Patent Application
20170365245
This disclosure generally relates to active noise control (ANC) systems, such as ANC systems deployed in headphones.
Active noise control involves cancelling unwanted noise by generating a substantially opposite signal often referred to as anti-noise.
In one aspect, this document describes a computer-implemented method that includes receiving a portion of a feedback signal of an active noise control (ANC) system, and processing the portion of the feedback signal using an adaptive line enhancer (ALE) filter to detect a tonal signature. The method also includes determining, by one or more processing devices, that the tonal signature represents an unstable condition, and responsive to determining that the tonal signature represents an unstable condition, generating one or more control signals for adjusting one or more parameters of the ANC system, to mitigate the unstable condition.
In another aspect, this document describes an active noise control (ANC) system that includes an error sensor configured to provide a feedback signal, and an instability detector. The instability detector includes an adaptive line enhancer (ALE) filter configured to process at least a portion of the feedback signal to detect a tonal signature, and a detection engine comprising one or more processing devices. The detection engine is configured to determine that the tonal signature represents an unstable condition, and responsive to determining that the tonal signature represents an unstable condition, generate one or more control signals for adjusting one or more parameters of the ANC system, to mitigate the unstable condition.
In another aspect, this document describes a machine-readable storage device having encoded thereon computer readable instructions for causing one or more processors to perform various operations. The operations include receiving a portion of a feedback signal of an active noise control (ANC) system, and processing the portion of the feedback signal using an adaptive line enhancer (ALE) filter to detect a tonal signature. The operations also include determining that the tonal signature represents an unstable condition, and responsive to determining that the tonal signature represents an unstable condition, generating one or more control signals for adjusting one or more parameters of the ANC system, to mitigate the unstable condition.
Implementations of the above aspects can include one or more of the following features.
The feedback signal can be obtained using an error sensor of the ANC system. The feedback signal can be processed by a digital bandpass filter to generate the portion of the feedback signal processed by the ALE filter. The ALE filter can be implemented as a single-tap infinite impulse response (IIR) filter. Determining that the tonal signature represents an unstable condition can include determining that the tonal signature includes components within a predetermined frequency range. The predetermined frequency range can be substantially between 1.5 KHz and 5 KHz or between 500 Hz and 2 KHz. A quantity indicative of a relative strength of the tonal signature in an output of an acoustic transducer of the ANC system can be computed, and a determination may be made that the tonal signature represents an unstable condition based on the quantity satisfying a threshold condition. Computing the quantity can include receiving a measure of residual error from the ALE filter, receiving a portion of a signal-of-interest to be output by the acoustic transducer, and computing the quantity as a ratio of a first quantity and a second quantity. The first quantity can be indicative of the energy of the tonal signature, and the second quantity can be indicative of the energy of a combination of the residual error and the portion of the signal-of-interest. The second quantity can also be indicative of the energy of a portion of a signal captured by a feedforward microphone of the ANC system. The one or more parameters being adjusted to mitigate the unstable condition can include at least one of: a gain associated with a filter applied to a feedback microphone of the ANC system, and a gain associated with a filter applied to a feedforward microphone of the ANC system. The ANC system can be deployed in a noise-reducing headphone. The one or more control signals can be configured to adjust one or more coefficients of an adaptive filter of the ANC system to compensate for changes to a transfer function of a secondary path of the ANC system.
Various implementations described herein may provide one or more of the following advantages. A low-complexity adaptive filter such as an adaptive line enhancer (ALE) may be used to quickly detect the presence of unstable condition in an active noise control (ANC) system without having to use expensive hardware. Responsive to such determination, the unstable condition can be mitigated early in the process. In some cases where the ANC system is deployed in noise cancelling headphones or earphones, such early mitigation may prevent the headphone or earphones from producing loud sounds that may be uncomfortable to the user. In some cases, the ability to detect and respond to unstable conditions may allow for design of more aggressive feedback or feedforward compensators that operate over a wider range of frequencies than would be otherwise possible.
