CN113345400B - Calibration method and device of active noise reduction system of wearable device, storage medium and terminal - Google Patents
Calibration method and device of active noise reduction system of wearable device, storage medium and terminal Download PDFInfo
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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
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- 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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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
- H04R1/00—Details of transducers, loudspeakers or microphones
- H04R1/10—Earpieces; Attachments therefor ; Earphones; Monophonic headphones
- H04R1/1083—Reduction of ambient noise
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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
- G10K2210/50—Miscellaneous
- G10K2210/504—Calibration
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
- H04R2460/00—Details of hearing devices, i.e. of ear- or headphones covered by H04R1/10 or H04R5/033 but not provided for in any of their subgroups, or of hearing aids covered by H04R25/00 but not provided for in any of its subgroups
- H04R2460/01—Hearing devices using active noise cancellation
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Abstract
A calibration method and device for an active noise reduction system of a wearable device, a storage medium and a terminal, wherein the method comprises the following steps: starting the active noise reduction system, controlling the audio playing module to play a noise test signal, and collecting the noise test signal through the sound collecting module; calculating a secondary path estimate of the active noise reduction system; stopping playing the noise test signal, playing environmental noise through an external playing module, and configuring initial parameters of the active noise reduction system and calibration coefficients preset by the filter, wherein the initial parameters comprise the secondary path estimation; and controlling the audio playing module to play the noise reduction signal, and acquiring a target coefficient of the filter, wherein the target coefficient is used for calibrating the filter. According to the scheme, the mass production yield of the wearable equipment can be improved, and the noise reduction performance of the wearable equipment is further improved.
Description
Technical Field
The present invention relates to the field of audio signal processing, and in particular, to a method and apparatus for calibrating an active noise reduction system of a wearable device, a storage medium, and a terminal.
Background
In wearable devices such as headphones for audio processing, an active noise reduction (Active Noise Cancellation, ANC for short) system is generally included, and the active noise reduction system plays sound waves opposite to ambient noise through an audio playing module (such as a speaker), so as to neutralize and offset the noise, thereby realizing the noise reduction effect. In order to improve the noise reduction effect, the wearable equipment with few active noise reduction is improved from a single structure of single feedforward and single feedback to a mixed structure of feedforward and feedback, and the noise reduction depth and width can be improved. However, no matter which structure is adopted, the optimal noise reduction experience can be achieved only by obtaining the optimal coefficient of the noise reduction filter through calibration.
For the wearable equipment of the earphone, the mass production stage comprises a front-stage working section and a rear-stage working section. The former working section mainly generates devices in the equipment, and the requirements on the devices and the structures in the former working section are very high in order to ensure the yield of finished products in the subsequent working section, so that the yield of earphone tests (such as consistency tests, air tightness tests and the like) is low. The later stage working section mainly carries out optimal adjustment and calibration on the individual earphone, carries out offline commonality ANC coefficient design based on a filter design link of the earphone, scans gain according to the designed coefficient, and obtains a gain value corresponding to the maximum noise reduction amount as the optimal gain for calibration so as to carry out production line calibration on the individual earphone.
However, the gain calibration adopted by the conventional production line calibration scheme cannot change the frequency response characteristic of the earphone, and when the frequency response difference exists among earphone individuals, the performance under the optimal gain cannot represent the optimal performance of the individual earphone, which also affects the yield of the final finished product and further affects the noise reduction performance of the earphone.
In summary, the existing production line calibration scheme may have the problems of low yield of the wearable equipment in mass production and limited noise reduction performance.
Disclosure of Invention
The invention solves the technical problems of low yield and limited noise reduction performance of the conventional calibration scheme.
To solve the above problems, an embodiment of the present invention provides a calibration method of an active noise reduction system of a wearable device, where the active noise reduction system includes: the audio playing module is used for playing the input audio signals; the sound collection module is used for collecting the audio signals played by the audio playing module or the audio signals played by the external playing module; the filter is used for filtering the audio signals acquired by the sound acquisition module to obtain noise reduction signals; an adaptive module for adjusting coefficients of the filter; the method comprises the following steps: starting the active noise reduction system, controlling the audio playing module to play a noise test signal, and collecting the noise test signal through the sound collecting module; calculating a secondary path estimate of the active noise reduction system; stopping playing the noise test signal, playing environmental noise through an external playing module, and configuring initial parameters of the active noise reduction system and calibration coefficients preset by the filter, wherein the initial parameters comprise the secondary path estimation; and controlling the audio playing module to play the noise reduction signal, and acquiring a target coefficient of the filter, wherein the target coefficient is used for calibrating the filter.
