CN113299265B - Active noise reduction method and device and active noise reduction earphone - Google Patents
Active noise reduction method and device and active noise reduction earphone Download PDFInfo
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- CN113299265B CN113299265B CN202110845978.8A CN202110845978A CN113299265B CN 113299265 B CN113299265 B CN 113299265B CN 202110845978 A CN202110845978 A CN 202110845978A CN 113299265 B CN113299265 B CN 113299265B
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
- G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
- G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
- G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
- G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
- G10K11/1781—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase characterised by the analysis of input or output signals, e.g. frequency range, modes, transfer functions
- G10K11/17813—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase characterised by the analysis of input or output signals, e.g. frequency range, modes, transfer functions characterised by the analysis of the acoustic paths, e.g. estimating, calibrating or testing of transfer functions or cross-terms
- G10K11/17817—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase characterised by the analysis of input or output signals, e.g. frequency range, modes, transfer functions characterised by the analysis of the acoustic paths, e.g. estimating, calibrating or testing of transfer functions or cross-terms between the output signals and the error signals, i.e. secondary path
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
- G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
- G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
- G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
- G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
- G10K11/1785—Methods, e.g. algorithms; Devices
- G10K11/17853—Methods, e.g. algorithms; Devices of the filter
- G10K11/17854—Methods, e.g. algorithms; Devices of the filter the filter being an adaptive filter
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
- G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
- G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
- G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
- G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
- G10K11/1787—General system configurations
- G10K11/17879—General system configurations using both a reference signal and an error signal
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
- G10K2210/00—Details of active noise control [ANC] covered by G10K11/178 but not provided for in any of its subgroups
- G10K2210/10—Applications
- G10K2210/108—Communication systems, e.g. where useful sound is kept and noise is cancelled
- G10K2210/1081—Earphones, e.g. for telephones, ear protectors or headsets
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
- G10K2210/00—Details of active noise control [ANC] covered by G10K11/178 but not provided for in any of its subgroups
- G10K2210/30—Means
- G10K2210/301—Computational
- G10K2210/3028—Filtering, e.g. Kalman filters or special analogue or digital filters
Abstract
The application provides an active noise reduction method and device and an active noise reduction earphone. The method comprises the following steps: collecting an original noise signal by a reference microphone; collecting an error signal through an error microphone, wherein the error signal comprises an error between an original noise signal transmitted to a space point where the error microphone is located and a noise reduction signal, and the noise reduction signal is determined according to the original noise signal and an initial filter coefficient; inputting an original noise signal into a secondary path estimation unit to obtain a delay reference signal, wherein the secondary path estimation unit is used for simulating a secondary path; and determining the filter coefficient according to the error signal and the delay reference signal. According to the active noise reduction method, the original noise signal is actively delayed in the process of adaptively adjusting the filter coefficient so as to accurately correspond to the error signal in time, and adverse effects caused by a secondary path can be overcome, so that the stability of the active noise reduction process is improved.
Description
Technical Field
The application relates to the technical field of acoustics, in particular to an active noise reduction method and device and an active noise reduction earphone.
Background
In recent years, with the dramatic increase in market demand, Active Noise Cancellation (ANC) headphones are gaining more and more attention. The core of the design of an active noise reduction headphone is a filter, e.g. a feedforward filter W ff Feedback filter W fb 。
However, the structure of the active noise reduction headphone leads to the presence of secondary paths in the headphone, which can adversely affect the stability of the active noise reduction system during the filter design process. Therefore, how to overcome the influence of the secondary path to improve the system stability becomes a problem to be solved in the field.
Disclosure of Invention
In view of this, embodiments of the present application provide an active noise reduction method and apparatus, and an active noise reduction earphone, so as to solve the technical problem that the stability of an active noise reduction system in the prior art cannot be further improved due to the influence of a secondary path.
A first aspect of the present application provides an active noise reduction method, including: collecting an original noise signal through a reference microphone; collecting an error signal through an error microphone, wherein the error signal comprises an error between an original noise signal transmitted to a space point where the error microphone is located and a noise reduction signal, and the noise reduction signal is determined according to the original noise signal and an initial filter coefficient; inputting an original noise signal into a secondary path estimation unit to obtain a delay reference signal, wherein the secondary path estimation unit is used for simulating a secondary path; and determining the filter coefficient according to the error signal and the delay reference signal.
In an embodiment, the active noise reduction method further includes: playing a test signal through a speaker, wherein the test signal is uncorrelated with the original noise signal; obtaining a delay test signal according to the test signal and an initial secondary path estimation unit; determining the difference between the error signal and the delayed test signal as a test error signal, wherein the error signal also comprises the test signal transmitted to the spatial point of the error microphone; a secondary path estimation unit is determined based on the test error signal and the test signal.
In one embodiment, determining a secondary path estimation unit based on the test error signal and the test signal includes: adjusting the initial secondary path estimation unit according to the test error signal; a. determining an updated test error signal based on the test signal and the adjusted secondary path estimation unit; b. when the expected power of the updated test error signal does not reach the minimum value, adjusting the adjusted secondary path estimation unit; iteratively executing the steps a and b until the expected power reaches the minimum value; and determining the current adjusted secondary path estimation unit as the secondary path estimation unit.
In one embodiment, the secondary path estimation unit is predetermined based on the test signal.
In one embodiment, determining filter coefficients based on the error signal and the delayed reference signal comprises: inputting the error signal into a sound weighting unit to obtain a weighted error signal; and determining the filter coefficient according to the weighted error signal and the delay reference signal.
A second aspect of the present application provides an active noise reduction device comprising: a reference microphone for collecting an original noise signal; the error microphone is used for acquiring an error signal, wherein the error signal comprises an error between an original noise signal transmitted to a space point where the error microphone is located and a noise reduction signal, and the noise reduction signal is determined according to the original noise signal and an initial filter coefficient; the first calculation module is used for inputting an original noise signal into a secondary path estimation unit to obtain a delay reference signal, wherein the secondary path estimation unit is used for simulating a secondary path; and the second calculation module is used for determining the filter coefficient according to the error signal and the delay reference signal.
A third aspect of the present application provides an active noise reduction headphone comprising: a filter, the filter coefficients of which are determined by the active noise reduction method provided in any embodiment of the first aspect of the present application.
