阅读说明：本技术 用于有源噪声消除系统的风噪声抑制和方法 (Wind noise suppression and method for active noise cancellation systems ) 是由 芮立扬 G·肯南 于 2020-04-30 设计创作，主要内容包括：有源噪声消除(ANC)包括用于感测外部噪声并生成参考信号的参考传感器、用于感测噪声消除区中的噪声并生成误差信号的误差传感器、用于接收参考信号和误差信号并生成第一抗噪声信号以消除噪声消除区中的外部噪声的前馈ANC子系统、用于接收误差信号并生成第二抗噪声信号以消除消除区中的外部噪声的反馈ANC子系统、用于检测参考信号中是否存在风噪声并输出风噪声检测状态的风检测器、以及用于根据风噪声检测状态控制前馈ANC子系统和反馈ANC子系统的适配处理并且将第一与第二抗噪声信号混合以生成输出抗噪声信号的风处理机。(Active Noise Cancellation (ANC) includes a reference sensor for sensing external noise and generating a reference signal, an error sensor for sensing noise in a noise cancellation zone and generating an error signal, a feedforward ANC subsystem for receiving the reference signal and the error signal and generating a first anti-noise signal to cancel the external noise in the noise cancellation zone, a feedback ANC subsystem for receiving the error signal and generating a second anti-noise signal to cancel the external noise in the cancellation zone, a wind detector for detecting whether wind noise is present in the reference signal and outputting a wind noise detection state, and a wind processor for controlling adaptation processes of the feedforward ANC subsystem and the feedback ANC subsystem according to the wind noise detection state and mixing the first and second anti-noise signals to generate an output anti-noise signal.)

1. An active noise cancellation system comprising:

a reference sensor configured to generate a reference signal from external noise;

an error sensor configured to generate an error signal from sound sensed in the noise cancellation zone;

a feedforward noise cancellation subsystem configured to generate a first anti-noise signal using the reference signal and the error signal;

a feedback noise cancellation subsystem configured to generate a second anti-noise signal using the error signal;

a wind detection module configured to determine whether wind noise is present in the reference signal and output a wind noise detection state; and

a wind processor module configured to control the feedforward and feedback noise cancellation subsystems according to the wind noise detection state and to generate an output anti-noise signal using the first and second anti-noise signals.

2. The active noise cancellation system of claim 1, further comprising a first variable gain module configured to adjust a first gain of the first anti-noise signal and a second variable gain module configured to adjust a second gain of the second anti-noise signal, and wherein the wind processor module is configured to set the first gain and the second gain in response to the wind noise detection state.

3. The active noise cancellation system of claim 2, wherein the output anti-noise signal includes a first gain-adjusted anti-noise signal and a second gain-adjusted anti-noise signal.

4. The active noise cancellation system of claim 3, wherein the wind processor is further configured to transition between feedback adaptive noise cancellation and feedforward adaptive noise cancellation in response to a change in the wind noise detection state.

5. The active noise cancellation system of claim 1, wherein the wind processor module is configured to disable adaptive feed forward noise cancellation in response to detected wind.

6. The active noise cancellation system of claim 1, wherein the wind processor module is configured to disable adaptive feedback noise cancellation if wind noise is not present.

7. The active noise cancellation system of claim 1, wherein the wind detection module is configured to detect wind noise that is not correlated to ambient noise received in the noise cancellation zone.

8. The active noise cancellation system of claim 1, further comprising a processor and a memory storing program instructions for execution by the processor, and wherein the wind processor module comprises program instructions stored in the memory.

9. The active noise cancellation system of claim 1, further comprising a summer configured to combine the first anti-noise signal and the second anti-noise signal to generate the output anti-noise signal.

10. The active noise cancellation system of claim 1, wherein the active noise cancellation system comprises an active noise cancellation earpiece, earplug, or hearing aid.

11. A method, comprising:

generating a reference signal from external noise;

generating an error signal from the noise sensed in the noise cancellation zone;

generating a first anti-noise signal using the reference signal and the error signal using a feed-forward noise cancellation process;

generating a second anti-noise signal using the error signal using a feedback noise cancellation process;

determining whether wind noise exists in the reference signal and setting a corresponding wind noise detection state; and

controlling adaptation processes in the feedforward and feedback noise cancellation processes in accordance with the wind noise detection state and mixing the first anti-noise signal with the second anti-noise signal to generate an output anti-noise signal.