Optionally, the obtaining the target coefficient of the filter includes: and after the coefficient of the filter converges for a preset time, acquiring the coefficient of the filter as the target coefficient.
Optionally, after stopping playing the noise test signal and before controlling the audio playing module to play the noise reduction signal, the method further includes: closing the active noise reduction system, and measuring the passive noise reduction level of the wearable equipment; starting the active noise reduction system and measuring the active noise reduction level of the wearable equipment; the obtaining the target coefficient of the filter includes: and when the difference value between the active noise reduction level and the passive noise reduction level is in a preset value interval and the coefficient of the filter converges for a preset time, acquiring the coefficient of the filter as the target coefficient.
Optionally, the passive noise reduction level is measured by measuring a passive noise reduction curve, and the active noise reduction level is tested by measuring an active noise reduction curve.
Optionally, the sound collection module includes a reference microphone, the filter is an FxLMS filter, and the filter coefficient convergence formula is as follows: n is used for representing time, the value of n is a positive integer, W (n) is a filter coefficient corresponding to time n, W (n+1) is a filter coefficient corresponding to time n+1, mu is a fixed step factor, m (n) is an intermediate error signal,/> A signal acquired by the reference microphone after passing through a secondary path; wherein/>S (n) is a secondary path estimation obtained by secondary path self-adaptive modeling corresponding to the moment n, and x (n) is a signal acquired by the reference microphone; m (n) =f (n) +x (n) W T (n); f (n) is a signal of x (n) after passing through the main path, and W T (n) is a transposed matrix of W (n).
Optionally, the calculating a secondary path estimate of the active noise reduction system includes: and estimating a transfer function of a secondary path according to the noise test signal played by the audio playing module and the noise test signal acquired by the sound acquisition module to obtain the secondary path estimation.
Optionally, the sound collection module further includes an error microphone, and the secondary path estimation is obtained according to the following formula, including: s (n+1) =s (n) +2μe (n) spk (n); wherein n is used for representing time, the value of n is a positive integer, S (n) is a secondary path estimation obtained by secondary path self-adaptive modeling corresponding to time n, S (n+1) is a secondary path estimation obtained by secondary path self-adaptive modeling corresponding to time n+1, mu is a fixed step factor, spk (n) is a noise test signal played by the audio playing module, and e (n) is an intermediate error signal; wherein e (n) =d (n) -spk (n) S T (n); d (n) is a noise test signal collected by the error microphone, and S T (n) is a transposed matrix of S (n).
Optionally, the filter comprises a single feedforward filter or a single feedback filter or a feedforward plus feedback hybrid filter.
Optionally, the audio playing module is controlled to play the noise test signal in the noise reduction environment.
Optionally, after the obtaining the coefficient of the filter as the target coefficient, the method further includes: storing the target coefficients into the wearable device.
Optionally, the preset calibration coefficient relates to a scenario in which the wearable device is used, and the configuring the preset calibration coefficient of the filter includes: and configuring corresponding calibration coefficients according to the scene used by the wearable equipment.
The embodiment of the invention also provides a calibration device of the active noise reduction system of the wearable device, wherein the active noise reduction system comprises: the audio playing module is used for playing the input audio signals; the sound collection module is used for collecting the audio signals played by the audio playing module or the audio signals played by the external playing module; the filter is used for filtering the audio signals acquired by the sound acquisition module to obtain noise reduction signals; an adaptive module for adjusting coefficients of the filter; the calibration device comprises: the noise test signal playing module is used for starting the active noise reduction system, controlling the audio playing module to play a noise test signal and collecting the noise test signal through the sound collecting module; a secondary path estimation module for calculating a secondary path estimate of the active noise reduction system; the environment noise playing module is used for stopping playing the noise test signal, closing the active noise reduction system and playing the environment noise through the external playing module; the configuration module is used for configuring initial parameters of the active noise reduction system and preset calibration coefficients of the filter, wherein the initial parameters comprise the secondary path estimation; the target coefficient acquisition module is used for starting the active noise reduction system, controlling the audio playing module to play the noise reduction signal, and acquiring a target coefficient of the filter, wherein the target coefficient is used for calibrating the filter.
Embodiments of the present invention also provide a storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method of calibrating an active noise reduction system of any of the wearable devices.
The embodiment of the invention also provides a terminal, which comprises the calibration device of the active noise reduction system of the wearable equipment, or comprises a memory and a processor, wherein the memory is stored with a computer program which can be run on the processor, and the processor executes the steps of the calibration method of the active noise reduction system of any one of the wearable equipment when running the computer program.
