Patent Publication Number: US-11386881-B2

Title: Active noise cancelling based on leakage profile

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application claims priority to and the benefit of U.S. Provisional Patent Application No. 63/001,205 filed Mar. 27, 2020, entitled “ACTIVE NOISE CANCELLATION SYSTEMS AND METHODS”, which is hereby incorporated by reference in its entirety. 
    
    
     TECHNICAL FIELD 
     The present application relates generally to noise cancelling systems and methods, and more specifically, for example, to active noise cancelling (ANC) systems and methods for use in headphones (e.g., circum-aural, supra-aural and in-ear types), earbuds, hearing aids, and other personal listening devices. 
     BACKGROUND 
     Active noise cancellation systems commonly operate by sensing noise through a reference microphone and generating a corresponding anti-noise signal that is approximately equal in magnitude, but opposite in phase, to the sensed noise. The noise and anti-noise signal cancel each other acoustically, allowing the user to hear only a desired audio signal. To achieve this effect, a low-latency, filter path from the reference microphone to a loudspeaker that outputs the anti-noise signal may be implemented. In operation, conventional anti-noise filtering systems do not completely cancel all noise, leaving residual noise and/or generating audible artefacts that may be distracting to the user. In some implementations, the user may desire to selectively listen to certain external noises, which can affect ANC adaption and other processing. Performance of these active noise cancellation systems may be further degraded due to leakage, which may vary from person-to-person and device-to-device due to the various ways that a listening devices couples to the user&#39;s anatomy. 
     In view of the foregoing, there is a continued need for improved active noise cancellation systems and methods for headphones, earbuds and other personal listening devices. 
     SUMMARY 
     Systems and methods are disclosed for improved active noise cancellation in personal listening devices. In various embodiments, for example, active noise cancellation systems and methods provide improved leakage control and/or improved transparency processing. 
     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 a noise cancellation zone and generate a corresponding error signal, and a noise cancellation path comprising a noise cancellation filter and an adaptive gain filter. The noise cancellation path, such as a feedforward ANC path, is configured to receive the reference signal and generate a corresponding anti-noise signal to cancel the ambient noise at an eardrum reference point. An adaptation engine is configured to receive the reference signal and the error signal and control various components of the active noise cancellation system, including adaptively adjusting weights of the noise cancellation filter and/or the adaptive gain filter. 
     In some embodiments, the adaptation engine comprises adaptive gain control logic configured to update the adaptive gain filter. Inputs to the adaptive gain control logic may be conditioned using programmable filters operable to protect against low frequency transients and/or high frequency distractors in the environmental noise. The programmable filters may include a low pass filter that filters out high frequencies determined to be in a range that creates constructive interference between the cancellation zone and the eardrum reference point, and/or a high pass filter that filters out low frequencies determined to be in a range that cannot be heard by a user of the noise cancellation system. The adaptation engine may be tuned to cancel noise at the eardrum reference point, using the error signal sensed in the noise cancellation zone. 
     In various embodiments, the adaptation engine includes leakage control logic configured to track the adaptive gain value of the adaptive gain filter and select optimal leakage control settings based on the adaptive gain value. In some embodiments, the adaptation engine is configured with a plurality of leakage profiles adapted for a corresponding plurality of leakage conditions relating to the positioning and/or fit of the personal listening device with respect to the user&#39;s anatomy. For example, leakage profiles may include modeling for a tight seal between a personal listening device and the user&#39;s ear structure, and modeling of one or more leakage scenarios associated with improper headset positions and/or leaky fit conditions. In various embodiments, the adaptation engine is configured to track the adaptive gain value and switch between leakage profiles based on changes to the adaptive gain value of the adaptive gain filter. 
     In various embodiments, the ANC system further includes a second processing path configured to generate a transparency output for the user representing ambient noise detected by the reference microphone. The second processing path is configured to process the transparency output in parallel with a feedforward processing path of the ANC system. In some embodiments, the transparency output path includes an adaptive transparency processing filter configured to generate the transparency output in accordance with one or more conditions, including but not limited to, settings associated with an active leakage profile. The adaptation engine or other control module is configured to detect a user input selection of a listening mode associated with a transparency mode and/or ANC mode and selectively enable or disable the transparency output. 
     In one or more embodiments, a method includes receiving a reference signal from a first sensor, the reference signal representing ambient noise, processing the reference signal through a noise cancellation path comprising an adaptive noise cancellation filter and a van adaptive gain filter, to generate an anti-noise signal, receiving an error signal from a second sensor, the error signal representing noise in a noise cancellation zone and adaptively adjusting the adaptive noise cancellation filter in response to the reference signal, the error signal and an adaptive gain control process to cancel the ambient noise at an eardrum reference point. 
