WO2021175267A1

WO2021175267A1 - Method for implementing active noise cancellation, apparatus, and electronic device

Info

Publication number: WO2021175267A1
Application number: PCT/CN2021/078951
Authority: WO
Inventors: 施栋; 苏杰
Original assignee: 华为技术有限公司
Priority date: 2020-03-03
Filing date: 2021-03-03
Publication date: 2021-09-10
Also published as: CN113365176B; CN113365176A

Abstract

The embodiments of the present application provide a method for implementing active noise cancellation, an apparatus, and an electronic device. Said method comprises: acquiring a playback content signal; determining, according to the playback content signal, the masking effect generated by the playback content signal on an external noise signal; and according to the masking effect generated by the playback content signal on the external noise signal, generating an active noise signal for implementing active noise cancellation, wherein the active noise signal is used to control the frequency spectrum of the external noise signal arriving at a human ear to be below the masking effect of the frequency spectrum of the playback content signal. Compared with the prior art, the method according to the embodiments of the present application improves the noise reduction effect.

Description

Method, device and electronic equipment for realizing active noise elimination

Technical field

This application relates to the technical field of smart terminals, and in particular to a method, device and electronic equipment for realizing active noise cancellation.

Background technique

In the application scenario of earphones, there are many different earphone noise reduction technical solutions, and one of the common earphone noise reduction technical solutions is Active Noise Cancellation (ANC) solution. The ANC scheme is to reduce noise at the human ear. Its principle is: all sounds are composed of a certain frequency spectrum. If a sound (active noise) can be found, its frequency spectrum is exactly the same as the external noise to be eliminated, but the phase is just right. On the contrary (a difference of 180°), the external noise can be completely cancelled out. For example, in an implementation of the ANC solution, the active noise is output to the human ear. At the human ear, the active noise and the external noise are cancelled out, and the noise reduction of the earphone can be realized.

Although in theory, according to the realization principle of the ANC scheme, the noise reduction can be achieved by offsetting the active noise with external noise at the human ear. However, in the actual application scenario of the ANC scheme, there is a situation where a part of the external noise is still heard by the human ear after the active noise is canceled by the external noise at the human ear, and the noise reduction effect after the implementation of the ANC scheme is not ideal.

Summary of the invention

This application provides a method, device and electronic equipment for realizing active noise cancellation. This application also provides a computer-readable storage medium to provide an active noise cancellation solution and improve the noise reduction effect of the active noise cancellation solution.

Aiming at the problem that the noise reduction effect after the implementation of the ANC scheme in the prior art is not ideal, the embodiments of the present application propose the following technical solutions:

In the first aspect, an embodiment of the present application proposes a method for realizing active noise cancellation, including:

Obtain the playback content signal;

Determining, according to the playback content signal, the masking effect of the playback content signal on the external noise signal;

According to the masking effect of the playback content signal on the external noise signal, an active noise signal for realizing active noise cancellation is generated, wherein the active noise signal is used to control the frequency spectrum of the external noise signal reaching the human ear at the Under the masking effect of the frequency spectrum of the content signal.

In an implementation manner of the foregoing first aspect, an active noise signal for realizing active noise cancellation is generated according to the masking effect of the playback content signal on the external noise signal, wherein:

Determine the intensity of the active noise in the first frequency band according to the masking effect of the playback content signal on the external noise signal in the first frequency band.

In an implementation manner of the foregoing first aspect, determining, according to the playback content signal, the masking effect of the playback content signal on the external noise signal includes:

Obtain the noise signal in the ear;

Determine the masking effect of the playback content signal on the ear noise signal.

In an implementation manner of the foregoing first aspect, generating an active noise signal for realizing active noise cancellation according to the masking effect of the playback content signal on the external noise signal includes:

Determining the feedback input of the in-ear noise signal in the control strategy of active noise cancellation according to the masking effect of the playback content signal on the in-ear noise signal;

Based on the feedback input of the ear noise signal, the active noise signal is generated according to the control strategy of the active noise cancellation.

In an implementation manner of the above-mentioned first aspect, the feedback input of the ear noise signal in the control strategy of active noise cancellation is determined according to the masking effect of the playback content signal on the ear noise signal, wherein, according to The masking effect of the play content signal on the ear noise signal on the first frequency band determines the strength of the feedback input of the ear noise signal on the first frequency band.

In an implementation manner of the foregoing first aspect, determining the masking effect of the playback content signal on the ear noise signal includes:

Calculating the frequency spectrum of the ear noise signal according to the ear noise signal;

Calculating the frequency spectrum of the playback content signal according to the playback content signal;

According to the frequency spectrum of the ear noise signal and the frequency spectrum of the playback content signal, the masking effect of the playback content signal on the ear noise signal in each frequency band is determined.

Determine the frequency band weights corresponding to different frequency bands of the ear noise signal according to the masking effect produced by the frequency spectrum of the playback content signal on the frequency spectrum of the ear noise signal. The stronger the masking effect, the higher the corresponding frequency band weight. small;

According to the frequency band weights corresponding to different frequency bands of the in-ear noise signal, the in-ear noise signal is filtered to obtain the in-ear noise filtering result signal, wherein the smaller the frequency band weight is, the in-ear noise filtering result signal is The lower the signal strength of the corresponding frequency band;

The in-ear noise filtering result signal is used as the feedback input of the in-ear noise signal in the control strategy of active noise cancellation.