Two or more of the features described in this disclosure, including those described in this summary section, may be combined to form implementations not specifically described herein.
The details of one or more implementations are set forth in the accompanying drawings and the description below. Other features, objects, and advantages will be apparent from the description and drawings, and from the claims.
This document describes technology that detects unstable conditions in an active noise control (ANC) system relatively quickly such that the unstable conditions may be mitigated before adversely affecting the performance of the ANC system. For example, when an ANC system is deployed in noise canceling headphones, certain unstable conditions, if not addressed quickly, can cause the headphones to generate a loud noise that is uncomfortable for the user. The technology described herein may allow for detecting an unstable condition using low complexity filters such as an adaptive line enhancer (ALE), and based on quantities computed over a small number of samples of an input signal. This in turn may allow for early detection of unstable conditions, which may then be mitigated before the performance of the ANC system is adversely affected. In some cases, this may enable better performance of the ANC system, for example, by facilitating realization of aggressive compensators that can operate over a wider range of frequencies.
Acoustic noise control systems are used for cancelling or reducing unwanted or unpleasant noise. For example, such noise control systems may be used in personal acoustic devices such as headsets, earphones, etc. to reduce the effect of ambient noise. Unless specified otherwise, the term headphone, as used in this document, includes various types of such personal acoustic devices such as headsets, earphones, earbuds, and hearing aids. Acoustic noise control can also be used in automotive or other transportation systems (e.g., in cars, trucks, buses, aircrafts, boats or other vehicles) to cancel or attenuate unwanted noise produced by, for example, mechanical vibrations or engine harmonics.
In some cases, Active Noise Control (ANC) systems can be used for attenuating or canceling unwanted noise. In some cases, an ANC system can include an electroacoustic or electromechanical system that can be configured to cancel at least some of the unwanted noise (often referred to as primary noise) based on the principle of superposition. This can be done by identifying an amplitude and phase of the primary noise and producing another signal (often referred to as an anti-noise signal) of about equal amplitude and opposite phase. An appropriate anti-noise signal combines with the primary noise such that both are substantially canceled at the location of an error sensor (e.g., canceled to within a specification or acceptable tolerance). In this regard, in the example implementations described herein, “canceling” noise may include reducing the “canceled” noise to a specified level or to within an acceptable tolerance, and does not require complete cancellation of all noise. ANC systems can be used in attenuating a wide range of noise signals, including, for example, broadband noise and/or low-frequency noise that may not be easily attenuated using passive noise control systems. In some cases, ANC systems provide feasible noise control mechanisms in terms of size, weight, volume, and cost.
In some implementations, the system 100 includes a reference sensor 110 that detects the noise from the noise source 105 and provides a signal to an ANC engine 120 (e.g., as a digital signal x(n)). The ANC engine 120 produces an anti-noise signal (e.g., as a digital signal y(n)) that is provided to a secondary source 125. The secondary source 125 produces a signal that cancels or reduces the effect of the primary noise. For example, when the primary noise is an acoustic signal, the secondary source 125 can be configured to produce an acoustic anti-noise that cancels or reduces the effect of the acoustic primary noise. Any cancellation error can be detected by an error sensor 115. The error sensor 115 provides a signal (e.g., as a digital signal e(n)) to the ANC engine 120 such that the ANC engine can modify the anti-noise producing process accordingly to reduce or eliminate the error. For example, the ANC engine 120 can include an adaptive filter, the coefficients of which can be adaptively changed based on variations in the primary noise.
The ANC engine 120 can be configured to process the signals detected by the reference sensor 110 and the error sensor 115 to produce a signal that is provided to the secondary source 125. The ANC engine 120 can be of various types. In some implementations, the ANC engine 120 is based on feed-forward control, in which the primary noise is sensed by the reference sensor 110 before the noise reaches a secondary source such as secondary source 125. In some implementations, the ANC engine 120 can be based on feedback control, where the ANC engine 120 cancels the primary noise based on the residual noise detected by the error sensor 115 and without the benefit of a reference sensor 110. In some implementations, both feed-forward and feedback control are used. The ANC engine 120 can be configured to control noise in various frequency bands. In some implementations, the ANC engine 120 can be configured to control broadband noise such as white noise. In some implementations, the ANC engine 120 can be configured to control narrow band noise such as harmonic noise from a vehicle engine.
