Patent Publication Number: US-2022232310-A1

Title: Wearable audio device with inner microphone adaptive noise reduction

Description:
PRIORITY CLAIM 
     This continuation application claims priority to co-pending U.S. application Ser. No. 16/999,353, entitled WEARABLE AUDIO DEVICE WITH INNER MICROPHONE ADAPTIVE NOISE REDUCTION, filed on Aug. 21, 2020, the contents of which are hereby incorporated by reference. 
    
    
     TECHNICAL FIELD 
     This disclosure generally relates to wearable audio devices. More particularly, the disclosure relates to wearable audio devices that enhance the user&#39;s speech signal by employing adaptive noise reduction on an inner microphone. 
     BACKGROUND 
     Wearable audio devices such as headphones commonly provide for two way communication, in which the device can both output audio and capture user speech signals. To capture speech, one or more microphones are generally located somewhere on the device. Depending on the form factor of the wearable audio device, different types and arrangements of microphones may be utilized. For example, in over-ear headphones, a boom microphone may be deployed that sits near the user&#39;s mouth. In other cases, such as with in-ear devices, microphones may be integrated within an earbud proximate the user&#39;s ear. Because the location of the microphone is farther away from the user&#39;s mouth with in-ear devices, accurately capturing user voice signals can be more technically challenging. 
     SUMMARY 
     All examples and features mentioned below can be combined in any technically possible way. 
     Systems and approaches are disclosed that adaptively enhance in internal microphone on a wearable audio device. Some implementations include an external microphone configured to be acoustically coupled to an environment outside an ear canal of a user; an inner microphone configured to be acoustically coupled to an environment inside the ear canal of the user; and an adaptive noise cancelation system configured to process an internal signal captured by the inner microphone and generate a noise reduced internal signal, wherein the noise reduced internal signal is adaptively generated in response to an external signal captured by the external microphone. 
     In additional particular implementations, a method for processing signals associated with a wearable audio device includes: capturing an external signal with an external microphone configured to be acoustically coupled to an environment outside an ear canal of a user; capturing an internal signal with an inner microphone configured to be acoustically coupled to an environment inside the ear canal of the user; and processing the internal signal captured by the inner microphone to generate a noise reduced internal signal, wherein the noise reduced internal signal is adaptively generated in response to the external signal captured by the external microphone. 
     A further implementation includes wearable two-way communication audio device, having: an external microphone configured to be acoustically coupled to an environment outside an ear canal of a user; an inner microphone configured to be acoustically coupled to an environment inside the ear canal of the user; an external processing system that processes signals from the external microphone and generates a processed external signal; an internal processing system that processes signals from the inner microphone and generates a processed internal signal; and a mixer that mixes the processed external signal with the processed internal signal to generate a mixed signal, wherein a mixing ratio of the processed external signal and the processed internal signal is based on a detected speech of the user and an amount of detected external noise. 
     In particular implementations, a method for processing signals associated with a wearable audio device includes: capturing an external signal with an external microphone configured to be acoustically coupled to an environment outside an ear canal of a user; capturing an internal signal with an inner microphone configured to be acoustically coupled to an environment inside the ear canal of the user; processing signals from the external microphone to generate a processed external signal; processing signals from the inner microphone to generate a processed internal signal; and mixing the processed external signal with the processed internal signal to generate a mixed signal, wherein a mixing ratio of the processed external signal and the processed internal signal is based on a detected speech of the user and an amount of detected external noise. 
     Implementations may include one of the following features, or any combination thereof. 
     In some cases, an adaptive noise cancellation system is configured to generate the noise reduced internal signal by: inputting the external signal; continuously calculating a set of noise cancellation parameters in response to the external signal; establishing a current set of noise cancelation parameters in response to a detection of speech by the user; and utilizing the current set of noise cancellation parameters to process the internal signal. 
     In particular implementations, the adaptive noise cancelation system is further configured to: in response to a determination that the user is no longer speaking: cease utilization of the current set of noise cancellation parameters to process the internal signal; and continuously calculate the set of noise cancellation parameters in response to the external signal. 
     In some cases, the detection of speech is detected with a voice activity detector (VAD). 