     The method may further include conditioning inputs to the adaptive gain control process using programmable filters to protect against low frequency transients and/or high frequency distractors in the external noise. The conditioning may further include low pass filtering out high frequencies determined to be in a range that (i) creates constructive interference between the cancellation zone and the eardrum reference point and (ii) differs in noise cancellation performance between the cancellation zone and the eardrum reference point, and/or high pass filtering out low frequencies determined to be in a range that cannot be heard by a user. The method may further include tuning the noise cancellation path to cancel noise at the eardrum reference point, using the error signal sensed in the noise cancellation zone. 
     In various embodiments, the method further includes a leakage control process including tracking the adaptive gain value of an adaptive gain filter and selecting leakage control settings based on the adaptive gain value. In some embodiments, the leakage control process further includes configuring a plurality of leakage profiles adapted for a corresponding plurality of leakage conditions relating to the positioning and/or fit of the listening device with respect to the user&#39;s anatomy. The configuring of the plurality of leakage profiles may include modeling various headset positions and/or fit conditions and defining associated leakage profiles. The method may further include tracking the adaptive gain value and switching between leakage profiles based on changes to the adaptive gain value of the adaptive gain filter. 
     In various embodiments, the method further includes processing a transparency processing path for the user representing ambient noise detected by a reference microphone, in parallel with a feedforward processing path of the ANC system. In some embodiments, the method includes updating filter values of a transparency processing filter and generating the transparency output in accordance with one or more conditions, including but not limited to, settings associated with an active leakage profile. The method further includes detecting and/or receiving a user input selection of a listening mode associated with a transparency mode and/or ANC mode and selectively enabling and/or disabling the transparency output. 
     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 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 of one or more embodiments. Reference will be made to the appended sheets of drawings that will first be described briefly. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Aspects of the disclosure and their advantages can be better understood with reference to the following drawings and the detailed description that follows. It should be appreciated that like reference numerals are used to identify like elements illustrated in one or more of the figures, wherein showings therein are for purposes of illustrating embodiments of the present disclosure and not for purposes of limiting the same. 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 cancellation device, in accordance with one or more embodiments of the present disclosure. 
         FIG. 2  illustrates an active noise cancellation system, including an adaptive gain filter, profile switching and parallel transparency processing, in accordance with one or more embodiments of the present disclosure. 
         FIGS. 3A, 3B, 3C and 3D  illustrate ear coupling of a personal listening device, in accordance with one or more embodiments of the present disclosure. 
         FIGS. 4A and 4B  illustrate example adaptive gain control tuning and use implementations, in accordance with one or more embodiments. 
         FIG. 5A  is a flow diagram illustrating an example process for creating leakage profiles, in accordance with one or more embodiments. 
         FIG. 5B  is a flow diagram illustrating an example process for gain adjusted profile switching, in accordance with one or more embodiments. 
         FIG. 6  is a state diagram illustrating an example profile switching process, in accordance with one or more embodiment. 
         FIG. 7  illustrates an example implementation of a hybrid ANC system, in accordance with one or more embodiments. 
     
    
    
     DETAILED DESCRIPTION 
     In accordance with various embodiments, improved active noise cancellation (ANC) systems and methods are disclosed. An ANC system for a headphones, earbuds or other personal listening devices may include a noise sensing reference microphone for sensing ambient noise external to the personal listening device, an error microphone for sensing an acoustic mixture of the noise and anti-noise generated by the ANC system, and a low latency signal processing sub-system that generates the anti-noise to cancel the sensed ambient noise. The signal processing sub-system may be configured to adapt the anti-noise signal in real-time to the ambient noise, the coupling of the personal listening device with respect to the user, user-selectable modes and other factors to achieve consistent noise cancellation performance. In various embodiments, the systems and methods disclosed herein improve cancellation of ambient noise under various ear coupling and leakage scenarios, improve processing of ambient noise in a transparency mode that passes through some or all of the ambient noise to the user, and reduce related adaptation artefacts perceptible by the user. 
     It is recognized that high leakage can result in breakdown of ANC performance. For example, a feedback ANC path tracks and adapts to an error microphone signal, which may typically provide a good measure of ANC performance at the user&#39;s ear drum. However, in the presence of higher leakage, the loudspeaker may not be physically able to push enough air to achieve desired performance at the ear drum. The present disclosure addresses these and other leakage issues by having fixed ANC profiles tuned for different leakage scenarios. The leakage is tracked by tracking the gain value of an adaptive gain control block, which is then used to select an appropriate leakage profile. 
     Improved adaptive systems and methods disclosed herein include an adaptive gain filter in a feedforward path to generate a robust anti-noise signal. An adaptation engine is configured to receive the reference signal and the error signal and control various components of the active noise cancellation system, including adaptively adjusting weights of a feedforward adaptive noise cancellation filter and/or the adaptive gain filter. In various embodiments, leakage control logic is configured to track parameters related to the adaptive gain filter and to provide improved leakage control. 
