instructions are executed by a computer, the computer is made to execute any one of the above - mentioned acoustic feedback suppression methods.

[0063] In some embodiments, the embodiments of the present invention further provide an electronic device, which includes: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and when the instructions are executed by the at least one processor, the at least one processor is enabled to execute the acoustic feedback suppression method.

[0064] Figure 6 It is a schematic diagram of the hardware structure of an electronic device that executes the acoustic feedback suppression method provided by another embodiment of the present application. As Figure 6 shown, the device includes:

[0065] One or more processors 610 and a memory 620, Figure 6 Taking one processor 610 as an example.

[0066] The device that executes the acoustic feedback suppression method may further include: an input device 630 and an output device 640.

[0067] The processor 610, the memory 620, the input device 630, and the output device 640 may be connected through a bus or other means, Figure 6 Taking the connection through a bus as an example.

[0068] The memory 620, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as the program instructions / modules corresponding to the acoustic feedback suppression method in the embodiments of the present application. The processor 610 executes various functional applications and data processing of the server by running the non-volatile software programs, instructions, and modules stored in the memory 620, that is, implementing the acoustic feedback suppression method in the above method embodiments.

[0069] The memory 620 may include a program storage area and a data storage area. Among them, the program storage area can store an operating system and application programs required for at least one function; the data storage area can store data created according to the use of the acoustic feedback suppression device, etc. In addition, the memory 620 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices. In some embodiments, the memory 620 may optionally include a memory remotely set relative to the processor 610, and these remote memories can be connected to the acoustic feedback suppression device through a network. Examples of the above networks include, but are not limited to, the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0070] The input device 630 can receive input digital or character information, and generate signals related to the user settings and function control of the acoustic feedback suppression device. The output device 640 may include a display device such as a display screen.

[0071] The one or more modules are stored in the memory 620, and when executed by the one or more processors 610, execute the acoustic feedback suppression method in any of the above method embodiments.

[0072] The above products can execute the methods provided in the embodiments of the present application, and have the corresponding functional modules and beneficial effects for executing the methods. For technical details not described in detail in this embodiment, reference may be made to the methods provided in the embodiments of the present application.

[0073] The electronic devices in the embodiments of the present application exist in various forms, including but not limited to:

[0074] (1) Mobile communication devices: These devices are characterized by having mobile communication functions and mainly aim to provide voice and data communication. Such terminals include: smart phones, multimedia phones, functional phones, and low-end phones, etc.

[0075] (2) Ultra-mobile personal computer devices: These devices belong to the category of personal computers, have computing and processing functions, and generally also have the characteristic of mobile Internet access. Such terminals include: PDA, MID, and UMPC devices, etc.

[0076] (3) Portable entertainment devices: These devices can display and play multimedia content. Such devices include: audio and video players, handheld game consoles, e-books, and intelligent toys and portable vehicle navigation devices.

[0077] (4) Other airborne electronic devices with data interaction functions, such as in-vehicle device installed on a vehicle.

[0078] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution in this embodiment.

[0079] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the essence of the above technical solution, or the part that contributes to the related technology, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0080] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. An acoustic feedback suppression method, comprising: Obtaining an input signal and reducing the correlation between the input signal and the speaker feedback signal, including whitening the input signal and the speaker feedback signal using a pre-filter to reduce the correlation, wherein the pre-filter is the inverse of the estimated speech model; Calculating the correlation between the estimated pure speech signal after whitening and the speaker feedback signal after whitening, wherein the estimated pure speech signal is the input signal minus the estimated feedback signal, and the estimated feedback signal is obtained from the speaker feedback signal through an estimated feedback function; Obtaining a pre-estimated signal-to-noise ratio based on the calculated correlation and using the pre-estimated signal-to-noise ratio to calculate the required white noise signal strength; Reducing the energy proportion of the feedback signal in the input signal to obtain an output signal, wherein the feedback signal is the signal obtained from the speaker feedback signal through a feedback function.

2. The method according to claim 1, wherein The calculating the correlation between the estimated pure speech signal after whitening and the speaker feedback signal after whitening includes: Calculating the estimated pure speech signal and the pre-filter to obtain the pure speech signal after whitening; Then calculating the speaker feedback signal and the pre-filter to obtain the speaker feedback signal after whitening.

3. The method according to claim 1, wherein, The estimated pure speech signal being the input signal minus the estimated feedback signal includes: Calculating the estimated pure speech signal by calculating the input signal, the estimated feedback function of the previous frame, and the feedback signal, wherein the input signal is a pure input signal that only includes a speech signal, a feedback signal, and an environmental noise signal.

4. The method according to claim 1, wherein After reducing the correlation between the input signal and the speaker feedback signal, it includes: Calculating the speaker feedback signal after de-correlation and the pure speech signal after de-correlation to obtain an estimate of the feedback function.

5. The method according to claim 1, wherein Using a pre-filter to reduce the energy proportion of the feedback signal in the input signal, the method further includes: The estimation of the whitened pure speech signal \(R(\omega)=(u P (\omega) / e P (\omega)) 2 is calculated to obtain \(R(\omega)\), where the superscript \(P\) represents the signal after whitening processing. Here, \(u p (\omega)\) is the whitened loudspeaker feedback signal, \(e p (\omega)\) is the whitened pure speech signal, and \(R(\omega)\) is the energy ratio of \(u p (\omega)\) and \(e p (\omega)\) after whitening; Calculating white noise by calculating the R(ω) and a preset white noise source.

6. The method according to claim 5, further comprising: Calculating the input signal, the estimated feedback function of the previous frame, and the speaker feedback signal to obtain an amplified signal; Calculating the output signal by performing a transfer function calculation on the amplified signal, the speaker gain, and the white noise.

7. An electronic device, comprising: At least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the steps of the method according to any one of claims 1 to 6.

8. A storage medium having a computer program stored thereon, characterized in that, When the program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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