     In certain aspects, the wearable audio device includes an accelerometer that generates an accelerometer signal, wherein the adaptive noise cancelation system is configured to mix the accelerometer signal with the noise reduced internal signal to enhance frequency responses above approximately 2.5 kilohertz. (kHz) to approximately 3.0 kHz. 
     In some implementations, the set of noise cancellation parameters comprise a set of filter coefficients. 
     In various cases, the wearable audio device further includes: a second adaptive noise cancelation system configured to generate a noise reduced external signal by reducing noise in the external signal; and a mixer that selectively mixes the noise reduced external signal with the noise reduced internal signal to generate a mixed signal. 
     In certain cases, the mixer includes a voice activity detector (VAD) input that signals the user is speaking; and a noise detection input that signals a presence of environmental noise. 
     In some cases, the mixed signal primarily includes the noise reduced internal signal in response to a detection that the user is speaking and environmental noise is present. 
     In other cases, the mixed signal primarily includes the noise reduced external signal in response to a detection that no environmental noise is present. 
     In certain implementations, the wearable audio device includes an accelerometer that generates an accelerometer signal to the mixer, wherein the accelerometer signal is selectively mixed with the noise reduced internal signal to provide an enhanced response for frequencies above approximately 2.5 kilohertz (kHz) to approximately 3.0 kHz. 
     In some cases, the accelerometer signal is further utilized by the VAD to detect whether the user is speaking. 
     In particular implementations, the mixed signal is further processed using a short time spectral amplitude process. 
     In some implementations, the wearable audio device further includes an equalizer that processes the mixed signal based on equalizer settings that are determined in response to an amount of the noise reduced external signal and an amount of the noise reduced internal signal present in the mixed signal. 
     In certain cases, the wearable audio device further includes: a first equalizer configured to process the noise reduced external signal prior to input to the mixer, and a second equalizer configured to process the noise reduced internal signal prior to input to the mixer. 
     In certain implementations, in response to a detection that the user is speaking and the noise reduced external signal is unavailable due to a predetermined amount of environmental noise: optionally processing the noise reduced internal signal with a bandwidth extension signal extractor to generate high frequency components and mixing the high frequency components with the noise reduced internal signal. 
     In other cases, in response to a detection that the user is speaking and a predetermined amount of environmental noise is detected: processing an external microphone signal with a high pass filter to obtain high frequency components and mixing the high frequency components with the noise reduced internal signal to generate the mixed signal. 
     In other cases, the VAD compares a first output from an internal microphone VAD with a second output from an external microphone VAD to detect a failure condition. 
     In various implementations, the internal signal and external signal are processed according to a method that includes: outputting an audio signal based on the noise reduced external signal in response to no detection of speech by the user; continuously calculating a set of noise cancellation parameters based on the external signal; establishing a current set of noise cancellation parameters in response to a detection of speech by the user, utilizing the current set of noise cancellation parameters to process the internal signal to generate the noise reduced internal signal; supplying the noise reduced external signal and the noise reduced internal signal to the mixer, mixing the noise reduced external signal and the noise reduced internal signal, wherein the mixing is based on an amount of environmental noise detected; and outputting the audio signal based on the mixed signal. 
     In some cases, the method further includes, in response to a determination that the user is no longer speaking, ceasing utilization of the current set of noise cancellation parameters to process the internal signal; continuously calculating the set of noise cancellation parameters based on the external signal; and outputting the audio signal based on the noise reduced external signal. 
     In some cases, the mixing ratio substantially comprises the processed internal signal in response to detected speech of the user and detected external noise; and substantially comprises the processed external signal in response to no detected external noise. 
     In various cases, the internal processing system generates a noise reduced internal signal that is adaptively generated in response to the signals captured by the external microphone, and the external processing system includes a beamformer and an adaptive canceler. 
     In certain embodiments, a VAD processor detects speech of the user and the VAD processor inputs signals from an internal microphone VAD and an external microphone VAD and compares the signals to detect error conditions. 
     In some cases, a wind sensor detects external noise and the external processing system comprises a high pass filter that only passes high frequency components of the external microphone signals to the mixer when external noise is detected by the wind detector. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a block diagram depicting an example wearable audio device according to various disclosed implementations. 