In the second aspect, an embodiment of the present application also proposes a device for realizing active noise cancellation, including:

The first signal acquisition module, which is used to acquire the playback content signal;

A masking effect analysis module, which is used to determine the masking effect of the playback content signal on the external noise signal;

The active noise generation module is used to generate an active noise signal for realizing active noise cancellation according to the masking effect of the playback content signal on the external noise signal, so that the frequency spectrum of the external noise signal reaching the human ear is controlled in the Under the masking effect of the frequency spectrum of the content signal.

In the third aspect, an embodiment of the present application also proposes an electronic device. The electronic device includes a memory for storing computer program instructions and a processor for executing the program instructions, wherein when the computer program instructions are executed by the processor At this time, the electronic device is triggered to execute the method steps described in the embodiments of the present application.

In a fourth aspect, an embodiment of the present application also proposes a computer-readable storage medium. The computer-readable storage medium stores a computer program, which when running on a computer, causes the computer to execute the method of the embodiment of the present application.

The foregoing at least one technical solution adopted in the embodiments of the present application can achieve the following beneficial effects:

According to the method of the embodiment of the present application, an active noise signal for realizing active noise cancellation is generated based on the masking effect generated by the playing content signal on the external noise signal, so that the frequency spectrum of the external noise signal reaching the human ear is controlled at the level of the playing content signal. Under the masking effect of the frequency spectrum, the external noise heard by the user can be effectively reduced; compared with the prior art, the method according to the embodiment of the present application can greatly improve the noise reduction effect.

Description of the drawings

Fig. 1 shows a flowchart of an embodiment of an active noise cancellation method according to the present application;

Figure 2 shows a schematic diagram of an application scenario of an implementation of the ANC solution;

Fig. 3 is a flowchart of an embodiment of an active noise cancellation method according to the present application;

Figure 4 shows a schematic diagram of an implementation of the ANC scheme;

FIG. 5 shows a schematic diagram of an ANC solution according to an embodiment of the present application;

Fig. 6 shows a flowchart of an embodiment of an active noise cancellation method according to the present application;

Figure 7 shows a schematic diagram of the comparison of the implementation effects of two active noise cancellation schemes;

Fig. 8 is a structural diagram of an embodiment of an active noise cancellation device according to the present application.

Detailed ways

In order to make the purpose, technical solutions and advantages of the present application clearer, the technical solutions of the present application will be described clearly and completely in conjunction with specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of this application.

The terms used in the implementation mode part of this application are only used to explain specific embodiments of this application, and are not intended to limit this application.

In view of the problem that the noise reduction effect after the implementation of the ANC scheme in the prior art is not ideal, the embodiment of the present application proposes a method for realizing active noise cancellation. In order to propose the method of the embodiment of the present application, the inventor first analyzes the principle essence of the ANC solution and the actual application scenario of the ANC solution.

The principle of the ANC scheme is: all sounds are composed of a certain frequency spectrum. If you can find a sound (active noise) whose frequency spectrum is exactly the same as the external noise to be eliminated, but the phase is exactly opposite (a difference of 180°), you can Completely cancel out the external noise. Analysis based on the foregoing principles shows that in the ANC solution, the realization of noise reduction is essentially to reduce (minimize) the energy of external noise reaching the human ear, that is, the energy of the noise in the user's ear. However, in actual application scenarios, the external noise introduced into the user's ear does not mean that the user can perceive the external noise. For example, in a scene where a user listens to music, even if external noise leaks into the ear, as long as the music of the earphone exceeds the noise energy by more than a certain value, a masking effect will occur, causing the user to not hear the external noise. At this time, the active noise cancellation is still carried out according to the scheme of reducing (minimizing) the energy of the external noise reaching the human ear, which will result in the final external noise in the ear being cancelled by the active noise, and a part of it may still be heard by the user .

Therefore, in an embodiment of the present application, when the active noise cancellation scheme is implemented, when generating active noise, the masking effect generated by the playback content signal on the external noise signal is first determined, and then the active noise is determined based on the masking effect.

The technical solutions provided by the embodiments of the present application will be described in detail below with reference to the accompanying drawings.

Fig. 1 shows a flowchart of an embodiment of an active noise cancellation method according to the present application. In an embodiment of the present application, as shown in FIG. 1, the active noise cancellation method includes:

Step 110: Obtain a play content signal;

Step 120: Determine, according to the playback content signal, the masking effect of the playback content signal on the external noise signal;

Step 130: Generate an active noise signal for realizing active noise cancellation according to the masking effect of the playback content signal on the external noise signal, where the active noise signal is used to control the frequency spectrum of the external noise signal reaching the human ear to the playback content signal Under the masking effect of the spectrum.

Further, in the specific actual process of the embodiment shown in FIG. 1, each step of the embodiment shown in FIG. 1 may adopt a variety of different specific implementation manners.

In a specific application scenario, the active noise is divided into multiple different frequency bands, and the active noise of the different frequency bands are respectively determined to form a complete active noise finally. Therefore, in an implementation of step 130, in the process of generating an active noise signal for realizing active noise cancellation according to the masking effect of the broadcast content signal on the external noise signal, according to the broadcast content signal in a certain frequency band The masking effect on the external noise signal determines the strength of the active noise in this frequency band. For example, for the first frequency band (the first frequency band may be any frequency band), the strength of the active noise in the first frequency band is determined according to the masking effect of the playing content signal on the external noise signal in the first frequency band.