In some implementations, the ANC engine 120 includes an adaptive digital filter, the coefficients of which can be adjusted based on, for example, the variations in the primary noise. In some implementations, the ANC engine is a digital system, where signals from the reference and error sensors (e.g., electroacoustic or electromechanical transducers) are sampled and processed using processing devices such as digital signal processors (DSP), microcontrollers or microprocessors. Such processing devices can be used to implement adaptive signal processing techniques used by the ANC engine 120.
In some implementations, an ANC system deployed in a headset can also be used to shape a frequency response of the signals passing through the headset. For instance, a feedback controller may be used to change an acoustic experience of having an earbud blocking the ear canal to one where ambient sounds (e.g., the user's own voice) sound more natural to the user. In some implementations, the headphone 150 can include a feature that may be referred to as an “aware mode” or “talk-through.” In such a mode, the external microphone 156 can be used to detect external sounds that the user might want to hear, and the active noise control engine 120 can be configured to pass such sounds through, for example, to be reproduced by the secondary source 125. In some cases, the external microphone used for the talk-through feature can be a microphone separate from the microphone 156. In some implementations, signals captured by multiple microphones can be used (e.g., using a beamforming process) to focus, for example, on the user's voice or another source of ambient sound. In some implementations, the active noise control engine 120 can be configured to implement the talk-through feature by allowing signals captured by the microphone 156 to pass to the secondary source 125 (or another acoustic transducer) without substantial signal processing. For example, the ANC engine 120 can be configured to pass a talk-through signal with only a small amount of amplification or a gain substantially equal to unity. In such cases, the talk-through system may be referred to as a “direct talk-through” system. Direct talk-through systems can be configured to use a band-pass filter to restrict the external sounds to voice-band or some other band of interest. In some implementations, the direct talk-through feature may be manually triggered, or automatically triggered by detection of a sound of interest, such as voice or an alarm.
In some implementations, the ANC engine 120 can be configured to process the talk-through signals, for example, to preserve the acoustic naturalness of the signals. This may be referred to as “ambient naturalness,” and can be accomplished, for example, through one or more filters disposed within the ANC engine 120. For example, if the ANC engine 120 includes both feedback and feed-forward noise cancellation circuits, either or both cancellation circuits may be modified to process the talk-through signals. As explained in U.S. Pat. No. 8,155,334, the entire content of which is incorporated herein by reference, a feed-forward filter implemented using a digital signal processor can be modified to provide talk-through by not cancelling at least a portion of the ambient noise. Other methods and systems for improving naturalness of talk-through signals are described in U.S. Pat. No. 8,798,283, the entire content of which is incorporated herein by reference.
In implementations where a headphone includes an aware mode, some conditions can lead to the onset of an unstable condition. For example, if the output of the secondary source 125 gets fed back to the external (or feedforward) microphone 156, and the ANC engine 120 passes the signal back to the secondary transducer (as typical in an aware mode), this can lead to a fast-deteriorating unstable condition that results in an objectionable sound emanating from the secondary transducer. This can be demonstrated, for example, by cupping a hand around a headphone to facilitate a feedback path between the secondary source 125 and the external microphone 156. Such a feedback path may be established during the use of the headphone, for example, if the user puts on a headgear (e.g., a head sock or winter hat) over the headphone.