         FIG. 2  is a block diagram depicting an inner microphone signal processing system according to various implementations. 
         FIG. 3  is a block diagram depicting of a hybrid microphone processing system according to various additional implementations. 
         FIG. 4  is a block diagram of an additional aspect to the system of  FIG. 3  that incorporates a bandwidth extension signal extractor according to various additional implementations. 
         FIG. 5  is a block diagram of an additional aspect to the system of  FIG. 3  that incorporates a high pass filter according to various additional implementations. 
         FIG. 6  is a block diagram of an additional aspect to the system of  FIG. 3  that incorporates and external and internal VAD according to various additional implementations. 
     
    
    
     It is noted that the drawings of the various implementations are not necessarily to scale. The drawings are intended to depict only typical aspects of the disclosure, and therefore should not be considered as limiting the scope of the implementations. In the drawings, like numbering represents like elements between the drawings. 
     DETAILED DESCRIPTION 
     This disclosure is based, at least in part, on the realization that an internal signal captured from an inner microphone within a wearable audio device can be adaptively processed and utilized for communicating the user&#39;s voice when external environmental noise exists. Furthermore, the adaptive processing can be integrated into a hybrid system that selectively utilizes and/or mixes a processed internal signal with a processed external signal. 
     Aspects and implementations disclosed herein may be applicable to a wide variety of wearable audio devices in various form factors, but are generally directed to devices having at least one inner microphone that is substantially shielded from environmental noise (i.e., acoustically coupled to an environment inside the ear canal of the user) and at least one external microphone substantially exposed to environmental noise (i.e., acoustically coupled to an environment outside the ear canal of the user). Further, various implementations are directed to wearable audio devices that support two-way communications, and may for example include in-ear devices, over-ear devices, and near-ear devices. Form factors may include, e.g., earbuds, headphones, hearing assist devices, and wearables. Further configurations may include headphones with either one or two earpieces, over-the-head headphones, behind-the neck headphones, in-the-ear or behind-the-ear hearing aids, wireless headsets (i.e., earsets), audio eyeglasses, single earphones or pairs of earphones, as well as hats, helmets, clothing or any other physical configuration incorporating one or two earpieces to enable audio communications and/or ear protection. Further, what is disclosed herein is applicable to wearable audio devices that are wirelessly connected to other devices, that are connected to other devices through electrically and/or optically conductive cabling, or that are not connected to any other device, at all. 
     It should be noted that although specific implementations of wearable audio devices are presented with some degree of detail, such presentations of specific implementations are intended to facilitate understanding through provision of examples and should not be taken as limiting either the scope of disclosure or the scope of claim coverage. 
       FIG. 1  is a block diagram of an example of an in-ear wearable audio device  10  having two earpieces  12 A and  12 B, each configured to direct sound towards an ear of a user. (Reference numbers appended with an “A” or a “B” indicate a correspondence of the identified feature with a particular one of the two earpieces. The letter indicators are however omitted from the following discussion for simplicity, e.g., earpiece  12  refers to either or both earpiece  12 A and earpiece  12 B.) Each earpiece  12  includes a casing  14  that defines a cavity  16  that contains an electroacoustic transducer  28  for outputting audio signals to the user. In addition, at least one inner microphone  18  is also disposed within cavity  16 . In implementations where wearable audio device  10  is ear-mountable, an ear coupling  20  (e.g., an ear tip or ear cushion) attached to the casing  14  surrounds an opening to the cavity  16 . A passage  22  is formed through the ear coupling  20  and communicates with the opening to the cavity  16 . In various implementations, one or more outer microphones  24  are disposed on the casing in a manner that permits acoustic coupling to the environment external to the casing  12 . 
     Audio output by the transducer  28  and speech capture by the microphones  18 ,  24  within each earpiece is controlled by an audio processing system  30 . Audio processing system  30  may be integrated into one or both earpieces  12 , or be implemented by an external system. In the case where audio processing system  30  is implemented by an external system, each earpiece  12  may be coupled to the audio processing system  30  either in a wired or wireless configuration. In various implementations, audio processing system  30  may include hardware, firmware and/or software to provide various features to support operations of the wearable audio device  10 , including. e.g., providing a power source, amplification, input/output, network interfacing, user control functions, active noise reduction (ANR), signal processing, data storage, data processing, voice detection, etc. 