Figure 2 shows a schematic diagram of an application scenario of an implementation of the ANC solution. As shown in FIG. 2, the microphone 201 is a microphone arranged on the non-ear part of the earphone, and the microphone 202 is a microphone arranged on the ear part of the earphone. The microphone 202 can collect environmental noise signals (in-ear noise signals) that can be heard by the ear; the microphone 201 can collect external noise signals (external noise signals).

In the actual application scenario shown in Figure 2, one implementation of the ANC solution is to transmit the noise signal in the ear and the noise signal outside the ear to the control circuit, and perform real-time calculations to generate an active signal with the opposite phase and the same amplitude as the noise in the ear. Noise signal 212; the active noise signal 212 is transmitted through the speaker on the earphone to cancel the noise. The noise signal 211 passes through the earphone into the ear outside the ear, and cancels out with the active noise signal 212 in the ear.

In the application scenario shown in Figure 2, the noise signal in the ear is the noise signal reaching the human ear. Therefore, for the application scenario shown in FIG. 2, in an implementation of step 120 shown in FIG. 1, determining the masking effect of the playback content signal on the external noise signal is to determine the effect of the playback content signal on the ear noise signal. The resulting masking effect.

Fig. 3 shows a flowchart of an embodiment of an active noise cancellation method according to the present application. In an implementation manner of step 120, as shown in FIG. 3, the process of determining the masking effect of the playing content signal on the external noise signal includes:

Step 310: Obtain a noise signal in the ear;

Step 320: Determine the masking effect of the playing content signal on the ear noise signal.

Further, in an application scenario shown in FIG. 2, in the control strategy of active noise cancellation, a closed-loop feedback scheme is used to generate the active noise signal 212. Specifically, the calculation circuit uses the ear noise signal acquired by the microphone 202 as a feedback signal, performs closed-loop feedback calculation based on the feedback signal, and processes the signal acquired by the microphone 201 to generate noise waves with opposite phases to cancel each other in the ear.

Taking a specific application scenario as an example, Figure 4 shows a schematic diagram of an implementation of the ANC solution. As shown in FIG. 4, the data input node 401 refers to the microphone 201 arranged on the non-ear part of the headset shown in FIG. 2, and the data input node 402 refers to the microphone 202 arranged on the ear part of the headset shown in FIG. 2. The

modules

403, 405, and 406 respectively use calculation functions P(z), S(z), and S(z) to perform calculation processing on their input to generate output.

The input of 401 is the external-ear noise signal x(n), where n represents the sampling point.

The module 403 is used to simulate the transmission environment in which external noise penetrates into the ear through the earphone. P(z) represents the transfer function of the external noise penetrating the ear through the earphone. Therefore, the output d(n) of the module 411 is the ear noise signal.

The module 406 is used to simulate the transmission environment of the active noise signal in the ear. S(z) is the transfer function from the earphone speaker to the microphone 402. S(z) can be measured in advance or estimated in real time (for example, when the earphone is playing music downstream).

Module 404 is used to refer to an adaptive filter that generates an active noise signal. The adaptive filter processes the external noise signal x(n) to generate an active noise signal, and H(z) represents the parameters of the adaptive filter.

In this ANC implementation scheme, when generating active noise signals, the purpose of the calculation module is to estimate H(z) to make it as close to P(z) as possible. Then x(n) obtains y(n) through H(z) and S(z), which can cancel out the noise signal d(n) in the ear. With H(z) as the working parameter of the adaptive filter, it is possible to output an active noise signal that can actively cancel and reduce noise. Specifically, closed-loop feedback is used to adjust H(z). The e(n) input by 402 is the residual noise signal (error signal) that y(n) and d(n) cancel out. The module 407 is based on the Least Mean Square (LeastMeanSquare, LMS) algorithm, takes e(n) as the feedback input, and adjusts the H(z) parameter according to the e(n) and the output of the module 405.

For the control strategy of active noise cancellation using feedback calculation shown in Figure 4. In an implementation of step 120 shown in FIG. 1, the in-ear noise signal obtained by the microphone 202 is not directly used as the feedback signal, but is based on the masking effect of the broadcast content signal on the in-ear noise signal on the in-ear noise signal. Perform processing to determine the feedback signal.

Specifically, in an implementation manner of step 120, as shown in FIG. 3, the process of generating an active noise signal for realizing active noise cancellation according to the masking effect generated by the playback content signal on the external noise signal includes:

Step 330: Determine the feedback input of the in-ear noise signal in the control strategy of active noise cancellation according to the masking effect of the playing content signal on the in-ear noise signal;

Step 340: Generate active noise according to the control strategy of active noise cancellation based on the feedback input of the noise signal in the ear.

Taking a specific application scenario as an example, FIG. 5 shows a schematic diagram of an ANC solution according to an embodiment of the present application. As shown in FIG. 5, the data input node 501 refers to the microphone 201 placed on the non-ear part of the headset shown in FIG. 2, and the data input node 502 refers to the microphone 202 placed on the ear part of the headset shown in FIG. 2. The

modules

503, 505, and 506 respectively use calculation functions P(z), S(z), and S(z) to perform calculation processing on their input to generate an output.

The input of 501 is the external-ear noise signal x(n), where n represents the sampling point.

The module 503 is used to simulate the transmission environment in which external noise penetrates into the ear through the earphone. P(z) represents the transfer function of the external noise infiltrating the ear through the earphone. Therefore, the output d(n) of the module 511 is the ear noise signal.

The module 506 is used to simulate the transmission environment of the active noise signal in the ear. S(z) is the transfer function from the earphone speaker to the microphone 402. S(z) can be measured in advance or estimated in real time (for example, when the earphone is playing music downstream).