     In various embodiments, the adaptation engine includes leakage control logic configured to track adaptive gain parameters of the adaptive gain filter and select optimal leakage control settings based on the adaptive gain value. In some embodiments, the adaptation engine is configured with a plurality of pre-configured user leakage profiles adapted for a corresponding plurality of leakage conditions relating to the positioning and/or fit of the listening device with respect to the user&#39;s anatomy. The user leakage profiles may include modeling for a tight seal between a personal listening device and the user&#39;s ear, and modeling of one or more leakage paths associated with leaky device positions and/or fit conditions. In various embodiments, the adaptation engine is configured to track one or more adaptive gain parameters and automatically switch between user leakage profiles based on changes detected in the adaptive gain parameters for optimal filtering. 
     In various embodiments, the ANC system further includes a second feedforward processing path configured to generate a transparency output. A transparency mode may be selected by the user to allow certain ambient noise to pass through the system for playback by the personal listening device and may be used with and/or without enablement of ANC processing. This transparency processing path is configured to process the transparency output in parallel with a feedforward processing path of the ANC system. In some embodiments, the transparency processing path includes an adaptive transparency filter configured to generate the transparency output in accordance with one or more conditions, including but not limited to, settings associated with an active leakage profile. The adaptation engine and/or other control logic is configured to detect a user input selection of a listening mode associated with a transparency mode and/or ANC mode and selectively enable or disable the transparency output. 
     Example embodiments of active noise cancelling systems of the present disclosure will now be described with reference to the figures. Referring to  FIG. 1 , an active noise cancelling system  100  includes a personal listening device  110  and audio processing components, which may include a low latency engine (LLE)  120 , a digital to analog converter (DAC)  130 , an amplifier  132 , a reference audio sensor  140 , a loudspeaker  150 , an error sensor  162 , and/or other components. 
     In operation, a listener may hear external noise d(n), which may pass through the housing and components of the personal listening device  110 . To cancel the noise d(n), the reference audio sensor  140  senses the external noise, producing a reference signal x(n) which is fed through an analog-to-digital converter (ADC)  142  to the LLE  120 . The LLE  120  may include hardware and/or software configured to generate an anti-noise signal y(n), which is fed through the DAC  130  and the amplifier  132  to the loudspeaker  150  to generate anti-noise in a noise cancellation zone  160 . The noise d(n) will be cancelled in the noise cancellation zone  160  when the anti-noise is equal in magnitude and opposite in phase to the noise d(n) in the noise cancellation zone  160 . The resulting mixture of noise and anti-noise is captured by the error sensor  162  which generates an error signal e(n) to measure the effectiveness of the noise cancellation. The error signal e(n) is fed through ADC  164  to the LLE  120 , which adapts the anti-noise signal y(n) to minimize the error signal e(n) within the cancellation zone  162  (e.g., drive the error signal e(n) to zero). In some embodiments, the loudspeaker  150  may also generate desired audio (e.g., music) which is received by the error sensor  162  and removed from the error signal e(n) during processing. 
     In various embodiments, the personal listening device  110  may include headphones (e.g., circum-aural, supra-aural and in-ear types), earbuds, hearing aids, and other personal listening devices. The personal listening device  110  may be a standalone device, such as a hearing aid, or be implemented as an audio listening device connected (e.g., physically and/or wirelessly) to one or more external devices, such as a computer (e.g., desktop, laptop, notebook, tablet), mobile phone, audio playback device (e.g., an MP3 player), video game system, or another device. The reference audio sensor  140  and the error sensor  162  may comprises one or more audio sensors, transducers, microphones or other components configured to detect a sound and convert the detected sound into an electrical audio signal. 
     The LLE  120  may include a single sample processor, digital signal processor, a controller, a central processing unit with program instructions stored in memory, and/or other logic device configured to perform one or more of the processes disclosed herein. The LLE  120  may include programmed logic and/or hardware components for causing the LLE  120  to perform certain processes including ANC processing (e.g., through ANC logic  122 ), profile switching (e.g., through profile switching logic  124 ), detection of ear coupling status, such as leakage (e.g., ear coupling detection logic  126 ), and transparency mode enablement and disablement (e.g., transparency logic  128 ). The LLE  120  may receive instructions, such as ANC and/or transparency mode selection, from user controls  170 , which may include one or more physical buttons, sliders, dials or other physical input components, a touchscreen with associated graphical user interface, or other user input device, component or logic. 
     It will be appreciated 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 active noise cancelling implementations that include a reference microphone and an error microphone. It will further be appreciated that the embodiment of  FIG. 1  may be used with additional components in various embodiments, including audio playback components for receiving and generating a playback signal for output (e.g., music, audio from a voice conference) through the loudspeaker  150 . 