12. The method of claim 11, further comprising adjusting a first gain of the first anti-noise signal and a second gain of the second anti-noise signal in response to the wind noise detection state.

13. The method of claim 12, further comprising generating the output anti-noise signal by combining the first anti-noise signal and the second anti-noise signal after adjusting the first gain of the first anti-noise signal and the second gain of the second anti-noise signal.

14. The method of claim 13, further comprising detecting a change in the wind noise detection state and a transition between a feedback adaptive noise cancellation process and a feedforward adaptive noise cancellation process.

15. The method of claim 11, further comprising disabling adaptive feed forward noise cancellation if wind noise is detected.

16. The method of claim 11, further comprising disabling adaptive feedback noise cancellation if wind noise is not present.

17. The method of claim 11, wherein the wind noise is uncorrelated with ambient noise received in the noise cancellation zone.

18. The method of claim 11, wherein the adaptation process that controls the feed forward noise cancellation process is performed by a wind processor module of a digital signal processor.

19. The method of claim 11, further comprising combining the first anti-noise signal and the second anti-noise signal to generate the output anti-noise signal.

20. The method of claim 11, wherein the method is performed in an active noise cancellation earpiece, earplug, or hearing aid.

Technical Field

The present application relates generally to noise cancellation systems and methods, and more particularly, for example, to adaptive cancellation and/or suppression of wind noise in earphones (e.g., over-the-ear, and in-ear), earplugs, hearing aids, and other personal listening devices.

Background

Active Noise Cancellation (ANC) systems typically operate by: ambient noise is sensed by a reference microphone and a corresponding anti-noise signal that is approximately equal in magnitude but opposite in phase to the sensed ambient noise is generated. The ambient noise and the anti-noise signal acoustically cancel each other, allowing the user to hear only the desired audio signal. To achieve this effect, a low latency, programmable filter path from the reference microphone to the speaker outputting the anti-noise signal may be implemented. In operation, conventional anti-noise filtering systems may not completely remove all noise, leave residual noise and/or generate audible artifacts (audible artifacts) that may distract the user.

Unlike ambient noise, wind noise appears at the reference microphone due to local air turbulence and is uncorrelated with the ambient noise reaching the ear canal. Wind noise degrades ANC performance in at least two ways. First, wind noise typically passes through an adaptive filter and will be audible to the user. Second, the presence of wind noise may result in incorrect reference signals, anti-noise signals, and/or incorrect adaptation of the ANC filter.

In view of the foregoing, there is a continuing need for improved active noise cancellation systems and methods for headsets, earpieces, and other personal listening devices that can operate in windy environments.

Disclosure of Invention

Systems and methods for active noise cancellation in audio listening devices that may be used in windy environments are disclosed. In one or more embodiments, an active noise cancellation system includes: a reference sensor configured to sense ambient noise and generate a corresponding reference signal; an error sensor configured to sense noise in the noise cancellation zone and generate a corresponding error signal; a noise cancellation filter configured to receive the reference signal and the error signal and generate an anti-noise signal to cancel ambient noise in a cancellation zone; an adaptation module configured to receive a reference signal and an error signal and to adaptively adjust an anti-noise signal; and a wind noise detection module configured to receive the reference signal, detect a wind noise event, and selectively enable and disable the adaptation module in response to the wind noise event information. In some embodiments, the active noise cancellation system includes a wind detector module configured to detect the presence of wind noise in the reference signal, and a wind processor module configured to adjust signal gain and/or adaptation parameters to suppress the detected wind noise.

In various embodiments, an active noise cancellation system includes a reference sensor configured to generate a reference signal from external noise and an error sensor configured to generate an error signal from noise sensed in a noise cancellation zone. The feedforward noise cancellation subsystem is configured to generate a first anti-noise signal using the reference signal and the error signal, and the feedback noise cancellation subsystem is configured to generate a second anti-noise signal using the error signal. The wind detection module is configured to determine whether wind noise is present in the reference signal and output a wind detection state, and the wind processor module is configured to control the feedforward and feedback noise cancellation subsystems according to the wind detection state and generate an output anti-noise signal using the first and second anti-noise signals.