Module 504 is used to refer to an adaptive filter that generates an active noise signal. The adaptive filter processes the external noise signal x(n) to generate an active noise signal, and H(z) represents the parameters of the adaptive filter.

In this ANC implementation scheme, when generating active noise signals, the purpose of the calculation module is to estimate H(z) to make it as close to P(z) as possible. Then x(n) obtains y(n) through H(z) and S(z), which can cancel out the noise signal d(n) in the ear. With H(z) as the working parameter of the adaptive filter, it is possible to output an active noise signal that can actively cancel and reduce noise. Specifically, closed-loop feedback is used to adjust H(z). The module 507 is based on the least mean square algorithm (LeastMeanSquare, LMS), and adjusts the H(z) parameter according to the feedback input and the output of the module 505.

502 input e(n) is y(n) and d(n) to cancel the residual noise signal. Different from the embodiment shown in FIG. 4, in the embodiment shown in FIG. 5, when the module 507 performs closed-loop feedback adjustment H(z), it does not use e(n) as the feedback input, but uses the output q( n) is the feedback input.

The block 508 refers to a filter with W(z) as the filter parameter. The masking effect analyzer 510 inputs the analysis result of the masking effect generated by the playback content signal on the ear noise signal to the module 508. The module 508 adjusts e(n) based on the analysis result of the masking effect, and inputs the adjustment result as a feedback input to the module 508. Module 507.

Specifically, in an implementation manner of step 330, in the process of determining the feedback input of the in-ear noise signal in the control strategy of active noise cancellation according to the masking effect generated by the playback content signal on the in-ear noise signal, according to the playback content The masking effect of the signal on the ear noise signal in a certain frequency band determines the strength of the feedback input of the ear noise signal in this frequency band. For example, for the first frequency band (the first frequency band can be any frequency band), the strength of the feedback input of the ear noise signal in the first frequency band is determined according to the masking effect of the broadcast content signal on the ear noise signal in the first frequency band .

Further, in an implementation manner of step 120, the masking effect is analyzed by analyzing the frequency spectrum of the audio signal. Fig. 6 shows a flowchart of an embodiment of an active noise cancellation method according to the present application. In an implementation manner of step 120, as shown in FIG. 6, the process of determining the masking effect of the playing content signal on the ear noise signal includes:

Step 610: Calculate the frequency spectrum of the ear noise signal according to the ear noise signal;

Step 620: Calculate the frequency spectrum of the played content signal according to the played content signal;

Step 630: Determine, according to the frequency spectrum of the noise signal in the ear and the frequency spectrum of the playback content signal, the masking effect of the playback content signal in each frequency band on the noise signal in the ear.

Further, in an implementation manner of step 120, the masking effect of the playing content signal on each frequency band of the ear noise signal is represented by allocating corresponding weights to each frequency band of the ear noise signal. Specifically, for a certain frequency band, the stronger the shielding effect of the broadcast content signal on the ear noise signal, the smaller the frequency band weight corresponding to the frequency band of the ear noise signal.

Specifically, as shown in FIG. 6, in an implementation manner of step 120, the process of generating an active noise signal for realizing active noise cancellation according to the masking effect generated by the playback content signal on the external noise signal includes:

Step 640: Determine frequency band weights corresponding to different frequency bands of the ear noise signal according to the masking effect produced by the frequency spectrum of the playing content signal on the frequency spectrum of the ear noise signal, where the stronger the masking effect, the smaller the corresponding frequency band weight;

Step 650: Filter the in-ear noise signal according to the frequency band weights corresponding to different frequency bands of the in-ear noise signal to obtain the in-ear noise filtering result signal, where the smaller the frequency band weight, the signal strength of the corresponding frequency band in the in-ear noise filtering result signal Smaller

Step 660: Use the in-ear noise filtering result signal as a feedback input of the in-ear noise signal in the control strategy of active noise cancellation.

Taking a specific application scenario as an example, as shown in FIG. 5, the masking effect analyzer 510 includes an in-ear noise spectrum estimation module 511, a playback content spectrum estimation module 512, and a frequency band weight allocation module 513. The ear noise frequency spectrum estimation module 511 is used to implement step 610 to calculate the frequency spectrum of the ear noise signal. The played content frequency spectrum estimation module 512 is used to implement step 520 to calculate the frequency spectrum of the played content signal. The frequency band weight allocation module 513 is used to implement

steps

630 and 640, and determine the weights corresponding to the respective frequency spectrums of the ear noise signals according to the frequency spectrum of the ear noise signal and the frequency spectrum of the playing content signal. The module 508 is used to implement

steps

650 and 660, adjust e(n) according to the weight corresponding to each spectrum of the noise signal in the ear, attenuate the frequency with lower weight in e(n), and output the adjusted error signal q(n ).

Specifically, in an implementation manner of steps 610 to 660, as shown in FIG. 5, in the process of implementing step 610, in an ideal state, y(n) and d(n) are completely canceled, and the ear noise spectrum is estimated The input of block 511 is y(n). However, in actual operation, y(n) and d(n) are not completely offset, and e(n) exists. Therefore, the input of the ear noise spectrum estimation module 511 is y(n) and e(n).

Let Y(w,n) and E(w,n) represent the Fourier transform of y(n) and e(n), where w represents the frequency. _{Then the instantaneous energy N in} (ω, n) of the total noise in the ear can be expressed as

N _in (ω,n)=|Y(ω,n)| ² +|E(ω,n)| ² . (Formula 1)

In formula 1, |E(ω,n)| ² can be calculated when the downlink is muted to prevent the energy of the content from being mixed into the noise energy estimation during downlink playback.