A fourth aspect of the present application provides an active noise reduction headphone, comprising: the reference microphone, the loudspeaker, the error microphone and the chip are used for the active noise reduction method provided by any embodiment of the first aspect of the present application to determine the filter coefficients in real time.
A fifth aspect of the present application provides an electronic device, comprising: a processor; a memory including computer instructions stored thereon, which, when executed by the processor, cause the processor to perform the active noise reduction method provided by any of the embodiments of the first aspect of the present application.
A sixth aspect of the present application provides a computer-readable storage medium comprising computer instructions stored thereon, which, when executed by a processor, cause the processor to perform the active noise reduction method provided by any of the embodiments of the first aspect of the present application.
Based on the active noise reduction method, the active noise reduction device and the active noise reduction earphone, an original noise signal (namely, environmental noise) is actively delayed in the process of adaptively adjusting the filter coefficient so as to accurately correspond to an error signal (namely, residual noise) in time, adverse effects caused by a secondary path can be overcome, and the stability of the active noise reduction process is improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
Drawings
In order to make the objects, technical solutions and advantages of the embodiments of the present application more apparent, the embodiments of the present application will be described in further detail below with reference to the accompanying drawings. It is to be understood that the drawings form a part of the specification, illustrate the present application together with embodiments thereof, and are not to be construed as limiting the present application. In the drawings, like reference numerals and characters generally refer to like steps or components, unless otherwise specified.
FIG. 1 is a schematic diagram of an exemplary active noise reduction system.
Fig. 2 is a schematic diagram illustrating an exemplary active noise reduction system according to an embodiment of the present application.
Fig. 3 is a schematic flow chart of an active noise reduction method according to an embodiment of the present application.
Fig. 4 is a schematic diagram of a secondary path measurement system according to an embodiment of the present application.
Fig. 5 is a flowchart illustrating a method for determining a secondary path estimation unit according to an embodiment of the present application.
Fig. 6 is a schematic diagram illustrating an exemplary active noise reduction system according to another embodiment of the present application.
Fig. 7 is a schematic flowchart illustrating an active noise reduction method according to another embodiment of the present application.
Fig. 8 is a schematic flow chart illustrating a process of determining a secondary path estimation unit in an active noise reduction method according to another embodiment of the present application.
Fig. 9 is a schematic diagram illustrating an exemplary active noise reduction system according to another embodiment of the present application.
Fig. 10 is a schematic structural diagram of an active noise reduction device according to an embodiment of the present application.
Fig. 11 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
Application scenario overview
In an active noise reduction headphone, the noise reduction parameters (i.e., filter coefficients) of the filter may be determined by either an off-line design or an on-line design. The off-line design means that the filter coefficient is determined before the earphone leaves a factory and cannot be adjusted again after leaving the factory; the on-line design means that the active noise reduction system in the headset can adjust the filter coefficients at the user using stage to make it more fit the actual noise environment.
In any filter design mode, in the process of determining or adjusting the filter coefficient, the original noise signal collected by the reference microphone and the error noise signal collected by the error microphone can be used, the original noise signal and the error noise signal are input into the adaptive module, the filter coefficient is gradually adjusted through the adaptive calculation process, and the optimal filter coefficient is determined when the error noise signal is converged.
For example, fig. 1 shows an active noise reduction system using an adaptive algorithm, which may use an LMS (Least Mean Square) algorithm. The active noise reduction system includes: a reference microphone 110, a filter 120, a speaker (not shown), an error microphone 130, and an adaptation module 140.
In addition, paths shown by dotted lines in fig. 1 represent propagation paths of acoustic signals other than the circuit, and specifically include a primary path (transfer function is P) formed by the space between the reference microphone 110 and the error microphone 130, and a secondary path (transfer function is G) formed by the speaker itself and the space between the speaker and the error microphone 130 together.
As shown in fig. 1, the original noise at the reference microphone 110 is transferred to the spatial point where the error microphone 130 is located through the primary path. Meanwhile, the reference microphone 110 collects the original noise and converts it into an original noise signal d (n), and transmits it to the filter 120; the filter 120 calculates a noise reduction signal y (n) with a phase opposite to that of the original noise signal d (n) based on the filter coefficient W according to the original noise signal d (n), and outputs the noise reduction signal y (n) to the loudspeaker; the speaker plays the noise reduced sound wave based on the noise reduction signal y (n) so that the noise reduced sound wave is delivered to the spatial point where the error microphone 130 is located. That is, the noise reduction signal y (n) is output by the filter 120 and then is transmitted to the spatial point of the error microphone 130 via the secondary path. At this time, the original noise signal d (n) and the noise reduction signal y (n) are respectively transmitted to the error microphone 130 via different paths to form a superposition, so that the error microphone 130 collects the error therebetween (i.e. the error signal e (n)).
Furthermore, in order to adjust the filter coefficient W, the reference microphone 110 transmits the original noise signal d (n) to the adaptation module 140; error microphone 130 delivers an error signal e (n) to adaptation module 140. Based on the original noise signal d (n) and the error signal e (n), the adaptive module 140 iteratively updates the filter coefficient W to finally determine an optimal filter coefficient.
However, as can be understood from the above description, unlike the original noise signal d (n) directly input to the adaptation module 140 from the reference microphone 110, the error signal e (n) is collected by the error microphone 130 after the noise reduction signal reaches the spatial point where the error microphone 130 is located through the secondary path. Thus, as shown in fig. 1, the error signal received by the adaptation module 140 at the same time as the original noise signal d (n) is not e (n) corresponding to d (n), but is e (n ') corresponding to the original noise signal d (n') whose acquisition time is earlier than d (n). That is, in the prior art, two input signals that are used as the basis for calculation of the adaptive module 140 do not correspond to each other exactly, and if the filter coefficients are adjusted according to such input signals, the stability of the active noise reduction system is impaired, and in a severe case, even a system downtime may occur, so that active noise reduction cannot be performed.
In order to solve the above problems faced by the existing active noise reduction technology, embodiments of the present application aim to provide an active noise reduction method, an active noise reduction device, and an active noise reduction earphone, which implement to improve the stability of an active noise reduction system and further implement optimized noise reduction by correcting a time difference between two input signals (an original noise signal and an error signal) of a self-adaptive module.