The active noise cancellation system may further include: a first variable gain module configured to adjust a first gain of the first anti-noise signal; and a second variable gain module configured to adjust a second gain of the second anti-noise signal. The wind processor module is configured to set the first gain and the second gain in response to a wind detection state. The output anti-noise signal may include a first anti-noise signal that is gain-adjusted by a first gain and a second anti-noise signal that is gain-adjusted by a second gain. The wind processor may be further configured to transition between feedback adaptive noise cancellation and feedforward adaptive noise cancellation in response to a change in the wind noise detection state. In some embodiments, the wind processor module is configured to disable adaptive feed forward noise cancellation in response to detected wind noise and disable adaptive feedback noise cancellation if wind noise is not detected.

The active noise cancellation system may include a processor and a memory storing program instructions for execution by the processor, and the wind processor module may include program instructions stored in the memory. The active noise cancellation system may also include a summer configured to combine the first anti-noise signal and the second anti-noise signal to generate an output anti-noise signal. In various embodiments, the active noise cancellation system may be implemented in an active noise cancellation earpiece, earplug, hearing aid, or other device.

In various embodiments, a method for suppressing wind noise in an active noise cancellation system includes: the method includes generating a reference signal from external noise, generating an error signal from noise sensed in a noise cancellation zone, generating a first anti-noise signal using the reference signal and the error signal using a feedforward noise cancellation process, and generating a second anti-noise signal using the error signal using a feedback noise cancellation process. The method also includes determining whether wind noise is present in the reference signal and setting a corresponding wind noise detection state, and controlling adaptation processes in the feedforward and feedback noise cancellation processes and mixing the first anti-noise signal with the second anti-noise signal to generate an output anti-noise signal according to the wind noise detection state.

The method may further include adjusting a first gain of the first anti-noise signal and/or a second gain of the second anti-noise signal in response to the wind noise detection state, and generating the output anti-noise signal by combining the first anti-noise signal and the second anti-noise signal after adjusting the first gain of the first anti-noise signal and/or the second gain of the second anti-noise signal. The method may further include detecting a change in a wind noise detection state and transitioning between a feedback adaptive noise cancellation process and a feedforward adaptive noise cancellation process, disabling adaptive feedforward noise cancellation if wind noise is detected, and/or disabling adaptive feedback noise cancellation if wind noise is not present.

In some embodiments, the adaptation process that controls the feed forward noise cancellation process is performed by a wind processor module of the digital signal processor. The method may also include combining the first anti-noise signal and the second anti-noise signal to generate an output anti-noise signal.

The scope of the invention is defined by the claims, which are incorporated into this section by reference. A more complete understanding of embodiments of the present disclosure will be afforded to those skilled in the art, as well as a realization of additional advantages thereof, by a consideration of the following detailed description. Reference will be made to the appended sheets of drawings which will first be described briefly.

Drawings

Aspects of the present disclosure and its advantages are better understood by referring to the following drawings and detailed description. It should be understood that like reference numerals are used to identify like elements illustrated in one or more of the figures, which are presented for purposes of illustrating embodiments of the present disclosure and not for purposes of limiting the embodiments of the present disclosure. The components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present disclosure.

Fig. 1 illustrates an active noise cancelling headset providing wind noise cancellation and/or suppression in accordance with one or more embodiments of the present disclosure.

Fig. 2 illustrates an active noise cancellation system including components that provide wind noise detection and processing in accordance with one or more embodiments of the present disclosure.

Fig. 3 illustrates a process for detecting and processing wind noise in an active noise cancellation system according to one or more embodiments of the present disclosure.

Fig. 4 illustrates an active noise cancellation system including noise event detection and processing components in accordance with one or more embodiments of the present disclosure.