     Referring to  FIG. 2 , example embodiments of ANC processing including ear coupling detection, profile switching, adaptive leakage compensation, and improved transparency signal processing will now be described. An active noise cancelling system  200  is configured to sense ambient noise at a reference sensor, such as an external microphone  212  (e.g., reference audio sensor  140  of  FIG. 1 ), which produces an external noise signal, x(n). The ambient noise also passes through a noise path (e.g., a primary path P(z)), which may include the housing and components of the personal listening device and is received at an error sensor  234  (e.g., error microphone  162 ). As used herein, a primary path P(z) represents a transfer function modeling the acoustic path between the reference sensor  212  and the error sensor  234 . 
     The ANC system  200  includes a feedforward path configured to generate the anti-noise signal from the received external noise signal x(n), including a decimator  214  configured to down-sample the external noise signal x(n) for processing by the ANC system  200  and a feedforward adaptive filter  216  (W ff (z)) configured to adaptively estimate the primary path P(z) to produce an anti-noise signal y(n) for cancelling the external noise signal (e.g., d(n)). In various embodiments, the adaptive filter(s) of the present embodiment may be implemented using a least mean square (LMS) process, a filtered LMS (FxLMS) process, an infinite impulse response filter, a finite impulse response, and other filter types as known in the art. 
     The anti-noise signal y(n) is gain adjusted by adaptive gain filter  218  and mixed (at block  220 ) with and/or further modified by a playback signal  222  (e.g., voice communications in a VoIP call, music, recorded voice, audio accompanying a video, etc.), a transparency signal generated by an adaptive transparency filter  290  ((B AI (z)), and/or an error signal generated by an feedback adaptive filter  270  ((W fb (z)) to generate an output signal. The adaptive transparency filter  290  adapts to the reference signal in parallel to generate a transparency signal for playback through the loudspeaker  230  to allow the user to hear all or part of the ambient noise when transparency is enabled. The output signal is up-sampled by interpolator  224  for output to a loudspeaker  230 . The adaptation engine may further adapt the playback signal (from playback  222 ) using an adaptive playback compensation filter  223 . In one or more embodiments, the playback compensation filter  223  is an equalizer that adapts the playback signal (e.g., gain adjust) based on a detected leakage scenario. 
     The error sensor  234  receives a mix of the output signal, including desired audio (e.g., a playback signal, an ambient inclusion signal from a transparency processing path) and the anti-noise signal, and the external noise d(n) through the primary path P(z). The playback signal  222  (and transparency signal if transparency mode is active) is adjusted to account for the secondary path through adaptive filter  272  and removed from the error signal at block  274 . As used herein, a secondary path S(z) represents a transfer function modeling the electrical path (e.g., D/A, A/D, etc.) and acoustic path between the loudspeaker and the error sensor. The residual error is down-sampled for processing by the ANC system  200  through decimator  276  and provided as an input to feedback adaptive filter  270 , which outputs an error correction signal to minimize the residual error. 
     In the illustrated embodiment, the adaptation engine  280  receives the residual error signal, filtered through a filter  278  (G(z)) that models the transfer function between the loudspeaker  230  and the error sensor  234 , and a copy of the reference signal, which is filtered through an estimate of the secondary path  291  and a signal conditioning filter  292  (H(z)). 
     The ANC system  200  further includes an adaptation engine  280 , which includes logical components for adaptive gain control (ADG)  282 , ear coupling and profile switching  284  and transparency management  286 . In various embodiments, the ADG  282  is configured to minimize wide-band fluctuations in the anti-noise path, the ear coupling and profile switching  284  is configured to continually track and compensate for various ear coupling and leakage scenarios and switch to an appropriate filter profile to optimize ANC performance, and the transparency management  286  is configured to adapt transparency performance in the parallel transparency path. In some embodiments, the ear coupling and profile switching  284  tracks current gain parameters from adaptive gain control  218  and modifies the feedforward processing at one or more adaptive filters in the feedforward path to accommodate the current leakage scenario. 
     In one or more embodiments, the hybrid ANC system  200  is tuned to achieve certain noise cancellation performance. For example, in the feedforward path, the adaptive filters  216  and  218  are pre-tuned and then adapted during operation based on the received audio signal from reference sensor  212  to maximize the noise cancellation. In some embodiments, the tuning of the ANC system  200  may be based in a tight seal setup between the personal listening device and the user&#39;s ear, such that there is little to no leakage. If there is more leakage (e.g., ear coupling between personal listening device and ear isn&#39;t consistent with the modeled tuning), then less low frequency sounds may be sensed and the adaptive gain control  218  will adapt by increasing the gain. It is further recognized that a detected increase in gain on the feedforward path generally corresponds to less coupling and more leakage than expected. In some embodiments, an adaptive gain filter may be placed on the feedback path (see, e.g.,  FIG. 7 ) and monitored to detect coupling status and leakage. 