In some implementations, the unstable condition can also occur, for example, due to changes in the transfer function of a secondary path 135 of the ANC system. This can happen, for example, if the acoustic path between the secondary source and the feedback microphone is changed in size or shape. The condition may be demonstrated, for example, by blocking the opening (e.g., using a finger or palm) through which sound emanates out of the headphone. In the case of a headphone having a nozzle with an acoustic passageway that acoustically couples a front cavity of an acoustic transducer to a user's ear canal, this condition may be referred to as a blocked-nozzle condition. This condition can result in practice, for example, during placement/removal of the headphone in the ear. This effect may be particularly observable in smaller headphones (e.g., in-ear earphones) or in-ear hearing aids, where the secondary path can change if the earphone or hearing-aid is moved while being worn. For example, moving an in-ear earphone or hearing aid can cause the volume of air in the corresponding secondary path to change, thereby causing the ANC system to be rendered unstable. In some cases, pressure fluctuations in the ambient air can also cause the ANC system to go unstable. For example, when the door or window of a vehicle (e.g., a bus door) is closed, an accompanying pressure change may cause an ANC system become unstable. Another example of pressure fluctuations that can result in an unstable condition is a significant change in the ambient pressure of air relative to normal atmospheric pressures at sea level.
Unless an unstable condition is quickly detected and addressed, the unstable condition may deteriorate quickly and potentially cause a loud audible feedback to be produced by the secondary source 125, which may be uncomfortable for the wearer. The technology described herein allows for detecting an unstable condition quickly (e.g., by processing a small number of samples, or on a sample-by-sample basis) and taking steps to mitigate the condition so that the unstable condition does not reach a stage where a loud audible feedback is produced. In some implementations, this may be done by processing feedback samples to detect a tonal signature indicative of an unstable condition, and determining a quantity that represents the strength of the tonal signature within the other signals emanating from the secondary source. For example, the strength of the tonal signature may be determined using a “quasi-SNR” quantity where the numerator represents the tonal signature, and the denominator represents the other signals emanating from the secondary source. This document refers to such a quantity as a “quasi-SNR” measure because unlike in a regular SNR, the signal-of-interest in the overall system (e.g., music, talk-through signal, etc.) is represented in the denominator.
In some implementations, the ANC engine 120 includes an instability detector 310 that can be configured to detect the presence of an unstable condition. The ANC system 120 also includes one or more compensators 315 that can be adjusted based on the output of the instability detector to mitigate any unstable condition detected by the instability detector 310. The output of the compensator 315 can be provided to a noise control circuit 320 that performs active noise cancellation on signals that are output through one or more acoustic transducers acting as the secondary source 125. In some implementations, a compensator 315 can be disposed between a microphone (e.g., an external microphone 156 or an internal microphone 158) and the instability detector 310. In some implementations, the compensator 315 can be adjusted to compensate for changes to the transfer function of a secondary path of the ANC system that could potentially be causing the instability. This can be done, for example, by a control signal generated by the instability detector 310 based on a feedback signal representing at least a portion of the signal provided to the secondary source 125. The signal paths corresponding to such feedback signals are represented by the dashed lines in
In some implementations, the instability detector 310 receives samples of signals obtained by the internal microphone 158 and detects the presence or absence of an unstable condition by processing the samples. For example, the instability detector 310 can be configured to detect a tonal signature of any unstable condition within a portion of the signal captured by the internal microphone 158, and calculate a quasi-SNR quantity that represents a relative strength of the tonal signature within a signal of interest associated with the system. This is illustrated using the block diagrams of
Referring now to
In some implementations, the signal of interest 405 includes a signal that is intended to be output by the secondary source 125. This can include, for example, a signal received from a source device 305 (as shown in
As shown in
Referring to
In some implementations, the instability detector 310 is configured to process the outputs of the one or more ALEs 415 and the signal of interest to generate the quasi-SNR quantity usable for detecting the presence of an unstable condition. This can be done, for example, by computing the relative strength of a tonal signature detected in the ALE output corresponding to the internal microphone to that of the combination of the other signals. In some implementations, the relative strength can be determined as a ratio of (i) a first quantity indicative of the energy of the tonal signature, to (ii) a second quantity indicative of the energy of a combination of the residual error and the portion of the signal-of-interest. The presence of an unstable condition can then be detected by comparing the ratio against a threshold. In some implementations, the instability detection may also be conditioned on the detected frequency 418 being within a predefined frequency range. In some implementations, an IIR filter used in a feedforward system can be slaved to the detected center frequency of an ALE for a feedback microphone (e.g., the internal microphone 158), thereby requiring a single ALE 415 in the instability detector 310.