Detailed Description

According to various embodiments, improved Active Noise Cancellation (ANC) systems and methods for cancelling and/or suppressing ambient and wind noise are disclosed. The headset or other personal listening device may include an Active Noise Cancellation (ANC) system to attenuate ambient noise. In a general arrangement, an ANC system includes a reference sensor (e.g., a microphone or other audio sensor), an adaptive filter, and an error sensor (e.g., a microphone or other audio sensor). The reference sensor senses ambient noise and generates a corresponding reference audio signal. The adaptive filter generates an anti-noise signal from the reference audio signal and the error signal and passes it to a speaker or other transducer to cancel the ambient sound at the listener's ear. An error sensor monitors the residual sound, providing feedback on the performance of the adaptive filter. The ANC system continuously evaluates the reference audio signal and the error signal and adaptively corrects the adaptive filter to achieve a better ambient noise attenuation effect.

Unlike ambient noise, wind noise occurs at the reference sensor due to local air turbulence. This wind noise is uncorrelated to the ambient noise heard by the listener and reduces ANC performance in at least two ways. First, wind noise may pass through the adaptive filter and be audible to the user. Second, wind noise may produce incorrect anti-noise, and the ANC filter may be incorrectly adapted. In various embodiments, a wind detector and wind event handler are provided to eliminate and/or suppress undesirable wind noise. When wind noise is not present, the wind event handler configures the ANC to adaptively filter the reference signal and generate anti-noise using both the reference signal and the error signal in a feed-forward arrangement. When wind noise is detected, the wind event handler configures the ANC to adaptively filter the error signal using the error signal in a feedback arrangement and generate anti-noise (without using a reference signal).

Example embodiments of an adaptive noise cancellation system for wind noise suppression will now be described with reference to the accompanying drawings. Fig. 1 illustrates an active noise cancelling headset providing wind noise cancellation and/or suppression in accordance with one or more embodiments of the present disclosure. Active Noise Cancellation (ANC) system 100 includes an audio device 110, such as a headphone, and an audio processing circuit 120, such as a Digital Signal Processor (DSP), a digital-to-analog converter (DAC) 130, an amplifier 132, a reference microphone 140, a speaker 150, an error microphone 162, and other components.

In operation, a listener can hear the external noise d (n) through the housing and components of the earpiece 110. To cancel the noise d (n), the reference microphone 140 senses external noise, such as ambient noise 180, producing a reference signal x (n) that is fed to the DSP 120 through an analog-to-digital converter (ADC) 142. The DSP 120 generates an anti-noise signal y (n) that is fed through the DAC 130 and amplifier 132 to the speaker 150 to generate anti-noise in the noise cancellation zone 160. The DSP 120 is configured to cancel and/or suppress the noise d (n) in the noise-canceling zone 160 by generating anti-noise that is equal in magnitude and opposite in phase to the noise d (n) in the noise-canceling zone 160. The resulting mix of noise and anti-noise is captured by an error microphone 162, which error microphone 162 generates an error signal e (n) to measure the effectiveness of noise cancellation. The error signal e (n) is fed to the DSP 120 through the ADC 164, and the DSP 120 adjusts the amplitude and phase of the anti-noise signal y (n) to minimize the error signal e (n) (e.g., drive the error signal e (n) to zero) within the cancellation zone 160.

In some embodiments, the speaker 150 may also generate desired audio (e.g., music) that is received by the error microphone 162 and removed from the error signal e (n) during processing by the DSP 120 (or other audio component). It will be understood that the embodiment of fig. 1 is one example of an active noise cancellation system, and that the systems and methods disclosed herein may be implemented with other adaptive noise cancellation implementations, including a reference microphone and an error microphone.

The reference microphone 140 may also generate audio signals associated with wind noise, such as audio signals generated from a wind 182 that may hit (hit) the reference microphone 140. In some implementations, the wind noise may be processed by standard ANC of the DSP 120 and played for the listener. In some embodiments, standard ANC processing of the DSP 120 may generate an anti-noise signal to cancel or suppress all or part of the wind noise. However, the wind noise picked up by the reference microphone 140 may not be correlated with the ambient noise 180 received at the error microphone 162 and/or the listener's ear canal, resulting in anti-noise artifacts that negatively impact the listening experience.