Exemplary System
Fig. 2 is a schematic diagram illustrating an exemplary active noise reduction system 200 according to an embodiment of the present application. The system comprises: reference microphone 210, processor 220, speaker 230, and error microphone 240, wherein processor 220 includes filter 221, adaptation module 222, and secondary path estimation unit 223.
Specifically, the reference microphone 210 is disposed on the earphone housing for collecting an original noise signal; the filter 221 is configured to receive the original noise signal from the reference microphone 210, calculate a noise reduction signal according to the original noise signal and a filter coefficient, and send the noise reduction signal to the speaker 230; the speaker 230 is used for playing the noise reduction sound wave according to the received noise reduction signal; the error microphone 240 is disposed near the ear canal of the user for collecting an error signal (i.e., an error between the original noise signal delivered to the spatial point where the error microphone 240 is located and the noise reduction signal); the adaptive module 222 is used for receiving the original noise signal from the reference microphone 210 and the error signal from the error microphone 240, and updating the filter coefficients according to the original noise signal and the error signal to obtain the optimal filter coefficients.
It should be understood that the paths shown by the dashed lines in fig. 2 represent the propagation paths of acoustic signals other than the circuit. Specifically, in the headphone, the space between the reference microphone 210 to the error microphone 240 forms a primary path, and the speaker 230 itself and the space between the speaker 230 to the error microphone 240 together constitute a secondary path. In the active noise reduction process, the original noise is transmitted to the error microphone 240 through the primary path, and the noise reduction signal is transmitted to the error microphone 240 through the secondary path, which are overlapped at the error microphone 240 to form an error signal.
In addition, as shown in fig. 2, in the active noise reduction system 200 provided in the embodiment of the present application, the processor 220 further includes a secondary path estimation unit 223. Specifically, the secondary path estimation unit 223 is disposed between the reference microphone 210 and the adaptive module 222, and when the reference microphone 210 sends an original noise signal to the adaptive module 222, the secondary path estimation unit 223 is configured to perform a delay processing on the original noise signal to obtain a delayed reference signal, and input the delayed reference signal to the adaptive module 222.
Exemplary method
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments that can be derived from the embodiments given herein by a person of ordinary skill in the art are intended to be within the scope of the present disclosure.
Fig. 3 is a schematic flow chart of an active noise reduction method according to an embodiment of the present application. The method may be performed, for example, by processor 220 in active noise reduction system 200. As shown in fig. 3, the method includes:
s310: the original noise signal is collected by a reference microphone.
S320: the error signal is collected by an error microphone.
The error signal comprises an error between an original noise signal transmitted to a space point where the error microphone is located and a noise reduction signal, and the noise reduction signal is determined according to the original noise signal and an initial filter coefficient.
Specifically, after the reference microphone collects the original noise signal d (n) at the first time, the filter may calculate the noise reduction signal y (n) corresponding to d (n) based on d (n) and the initial filter coefficient (i.e., the filter coefficient to be adjusted), and output it to the secondary path. y (n) reaches the spatial point where the error microphone is located through the secondary path, so that the error microphone acquires error signals e (n) corresponding to d (n) and y (n) at the second moment.
In the process, due to the delay of the secondary path, the second time when the error microphone acquires the error signal e (n) is necessarily later than the first time when the reference microphone acquires the original noise signal d (n).
S330: and inputting the original noise signal into a secondary path estimation unit to obtain a delay reference signal.
Wherein the secondary path estimation unit is used for simulating a secondary path.
At the first time, since the error signal e (n) corresponding to d (n) has not been acquired yet, if the original noise signal d (n) is directly input to the adaptation module, the error signal e (n) input at the same time is not necessarily the error signal e (n) corresponding to d (n), but the error signal e (n ') corresponding to d (n') acquired earlier than the first time. As mentioned above, it is the delay caused by the secondary path that causes this phenomenon.
Therefore, if the original noise signal d (n) collected at the first time is input to the adaptive module at the second time after passing through the equivalent secondary path, the adaptive module can receive d (n) and e (n) corresponding to each other in time at the same time.
Specifically, in the embodiment of the present invention, a secondary path estimation unit for simulating a secondary path is provided between the reference microphone and the adaptive module. After receiving the original noise signal d (n) collected by the reference microphone at the first time, the secondary path estimation unit may simulate the influence of the secondary path, delay d (n), and input the processed delayed reference signal d '(n) to the adaptive module at the second time, so that the delayed reference signal d' (n) and the error signal e (n) input to the adaptive module at the second time are mutually "aligned" in time, thereby canceling the influence brought by the secondary path.
S340: and determining the filter coefficient according to the error signal and the delay reference signal.
After the adaptive module receives the error signal and the delay reference signal, the initial filter coefficient can be adjusted, whether the adjusted filter coefficient is the optimal filter coefficient or not is judged, if not, adjustment is carried out again, and the process is repeated until the filter coefficient is optimal.
Specifically, in one embodiment, it may be determined whether the filter coefficients are optimal based on the error signal.
When the error signal is judged not to reach the preset optimal condition, the initial filter coefficient can be adjusted, and the updated noise reduction signal is determined by adopting the adjusted filter coefficient. After the loudspeaker plays the updated noise reduction signal, the error microphone can acquire the updated error signal. When the updated error signal is judged to still not reach the preset optimal condition, the filter coefficient can be adjusted again to obtain the error signal after being updated again. And repeating the steps until the error signal meets the preset optimal condition, stopping adjustment, and determining the current filter coefficient (namely the filter coefficient after the last adjustment) as the final filter coefficient.
In one embodiment, for example, the energy of the error signal reaching the minimum value may be set as the optimal condition, that is, whether the error signal satisfies the preset optimal condition is determined by determining whether the energy of the residual noise signal reaches the minimum value.
Here, the process of repeatedly adjusting the filter coefficients and updating the error signal may be implemented by using an adaptive algorithm, such as an LMS (Least Mean Square) algorithm, and the filter coefficients are updated each time until the error signal is optimized. It should be understood that the embodiments of the present application do not limit the algorithm actually used.