Compared with the prior art, the technical scheme of the embodiment of the invention has the following beneficial effects:
According to the calibration method for the active noise reduction system of the wearable equipment, provided by the embodiment of the invention, the secondary path estimation, the convergence step length, the order and the like of the active noise reduction system corresponding to the same model of the wearable equipment are taken as initial parameters, and the preset calibration coefficient of the filter is taken as an initial filter coefficient, so that the production line calibration is performed on the wearable equipment. The consistency requirement of the production line calibration on devices in the wearable equipment is low, so that the consistency test requirement in the traditional calibration can be omitted or reduced, and the overall mass production yield is improved; the individual optimal coefficient of the wearable equipment can be realized by carrying out self-adaptive calibration according to the self-adaptive module, and the noise reduction performance is better than that of the common ANC coefficient of the traditional offline design.
Further, by setting the convergence time of the filter coefficients at the time of line calibration, one-touch calibration can be performed, thereby improving the calibration efficiency.
Further, the noise reduction capability of the active noise reduction system of the wearable device is controlled by monitoring the difference between the active noise reduction level and the passive noise reduction level so as to accurately calibrate each wearable device.
Drawings
FIG. 1 is a schematic diagram of an active noise reduction system according to an embodiment of the present invention;
Fig. 2 is a flowchart of a calibration method of an active noise reduction system of a wearable device according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of another active noise reduction system according to an embodiment of the present invention;
Fig. 4 is a schematic structural diagram of a calibration device of an active noise reduction system of a wearable device according to an embodiment of the present invention.
Detailed Description
As described in the background art, the existing production line calibration scheme may have the problems of low yield of mass production and limited noise reduction performance of the wearable device.
To address the above issues, embodiments of the present invention provide a wearable device that includes an active noise reduction system 10. Referring to fig. 1, fig. 1 is a schematic diagram of an active noise reduction system 10. The active noise reduction system 10 includes: the audio playing module 101 is configured to play an input audio signal. The sound collection module 102 is configured to collect the audio signal played by the audio playing module 101 or the audio signal played by the external playing module 11. A filter 103 for filtering the audio signal collected by the sound collection module 102 to generate a noise reduction signal, where the filter may include a single feedforward filter or a single feedback filter or a feedforward-plus-feedback hybrid filter. An adaptation module 104 for adjusting the coefficients of the filter 103.
The wearable device is a wearable device to be subjected to audio processing, and may include various types of headphones (such as headphones, in-ear headphones, bluetooth headphones, and the like), and other wearable devices including active noise reduction systems. The audio playing module 101 in the active noise reduction system 10 may be configured to play the generated noise reduction signal, so as to implement an active noise reduction function; the audio playing module 101 may also be configured to play other sound signals, such as sound signals sent by a control module of the wearable device (such as a central processing unit (central processing unit, abbreviated as CPU) or the like) to the audio playing module 101. The audio playback module 101 may include a speaker, a microphone, and the like.
Referring to fig. 2, fig. 2 is a schematic diagram of a calibration method of an active noise reduction system of a wearable device according to an embodiment of the present invention, where the calibration method is performed by a terminal such as a computer, and the terminal is capable of being connected to the wearable device to control the on and off of the active noise reduction system, so as to perform the method, and the terminal is further connected to an external playing module 11 to control the external playing module 11 to play environmental noise. The method includes the following steps S201 to S204, which are described in detail below.
Optionally, before starting to execute the step S201, the wearable device (such as an earphone) is correctly worn on the artificial ear, where the correct wearing refers to that the wearable device is worn at a correct angle, so as to ensure that the tightness between the wearable device and the artificial ear is better.
Step S201, the active noise reduction system 10 is turned on, the audio playing module 101 is controlled to play the noise test signal, and the noise test signal is collected by the sound collection module 102.
The noise test signal may be a white noise test signal, a pink noise test signal, or other predetermined noise signals. Optionally, the terminal sends a noise test signal to the wearable device, and the control module of the wearable device controls the audio playing module 101 to play the noise test signal, and the sound collecting module 102 can collect the noise test signal.
Step S202 calculates a secondary path estimate of the active noise reduction system 10.
Wherein the secondary path is estimated as an estimate of the secondary path transfer function of the active noise reduction system 10.
And step 203, stopping playing the noise test signal, playing the environmental noise through an external playing module, and configuring initial parameters of the active noise reduction system and calibration coefficients preset by the filter, wherein the initial parameters comprise the secondary path estimation.