     Generally, the adaptation engine  280  includes logic for detecting, tracking and adapting to user-related and ambient conditions. User-related conditions may include, for example, tracking the gain adaptation to determine leakage mechanics, and modifying filter parameters in accordance with the determined leakage mechanics. Ambient conditions may include, for example, classifying ambient conditions (e.g., using a neural network classifier) detected through the reference sensor and optimizing filter performance in view of the classified ambient conditions. For example, known ambient conditions that include low frequency noise and/or speech can be modeled and optimized when classified. 
     Embodiments incorporating ear coupling detection and profile switching will now be described in further detail with reference to  FIG. 3A  through  FIG. 7 . Referring to  FIGS. 3A-D , a personal listening device, such as a wireless earbud  310 , is adapted to fit into an ear  320  of a user  300 . In operation, the wireless earbud  310  is operable to communicate wirelessly with a host system, such as mobile device  330 . The wireless earbud  310  is designed to be inserted into the user&#39;s ear canal  322  (or adjacent thereto) where the audio output from the wireless earbud  310  is sensed at the user&#39;s ear drum  324 . The personal listening device  310  includes a wireless transceiver for transmitting and receiving communications (e.g., audio streams) between the wireless earbud  310  and the mobile device  330 . 
     The user  300  will insert and remove the wireless earbud  310  into and from, respectively, the user&#39;s ear  320  as desired to listen to audio from the mobile device  330 . During this process, the wireless earbud  310  passes between a first position  314  in the open air to a second position  316  where the wireless earbud  310  is securely positioned in the ear  320 . In various embodiments, the wireless earbud  310  includes a soft tip (e.g., silicon, memory foam) that is designed to conform to the shape of the ear to create a tight seal that controls leakage. However, in practice when the wireless earbud  310  is positioned in the second position  316 , one or more gaps  326  and/or loose couplings/seals may be formed between the wireless earbud  310  and the anatomy of the user&#39;s ear  320  resulting in leakage. 
     Small variations in coupling are expected in practice as a user inserts and removes the wireless earbuds, which can be addressed through the adaptive gain control filter. However, larger gaps  326  may be formed that result in a leaky condition that cannot be accounted for with a gain adjustment, for example, due to the user&#39;s particular anatomy, the positioning of the wireless earbud  310  (e.g., a misalignment of the earbud relative to the ear, improper insertion depth, etc.), the size and shape of the wireless earbud  310 , changes to the shape of the earbud due to use, the user not recognizing when proper coupling is achieved and/or other factors. 
     The wireless earbud  310  includes an ANC system  312  to cancel ambient noise and/or passthrough certain ambient noise in a transparency mode. During operation, the adaptive components of the ANC system  312  adapt to optimize ANC performance. In various embodiments, the ANC system  312  includes adaptive gain control filter (e.g., adaptive gain filter  218 ) and adaptive gain control logic (e.g., ADG  282 ) to adjust the gain of the anti-noise signal to optimize cancellation. It is observed that the gain parameters of the adaptive gain control filter correlate to the level of leakage due to the position and/or fit of the wireless earbud  310  in the user&#39;s ear  320 . The ADG  282  tracks one or more gain parameters to determine a current gain applied to the anti-noise signal to identify a leakage scenario. 
     The correlation between gain and leakage conditions can be modeled, for example, by testing position and fit scenarios using a dummy head and optimizing ANC parameters for the detected leakage conditions, by testing people in the general population, by modeling the parameters of the ANC system, and/or other methods. It is observed that for a sample of the population of potential users, leakage scenarios often fall within two or three clusters, and in most cases, four or five clusters may be sufficient for acceptable performance. These clusters or other groupings can be used to define leakage profiles including adaptive filters tuned for the leakage scenario. Because leakage corresponding to the gain is known, filters in the feedforward path (e.g., W ff (z)), feedback path (e.g., W fb (z)), transparency path ((e.g., B AI (z)) and/or playback path ((e.g., S PL (z)), for example, can be switched to certain pre-tuned filters representing leakage scenarios based on the detected gain. 
     In some embodiments, the gain value may be used to detect other conditions such as an open-air condition detected during insertion or removal activities and used to trigger a change in an operation of the wireless earbud  310 , such as entering a low power mode, adjusting the output volume, and activating or disabling certain functions. 
     Referring to  FIG. 4A , an embodiment of an adaptive LMS system  422  is disclosed. The adaptive LMS system  422  continuously updates the feedforward ANC filter  402  coefficients to adjust for variations in the coupling paths. The input to the LMS system may be conditioned using a programmable filter B G (z), which is designed to protect against low frequency transients in the environments. Referring to  FIG. 4B , an embodiment of an adaptive gain (ADG) subsystem  400  is disclosed. An adaptive gain control logic  420  continuously updates an adjustable gain filter  404  to adjust for variations in the coupling paths. The inputs to the ADG  420  may be conditioned using a programmable filter B G (z) (e.g., programmable filter  408  and programmable filter  410 ), which is designed to protect against low frequency transients and high frequencies distractors in the environment. In some embodiments, the filter B G (z) may comprise a low pass filter and/or a band pass filter that further filters out very low frequencies (e.g., &lt;20 Hz that cannot be heard out of a loudspeaker). 