Based on the active noise reduction method provided by the embodiment of the application, the original noise signal is actively delayed in the process of adaptively adjusting the coefficient of the filter so as to accurately correspond to the error signal in time, and adverse effects caused by a secondary path can be overcome, so that the stability of the active noise reduction process is improved.
It should be noted that, in some embodiments of the present application, the secondary path estimation unit may be predetermined by offline calculation; in another embodiment of the present application, the secondary path estimation unit may further adjust the optimization in real time through online calculation during the actual use process of the user so as to adapt to different use environments.
Fig. 4 is a schematic diagram of a secondary path measurement system 400 according to an embodiment of the present disclosure. The secondary path measurement system 400 includes a player 410, a processor 420, a speaker 430, and an error microphone 440. The processor 420 includes a secondary path estimation unit 421, an adder 422, and an adaptation module 423.
Fig. 5 is a flowchart illustrating a method for determining a secondary path estimation unit according to an embodiment of the present application. The method for determining the secondary path estimation unit in advance through offline calculation may be implemented in a filter design stage before the earphone is shipped, and may be executed by the processor 420 in the secondary path measurement system 400 shown in fig. 4, for example.
S510: the test signal is played through a speaker.
Specifically, the test signal may be a white noise signal, a pink noise signal, etc. from the player 410, and the embodiment of the present application does not limit the specific selection of the test signal.
The player 410 inputs the test signal to the speaker 430 through the circuit, and the test signal is collected by the error microphone 440 after being transmitted from the speaker 430 to the spatial point where the error microphone 440 is located, i.e., after passing through the secondary path. That is, the error microphone 440 acquires the test signal affected by the delay of the secondary path.
S520: and obtaining a delay test signal according to the test signal and the initial secondary path estimation unit.
Specifically, as shown in fig. 4, in the present embodiment, a secondary path estimation unit 421 may be provided between the player 410 and the adder 422. Here, the unadjusted secondary path estimation unit is the initial secondary path estimation unit.
The player 410 inputs the test signal to the initial secondary path estimating unit through the circuit, and after receiving the test signal, the initial secondary path estimating unit may perform delay processing on the test signal to obtain a delayed test signal, and input the delayed test signal to the adder 422.
S530: a test error signal is determined based on the delayed test signal and the test signal delivered to the error microphone.
Specifically, error microphone 440 may input the test signal after receiving the secondary path delay contribution to summer 422. The adder 422 can compare the delayed test signal with the test signal affected by the delay of the secondary path to obtain an error therebetween, i.e., a test error signal.
S540: a secondary path estimation unit is determined based on the test error signal and the test signal.
It should be understood that when the secondary path estimating unit 421 is infinitely close to the real secondary path, the energy of the test error signal should be minimized, and the secondary path estimating unit at this time is the optimal secondary path estimating unit.
Therefore, to obtain an optimal secondary path estimation unit, the test signal and the test error signal may be input to the adaptation module 423, and the initial secondary path estimation unit may be iteratively adjusted by an adaptation algorithm to obtain an updated test error signal. When the expected power of the current updated test error signal is judged to reach the minimum value, the current (after the last adjustment) secondary path estimation unit can be determined to be the secondary path estimation unit closest to the real secondary path.
Based on the active noise reduction method provided by the embodiment of the application, the secondary path estimation unit is obtained through self-adaptive adjustment in the filter design stage, and the stability of the system is improved by using the secondary path estimation unit in the active noise reduction process, so that good use experience can be brought to a user.
In some other embodiments, other methods may be used to perform offline calculation on the secondary path estimation unit. For example, a white noise signal x (n) is played through a loudspeaker and is collected through an error microphone to obtain y (n); solving for the self-power spectrum P of x (n) respectively xx And cross-power spectra P of x (n) and y (n) xy (ii) a According to P xx And P xy The transfer function of the secondary path is calculated, and the secondary path estimation unit is set based on the transfer function of the secondary path.
Fig. 6 is a schematic diagram illustrating an exemplary active noise reduction system 600 according to another embodiment of the present application. This system differs from the exemplary active noise reduction system 200 shown in fig. 2 by further comprising a player 610, while the processor 620 comprises a filter 221, a first adaptation module 222, a secondary path estimation unit 621, an adder 622, and a second adaptation module 623.
Fig. 7 is a schematic flowchart illustrating an active noise reduction method according to another embodiment of the present application. The method may be performed, for example, by processor 620 in active noise reduction system 600 shown in fig. 6.
As mentioned above, fig. 4 of the present application illustrates a method for off-line calculating a secondary path estimation unit. However, since the secondary path estimation unit obtained by off-line calculation is predetermined before the earphone is shipped from the factory, it cannot be changed during actual use. Therefore, in the actual use of the user, the calibrated secondary path estimation unit cannot adapt to the real secondary path of each earphone in real time, so that the user experience cannot be optimal.
In view of this, the embodiment of the present application provides an active noise reduction method as shown in fig. 7, which can implement online calculation of the secondary path estimation unit. For example, during actual use by a user, the processor 620 may execute the method to optimize the secondary path estimation unit in real time, and perform active noise reduction using the optimized secondary path estimation unit.
It should be understood that, according to actual requirements, the method shown in fig. 7 may also be used for calculating the secondary path estimation unit offline, and the embodiment of the present application is not limited to a specific application scenario of the method.
As shown in fig. 7, the online calculation method includes:
s710: the original noise signal is collected by a reference microphone.
S720: the test signal is played through a speaker.
Where the test signal is a signal that is uncorrelated with the original noise signal. Specifically, the test signal may be a frequency sweep signal from the player 610 or the like.
Preferably, in another embodiment, since the active noise reduction method provided by this embodiment may be implemented in actual use of a user, the test signal may also be an acoustic signal actually played by the user, such as a voice call signal, a media audio signal, and the like. Such signals are non-stationary signals (predominantly medium to high frequencies) and can be considered as having no correlation with the original noise signals (stationary, predominantly low frequencies) from the environment.
It should be understood that S720 may also be performed before S710.
S730: the error signal is collected by an error microphone.
Similar to the previous embodiment, the filter 221 generates a noise reduction signal according to the original noise signal and the filter coefficient and transmits it to the speaker 230 for playing. The original noise signal and the noise reduction signal respectively pass through the primary path and the secondary path to reach the spatial point where the error microphone 240 is located, so that the error microphone 240 collects the error between the two signals.