To cancel and/or suppress wind noise, the DSP 120 includes a wind detector and wind handler component 124, the wind handler component 124 configured to detect wind noise generated by the reference microphone 140 and manage processing to suppress the detected wind noise. DSP 120 may include one or more of a processor, microprocessor, programmable logic device, digital signal processor, or other logic device. The wind detector and wind processor component 124, as well as other ANC components and processes disclosed herein, may include software instructions stored in memory for execution by the DSP 120.

In various embodiments, the DSP 120 is configured to process the anti-noise signal through a feedforward anc (ffanc) subsystem and a feedback anc (fbanc) subsystem. The FFANC subsystem is configured to analyze both the reference signal x (n) and the error microphone signal e (n) to generate an anti-noise signal for noise cancellation. When wind noise is not present (e.g., when wind noise has not been detected), the FFANC subsystem is activated by wind detector and wind processor component 124. The FBANC subsystem predicts an anti-noise signal based on the error signal e (n) (e.g., the anti-noise signal may be based on the error signal e (n) without using the reference signal x (n)) and configured to suppress detected wind noise. The FBANC subsystem is activated by the wind detection and wind processor component 124 when wind noise is present (e.g., when wind noise has been detected).

Fig. 2 illustrates an example Active Noise Cancellation (ANC) system 200 that includes improved wind noise cancellation performance substantially free of undesirable audio artifacts when compared to conventional systems. The ANC system 200 senses ambient noise at an external reference microphone (e.g., microphone 140 of fig. 1) that generates a reference signal x (n). The ambient noise also passes through a noise path p (z), includes the housing and components of the listening device, and is received at an error microphone (e.g., error microphone 162) as d (n).

The ANC system 200 includes a feedforward ANC subsystem 210 and a feedback ANC subsystem 240 for generating an anti-noise signal to cancel d (n). The feedforward ANC subsystem 210 may be implemented as a filtered X least mean square (FxLMS) adaptive filter, or another adaptive feedforward approach. The feedforward ANC subsystem 210 adaptively generates the anti-noise signal y (n) from the reference signal x (n) through a digital filter 214. The anti-noise signal is output through the speaker and received at the error microphone through a secondary path s (n) 262 that includes a path from the filter 214 through the speaker to the error microphone.

The feed forward adaptation module 212 (e.g., LMS adaptive filter) updates the weights W based on the error signal e (n) measured by the error microphone and the reference signal x (n)_FF(z) (e.g., a set of filter coefficients for the digital filter 214 in the feedforward path). In the illustrated embodiment, reference signal x (n) utilizes a secondary path 216 that aligns the phases of reference signal x (n) and error signal e (n)The model of (2) is filtered. The feedforward adaptation module 212 then adaptively adjusts the filter coefficients/weights W_FF(z) to minimize the expected mean square error。

The feedback ANC subsystem 240 is configured to generate without using the reference microphone signal x (n) as an inputAnd is immune to noise signals, thereby avoiding many of the problems associated with feed forward wind noise suppression. The feedback ANC subsystem 240 predicts the ambient sound d (n) from the estimates of the error signal e (n) and the anti-noise signal y (n). The input signal x '(n), which is an estimate of the ambient sound d (n), is generated by combining the error signal e (n) and the filtered version of the estimated anti-noise signal y' (n) via an adder 250. Filter 248 pair secondary path(e.g., the electro-acoustic path between the digital filter 246 and the error microphone) to align the phase of the anti-noise signal y (n) with the error signal e (n). Input signal x' (n) is provided as an input to feedback digital filter 246 and utilizes a secondary path via filter 244Is filtered (to account for delays in the electro-acoustic secondary path) for input to the feedback adaptation block 242. The feedback adaptation module 242 receives the error signal e (n) and the filtered estimated ambient sound x' (n) and updates the weights W of the filter 246_FB(z) to minimize the expected mean square error (e.g., using a similar LMS update procedure as discussed above with reference to the feed-forward ANC subsystem 210). In some embodiments, digital filters 214 and 246 may be implemented as Infinite Impulse Response (IIR) or Finite Impulse Response (FIR) filters.