Optionally, the initial parameter may include, in addition to the secondary path estimate, a convergence step size, an order, and other preset values. The secondary path estimate is configured to the adaptation module 104.
Optionally, the preset calibration coefficient relates to a scenario in which the wearable device is used, and the configuring the preset calibration coefficient of the filter includes: and configuring corresponding calibration coefficients according to a scene suitable for the wearable equipment.
The audio playing module 101 of the wearable device is controlled by the terminal to stop playing the noise test signal. The scenes used by the wearable device may be general life scenes, high-frequency noise scenes, low-frequency noise scenes, and the like. Further, environmental noise corresponding to a scene of use of the wearable device can be acquired and played. Thus, the production line calibration can be performed for the scene of the wearable device.
Step S204, controlling the audio playing module to play the noise reduction signal, and obtaining a target coefficient of the filter, where the target coefficient is used to calibrate the filter.
After the environmental noise is played, the active noise reduction system 10 performs active noise reduction, that is, the audio playing module 101 plays the noise reduction signal to perform noise neutralization, and the adaptive module 104 automatically adjusts the coefficients of the filter 103 until convergence, so as to obtain the target coefficients for calibrating the filter 103, and complete the production line calibration.
By the method shown in fig. 2, the secondary path estimation, the convergence step length, the order and the like of the active noise reduction system corresponding to the same model of the wearable device are used as initial parameters, and the preset calibration coefficient of the filter is used as an initial filter coefficient to perform line calibration on the wearable device. The consistency requirement of the production line calibration on devices in the wearable equipment is low, so that the consistency test requirement in the traditional calibration can be omitted or reduced, and the overall mass production yield is improved; the individual optimal coefficient of the wearable equipment can be realized by carrying out self-adaptive calibration according to the self-adaptive module, and the noise reduction performance is better than that of the common ANC coefficient of the traditional offline design.
In one embodiment, the obtaining the target coefficient of the filter in step S204 may include: and after the coefficient of the filter converges for a preset time, acquiring the coefficient of the filter as the target coefficient. The preset time may be a time with a better convergence effect measured by experiments, such as 10 seconds, 20 seconds, and the like.
In this embodiment, by setting the convergence time of the filter coefficient, one-key calibration can be performed on the production line, thereby improving the calibration efficiency.
In one embodiment, after stopping playing the noise test signal in step S203 and before controlling the audio playing module to play the noise reduction signal in step S204, the method may further include: closing the active noise reduction system, and measuring the passive noise reduction level of the wearable equipment; starting the active noise reduction system and measuring the active noise reduction level of the wearable equipment; the obtaining the target coefficient of the filter in step S204 includes: and when the difference value between the active noise reduction level and the passive noise reduction level is in a preset value interval and the coefficient of the filter converges for a preset time, acquiring the coefficient of the filter as the target coefficient.
The active noise reduction system 10 is turned off, that is, the active noise reduction function of the wearable device is deactivated, and at this time, the wearable device can only perform passive noise reduction. The passive noise reduction refers to the noise reduction capability of the wearable device after the active noise reduction system is closed, and mainly refers to the isolation of the ear from external noise through a sound insulation material.
Optionally, the passive noise reduction level of the wearable device is measured by measuring a passive noise reduction curve of the wearable device. Optionally, the passive noise reduction curve is measured by an external measuring device, and the passive noise reduction level may also be a parameter capable of reflecting the passive noise reduction capability of the wearable device, where the parameter is related to factors such as a material and a shape of the sound insulation material.
After starting the active noise reduction system 10, an adaptation module 104 is enabled, which adaptation module 104 is able to adjust the coefficients of the filter 103 according to the noise reduction of the wearable device. The active noise reduction level refers to the noise reduction capability of the wearable device after the active noise reduction system 10 is turned on, and optionally, the noise reduction level may be a parameter capable of reflecting the noise reduction capability of the wearable device after the active noise reduction system 10 is turned on.
Optionally, the active noise reduction level of the wearable device is measured by measuring an active noise reduction curve of the wearable device. The active noise reduction curve is a noise reduction curve of the wearable device measured by an external measuring device after the active noise reduction system 10 is turned on.
Optionally, the active noise reduction curve and the passive noise reduction curve are curves drawn with frequency as an abscissa and noise reduction volume as an ordinate.