In addition, in the present embodiment, the test signal also passes through the secondary path to the spatial point where the error microphone 240 is located. Since the test signal is uncorrelated with the original noise signal, it can be understood that the error signal collected by the error microphone 240 includes the error between the original noise signal delivered to the spatial point of the error microphone 240 and the noise reduction signal, and also includes the test signal.
S740: and obtaining a delay test signal according to the test signal and the initial secondary path estimation unit.
Similarly to the embodiment shown in fig. 4, in the present embodiment, a secondary path estimation unit 621 may be provided between the player 610 and the adder 622. Here, the unadjusted secondary path estimation unit is the initial secondary path estimation unit.
The player 610 may directly transmit the test signal to the initial secondary path estimating unit through the circuit, and after receiving the test signal, the initial secondary path estimating unit may perform delay processing on the test signal to obtain a delayed test signal, and transmit the delayed test signal to the adder 622.
In another embodiment, the secondary path estimation unit 621 may also be disposed between the speaker 230 and the adder 622 (not shown). At this time, the speaker 230 may input the noise reduction signal and the test signal to the initial secondary path estimating unit through the circuit while playing the noise reduction signal and the test signal after receiving the noise reduction signal from the filter 221 and the test signal from the player 610. After the initial secondary path estimation unit receives the noise reduction signal and the test signal, delay processing can be performed to obtain a delay test signal. It should be understood that in this embodiment, the delayed test signal includes the noise reduction signal and the test signal that are delayed.
S750: the difference between the error signal and the delayed test signal is determined as a test error signal.
Specifically, the error microphone 240 may input the error signal to the adder 622 after receiving the error signal. The adder 622 can compare the error signal from the error microphone 240 with the delayed test signal from the initial secondary path estimation unit to obtain the error between the two, i.e., the test error signal.
S760: a secondary path estimation unit is determined based on the test error signal and the test signal.
Similar to the embodiment shown in fig. 5, when the secondary path estimating unit 621 is infinitely close to the real secondary path, the energy of the test error signal should be minimized, and the secondary path estimating unit at this time is the optimal secondary path estimating unit.
Therefore, to obtain an optimal secondary path estimation unit, the test signal and the test error signal may be input to the second adaptation module 623, and the initial secondary path estimation unit may be iteratively adjusted by an adaptation algorithm to obtain an updated test error signal. When the expected power of the current updated test error signal is judged to reach the minimum value, the current (after the last adjustment) secondary path estimation unit can be determined to be the secondary path estimation unit closest to the real secondary path.
S770: and inputting the original noise signal into a secondary path estimation unit to obtain a delay reference signal.
Similarly to the embodiment shown in fig. 3, in order to overcome the time difference between the original noise signal and the error signal, the original noise signal may be delayed by the secondary path estimation unit to obtain a corresponding delayed reference signal, and the delayed reference signal is input to the first adaptive module 222.
It should be appreciated that in the active noise reduction system 600, as shown by the dashed line in fig. 6, after the secondary path estimation unit 621 is determined by the second adaptation module 623, the secondary path estimation unit can be used as a secondary path estimation unit between the reference microphone 210 and the first adaptation module 222, and the original noise signal is input thereto so as to perform the delay processing on the original noise signal.
The way in which the real-time optimized secondary path estimation unit is used for filter coefficient adjustment can be designed by those skilled in the art according to actual needs. For example, two sets of input/output ports may be provided for one secondary path estimation unit, and a first set of ports (for example, the input terminal is connected to the player 610 and the second adaptation module 623, and the output terminal is connected to the adder 622) may be used when debugging the secondary path estimation unit, and a second set of ports (for example, the input terminal is connected to the reference microphone 210, and the output terminal is connected to the first adaptation module 222) may be used instead to participate in the adaptive calculation of the filter coefficients after the debugging is completed. Alternatively, two secondary path estimation units may be provided, one for parameter adaptation based on the second adaptation module 623 and the other for participating in adaptive computation of filter coefficients in cooperation with the first adaptation module 222, wherein the former may dynamically transmit the adapted secondary path estimation unit parameters to the latter to update the latter to the optimized secondary path estimation unit.
S780: and determining the filter coefficient according to the error signal and the delay reference signal.
Similar to the embodiment shown in fig. 3, after receiving the error signal and the delay reference signal, the first adaptive module 222 may adjust the initial filter coefficient, determine whether the adjusted filter coefficient is the optimal filter coefficient, and if not, adjust again, and repeat the above process until the filter coefficient reaches the optimal filter coefficient.
Specifically, in one embodiment, it may be determined whether the filter coefficients are optimal based on the error signal. When the error signal is judged not to reach the preset optimal condition, the initial filter coefficient can be adjusted, and the updated noise reduction signal is determined by adopting the adjusted filter coefficient. After the speaker 230 plays the updated noise reduction signal, the error microphone 240 can collect the updated error signal. When the updated error signal is judged to still not reach the preset optimal condition, the filter coefficient can be adjusted again to obtain the error signal after being updated again. And repeating the steps until the error signal meets the preset optimal condition, stopping adjustment, and determining the current filter coefficient as the final filter coefficient.
In one embodiment, for example, the energy of the error signal reaching the minimum value may be set as the optimal condition, that is, whether the error signal satisfies the preset optimal condition is determined by determining whether the energy of the residual noise signal reaches the minimum value.
Here, the process of repeatedly adjusting the filter coefficients and updating the error signal may be implemented by using an adaptive algorithm, such as an LMS algorithm, and the filter coefficients are updated each time until the error signal is optimized. It should be understood that the embodiments of the present application do not limit the algorithm actually used.
In an embodiment, as shown in fig. 8, S760 in the method shown in fig. 7 may specifically include the following steps:
s761: the initial secondary path estimation unit is adjusted based on the test error signal.
S762: an updated test error signal is determined based on the test signal and the adjusted secondary path estimation unit.
S763: judging whether the expected power of the current updated test error signal reaches the minimum value, and executing S764 when the expected power of the updated test error signal does not reach the minimum value; when the desired power of the updated test error signal reaches a minimum value, S765 is performed.