     As previously discussed, the physical geometries and person-to-person fit variations of the personal listening device can affect noise cancellation performance. For example, the shape of the outer ear and length of the ear canal can alter the acoustic transfer functions of interest in an ANC system. In some embodiments, an ANC system in a personal listening device (e.g., the system of  FIG. 1 ) uses a noise sensing reference microphone, an error microphone, and a DSP sub-system that generates the appropriate anti-noise to cancel the noise field as measured by the error microphone. This results in a cancellation zone where the degree of cancellation is maximized at the error microphone location and degrades inversely proportional to the wavelength. As a result, the cancellation performance at the eardrum (which is roughly 25 mm away from the error microphone) drops significantly for higher frequencies (lower wavelengths) leading to loss of cancellation bandwidth as perceived by the user of the noise cancelling system. The embodiments of  FIGS. 4A-B  address these and other issues by maximizing the cancellation bandwidth at the eardrum during the tuning stage and formulating an adaptive approach that uses the error microphone to adapt to user specific characteristics during operation. 
     For the purposes of this embodiment, let the error microphone location be termed as ERP (Error Reference Point) and the ear-drum location be termed as DRP (Drum Reference Point). For ANC systems tuned at the DRP, the error microphone is a good indicator of low frequency cancellation at DRP and hence a robust error correcting signal can be derived from a low-passed version of the error microphone signal. This correcting signal may then be used to adapt a gain in the anti-noise signal path. 
     To maximize cancellation, an ideal placement of an error microphone would be at the eardrum, but that location is not practical for many consumer devices. Thus, the ERP is used to provide a practical signal that is roughly indicative of the cancellation performance at the DRP. The adaptive algorithm attempts to minimize the ERP signal which results in (i) diminished cancellation at high frequency signals at the DRP, and (ii) higher possibility of hiss sounding artefacts due to constructive interference of high frequencies at the DRP. In conventional approaches, adaptive algorithms are employed that use the transfer function from ERP to DRP. These approaches have many drawbacks including that the transfer function estimation is inaccurate at high frequencies, low estimation accuracy can affect the broad band cancellation performance and cause transitory hiss levels, high computational costs, and difficulty to tune and calibrate for all use conditions making deployment impractical for many devices. The embodiments of  FIGS. 4A-B  provide a computationally inexpensive approach that overcomes many of the drawbacks of conventional systems, is easy to tune, for example by measuring certain transfer functions during system design and is self-calibrating. 
       FIG. 4A  illustrates a calibration and tuning arrangement for the adaptive gain subsystem. In this arrangement, the ANC filter  402  is optimized to cancel noise at the DRP during an initial tuning stage. In one embodiment, the device is placed on a head and torso simulator which has a second error microphone at the DRP. P E2D (z), S E2D (z) model the ERP to DRP transfer functions in the denoted acoustic paths. The system can then be optimized using least mean squares block  422  to perform ANC tuning to derive an optimum W DRP (Z), based on the error signal, e′(n). Tuning in this manner helps achieving extended cancellation bandwidth and better performance in high frequency bands. In various embodiments, the device is placed in various position (e.g., secure fit, misaligned, improper insertion depth, etc.), fit (e.g., different head and ear anatomies), configuration (e.g., removable tips on an earbud), and wear scenarios to tune ANC performance for different leakage conditions. In various embodiments, the various scenarios may be grouped by associated adaptive gain values to create profiles for optimizing ANC performance for various leakage scenarios. 
     As illustrated in  FIG. 4B , the adaptive algorithm is set-up to continuously update a gain element  404 , G, that empowers the system to adjust for variations in the various coupling paths. In some embodiments, the signal is low pass filtered and gain adjusted for good low frequency cancellation. The inputs to the adaptive algorithms may be conditioned using a programmable filter, B G (z), which is programmed such that the ERP signal can mimic the cancellation performance at DRP. Additionally, B G (z), can be programmed to optimize performance during low frequency transients and high frequency distractors in the environment. It will be appreciated that the embodiments of  FIGS. 4A-B  are example implementations, and that the approaches disclosed therein can be modified for adaptive versions of feedback, feedforward and hybrid ANC solutions. 