     Audio processing system  30  can also include a sensor system for detecting one or more conditions of the environment proximate personal audio device  10 . Such a sensor system, e.g., ensures that adapting the system is minimized in case the main VAD system has false negatives (e.g., the user is not talking loud enough, etc.). A sensor system by itself may not be reliable for VAD, but if the sensor system outputs activity that might indicate suspicion of voice activity along with a lower threshold VAD activity, adapting to minimize coefficient corruption can be avoided. 
     In implementations that include ANR for enhancing audio signals, the inner microphone  18  may serve as a feedback microphone and the outer microphones  24  may serve as feedforward microphones. In such implementations, each earphone  12  may utilize an ANR circuit that is in communication with the inner and outer microphones  18  and  24 . The ANR circuit receives an internal signal generated by the inner microphone  18  and an external signal generated by the outer microphones  24  and performs an ANR process for the corresponding earpiece  12 . The process includes providing a signal to an electroacoustic transducer (e.g., speaker)  28  disposed in the cavity  16  to generate an anti-noise acoustic signal that reduces or substantially prevents sound from one or more acoustic noise sources that are external to the earphone  12  from being heard by the user. 
     As noted, in addition to outputting audio signals, wearable audio device  10  is configured to provide two-way communications in which the user&#39;s voice or speech is captured and then outputted to an external node via the audio processing system  20 . Various challenges may exist when attempting to capture the user&#39;s voice in an arrangement such as that shown in  FIG. 1 . For instance, the external microphones  24  are susceptible to picking up environmental noise, e.g., wind, which interferes with the user&#39;s speech. While the inner microphone  18  is not subject to environmental interference, speech coupled to the inner microphone  18  is primarily via bone conduction due to occlusion. As such, the naturalness of the voice picked up by the inner microphone is compromised and the useable bandwidth is approximately no more than 2 Khz. To address these shortcomings, as well as others, audio processing system  30  incorporates an internal signal processing system  40 . In further implementations, audio processing system  30  includes a hybrid microphone processing system  100  that incorporates features of the internal signal processing system  40 . 
       FIG. 2  depicts an illustrative embodiment of an internal signal processing system  40 , that generally includes: an earpiece  42  configured to capture at least one external signal  44  from an external microphone and at least one internal signal  46  from an inner microphone; a domain converter  48  that converts signals  44 ,  46  from the time (i.e., acoustic) domain to the frequency (i.e., electrical) domain; a voice activity detector (VAD)  60  that detects voice activity of the user; an adaptive canceller  50  that generates a noise reduced internal signal  47 ; and an inverse domain converter  68  that generates a time domain output signal  68 . Domain converter  48  may for example be configured to convert the time domain signal into 64 or 128 frequency bands using a four channel weighted overlap add (WOLA) analysis, and inverse domain converter  68  may be configured to perform the opposite function. In some implementations, additional output stage processing features may include a speech equalizer  62  and a short-time spectral amplitude (STSA) speech enhancement system  64  to further enhance the noise reduced internal signal  47 . 
     The adaptive canceller  50  calculates noise reduction parameters (e.g., filter coefficients) based on the external signal  44 , and applies the parameters to the internal signal  46  to generate the noise reduced internal signal  47 . In certain embodiments, adaptive canceller  50  includes a voice activity manager  52  that identifies when a non-voice activity period occurs based on inputs from VAD  60 . During the period when no voice signal is detected, filter coefficient calculator  54  analyzes the external signal  44  to adaptively determine filter coefficients that will cancel any external acoustic noise from the internal signal  46 . The filter coefficients can be calculated adaptively using any well-known adaptive algorithms such the normalized least means square (NLMS) algorithm. The coefficients represent the feedforward path between the external microphone and the internal microphone. In some cases adaptive canceller  50  can be preloaded with predetermined coefficients and adapt to changes to enable faster adaptation. 