S764: the adjusted secondary path estimating unit is adjusted, and S762 is performed again.
Steps S762 (hereinafter referred to as a) and S764 (hereinafter referred to as b) may be iteratively performed until the desired power of the test error signal reaches the minimum value before the desired power of the updated test error signal reaches the minimum value.
S765: and determining the current adjusted secondary path estimation unit as the secondary path estimation unit.
Here, the process of iteratively performing steps a, b until the expected power of the updated test error signal reaches a minimum value may be implemented using an adaptive algorithm, such as an LMS algorithm.
It should be understood that in other embodiments of the present application, some steps of the method shown in fig. 7 may be omitted, or may be performed in other orders.
For example, in an embodiment, the above method may be performed without turning on the active noise reduction function, i.e., S770, S780 may be omitted and filters and noise reduction signals are not required during the execution of each step. That is, when the user does not turn on the active noise reduction, the secondary path estimation unit can be debugged only by using the original noise signal and the test signal, and the filter coefficient is not adjusted. Therefore, when the user opens the noise reduction function, the secondary path estimation unit is already in the optimal state, and the link of optimizing the filter coefficient can be directly entered, so that a large amount of debugging time can be saved.
For another example, in another embodiment, the filter coefficients may be iteratively adjusted while the secondary path estimation unit is iteratively adjusted. That is, before determining the secondary path estimation unit, that is, when the secondary path estimation unit has not reached the optimum yet, the currently adjusted secondary path estimation unit may be dynamically used in the adaptive segment of the filter coefficients after adjusting the secondary path estimation unit each time, and the original noise signal is subjected to the delay processing by using the currently adjusted secondary path estimation unit and is input to the first adaptive module 222. Through the execution sequence, the adjustment operation of the secondary path estimation unit and the filter coefficient can be synchronously performed, so that the optimization of the filter coefficient is started as soon as possible, and the user experience is improved.
Based on the active noise reduction method provided by the embodiment of the application, the sound signal actually played by the user is used as the test signal, so that the optimization of the secondary path estimation unit can be naturally realized when the user uses the earphone to play audio or calls, the stability of the active noise reduction system is improved, the debugging process is more friendly and softer, and great convenience and good experience are brought to the user.
In real life, the human ear experiences different frequencies of sound to different extents. Therefore, the sound pressure level of the real noise collected by the microphone and the noise heard by the human ear at the same frequency are not necessarily the same. For active noise reduction headphones, the underlying goal is to reduce the noise level heard by the human ear, and not simply focus on the true noise level.
From this perspective, the active noise reduction method provided by another embodiment of the present application may adaptively update the filter coefficient based on considering the response characteristics of the human ear to different frequency noises, so as to achieve an active noise reduction effect more fitting the auditory sense of the human ear.
Fig. 9 is a schematic diagram illustrating an exemplary active noise reduction system 900 according to another embodiment of the present application. As shown in fig. 9, on the basis of the active noise reduction system 200 shown in fig. 2, the processor 220 of the active noise reduction system 900 is further provided with a sound weighting unit 250.
In addition, the active noise reduction system 600 shown in fig. 6 may further include an acoustic weighting unit (not shown) disposed between the error microphone 240 and the first adaptive module 222.
In this embodiment, step S340 of the active noise reduction method shown in fig. 3 or step S780 of the active noise reduction method shown in fig. 7 may specifically include the following steps: inputting the error signal into a sound weighting unit to obtain a weighted error signal; and determining the filter coefficient according to the weighted error signal and the delay reference signal.
Specifically, the weighted error signal can be obtained by performing weighted correction on the spectral shape of the error signal collected by the error microphone 240 through the acoustic weighting unit 250. For example, the acoustic weighting unit 250 may a-weight the error signal to make the noise spectrum of the weighted error signal more closely approximate to the hearing of the human ear.
Based on the active noise reduction method provided by the embodiment of the application, the weighted error signal replaces the original error signal and is input into the adaptive module to participate in the adjustment process of the filter coefficient, and the filter coefficient can be guided to be optimized towards the actual noise reduction demand direction of human ears, so that the active noise reduction effect is obviously improved, and better hearing experience is brought to users.
It should be noted that, in the embodiments of the present application, it is not limited whether the earphone is further provided with a feedback noise reduction system, and a feedback noise reduction loop may be further added to the active noise reduction system provided in any of the embodiments of the present application, so as to form a hybrid active noise reduction earphone including a feedforward adaptive active noise reduction system and a feedback active noise reduction system.
Exemplary devices
Fig. 10 is a schematic structural diagram of an active noise reduction device 1000 according to an embodiment of the present disclosure.
As shown in fig. 10, the active noise reduction device 1000 includes: a reference microphone 1010 for collecting an original noise signal; an error microphone 1020 for acquiring an error signal, wherein the error signal includes an error between an original noise signal transmitted to a spatial point where the error microphone 1020 is located and a noise reduction signal, and the noise reduction signal is determined according to the original noise signal and an initial filter coefficient; a first calculating module 1030, configured to input an original noise signal to a secondary path estimating unit to obtain a delay reference signal, where the secondary path estimating unit is configured to simulate a secondary path; and a second calculating module 1040, configured to determine filter coefficients according to the error signal and the delay reference signal.
Specifically, in order to enable the second calculation module 1040 to perform the adjustment operation of the filter coefficient based on the original noise signal and the error signal that accurately correspond to each other, the first calculation module 1030 provided in the embodiment of the present application is provided with a secondary path estimation unit for simulating a secondary path. After receiving the original noise signal d (n) acquired by the reference microphone at the first time, the first calculating module 1030 may simulate the influence of the secondary path, perform delay processing on d (n) by using the secondary path estimating unit, and input the processed delay reference signal d '(n) to the second calculating module 1040 at the second time, so that the delay reference signal d' (n) and the error signal e (n) input at the second time are "aligned" in time, thereby canceling the influence caused by the secondary path.
The second calculating module 1040 may include an adaptive module, and after receiving the error signal and the delay reference signal, the adaptive module may adjust the initial filter coefficient, and determine whether the adjusted filter coefficient is the optimal filter coefficient, if not, adjust again, and repeat the above process until the filter coefficient reaches the optimal filter coefficient.