The preset value interval is used to represent the noise reduction capability that the active noise reduction system 10 needs to achieve, and the specific value of the preset value interval is set according to experimental data. Specifically, the active noise reduction system may be started and converged for a period of time (e.g. 10 seconds), at this time, the active noise reduction level of the wearable device is obtained, whether the difference between the active noise reduction level and the passive noise reduction level meets a preset value interval is observed, and if yes, the production line calibration is completed; if not, continuing to converge for a period of time until a preset value interval is met.
In this embodiment, the noise reduction capability of the active noise reduction system of the wearable device is controlled by monitoring the difference between the active noise reduction level and the passive noise reduction level, so as to accurately calibrate each wearable device.
In an embodiment, referring to fig. 1 and 3, fig. 3 is a schematic structural diagram of another active noise reduction system 30, where the sound collection module 102 shown in fig. 1 may include a reference microphone 1022, and the reference microphone 1022 is used to collect a sound signal generated outside the wearable device, such as an audio signal played by the external playing module 11 or a noise signal in the environment. The filter 103 is a filtered least mean square (FxLMS) filter, and the filter coefficient convergence formula (1) is as follows:
The signal acquired by the reference microphone after passing through the secondary path can be obtained according to the formula (2):
m (n) is an intermediate error signal, which can be derived according to equation (3):
m(n)＝f(n)+x(n)WT(n) (3)
Wherein n is used for representing time, the value of n is a positive integer, W (n) is a filter coefficient corresponding to time n, W (n+1) is a filter coefficient corresponding to time n+1, mu is a fixed step factor, f (n) is a signal of x (n) after passing through the main channel, W T (n) is a transposed matrix of W (n), S (n) is a secondary channel estimation obtained by secondary channel adaptive modeling corresponding to time n, and x (n) is a signal acquired by the reference microphone.
It should be noted that, the filter 103 in the active noise reduction system 10 may employ other algorithms, such as a minimum mean Square error (LEAST MEAN Square, abbreviated as LMS), a Normalized minimum mean Square error (Normalized LEAST MEAN Square, abbreviated as NLMS), a variable step-based minimum mean Square error (variable STEP LEAST MEAN Square, abbreviated as VSLMS), and the like, and the corresponding convergence manner may refer to the existing scheme and will not be described herein.
In the present embodiment, after the active noise reduction system 10 is turned on, the secondary path transfer function can be estimated based on the adaptive modeling method, and the coefficient of filter convergence can be calculated according to the above formulas (1) to (3).
In one embodiment, the calculating the secondary path estimate of the active noise reduction system in step S202 may include: and estimating a transfer function of a secondary path according to the noise test signal played by the audio playing module and the noise test signal acquired by the sound acquisition module to obtain the secondary path estimation.
Optionally, the noise test signal played by the audio playing module 101 and the noise test signal collected by the sound collecting module 102 are respectively obtained. And carrying out wiener estimation on the transfer function of the secondary path to obtain the secondary path estimation.
Optionally, wiener estimating the transfer function of the secondary path to obtain the secondary path estimate includes: the noise test signal (namely, the input signal of the secondary path is denoted as y (n)) played by the audio playing module 101 and the noise test signal (namely, the output signal of the secondary path is denoted as y' (n)) acquired by the sound acquisition module 102 are measured; obtaining an autocorrelation matrix R yy of an input signal of a secondary path according to the following formula (4); obtaining a cross correlation matrix r yy' of the input signal of the secondary path and the output signal of the secondary path according to the following formula (5); the secondary path estimate S' (n) is obtained according to the following equation (6).
Ryy＝E[y(n)yT(n)] (4)
ryy'＝E[y(n)y’(n)] (5)
S’(n)＝Ryy -1ryy' (6)
Wherein E [ ] is a mathematical expectation of values in brackets, y T (n) is a transposed matrix of y (n), and n is a positive integer.
The solution of the present embodiment is capable of calculating a secondary path estimate in an off-line manner, the secondary path estimate value not varying with the adaptation module 104.
In one embodiment, referring to fig. 1 and 3, the sound collection module 102 in fig. 1 may include an error microphone 1021 for collecting the audio signal played by the audio playing module 101.
The calculation of the secondary path estimate of the active noise reduction system described in step S302 is performed according to the following formula (7):
S(n+1)＝S(n)+2μe(n)spk(n) (7)
wherein e (n) in the formula (7) is an intermediate error signal, and the calculation mode is as follows in the formula (8):
e(n)＝d(n)-spk(n)ST(n) (8)
Wherein n is used for representing time, the value of n is a positive integer, S (n) is a secondary path estimation obtained by secondary path self-adaptive modeling corresponding to time n, S (n+1) is a secondary path estimation obtained by secondary path self-adaptive modeling corresponding to time n+1, mu is a fixed step factor, spk (n) is a noise test signal played by the audio playing module, d (n) is a noise test signal acquired by the error microphone, and S T (n) is a transposed matrix of S (n).