Further, in order to obtain a more stable noise estimate, N _in (ω, n) is smoothed based on the following formula:

In formula 2, α is a pre-defined constant. For example, in an application scenario, the value of α is 0.99.

Based on the above formula 1 and formula 2, the in-ear noise spectrum estimation module 511 is implemented, so as to obtain the calculation result of the in-ear noise spectrum according to y(n) and e(n).

In the process of implementing step 620, as shown in FIG. 5, the broadcast content spectrum estimation module 512 calculates the downlink broadcast content spectrum based on the following formula:

In formula 3, M _d (ω, n) represents the energy spectrum of the instantaneous content;

Represents the smoothed music energy spectrum; S(ω) is the transfer function from the earphone speaker to the microphone 202.

Based on the above formula 3, the play content frequency spectrum estimation module 512 is implemented, so as to obtain the calculation result of the play content frequency spectrum.

In the process of implementing steps 630 to 640, as shown in FIG. 5, the input ear noise spectrum and the playback content spectrum of the frequency band weight allocation module 513 are:

and

Based on the above two values, it can be calculated which frequency bands can be reduced in weight (without cancellation) or which need to be cancelled by the ANC algorithm.

The specific weights are calculated as follows:

In formula 4, W(ω) is the weight of frequency ω, β and γ are preset constants (in an application scenario, β and γ can be set to 0.01 and 0.1, respectively).

β represents the masking effect of downstream content energy on noise. For example, in an application scenario, set:

If the noise energy is less than 0.01 times the energy of the content to be played, it can be considered that the noise is masked (the user cannot hear it), and the corresponding frequency band weight can be set to γ(0.1) at this time;

Otherwise, it is considered that the noise is not masked, and a weight of 1 is required.

In the process of implementing steps 650 to 660, as shown in Figure 5, the input of the module 508 is the weights W(ω) and e(n), and the module 508 filters e(n) to reduce the frequency with lower weight in the signal. Attenuation, the output is the adjusted error signal q(n). The filter parameter W(z) of the module 508 can be obtained according to the following method:

w(n)=FFT ^-1 (W). (Equation 5)

In formula 5, FFT ^-1 (x) represents the inverse Fourier transform of the vector x; w(n), n=0, 1,...N-1 is the impulse response of the filter parameter W(z) . W=[W(ω ₀ )W(ω ₁ )...W(ω _N-1 )] ^T represents the value of the weight at different frequencies, and W is obtained by formula 4. The relationship between the output and input of the filter parameter W(z) can be expressed as:

As shown in Fig. 5, according to formula 6, q(n) as the feedback input of the module 507 is filtered e(n). Compared with e(n), the frequency component of q(n) has been adjusted: the frequency band masked by the music energy will be attenuated; the other frequency bands remain unchanged. Therefore, when q(n) is used as the feedback input of the module 507, it can be ensured that the algorithm will pay more attention to the frequency band with high offsetting weight; thus, the energy spectrum of the residual noise can be dynamically adjusted, so that the frequency part that is not masked by the music is smaller; and The purpose of increasing the frequency part masked by music.

It can be understood that some or all of the steps or operations in the above-mentioned embodiments are merely examples, and the embodiments of the present application may also perform other operations or variations of various operations. In addition, each step may be executed in a different order presented in the foregoing embodiment, and it may not be necessary to perform all operations in the foregoing embodiment.

Figure 7 shows a schematic diagram of the comparison of the implementation effects of two active noise cancellation schemes. In an application scenario, as shown in Figure 7, the ordinate is energy and the abscissa is frequency. 701 represents the downstream content, 702 represents the noise floor, 703 represents the masking curve caused by the downstream content, 704 represents the final in-ear noise using the ANC system shown in Figure 4, and 705 represents The final in-ear noise using the ANC system shown in Figure 5.

703 in the figure shows that the downstream content brings a masking curve, that is, if the noise is smaller than this curve, the user will not be subjectively perceivable. The final in-ear noise using the ANC system shown in FIG. 4 is as shown in 704, which is slightly higher than the masking curve in the low frequency part, which is subjectively perceivable by the user. However, the ANC system shown in Figure 5 can be better balanced. As shown in 705, 705 is controlled below 703, the high-frequency noise is slightly increased (still under the masking curve) and the low-frequency is further reduced. Therefore, compared with the ANC system shown in FIG. 4, the ANC system shown in FIG. 5 can better minimize the noise subjectively perceived by the user.

Further, based on the active noise cancellation method proposed in an embodiment of the present application, an embodiment of the present application also proposes a device for realizing active noise cancellation. Fig. 8 is a structural diagram of an embodiment of an active noise cancellation device according to the present application. In an embodiment of the present application, as shown in FIG. 8, in an embodiment of the present application, active noise cancellation 800 includes:

A signal acquisition module 810, which is used to acquire a playback content signal;

A shielding effect analysis module 820, which is used to determine the shielding effect of the playback content signal on the external noise signal;

The active noise generation module 830 is used to generate an active noise signal for realizing active noise cancellation according to the masking effect generated by the playback content signal on the external noise signal, so that the frequency spectrum of the external noise signal reaching the human ear is controlled in the playback content signal Under the masking effect of the spectrum.

The device provided by an embodiment of the present application shown in FIG. 8 can be used to implement the technical solutions of the method embodiments of the embodiments of the present application. For its implementation principles and technical effects, further reference may be made to related descriptions in the method embodiments.