Specifically, in one embodiment, the second calculation module 1040 may determine whether the filter coefficients are optimal based on the error signal.
When the error signal is judged not to reach the preset optimal condition, the initial filter coefficient can be adjusted, and the updated noise reduction signal is determined by adopting the adjusted filter coefficient. After the updated noise reduction signal is played by the speaker, the error microphone 1020 can acquire the updated error signal. When the updated error signal is judged to still not reach the preset optimal condition, the filter coefficient can be adjusted again to obtain the error signal updated again. And repeating the steps until the error signal meets the preset optimal condition, stopping adjustment, and determining the current filter coefficient (namely the filter coefficient after the last adjustment) as the final filter coefficient.
In one embodiment, for example, the energy of the error signal reaching the minimum value may be set as the optimal condition, that is, whether the error signal satisfies the preset optimal condition is determined by determining whether the energy of the residual noise signal reaches the minimum value.
Here, the process of repeatedly adjusting the filter coefficients and updating the error signal may be implemented by using an adaptive algorithm, such as an LMS algorithm, and the filter coefficients are updated each time until the error signal is optimized. It should be understood that the embodiments of the present application do not limit the algorithm actually used.
Based on the active noise reduction device provided by the embodiment of the application, the original noise signal is actively delayed in the process of adaptively adjusting the coefficient of the filter so as to accurately correspond to the error signal in time, and adverse effects caused by a secondary path can be overcome, so that the stability of the active noise reduction process is improved.
It should be noted that, in some embodiments of the present application, the secondary path estimation unit described above may be determined in advance through offline calculation, for example, the determination method of the secondary path estimation unit provided in the embodiment shown in fig. 5 of the present application may be used for determining the secondary path estimation unit. In another embodiment of the present application, the secondary path estimation unit may further adjust the optimization in real time through online calculation during the actual use process of the user so as to adapt to different use environments.
Another embodiment of the present application provides an active noise reduction apparatus capable of adjusting a secondary path estimation unit through an online calculation, which is based on the apparatus shown in fig. 10 and further includes a third calculation module.
Specifically, when the active noise reduction device provided based on this embodiment performs active noise reduction, a test signal from the player may be played by using a speaker in the earphone, where the test signal is uncorrelated with the original noise signal.
Here, the third calculation module includes a secondary path estimation unit. The third computing module may receive the test signal from the player through the circuit, and then obtain the delay test signal according to the test signal and the initial secondary path estimating unit (the unadjusted secondary path estimating unit is the initial secondary path estimating unit). Or, the third computing module may also receive the noise reduction signal and the test signal from the speaker through the circuit, and simultaneously process the two signals based on the initial secondary path estimation unit, so as to obtain the processed noise reduction signal and the processed test signal as the delay test signal together.
Further, the third computing module may receive an error signal from the error microphone and determine a difference between the error signal and the delayed test signal as the test error signal. It should be understood that, in the present embodiment, the error signal includes both the error between the original noise signal and the noise reduction signal delivered to the spatial point of the error microphone, and the test signal delivered to the spatial point of the error microphone.
It should be understood that the energy of the test error signal should be minimized when the secondary path estimation unit is infinitely close to the true secondary path, and the secondary path estimation unit at this time is the optimal secondary path estimation unit.
Therefore, in order to obtain the optimal secondary path estimation unit, the third calculation module may repeatedly adjust the initial secondary path estimation unit through an adaptive algorithm according to the test error signal and the test signal to obtain an updated test error signal. When the expected power of the current updated test error signal is judged to reach the minimum value, the current (after the last adjustment) secondary path estimation unit can be determined to be the secondary path estimation unit closest to the real secondary path.
In particular, in an embodiment, the third calculation module may implement the following steps to determine the secondary path estimation unit:
adjusting the initial secondary path estimation unit according to the test error signal;
a. determining an updated test error signal based on the test signal and the adjusted secondary path estimation unit;
b. when the expected power of the updated test error signal does not reach the minimum value, adjusting the adjusted secondary path estimation unit;
iteratively executing the steps a and b until the expected power of the test error signal reaches the minimum value;
and determining the current adjusted secondary path estimation unit as the secondary path estimation unit.
After determining the secondary path estimation unit, the third computation module may synchronize the secondary path estimation unit to the first computation module such that the first computation module adjusts the filter coefficients based on the updated secondary path estimation unit.
It should be appreciated that in other embodiments of the present application, the above-described portions of the active noise reduction apparatus may be configured to actively reduce noise in other manners or sequences.
For example, in one embodiment, the above method may be performed without turning on the active noise reduction function, i.e., the filter and noise reduction signal may not be used during the performance of the steps. That is, when the user does not turn on the active noise reduction, the active noise reduction apparatus may only use the original noise signal and the test signal to debug the secondary path estimation unit, and temporarily does not adjust the filter coefficient. Therefore, when the user opens the noise reduction function, the secondary path estimation unit is already in the optimal state, and the link of optimizing the filter coefficient can be directly entered, so that a large amount of debugging time can be saved.
For another example, in another embodiment, the filter coefficients may be iteratively adjusted while the secondary path estimation unit is iteratively adjusted. That is, before determining the secondary path estimation unit, i.e., when the secondary path estimation unit has not reached the optimum yet, the third calculation module may dynamically synchronize the currently adjusted secondary path estimation unit to the first calculation module after each adjustment of the secondary path estimation unit, and use it in the adaptation of the filter coefficients. Through the execution sequence, the adjustment operation of the secondary path estimation unit and the filter coefficient can be synchronously performed, so that the optimization of the filter coefficient is started as soon as possible, and the user experience is improved.
Based on the active noise reduction device provided by the embodiment of the application, the acoustic signal actually played by the user is used as the test signal, so that the optimization of the secondary path estimation unit can be naturally realized when the user uses the earphone to play audio or calls, the stability of the active noise reduction system is improved, the debugging process is more friendly and softer, and great convenience and good experience are brought to the user.
Further, in another embodiment, the active noise reduction apparatus may further include a weighting unit. In the active noise reduction process, the acoustic weighting unit can process the error signal to obtain a weighted error signal, and the weighted error signal is input to the second calculation module to be used for adjusting the filter coefficient instead of the error signal.