     Referring to  FIGS. 5A and 5B , methods for operating the ANC systems (e.g., the systems of  FIGS. 1-4B  and  FIG. 7 ) to detect ear coupling using adaptive gain control parameters and select among available leakage profiles will now be described, in accordance with one or more embodiments. A configuration process  500  begins in step  502  by estimating transfer functions for a primary path P(z) and secondary path S(z) for a personal listening device across a population range and using different device customizations (e.g., different sized tips for an earbud). In step  504 , a model of leakage behavior for the device is generated, which may include one or more gain parameters and coefficients for one or more tuned adaptive filters. In step  506 , the process acquires data for supervisory detectors of the adaptation engine and determines tuning parameters. In some embodiments, a fixed number of profiles is generated (e.g., four profiles), representing variations in coupling between the personal listening device and the person&#39;s ear or head. The profiles may be selected to cover a range of leakage factors and/or a range of common personal listening device configurations and positions/fits, such as a tight coupling configuration, an open air (or highly leaky) configuration and intermediate leaky scenarios. 
     In step  508 , gain and threshold values for the different leakage scenarios are determined. In one embodiment, a profile representing a tight coupling between the personal listening device and the user&#39;s ear/head may be associated with a gain value and a threshold that may be used to trigger a change in profile. For example, when the gain value is above a first predetermined threshold, the profile switches to a second profile associated with a second (e.g., higher) gain factor. The second profile may have an upper threshold, above the which the profile switches to a third profile associated with a third (e.g., higher) gain factor. The second profile may also have a lower threshold, below which the profile switches back to the first profile. Additional profiles are defined in a similar manner with a gain value associated with the tuned leakage profile and a threshold range in which the filter provides acceptable performance (e.g., as determined by system requirements). In one embodiment, the gain ranges define a range of ANC performance that meets or exceed the performance standards for the personal listening device. For example, as a gain value deviates more from the profile gain value, the performance degrades and a new profile, defined by a new gain value and upper and lower thresholds is defined and tuned. 
     A method  550  for operating an ANC system comprises, in step  552 , tracking a current profile state, including a gain value and upper and lower thresholds, as available, for the current profile. In step  554 , the method  550  tracks the gain parameters of the adaptive gain controller in the feedforward path. In step  556 , the tracked gain parameters are compared to the current threshold values to determine whether there has been a change in the leakage profile. If the tracked gain value is higher than the current upper threshold or lower than a lower threshold, then the process switches to the appropriate profile. In step  558 , the parameters for the adaptive filters of the ANC system are updated to implement the current leakage profile. 
     Referring to  FIG. 6 , an example profile switching process  600  will be described in further detail, in accordance with one or more embodiments. The profile switching process  600  switches between four pre-defined profiles, numbered 1-4 in the illustrated embodiment. A first profile (e.g., Profile  1 ) is tuned for the tightest seal, where coupling is the highest, and the fourth profile (e.g., Profile  4 ) is tuned for a leaky scenario, such as where the device is substantially out of position. The remaining two profiles cover intermediate leakage scenarios. It will be appreciated that although four profiles are used in the illustrated embodiment, the number of profiles used may be more or less in a particular implementation. 
     In various embodiments, each profile is tuned for a particular gain value/leakage scenario and includes a high (H) and low (L) threshold value, defining a range of operation for each profile. When the detected gain is within the high (H) and low (L) threshold values of a profile, that profile will be active. Together, the threshold ranges for the pre-defined profiles span a range of gain values that may be encountered during use. In some embodiments, each profile is tuned to provide acceptable ANC performance around a baseline gain value, and the threshold values are defined to fall within a range of gain values that produce acceptable ANC performance for the tuned profile. 
     The profile switching process  600  starts by loading the parameters associated with profile  2  at step  602 . Control moves to step  614 , where the ANC system processes the anti-noise signal using profile  2 . The ANC system includes an adaptive gain filter in the feedforward path, which converges on a current gain value. The current gain is tracked and compared to an upper threshold T 2 , H and a lower threshold T 2 , L. The process state remains at step  614  while the gain is within the threshold range. If the gain falls below the lower threshold (T 2 , L), then profile  1  is loaded in step  612 , and control moves to step  610  to process anti-noise signal using profile  1  while the gain is less than an upper threshold (e.g., gain is less than or equal to T 1 , H). If the gain exceeds the upper threshold T 1 , H, then control passes to step  602 , the profile  2  is loaded and control passes to step  614  as previously discussed. 
     As step  614 , if the gain value exceeds the threshold upper limit (e.g., T 2 , H), then control passes to step  616  to load profile  3 , and control passes to step  618 , which performs ANC processing while the adaptive gain value is between a lower threshold limit T 3 , L and an upper threshold limit T 3 , H. If the gain is lower than the lower threshold limit T 3 , L, then control passes back to step  602  to load profile  2 . If the gain exceeds the higher threshold limit T 3 , H, then control passes to step  606 , where profile  6  is loaded, and then to step  620  where ANC processing using profile  4  will continue while the gain exceeds the lower threshold limit T 4 , L. If the gain falls below the lower threshold T 4 , L, then control passes back to step  616  to load profile  3  for ANC processing. 