Specifically, in an implementation of the active noise generating module 830, the active noise generating module 830 is configured to determine the strength of the active noise in the first frequency band according to the masking effect of the playing content signal on the external noise signal in the first frequency band.

Specifically, in an implementation manner of the shielding effect analysis module 820, the shielding effect analysis module 820 includes:

The ear noise signal acquisition module is used to acquire the ear noise signal. Taking the application scenario of the embodiment shown in FIG. 5 as an example, the data input node 502 corresponds to the ear noise signal acquisition module;

The masking effect analyzer is used to determine the masking effect of the playback content signal on the ear noise signal. Taking the application scenario of the embodiment shown in FIG. 5 as an example, the module 510 corresponds to the masking effect analyzer.

Specifically, in an implementation manner of the active noise generating module 830, the active noise generating module 830 includes:

The feedback input calculation module is used to determine the control strategy of active noise cancellation according to the masking effect of the content signal on the ear noise signal. The feedback input of the noise signal in the ear is taken as an example in the application scenario of the embodiment shown in FIG. 5 , The module 508 corresponds to the feedback input calculation module;

Active noise generator, which is used to generate active noise according to the control strategy of active noise cancellation based on the feedback input of the noise signal in the ear. Taking the application scenario of the embodiment shown in FIG. 5 as an example,

modules

507 and 504 correspond to active noise generation Part of the functional module of the device.

Specifically, in an implementation of the feedback input calculation module, the feedback input calculation module is used to determine the in-ear noise signal in the first frequency band according to the masking effect of the playback content signal on the in-ear noise signal in the first frequency band. The strength of the feedback input of the noise signal.

Specifically, in an implementation of the masking effect analyzer, the masking effect analyzer includes:

An ear noise spectrum estimation module, which is used to calculate the spectrum of the ear noise signal according to the ear noise signal, such as the module 511 in the application scenario of the embodiment shown in FIG. 5;

The play content frequency spectrum estimation module is used to calculate the frequency spectrum of the play content signal according to the play content signal, such as the module 512 in the application scenario of the embodiment shown in FIG. 5;

The frequency band weight allocation module, for example, the module 513 in the application scenario of the embodiment shown in FIG. 5, the frequency band weight allocation module is used for:

According to the frequency spectrum of the noise signal in the ear and the frequency spectrum of the playback content signal, determine the masking effect of the playback content signal on the ear noise signal in each frequency band;

The frequency band weight corresponding to different frequency bands of the ear noise signal is determined according to the masking effect of the frequency spectrum of the playing content signal on the frequency spectrum of the ear noise signal. The stronger the masking effect, the smaller the corresponding frequency band weight.

In an implementation of the feedback input calculation module, the feedback input calculation module is used to:

Filter the in-ear noise signal according to the frequency band weights corresponding to different frequency bands of the in-ear noise signal to obtain the in-ear noise filtering result signal. Among them, the smaller the frequency band weight, the smaller the signal strength of the corresponding frequency band in the in-ear noise filtering result signal;

Furthermore, in the 1990s, the improvement of a technology can be clearly distinguished between hardware improvements (for example, improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the method and process). ). However, with the development of technology, the improvement of many methods and processes of today can be regarded as a direct improvement of the hardware circuit structure. Designers almost always get the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that the improvement of a method flow cannot be realized by the hardware entity module. For example, a programmable logic device (Programmable Logic Device, PLD) (for example, a Field Programmable Gate Array (Field Programmable Gate Array, FPGA)) is such an integrated circuit whose logic function is determined by the accessing party's programming of the device. It is programmed by the designer to "integrate" a digital device on a PLD without requiring the chip manufacturer to design and manufacture a dedicated integrated circuit chip. Moreover, nowadays, instead of manually making integrated circuit chips, this kind of programming is mostly realized with "logic compiler" software, which is similar to the software compiler used in program development and writing, but before compilation The original code must also be written in a specific programming language, which is called Hardware Description Language (HDL), and there is not only one type of HDL, but many types, such as ABEL (Advanced Boolean Expression Language) , AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description), etc., currently most commonly used It is VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog. It should also be clear to those skilled in the art that just a little bit of logic programming of the method flow in the above-mentioned hardware description languages and programming into an integrated circuit can easily obtain the hardware circuit that implements the logic method flow.

The controller can be implemented in any suitable manner. For example, the controller can take the form of, for example, a microprocessor or a processor and a computer-readable medium storing computer-readable program codes (such as software or firmware) executable by the (micro)processor. , Logic gates, switches, application specific integrated circuits (ASICs), programmable logic controllers and embedded microcontrollers. Examples of controllers include but are not limited to the following microcontrollers: ARC625D, Atmel AT91SAM, Microchip PIC18F26K20 and Silicon Labs C8051F320, the memory controller can also be implemented as part of the memory control logic. Those skilled in the art also know that, in addition to implementing the controller in a purely computer-readable program code manner, it is entirely possible to program the method steps to make the controller use logic gates, switches, application specific integrated circuits, programmable logic controllers, and embedded logic. The same function can be realized in the form of a microcontroller or the like. Therefore, such a controller can be regarded as a hardware component, and the devices included in it for realizing various functions can also be regarded as a structure within the hardware component. Or even, the device for realizing various functions can be regarded as both a software module for realizing the method and a structure within a hardware component.