The ANC system 200 is also configured to suppress wind noise using both the feedforward ANC subsystem 210 and the feedback ANC subsystem 240. In one embodiment, the anti-noise y (n) is of G₁And G₂The feed forward digital filter 214 output of the gain factor and the output of the feedback digital filter 246 add (at adder 260). In one embodiment, the gain factor ranges between 0 and 1, where G₁And G₂The sum is approximately equal to 1.

The ANC system 200 also includes a wind detector 270 and a wind processor 272. The wind detector 270 receives the reference microphone signal x (n) asThe presence of wind noise in the reference microphone signal is input and detected. Wind processor 272 is triggered by the output of wind detector 270 (e.g., an output flag indicating whether wind noise has been detected) and controls feed-forward ANC adaptation and feedback ANC adaptation (via feed-forward adaptation module 212 and feedback adaptation module 242, respectively) and gain value G₁And G₂. In some embodiments, the wind detector 270 outputs a detection status indicating the detection or absence of wind noise. The wind detector 270 may be implemented using a variety of techniques, for example, based on power spectrum methods and related methods as are known in the art. Other wind noise detection components and processes may be used that can detect the presence or absence of wind noise in an input signal and produce an output indicative of at least two states: (i) wind noise is detected and (ii) wind noise is not detected.

In some embodiments, WIND NOISE DETECTION may be performed in accordance with the WIND NOISE DETECTION system and method disclosed in co-pending U.S. application serial No. 16/399,961, entitled "WIND NOISE DETECTION SYSTEM AND METHODS," filed concurrently with this application and incorporated by reference herein in its entirety. For example, the wind noise detector may be configured to receive a plurality of audio input signals from a plurality of reference microphones and output a plurality of wind noise detection flags, including a single channel wind noise detection flag and a cross-channel wind noise detection flag, each wind noise detection flag indicating the presence or absence of wind noise, and the fusion smoothing module is configured to receive the plurality of wind noise detection flags and generate an output wind noise detection flag. The wind processor configures the ANC system to generate an anti-noise signal according to an output wind noise detection signature as disclosed herein.

In various embodiments, the wind noise detector includes a single channel detector operable to receive a single audio channel and generate a single channel wind noise detection flag. The single channel detector may be operable to compare the single audio channel to a wind spectrum model that includes a mean and standard deviation of power ratios of a portion of the frequency components and a spectral slope (spread slope). The wind noise detector may be configured to: clearing the flag if the average of the power ratios is less than the threshold average and the standard deviation is greater than the threshold standard deviation (e.g., when it is determined that wind noise is not present); and setting a flag if the spectral slope is greater than a predetermined threshold spectral slope (e.g., when wind noise is determined to be present). The wind noise detector may also include a cross-channel detector operable to calculate an autocorrelation and a cross-correlation between two or more audio channels and, for example, set a flag if the autocorrelation is less than the cross-correlation.

The wind processor 272 is configured to control the ANC system 200 in response to the wind detector 270 output. For example, the wind processor 272 may be configured to selectively activate/deactivate the feed-forward ANC subsystem 210 and the feedback ANC subsystem 240. For example, when wind noise is detected, the wind processor 272 may freeze (freeze) the feedforward adaptation (e.g., via the feedforward adaptation module 212) and enable adaptation of the feedback ANC subsystem 240 (e.g., by the feedback adaptation module 242) to generate the anti-noise y (n). In this state, the gain value G₁Set to zero (no gain) and gain value G₂Set to one. When wind noise is not detected, the wind processor 272 may freeze the feedback adaptation (e.g., via the feedback adaptation module 242) and enable adaptation of the feedforward ANC subsystem 210 (e.g., by the feedback adaptation module 242) to generate anti-noise. In this state, the gain value G₂Is set to zero and has a gain value G₁Is set to one.