     Whenever the non-voice period ends. i.e., when VAD  60  identifies speech activity of the user, coefficient selector  56  selects (i.e., freezes) the currently calculated coefficients, which are then applied to the internal signal  46  to eliminate external noise. When the user is no longer speaking and a new non-voice period begins, as indicated by VAD  60 , adaptive canceller  50  discards the current set of noise cancellation filter coefficients and begins again to continuously calculate new sets of noise cancellation filter coefficients in response to the external signal  44 . 
     In some implementations, adaptive canceller  50  utilizes an adaptive feedforward like noise canceller similar in principal to how a feedforward ANR system functions. In one implementation, the canceller  50  operates in the frequency (i.e., electrical) domain and hence can in-situ (accounting for fit variations) cancel noise to very low levels relative to what would be possible with a traditional ANR time (i.e., acoustic) domain feedforward system, which is instead based on pre-tuned coefficients. Operating in the electrical domain, the canceller  50  is not bounded by processing latencies to create a causal system. However, in an alternative approach, the canceller  50  could operate in the time domain to, e.g., minimize system complexity. Canceller  50  requires only a single external signal  44  and single internal signal  46 , and does necessarily require any ANR system to be present. 
     With coefficients being determined in-situ during non-voice periods, the noise reduced internal signal  47  will have a high SNR due to an occlusion boost of the voice signal in the ear canal (typically below 1500 Hz), passive noise attenuation provided by the ear cup/bud which increases with frequency, and the continual cancellation of remaining external noise by the currently frozen coefficients. With this approach, voice energies up to three kilohertz (kHz) can be extracted, which then can be equalized with an appropriately designed speech equalizer  62  to provide an intelligible high SNR signal with acceptable voice quality to the far end. 
     In certain implementations, further bandwidth extension is possible by providing an accelerometer signal processor  58  that processes signals from a high frequency sensitive voice accelerometer  70 , which can pick-up voice energy via bone vibration coupling with minimal sensitivity to environmental acoustic noise. Accelerator signal processor  58  may for example achieve this using short time spectral amplitude (STSA) estimation. 
     Some low-level acoustic noise can be cleaned up on the accelerometer signal with the STSA speech enhancement system  64  using an STSA estimation technique such as spectral subtraction, which is then appropriately combined with the noise reduced internal signal  47  to provide a rich higher bandwidth output signal  68 . 
     The internal signal processing system  40  does not require any external microphone arrays, e.g., using Minimum Variance Distortionless Response (MVDR) beamforming, to operate. Depending on the system&#39;s requirements, this not only enables the potential for an inner microphone system to operate with just the two microphones (providing cost savings and eliminating any special factory calibration process), but allows the internal signal  46  to be relied upon in windy situations where traditional microphone arrays fail. Furthermore, the inner microphone is naturally shielded from the wind, so this enables the system to continue working in high noise and wind conditions than what is possible with traditional array based microphone systems, thus potentially solving a common complaint by headset users. 
     While the internal signal processing system  40  can provide very high SNR in high noise and wind environments relative to what an external microphone based system can do in similar conditions, the tradeoff is that some voice naturalness can be lost using the internal signal processing system  40  alone. The inner microphone voice quality can for example be compromised due to time varying multipath transmission paths, reverberant inner ear canal chamber, and poor high frequency voice pickup. In some implementations where a high voice quality is desired while maintaining intelligibility, a hybrid system is provided, such as that shown in  FIG. 3 . 
       FIG. 3  depicts an illustrative hybrid microphone processing system  100  that includes an external processing system  118  that processes (i.e., noise reduces) at least one external signal  104  and an inner processing system  119  that processes (i.e., noise reduces) at least one internal signal  106 . In various implementations, inner processing system  119  incorporates certain features of the internal signal processing system  40 , describe in  FIG. 2 . 
     In one implementation shown, a pair of external signals  104  from a pair of external microphones and at least one internal signals  106  from an inner microphone are captured from an earpiece  102  and converted from a time domain to a frequency domain by domain converter  108 . The external signals  104  are then processed by external processing system  118 . The internal signal  106  is processed by internal processing system  119 , based in part on at least one of the external signals  116 . An intelligent mixer  124  mixes the output  121  of the external processing system  118  and the output  123  of the inner processing system  119  and generates a mixed signal  125 . Depending on whether the user is speaking and the amount of external noise detected, the mixed signal  125  can include just one, or some of each, output  121 ,  123 . 