The adaptive modeling is a process of estimating the secondary path transfer function by using an adaptive filter, and the adaptive modeling method can refer to the existing modeling method, which is not described in detail herein. In this embodiment, the secondary path estimate of the active noise reduction system can be calculated online by adaptive modeling of the secondary path according to the above formula.
Optionally, the active noise reduction system 30 shown in fig. 3 may further include a downsampling module 1 (indicated by 301 in the figure) configured to downsample the audio signal acquired by the error microphone 1021, and output the downsampled audio signal to the filter 103; the active noise reduction system 30 may further include a downsampling module 2 (indicated by 302 in the figure) for downsampling the audio signal acquired by the reference microphone 1022 and outputting the downsampled audio signal to the filter 103; the downsampling modules 1-301 and downsampling modules 2-302 downsample the received signal onto the operating sampling rate of the filter 103 and the adaptation module 104. The active noise reduction system 30 may further include an up-sampling module 303, configured to up-sample the noise reduction signal generated, and send the up-sampled audio signal to the audio playing module 101, so as to play the audio signal in a sound cavity (such as a headphone sound cavity) of the wearable device, and interfere with noise that is transmitted into the sound cavity from an external environment, so as to achieve the purpose of active noise reduction.
The other modules of the active noise reduction system 30 shown in fig. 3 are referred to in the related description of fig. 1, and are not described herein.
In one embodiment, the audio playback module is controlled to play the noise test signal in a silenced environment. I.e. step S201 is performed in a anechoic chamber or box environment to avoid the influence of disturbing sound signals from the outside.
In one embodiment, after the obtaining the coefficients of the filter as target coefficients, the method further includes: storing the target coefficients into the wearable device. Optionally, the target coefficient is stored in a memory of the wearable device, so that after the wearable device leaves the factory, a user can acquire the target coefficient from the memory to perform self-service calibration.
Referring to fig. 4, fig. 4 is a calibration device 40 of an active noise reduction system of a wearable device, including: the noise test signal playing module 401 is configured to start the active noise reduction system, control the audio playing module to play a noise test signal, and collect the noise test signal through the sound collecting module; a secondary path estimation module 402 for calculating a secondary path estimate of the active noise reduction system; a configuration module 403, configured to stop playing the noise test signal, and play environmental noise through an external playing module, configure an initial parameter of the active noise reduction system and a calibration coefficient preset by the filter, where the initial parameter includes the secondary path estimation; the target coefficient obtaining module 404 is configured to turn on the active noise reduction system, control the audio playing module to play the noise reduction signal, and obtain a target coefficient of the filter, where the target coefficient is used to calibrate the filter.
The calibration device 40 shown in fig. 4 relates to the active noise reduction system 10 or the active noise reduction system 30 shown in fig. 1, and the calibration device 40 may be disposed on a terminal side such as a computer.
For more details of the working principle and the working manner of the calibration device 40 of the active noise reduction system of the wearable device, reference may be made to fig. 1 to 3 for a related description of the calibration method of the active noise reduction system of the wearable device, which is not repeated here.
In a specific implementation, the calibration device 40 of the active noise reduction System of the wearable device may correspond to a Chip with a calibration function of the active noise reduction System of the wearable device, or a Chip with a data processing function, such as a System-On-a-Chip (SOC), a baseband Chip, etc.; or corresponds to a chip module in the UE comprising a calibration function chip with an active noise reduction system of the wearable device; or corresponds to a chip module having a chip with a data processing function, or corresponds to a terminal.
In a specific implementation, regarding each apparatus and each module/unit included in each product described in the above embodiments, it may be a software module/unit, or a hardware module/unit, or may be a software module/unit partially, or a hardware module/unit partially.