Specifically, the acoustic weighting unit may perform weighting correction on a spectral shape of an error signal collected by the error microphone to obtain a weighted error signal. For example, the acoustic weighting unit may a-weight the error signal to make the noise spectrum of the weighted error signal closer to the auditory perception of the human ear.
Based on the active noise reduction device provided by the embodiment of the application, the weighted error signal replaces the original error signal to be used as the input signal of the self-adaptive calculation to participate in the adjustment process of the filter coefficient, and the filter coefficient can be guided to be optimized towards the actual noise reduction demand direction of human ears, so that the active noise reduction effect is obviously improved, and better hearing experience is brought to users.
It should be understood that the functions and technical effects of the modules in the active noise reduction apparatus provided in the foregoing embodiments may refer to corresponding contents in the exemplary method, and are not described in detail herein.
Exemplary device
Fig. 11 is a schematic structural diagram of an electronic device according to an embodiment of the present application. As shown in fig. 11, the electronic apparatus includes: a processor 1110; memory 1120, memory 1120 includes computer instructions stored thereon, which when executed by processor 1110, cause processor 1110 to perform an active noise reduction method as provided by any of the embodiments described above.
Exemplary computer readable storage Medium
Other embodiments of the present application further provide a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the active noise reduction method according to any of the above embodiments. It is understood that the computer storage medium can be any tangible medium, such as: floppy disks, CD-ROMs, DVDs, hard drives, network media, or the like.
The block diagrams of apparatuses, devices, systems referred to in this application are only given as illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. Those skilled in the art will appreciate that the devices, apparatus, systems, etc. may be connected, arranged, or configured in any manner. Words such as "comprising," "including," "having," and the like are open-ended words to "including, but not limited to," and may be used interchangeably therewith unless the context clearly dictates otherwise. The word "such as" is used herein to mean, and is used interchangeably with, the phrase "such as but not limited to".
It should also be noted that in the devices, apparatuses, and methods of the present application, the modules or steps may be decomposed and/or recombined. These decompositions and/or recombinations are to be considered as equivalents of the present application.
The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the scope of the application. Thus, the present application is not intended to be limited to the above aspects but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
The above description is intended to be illustrative and descriptive of the present technology. Furthermore, the description is not intended to limit embodiments of the application to the form disclosed above. While a number of exemplary aspects and embodiments have been discussed above, other variations, modifications, changes, additions, and sub-combinations will readily occur to those skilled in the art based upon the foregoing description.
The above description is only a preferred embodiment of the present application and should not be taken as limiting the present application, and any modifications, equivalents and the like that are within the spirit and scope of the present application should be included.
Claims (9)
1. An active noise reduction method, comprising:
collecting an original noise signal by a reference microphone;
playing a test signal through a loudspeaker, wherein the test signal is irrelevant to the original noise signal, and the test signal comprises a voice call signal or a media audio signal;
collecting an error signal through an error microphone, wherein the error signal is the superposition of an original noise signal, a test signal and a noise reduction signal which are transmitted to a space point where the error microphone is located, and the noise reduction signal is determined according to the original noise signal and an initial filter coefficient;
obtaining a delay test signal according to the test signal and an initial secondary path estimation unit;
determining a difference between the error signal and the delayed test signal as a test error signal;
determining a secondary path estimation unit according to the test error signal and the test signal, wherein the secondary path estimation unit is used for simulating a secondary path;
inputting the original noise signal into the secondary path estimation unit to obtain a delay reference signal;
and determining a filter coefficient according to the error signal and the delay reference signal.
2. The active noise reduction method of claim 1, wherein determining a secondary path estimation unit based on the test error signal and the test signal comprises:
adjusting the initial secondary path estimation unit according to the test error signal;
a. determining an updated test error signal based on the test signal and the adjusted secondary path estimation unit;
b. adjusting the adjusted secondary path estimation unit when the expected power of the updated test error signal does not reach a minimum value;
iteratively executing the steps a and b until the expected power reaches a minimum value;
and determining the current adjusted secondary path estimation unit as the secondary path estimation unit.
3. The active noise reduction method of claim 1, wherein the initial secondary path estimation unit is predetermined from a test signal.
4. The active noise reduction method according to any of claims 1 to 3, wherein determining filter coefficients from the error signal and the delayed reference signal comprises:
inputting the error signal into a sound weighting unit to obtain a weighted error signal;
and determining the filter coefficient according to the weighted error signal and the delay reference signal.
5. An active noise reduction device, comprising:
a reference microphone for collecting an original noise signal;
a speaker for playing a test signal, the test signal being uncorrelated with the original noise signal, the test signal comprising a voice call signal or a media audio signal;
the system comprises an error microphone, a signal processing unit and a signal processing unit, wherein the error microphone is used for acquiring an error signal, the error signal is the superposition of an original noise signal, a test signal and a noise reduction signal which are transmitted to a space point where the error microphone is located, and the noise reduction signal is determined according to the original noise signal and an initial filter coefficient;
a third calculation module to: obtaining a delay test signal according to the test signal and an initial secondary path estimation unit; determining a difference between the error signal and the delayed test signal as a test error signal; determining a secondary path estimation unit according to the test error signal and the test signal, wherein the secondary path estimation unit is used for simulating a secondary path;
the first calculation module is used for inputting the original noise signal into the secondary path estimation unit to obtain a delay reference signal;
and the second calculation module is used for determining the filter coefficient according to the error signal and the delay reference signal.
6. An active noise reducing headphone, comprising:
a filter, the filter coefficients of which are determined by the active noise reduction method of any of claims 1-4.
7. An active noise reduction earphone, comprising: a reference microphone, a speaker, an error microphone and a chip,
wherein the reference microphone, the loudspeaker, the error microphone and the chip are used to perform the active noise reduction method of any one of claims 1-4 for determining filter coefficients in real time.
8. An electronic device, comprising:
a processor;
a memory including computer instructions stored thereon that, when executed by the processor, cause the processor to perform the active noise reduction method of any of claims 1-4.
9. A computer readable storage medium comprising computer instructions stored thereon, which when executed by a processor, cause the processor to perform the active noise reduction method of any of claims 1-4.
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