For the configuration depicted in
wherein y(t) denotes the enhanced output 417, e(t) denotes the residual signal 416, and m(t) denotes the signal of interest. The operator dB(.) denotes conversion to decibel, the operator env(.) denotes envelope detection, and the operator delay(.) denotes a shift that may be needed for alignment of the various quantities. The comparison may be performed, for example, by a threshold detection engine 430, and the envelope detection may be performed, for example, by an envelope detector 420, both of which modules are depicted in
For the configuration depicted in
wherein the eff(t) denotes the residual feed-forward error 419. The equation (2) can be used, for example, in detecting an unstable condition for a headphone operating in the aware mode because the denominator includes a quantity derived from the signal captured by the external microphone 156.
Referring again to
Referring again to
In some implementations, the frequency response of the filter may also be adjusted, for example, to suppress the frequency or frequencies at which the unstable condition is detected. In some implementations, the compensator 315 can be configured to adjust the frequency response of the filter to compensate for changes to the transfer function of a secondary path of the ANC system that could potentially be causing the instability. Checking for changes to the transfer function between the secondary source and the error microphone can include, for example, detecting an instantaneous transfer function phase response corresponding to the instantaneous frequency 418 detected by the ALE 415. If the instantaneous phase response corresponds to a change within a given frequency range where an instability is expected, the feedback gain corresponding to that range may be adjusted to account for the instability. In some implementations, the instantaneous magnitude response of the transfer function may also be used, either as a standalone measure, or to corroborate a finding of a change in the instantaneous phase response. In some implementations, the instantaneous, single-frequency transfer function can be calculated using a demodulation process applied to signals from the source device 305 and the microphones. This can include low-pass filtering the signals using a filter having, for example, a 500 Hz roll-off frequency. In some cases, this can result in the calculated response being smooth for up to several-kHz, but still allow the compensator 315 to respond to rapid changes.
While
The compensator 315 can also be configured to process the signals captured by the microphones independently of the signal received from the instability detector. For example, a compensator 315 processing the signal captured by the external microphone 156 can be configured to amplify the frequencies that are suppressed when the ear is covered or blocked by the headphone, and/or to suppress the frequencies that are amplified when the ear is covered or blocked by the headphone.
In some cases, when a compensator mitigates an unstable condition at a particular frequency, the changes to the filter may cause instability at another frequency. Therefore, in the absence of the technology described herein, the range of frequencies over which unstable conditions are mitigated by the compensator may be limited. In some cases, this may result in a degraded performance for the ANC systems. For example, the resonance frequency for a particular headphone may be shifted to a lower frequency if a blocked-nozzle condition develops (e.g., from around 5 KHz to around 3 KHz). In such cases, it may be desirable for the compensator to operate over a larger frequency range. Because the technology described herein may facilitate detecting unstable conditions quickly (e.g., based on a small number of samples) and accurately, the technology can be leveraged to implement aggressive compensators that mitigate unstable conditions over a wide range of frequencies. In some implementations, information from the corresponding headphones for the two ears can be processed to reduce chances of false positives. For example, if the same (or substantially similar) stimulus is detected by each headphone, a determination may be made that the stimulus originates at an external source and is not due to a feedforward instability. This in turn may reduce the likelihood of false positives in detecting feedforward instability.