In accordance with one or more embodiments, the wind detector 270 is configured to set a wind noise detection flag to indicate whether wind noise has been detected, and the wind processor 272 is operable to configure the ANC system 200 in response to a change in the wind noise detection flag. If the wind noise detection flag changes from no wind noise present to a wind noise detected state, the wind handler 272 freezes the feedforward adaptation module 212 and changes G to₁Change from 1 to 0 and G₂Changing from 0 to 1 to convert the anti-noise from the feedforward ANC subsystem 210 to the feedback ANC subsystem 240. In response to the error signal e (n), the feedback adaptation module 242 is activated to adaptively remove wind noise. Different fading functions may be used to increase/decrease G during the transition₁And G₂To limit unwanted audio artifacts (e.g., to avoid/reduce audible clicks (click) and pops (pop)). In various embodiments, the fading functions may include linear, exponential, sinusoidal, and logarithmic functions and may be implemented in a sample-based or frame-based approach.

When the wind detector 270 changes the wind noise detection flag from detecting wind noise to not having wind noise, the wind handler 272 freezes the feedback adaptation module 242, coupling G to G₂Change from 1 to 0 and G₁Changing from 0 to 1 to convert the anti-noise signal from the feedback ANC subsystem 240 to the feedforward ANC subsystem 210. One or more fading functions may be used to gradually increase/decrease the gain value G₁And a gain value G₂To smooth the transition and limit unwanted audio artifacts. In response to the reference microphone signal x (n) and the error signal e (n), the feedforward adaptation module 212 is activated to adaptively generate the anti-noise signal.

An embodiment of the operation of the active noise cancellation system 200 of fig. 2 will now be described with reference to the process 300 of fig. 3. The process 300 begins operation using a feed-forward ANC subsystem. In step 302, the feedback adaptation is frozen and the gain is adjusted for the feedforward path and the feedback path in step 304 to pass the anti-noise received from the feedforward ANC subsystem to the speaker for noise cancellation. In step 306, feed forward adaptive noise cancellation is performed to cancel the sensed ambient noise.

The wind detector monitors the reference signal to detect wind noise. In step 308, if wind noise has not been detected, the ANC system continues the feed forward adaptive noise cancellation process. If wind noise is detected, the process proceeds to step 310 to switch the ANC system to use the feedback ANC subsystem to generate the anti-noise signal until wind noise is no longer detected. In step 310, the feed forward adaptation process is frozen. In step 312, the gain values of the feedforward and feedback paths are adjusted to deliver the anti-noise signal generated by the feedback ANC subsystem to the speaker for noise cancellation. In step 314, feedback adaptation is performed to adaptively generate the anti-noise signal. The process continues until wind noise is no longer detected (step 316), and then processing continues in step 302 to transition back to the feed-forward ANC processing mode.

In another embodiment, the feedback noise cancellation subsystem of the active noise cancellation system 200 of fig. 2 remains "on" during operation. The wind handler 272 is configured to turn the feedforward noise cancellation subsystem "on" and "off" based on the results from the wind detector 270. When wind noise is detected, the feedforward path is "closed" and an anti-noise signal is generated from the output of the feedback path. When wind noise is not detected, the feedforward path is "opened" and the anti-noise signal is generated as a superposition of the output from the feedforward path and the output from the feedback path.

The systems and methods disclosed herein may be implemented in various audio devices, such as earphones, headphones, cell phones, smart phones, tablets, and hearing aids. Embodiments may be applied to both adaptive ANC and fixed ANC. In some embodiments, the teachings of the present disclosure may be applied to other sources of local reference microphone noise (such as noise caused by temporary reference microphone faults). For example, as illustrated in fig. 4, the active noise cancellation system 400 includes a noise event detector module 470 and a noise event handler module 472 to transition between the feedforward adaptive noise cancellation subsystem 410 and the feedback adaptive noise cancellation subsystem 440 based on the state of the detected event. In some embodiments, the noise event may include detecting a noise event that is not correlated to an ambient noise condition. In operation, the anti-noise signal generated by each subsystem is represented by a gain value G₁And G₂Gain adjustments are made and combined at summer block 460.

The foregoing disclosure is not intended to limit the disclosure to the precise forms or particular fields of use disclosed. It is therefore contemplated that various alternative embodiments and/or modifications (whether explicitly described or implied herein) to the present disclosure are possible in light of the present disclosure. Having thus described examples of the present disclosure, persons of ordinary skill in the art will recognize that changes may be made in form and detail without departing from the scope of the disclosure. Accordingly, the disclosure is limited only by the claims.