In the description of the embodiments of this application, for the convenience of description, when describing the device, the functions are divided into various modules/units. The division of each module/unit is only a division of logical functions. At this time, the functions of each module/unit can be implemented in the same or multiple software and/or hardware.

Specifically, the devices proposed in the embodiments of the present application may be fully or partially integrated into one physical entity during actual implementation, or may be physically separated. And these modules can all be implemented in the form of software called by processing elements; they can also be implemented in the form of hardware; part of the modules can be implemented in the form of software called by the processing elements, and some of the modules can be implemented in the form of hardware. For example, the detection module may be a separately established processing element, or it may be integrated in a certain chip of the electronic device. The implementation of other modules is similar. In addition, all or part of these modules can be integrated together or implemented independently. In the implementation process, each step of the above method or each of the above modules can be completed by an integrated logic circuit of hardware in the processor element or instructions in the form of software.

For example, the above modules may be one or more integrated circuits configured to implement the above methods, such as: one or more application specific integrated circuits (ASICs), or one or more digital signal processors ( Digital Singnal Processor, DSP, or, one or more Field Programmable Gate Array (FPGA), etc. For another example, these modules can be integrated together and implemented in the form of a System-On-a-Chip (SOC).

An embodiment of the present application also proposes an electronic device. The electronic device includes a memory for storing computer program instructions and a processor for executing the program instructions. When the computer program instructions are executed by the processor, the electronic device is triggered. The device executes the method steps described in the embodiments of the present application.

Further, the electronic device shown in an embodiment of the present application may be an auxiliary device of the earphone or a circuit device built in the earphone. The device can be used to execute the functions/steps in the methods provided in the embodiments of the present application.

An embodiment of the present application also proposes a headset. The headset includes a microphone, a speaker, an audio signal input interface, a memory for storing computer program instructions, and a processor for executing program instructions. When the processor executes, the electronic device is triggered to execute the method steps described in the embodiments of the present application.

Specifically, in an embodiment of the present application, the foregoing one or more computer programs are stored in the foregoing memory, and the foregoing one or more computer programs include instructions. When the foregoing instructions are executed by the foregoing device/headset, the foregoing device/headset The headset executes the method steps described in the embodiments of the present application.

Specifically, in an embodiment of the present application, the processor of the electronic device/headphone may be an on-chip device SOC, and the processor may include a central processing unit (CPU), and may further include other types of processors . Specifically, in an embodiment of the present application, the processor of the electronic device may be a PWM control chip.

Specifically, in an embodiment of the present application, the processor involved may include, for example, a CPU, a DSP, a microcontroller, or a digital signal processor, and may also include a GPU, an embedded neural network processor (Neural-network Process Units, NPU). ) And image signal processing (Image Signal Processing, ISP), the processor may also include necessary hardware accelerators or logic processing hardware circuits, such as ASIC, or one or more integrated circuits used to control the execution of the program of the technical solution of this application Wait. In addition, the processor may have a function of operating one or more software programs, and the software programs may be stored in a storage medium.

Specifically, in an embodiment of the present application, the memory of the electronic device/headphone may be a read-only memory (read-only memory, ROM), other types of static storage devices that can store static information and instructions, and random access memory ( Random access memory, RAM) or other types of dynamic storage devices that can store information and instructions, and can also be electrically erasable programmable read-only memory (EEPROM), compact disc read -only memory, CD-ROM) or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital universal discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or can be used for Any computer-readable medium that carries or stores desired program codes in the form of instructions or data structures and can be accessed by a computer.

Specifically, in an embodiment of the present application, the processor and the memory may be combined into a processing device, and more commonly, components are independent of each other. The processor is used to execute the program code stored in the memory to implement the method described in the embodiment of the present application. . During specific implementation, the memory may also be integrated in the processor, or independent of the processor.

Further, the equipment, device, device, module, or unit illustrated in the embodiments of the present application may be specifically implemented by a computer chip or entity, or implemented by a product with a certain function.

Those skilled in the art should understand that the embodiments of the present application may be provided as methods, devices, or computer program products. Therefore, the present invention may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program codes.

In the several embodiments provided in this application, if any function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on this understanding, the technical solution of the present application essentially or the part that contributes to the existing technology or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including Several instructions are used to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in the various embodiments of the present application.

Specifically, an embodiment of the present application also provides a computer-readable storage medium, where a computer program is stored in the computer-readable storage medium, and when it runs on a computer, the computer executes the method provided in the embodiment of the present application.

An embodiment of the present application also provides a computer program product. The computer program product includes a computer program that, when running on a computer, causes the computer to execute the method provided in the embodiment of the present application.

The description of the embodiments in the present application is described with reference to the flowcharts and/or block diagrams of the methods, equipment (devices), and computer program products according to the embodiments of the present application. It should be understood that each process and/or block in the flowchart and/or block diagram, and the combination of processes and/or blocks in the flowchart and/or block diagram can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing equipment to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing equipment are generated It is a device that realizes the functions specified in one process or multiple processes in the flowchart and/or one block or multiple blocks in the block diagram.

These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing equipment to work in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including the instruction device. The device implements the functions specified in one process or multiple processes in the flowchart and/or one block or multiple blocks in the block diagram.

These computer program instructions can also be loaded on a computer or other programmable data processing equipment, so that a series of operation steps are executed on the computer or other programmable equipment to produce computer-implemented processing, so as to execute on the computer or other programmable equipment. The instructions provide steps for implementing the functions specified in one process or multiple processes in the flowchart and/or one block or multiple blocks in the block diagram.