     Referring to  FIG. 7 , an example implementation of a low latency hybrid ANC system  700  that may be used to implement one or more embodiments of the present disclosure will now be described. The hybrid ANC system  700  includes a reference microphone  702  and an error microphone  704  that convert sensed sounds into electronic analog signals. The reference microphone signal is converted to digital through analog-to-digital converter  706 , and the error microphone signal is converted to digital through analog-to-digital converter  708 . The microphones may include any device that senses sound waves and converts the sensed sound into electronic signals, such as a piezoelectric microphone, a microelectromechanical system microphone, audio transducer or similar device. In various embodiments, the hybrid ANC system may include one or more additional microphones, the microphones may include digital microphones that generate digital audio signals (e.g., eliminating the requirement of a separate analog-to-digital converter), and/or other modifications may be made consistent with the teachings of the present disclosure. 
     Hardware decimation unit  710  receives and downsamples the digital audio signals for processing by the ANC system. In the illustrated embodiment, the reference microphone signal is downsampled through a low latency decimation circuitry  712 , and the error microphone signal is downsampled through a low latency decimation circuitry  714 , and the signals are passed to a low latency router  716 , which routes the signals to various components of the hybrid ANC system  700  for processing. 
     In the illustrated embodiment, the hybrid ANC system  700  includes a low latency engine  720  that includes a feedforward ANC path, a parallel transparency path, and a feedback ANC path. The low latency engine  720  may be implemented in hardware, software or a combination of hardware and software. In some embodiments, the low latency engine  720  may be implemented as a single sample processor, a digital signal processor, a controller, a processor and memory storing instructions, and/or other logic device capable of low latency ANC processing described herein. As illustrated, the feedforward path includes a processing profile  722  comprising tuning and other parameters for generating an anti-noise signal from the reference signal, optional finite impulse response filters  724  and an adaptive gain component  726 . 
     A feedback path receives the error microphone signal and is configured to remove the playback signal (e.g., at component  742 ), which is filtered by secondary path filter  740  to account for secondary path effects. The feedback path further includes a plurality of BiQuads  744  (e.g., 12 BiQuads) configured to implement an infinite impulse response filter, and a gain component  746 . 
     The low latency engine  720  also includes a transparency signal processing path that receives the reference microphone signal, adaptively filters the reference microphone signal (e.g., through transparency processing components  732 ), and applies a gain  734 . In the illustrated embodiment, the transparency processing components run in parallel with the ANC processing and can be run with ANC enabled or disabled. The outputs of the feedforward path, feedback path and transparency path (if transparency mode is activated) are combined at mixing component  730  to generate an anti-noise signal. A low latency router  770  routes signals between the low latency engine, a hardware interpolation unit  780 , which is adapted to upsample the anti-noise signal for output, and an adaptation engine  750 . The hardware interpolation unit  780  includes low latency circuitry  782  for upsampling the anti-noise signal, a high quality upsampling circuitry  784  configured to receive a playback signal and generate a high-quality audio signal for output. The upsampled anti-noise signal and playback signal are combined at component  786 , fed to a digital to analog converter and amplifier  790 , which drives the output (e.g., for output through a loudspeaker). 
     The hardware interpolation unit  780  further includes a downsampler  788  for feeding the playback signal into the low latency engine  720  and adaptation engine  750  for further processing (e.g., removal of the playback signal from a received error microphone signal). 
     The adaptation engine  750  supervises the ANC processing and controls one or more components of the low latency engine  720  during operation to optimize ANC performance. The adaptation engine  750  may be implemented using a single sample processor, a numerical processing unit, a digital signal processor or other logic device and/or processing system. In the illustrated embodiment, the adaptation engine  750  includes components for adaptive secondary path processing  752 , an estimated secondary path filter  754 , adaptive profile processing  756  and profile selection  758 . The adaptation engine  750  may be configured to provide adaptive leakage compensation by tracking and compensating for leakage differences (e.g., by selectively switching profiles). In various embodiments, the adaptation engine  750  may include other processing components and control, such as howling control, wind control, ambient control, and other control logic. In some embodiments, additional detectors may be included (e.g., howling detector, wind detector, etc.) to provide input to one or more detectors, and the control elements may provide compensation for detected conditions by modifying the adaptation profile, one or more parameters of an adaptive filter (e.g., gain control to for howling compensation). 
     The hybrid ANC system  700  receives the audio playback from a separate device via an audio interface  760  such as I 2 S, PCM, or other interface protocol. The received playback signal is processed by audio processing components  762 , which may include an audio codec and other components configured to modify the playback signal for output. 
     The foregoing disclosure is not intended to limit the present disclosure to the precise forms or particular fields of use disclosed. As such, it is contemplated that various alternate embodiments and/or modifications to the present disclosure, whether explicitly described or implied herein, are possible in light of the disclosure. Having thus described embodiments 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 present disclosure. Thus, the present disclosure is limited only by the claims.