For example, for each device or product applied to or integrated on a chip, each module/unit included in the device or product may be implemented in hardware such as a circuit, or at least some modules/units may be implemented in software program, where the software program runs on a processor integrated inside the chip, and the remaining (if any) part of modules/units may be implemented in hardware such as a circuit; for each device and product applied to or integrated in the chip module, each module/unit contained in the device and product can be realized in a hardware manner such as a circuit, different modules/units can be located in the same component (such as a chip, a circuit module and the like) or different components of the chip module, or at least part of the modules/units can be realized in a software program, the software program runs on a processor integrated in the chip module, and the rest (if any) of the modules/units can be realized in a hardware manner such as a circuit; for each device, product, or application to or integrated with the terminal, each module/unit included in the device, product, or application may be implemented in hardware such as a circuit, where different modules/units may be located in the same component (e.g., a chip, a circuit module, etc.) or different components in the terminal, or at least some modules/units may be implemented in a software program, where the software program runs on a processor integrated within the terminal, and the remaining (if any) some modules/units may be implemented in hardware such as a circuit.
Embodiments of the present invention also provide a storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method of any of figures 1 to 3. The storage medium may be a computer readable storage medium, and may include, for example, a non-volatile memory (non-volatile) or a non-transitory memory (non-transitory) and may also include an optical disc, a mechanical hard disc, a solid state hard disc, and the like.
The embodiment of the invention also provides a terminal. The terminal may comprise a memory and a processor, the memory having stored thereon a computer program executable on the processor, the processor executing the steps of the method of any of figures 1 to 3 when the computer program is executed.
Specifically, in the embodiment of the present invention, the processor may be a central processing unit (central processing unit, abbreviated as CPU), which may also be other general purpose processors, digital signal processors (DIGITAL SIGNAL processors, abbreviated as DSP), application Specific Integrated Circuits (ASIC), off-the-shelf programmable gate arrays (field programmable GATE ARRAY, abbreviated as FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
It should also be appreciated that the memory in embodiments of the present application may be either volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The nonvolatile memory may be a read-only memory (ROM), a Programmable ROM (PROM), an erasable programmable ROM (erasable PROM EPROM), an electrically erasable programmable ROM (ELECTRICALLY EPROM, EEPROM), or a flash memory. The volatile memory may be a random access memory (random access memory, RAM for short) which acts as an external cache. By way of example, and not limitation, many forms of random access memory (random access memory, RAM) are available, such as static random access memory (STATIC RAM, SRAM), dynamic Random Access Memory (DRAM), synchronous Dynamic Random Access Memory (SDRAM), double data rate synchronous dynamic random access memory (double DATA RATE SDRAM, DDR SDRAM), enhanced synchronous dynamic random access memory (ENHANCED SDRAM, ESDRAM), synchronous link dynamic random access memory (SYNCHLINK DRAM, SLDRAM), and direct memory bus random access memory (direct rambus RAM, DR RAM).
It should be understood that the term "and/or" is merely an association relationship describing the associated object, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist together, and B exists alone. In this context, the character "/" indicates that the front and rear associated objects are an "or" relationship.
The term "plurality" as used in the embodiments of the present application means two or more.
The first, second, etc. descriptions in the embodiments of the present application are only used for illustrating and distinguishing the description objects, and no order is used, nor is the number of the devices in the embodiments of the present application limited, and no limitation on the embodiments of the present application should be construed.
The "connection" in the embodiment of the present application refers to various connection manners such as direct connection or indirect connection, so as to implement communication between devices, which is not limited in the embodiment of the present application.
Although the present invention is disclosed above, the present invention is not limited thereto. Various changes and modifications may be made by one skilled in the art without departing from the spirit and scope of the invention, and the scope of the invention should be assessed accordingly to that of the appended claims.
Claims (14)
1. A method of calibrating an active noise reduction system of a wearable device, the active noise reduction system comprising: the audio playing module is used for playing the input audio signals; the sound collection module is used for collecting the audio signals played by the audio playing module or the audio signals played by the external playing module; the filter is used for filtering the audio signals acquired by the sound acquisition module to obtain noise reduction signals; an adaptive module for adjusting coefficients of the filter; characterized in that the method comprises:
Starting the active noise reduction system, controlling the audio playing module to play a noise test signal, and collecting the noise test signal through the sound collecting module;
calculating a secondary path estimate of the active noise reduction system;
Stopping playing the noise test signal, playing environmental noise through an external playing module, and configuring initial parameters of the active noise reduction system and calibration coefficients preset by the filter, wherein the initial parameters comprise the secondary channel estimation;
and controlling the audio playing module to play the noise reduction signal, and acquiring a target coefficient of the filter, wherein the target coefficient is used for calibrating the filter.
2. The method of claim 1, wherein the obtaining the target coefficients of the filter comprises:
and after the coefficient of the filter converges for a preset time, acquiring the coefficient of the filter as the target coefficient.