Operations of the process 800 also include processing the portion of the feedback signal using an ALE filter (820) to detect a tonal signature. In some implementations, the feedback signal may be preprocessed, for example, using a bandpass filter, to generate the portion of the feedback processed by the ALE filter. In some implementations, the ALE filter is implemented as a single tap adaptive IIR filter (or another low-order filter). For example, the ALE filter can be substantially similar to the filter depicted in
Operations of the process 800 can further include determining that the tonal signature represents an unstable condition (830). For example, the tonal signature representing an unstable condition can be a narrowband signal that lies within a particular frequency range. Therefore, a tonal signature may be determined to represent an unstable condition only if the tonal signature lies in the particular frequency range, and the relative strength of the tonal signature in the overall signal generated by the secondary source is above a threshold. In some implementations, the particular frequency range can be substantially between 1.5 KHz-5 KHz, or 500 Hz-2 KHz. In some implementations, the determination may be done by one or more processing devices (e.g., one or more processing devices of a threshold detection engine 430) disposed within the ANC system. For example, the determination can include computing a quantity (e.g., a quasi-SNR quantity, as described above) indicative of a relative strength of the tonal signature in an output of an acoustic transducer of the ANC system, and determining that the tonal signature represents an unstable condition if the quantity satisfies a threshold condition. In some implementations, the quantity can be computed based on a measure of residual error from the ALE filter and a portion of a signal-of-interest to be output by the acoustic transducer. For example, the quantity may be computed as a ratio of (i) a first quantity indicative of the energy of the tonal signature, to (ii) a second quantity indicative of the energy of a combination of the residual error and the portion of the signal-of-interest. In some implementations, where the ANC system is deployed in a headphone operating in an aware mode, the second quantity can include a component indicative of the energy of a portion of a signal captured by a feedforward microphone (e.g., an external microphone 156) of the ANC system.
Operations of the process 800 can also include generating one or more control signals for adjusting one or more parameters of the ANC system (840). This can be done responsive to determining that the tonal signature represents an unstable condition, and the one or more control signals can be configured to mitigate the unstable condition. In some implementations, the one or more parameters can include a gain or frequency response associated with a filter applied to a feedback microphone (e.g., the internal microphone 158) of the ANC system, and/or a gain or frequency response associated with a filter applied to a feedforward microphone (e.g., the external microphone 156) of the ANC system. In some implementations, the one or more parameters of the ANC system can be adjusted based on a severity of the instability. For example, a high count of quasi-SNR per sample can prompt a large reduction of the feedforward and/or feedback gains. On the other hand, if several instabilities are detected over a period of time, the feedforward and/or feedback gains can be reduced by a fixed amount until the headphone is power-cycled.
The functionality described herein, or portions thereof, and its various modifications (hereinafter “the functions”) can be implemented, at least in part, via a computer program product, e.g., a computer program tangibly embodied in an information carrier, such as one or more non-transitory machine-readable media or storage device, for execution by, or to control the operation of, one or more data processing apparatus, e.g., a programmable processor, a computer, multiple computers, and/or programmable logic components.
A computer program can be written in any form of programming language, including compiled or interpreted languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment. A computer program can be deployed to be executed on one computer or on multiple computers at one site or distributed across multiple sites and interconnected by a network.
Actions associated with implementing all or part of the functions can be performed by one or more programmable processors executing one or more computer programs to perform the functions of the calibration process. All or part of the functions can be implemented as, special purpose logic circuitry, e.g., an FPGA and/or an ASIC (application-specific integrated circuit). In some implementations, at least a portion of the functions may also be executed on a floating point or fixed point digital signal processor (DSP) such as the Super Harvard Architecture Single-Chip Computer (SHARC) developed by Analog Devices Inc, or an Advanced RISC Machine (ARM) processor.
Processors suitable for the execution of a computer program include, by way of example, both general and special purpose microprocessors, and any one or more processors of any kind of digital computer. Generally, a processor will receive instructions and data from a read-only memory or a random access memory or both. Components of a computer include a processor for executing instructions and one or more memory devices for storing instructions and data.
Other embodiments and applications not specifically described herein are also within the scope of the following claims. For example, the level of control on the instability mitigation can be tailored based on various parameters such as probability of detection, and target false positive and/or false negative rates. Elements of different implementations described herein may be combined to form other embodiments not specifically set forth above. Elements may be left out of the structures described herein without adversely affecting their operation. Furthermore, various separate elements may be combined into one or more individual elements to perform the functions described herein.