It should also be noted that in the embodiments of the present application, "at least one" refers to one or more, and "multiple" refers to two or more. "And/or" describes the association relationship of the associated objects, indicating that there can be three types of relationships, for example, A and/or B, which can mean the situation where A exists alone, A and B exist at the same time, and B exists alone. Among them, A and B can be singular or plural. The character "/" generally indicates that the associated objects before and after are in an "or" relationship. "The following at least one item" and similar expressions refer to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, and c can mean: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, and c can be single, or There can be more than one.

In the embodiments of the present application, the terms "include", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, product, or equipment including a series of elements includes not only those elements, but also Other elements that are not explicitly listed, or also include elements inherent to such processes, methods, commodities, or equipment. If there are no more restrictions, the element defined by the sentence "including a..." does not exclude the existence of other identical elements in the process, method, commodity, or equipment that includes the element.

This application may be described in the general context of computer-executable instructions executed by a computer, such as a program module. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments. In these distributed computing environments, tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

The various embodiments in this application are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, as for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and for related parts, please refer to the part of the description of the method embodiment.

A person of ordinary skill in the art may realize that the units and algorithm steps described in the embodiments of the present application can be implemented by a combination of electronic hardware, computer software, and electronic hardware. Whether these functions are executed by hardware or software depends on the specific application and design constraint conditions of the technical solution. Professionals and technicians can use different methods for each specific application to implement the described functions, but such implementation should not be considered beyond the scope of this application.

Those skilled in the art can clearly understand that, for the convenience and conciseness of description, the specific working process of the device, device and unit described above can refer to the corresponding process in the foregoing method embodiment, which will not be repeated here.

The above are only specific implementations of this application. Any person skilled in the art can easily conceive of changes or substitutions within the technical scope disclosed in this application, and they should all be covered by the protection scope of this application. The protection scope of this application shall be subject to the protection scope of the claims.

Claims

A method for realizing active noise cancellation, which is characterized in that it includes:

Obtain the playback content signal;

Determining, according to the playback content signal, the masking effect of the playback content signal on the external noise signal;

According to the masking effect of the playback content signal on the external noise signal, an active noise signal for realizing active noise cancellation is generated, wherein the active noise signal is used to control the frequency spectrum of the external noise signal reaching the human ear at the Under the masking effect of the frequency spectrum of the content signal.
The method according to claim 1, wherein the active noise signal for realizing active noise cancellation is generated according to the masking effect of the playback content signal on the external noise signal, wherein:

Determine the intensity of the active noise in the first frequency band according to the masking effect of the playback content signal on the external noise signal in the first frequency band.
The method according to claim 1 or 2, wherein determining, according to the playback content signal, the masking effect of the playback content signal on the external noise signal, comprising:

Obtain the noise signal in the ear;

Determine the masking effect of the playback content signal on the ear noise signal.
The method according to claim 3, wherein generating an active noise signal for realizing active noise cancellation according to the masking effect of the playback content signal on the external noise signal includes:

Determining the feedback input of the in-ear noise signal in the control strategy of active noise cancellation according to the masking effect of the playback content signal on the in-ear noise signal;

Based on the feedback input of the ear noise signal, the active noise signal is generated according to the control strategy of the active noise cancellation.
The method according to claim 4, wherein the feedback input of the ear noise signal in the control strategy of active noise cancellation is determined according to the masking effect of the playback content signal on the ear noise signal, wherein And determining the strength of the feedback input of the ear noise signal on the first frequency band according to the masking effect of the play content signal on the ear noise signal on the first frequency band.
The method according to any one of claims 3 to 5, wherein determining the masking effect of the playback content signal on the ear noise signal includes:

Calculating the frequency spectrum of the ear noise signal according to the ear noise signal;

Calculating the frequency spectrum of the playback content signal according to the playback content signal;

According to the frequency spectrum of the ear noise signal and the frequency spectrum of the playback content signal, the masking effect of the playback content signal on the ear noise signal in each frequency band is determined.
The method according to claim 6, wherein generating an active noise signal for realizing active noise cancellation according to the masking effect of the playback content signal on the external noise signal includes:

Determine the frequency band weights corresponding to different frequency bands of the ear noise signal according to the masking effect produced by the frequency spectrum of the playback content signal on the frequency spectrum of the ear noise signal. The stronger the masking effect, the higher the corresponding frequency band weight. small;

According to the frequency band weights corresponding to different frequency bands of the in-ear noise signal, the in-ear noise signal is filtered to obtain the in-ear noise filtering result signal, wherein the smaller the frequency band weight is, the in-ear noise filtering result signal is The lower the signal strength of the corresponding frequency band;

The in-ear noise filtering result signal is used as the feedback input of the in-ear noise signal in the control strategy of active noise cancellation.
A device for realizing active noise cancellation, characterized in that it comprises:

The first signal acquisition module, which is used to acquire the playback content signal;

A masking effect analysis module, which is used to determine the masking effect of the playback content signal on the external noise signal;

The active noise generation module is used to generate an active noise signal for realizing active noise cancellation according to the masking effect of the playback content signal on the external noise signal, so that the frequency spectrum of the external noise signal reaching the human ear is controlled in the Under the masking effect of the frequency spectrum of the content signal.
An electronic device, characterized in that the electronic device includes a memory for storing computer program instructions and a processor for executing the program instructions, wherein when the computer program instructions are executed by the processor, the electronic device is triggered The device executes the method steps according to any one of claims 1-7.
A computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, and when it runs on a computer, the computer can execute the method according to any one of claims 1-7 .