3. The method of claim 1, wherein after the stopping playing the noise test signal and before controlling the audio playing module to play the noise reduction signal, further comprises:
closing the active noise reduction system, and measuring the passive noise reduction level of the wearable equipment;
Starting the active noise reduction system and measuring the active noise reduction level of the wearable equipment;
The obtaining the target coefficient of the filter includes:
And when the difference value between the active noise reduction level and the passive noise reduction level is in a preset value interval and the coefficient of the filter converges for a preset time, acquiring the coefficient of the filter as the target coefficient.
4. A method according to claim 3, characterized in that the passive noise reduction level is measured by measuring a passive noise reduction curve and the active noise reduction level is tested by measuring an active noise reduction curve.
5. The method of any one of claims 2 to 4, wherein the sound collection module includes a reference microphone, the filter is an FxLMS filter, and the filter coefficient convergence formula is as follows:
W(n+1)＝W(n)+2μm(n)x^(n)；
n is used for representing time, the value of n is a positive integer, W (n) is a filter coefficient corresponding to time n, W (n+1) is a filter coefficient corresponding to time n+1, mu is a fixed step factor, m (n) is an intermediate error signal, and x (n) is a signal acquired by the reference microphone after passing through a secondary channel;
wherein x (n) =x (n) S T (n);
s (n) is a secondary path estimation obtained by secondary path self-adaptive modeling corresponding to the moment n, and x (n) is a signal acquired by the reference microphone;
m(n)＝f(n)+x(n)WT(n)；
f (n) is a signal of x (n) after passing through the main path, and W T (n) is a transposed matrix of W (n).
6. The method of claim 1, wherein the calculating a secondary path estimate for the active noise reduction system comprises:
And estimating a transfer function of a secondary path according to the noise test signal played by the audio playing module and the noise test signal acquired by the sound acquisition module to obtain the secondary path estimation.
7. The method of claim 1, wherein the sound collection module further comprises an error microphone, and wherein the secondary path estimate is obtained according to the following formula, comprising:
S(n+1)＝S(n)+2μe(n)spk(n)；
Wherein n is used for representing time, the value of n is a positive integer, S (n) is a secondary path estimation obtained by secondary path self-adaptive modeling corresponding to time n, S (n+1) is a secondary path estimation obtained by secondary path self-adaptive modeling corresponding to time n+1, mu is a fixed step factor, spk (n) is a noise test signal played by the audio playing module, and e (n) is an intermediate error signal;
wherein e (n) =d (n) -spk (n) S T (n);
d (n) is a noise test signal collected by the error microphone, and S T (n) is a transposed matrix of S (n).
8. The method of claim 1, wherein the filter is a single feed forward filter or a single feedback filter or a feed forward plus feedback hybrid filter.
9. The method of claim 1, wherein the audio playback module is controlled to play a noise test signal in a muffled environment.
10. The method according to claim 1, wherein after the obtaining the coefficients of the filter as target coefficients, further comprising:
storing the target coefficients into the wearable device.
11. The method of claim 1, wherein the preset calibration coefficients relate to a scenario in which the wearable device is applicable, and the configuring the filter preset calibration coefficients comprises:
and configuring corresponding calibration coefficients according to the scene used by the wearable equipment.
12. A calibration apparatus of an active noise reduction system of a wearable device, the active noise reduction system comprising: the audio playing module is used for playing the input audio signals; the sound collection module is used for collecting the audio signals played by the audio playing module or the audio signals played by the external playing module; the filter is used for filtering the audio signals acquired by the sound acquisition module to obtain noise reduction signals; an adaptive module for adjusting coefficients of the filter; characterized in that the calibration device comprises: the noise test signal playing module is used for starting the active noise reduction system, controlling the audio playing module to play a noise test signal and collecting the noise test signal through the sound collecting module;
a secondary path estimation module for calculating a secondary path estimate of the active noise reduction system;
The configuration module is used for stopping playing the noise test signal, playing environmental noise through the external playing module, and configuring initial parameters of the active noise reduction system and calibration coefficients preset by the filter, wherein the initial parameters comprise the secondary channel estimation;
The target coefficient acquisition module is used for controlling the audio playing module to play the noise reduction signal, acquiring a target coefficient of the filter, and the target coefficient is used for calibrating the filter.
13. A storage medium having stored thereon a computer program, which when executed by a processor performs the steps of the method according to any of claims 1 to 11.
14. A terminal comprising the calibration device of claim 12, or comprising a memory and a processor, the memory having stored thereon a computer program executable on the processor, characterized in that the processor executes the steps of the method of any of claims 1 to 11 when the computer program is executed.
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