     In certain implementations, the mixed signal  125  is passed to STSA speech enhancement system  126  to further reduce noise and extend the bandwidth of the mixed signal  125 . STSA speech enhancement system  126  receives a noise reference signal  140  from the external processing system  118  and a reference speech signal (i.e., output  123 ) from the inner processing system  119 . The resulting signal is the converted back to the time domain by inverse domain converter system  128 , and processed by a speech equalizer (EQ)  132  and speech automatic gain control (AGC)  68 . In certain implementations, speech equalizer  132  may include an input from mixer  124  indicating the amount of each signal  121 ,  123  that was used by the mixer  124 . Based on the amounts, equalization can be set appropriately. In an alternative implementation, two separate speech equalizers may be utilized to process the signals  121 ,  123  before they are inputted into the mixer  124 , rather than after as shown in  FIG. 3 . As noted, the inner microphone low frequency parts of the speech are boosted above a natural level due to occlusion and the high frequency is picked up less. An EQ on signal  123  may be configured to emphasize speech sounds that can contribute most to intelligibility and at same time maintain speech naturalness. An EQ on signal  121  would perform a similar operation but the curve defining the equalization might be a different shape. 
     Similar to the implementation shown in  FIG. 2 , internal processing system  119  includes a VAD  130  that generates a voice detection flag N, which is provided to the internal signal adaptive canceller  120  to facilitate adaptation of the filter coefficients during non-voice periods. Adapting during non-voice periods ensures that the filter coefficients will only focus on cancelling the noise transmission path to the inner microphone. 
     In one implementation, adaptive canceller  120  inputs the external signal  116 , continuously calculates a set of noise cancellation parameters (i.e., filter coefficients) during non-voice periods in response to the external signal  116 , establishes (i.e., freezes) a current set of noise cancelation parameters in response to a detection of speech by the user via VAD  130 , and utilizes the current set of noise cancellation parameters to process the internal signal  106 . In response to a determination that the user is no longer speaking, adaptive canceller  120  repeats the process of continuously calculating the set of noise cancellation parameters in response to the external signal until voice is detected again. 
     In some implementations, an optional accelerometer  112  that operates in a manner similar to that described with reference to  FIG. 2  is provided, which can be utilized by both the VAD  130  to enhance voice detection and the mixer  124  to further enhance the mixed signal  125 . In other implementations, an optional driver signal  110  that contains noise information can also be collected from the earpiece  102  and combined with the internal signal  106  by a combiner  114  to enhance the internal signal  106 . Also shown is a wind sensor  131  that generates a wind signal W when high winds are detected. Both signals N and W are provided to the intelligent mixer  124  and STSA speech enhancement system  126 , and the VAD signal N is further provided to the external processing system  118 . Other types of sensors that detect environment noise other than wind could likewise be utilized. 
     In some implementations, processing of the external microphone signals  104  by external processing system  118  may include a single sided microphone-based noise reduction system that includes a minimum variance distortionless response (MVDR) beamformer  133 , a delay and subtract process (DSUB) 135 , and an external signal adaptive canceller  122 . In one approach, DSUB  135  time aligns and equalizes the two microphone to mouth direction signals and subtracts to provide a noise correlated reference signal. Other complex array techniques could alternatively be used to minimize speech pickup in the mouth direction. 
     As noted, outputs  121 ,  123  from the external processing system  118  and the inner processing system  119 , along with any accelerometer  112  output is fed into the intelligent mixer  124 , which determines the optimal mix to send to the output stages. In certain implementations, at low levels of external noise (e.g., as determined by the wind sensor  131 ), the intelligent mixer  124  will favor output  121  from the external processing system  118  due to the inherent superior voice quality of the external microphones. At moderate levels of external noise, a mixture of the two outputs  121 ,  123  can be used. At very high noise levels (e.g., if wind is detected), the mixer  124  will switch to the internal processing system output  123  exclusively. In further implementations, other inputs, such as detection of head movements or mobility of the user can also be used to determine the best artifact free output. In still further implementations, mixer  124  can be controlled by the user via a user control input to manually select the best setting. 
     In various implementations, thresholds for selecting the best mix by the mixer  124  are based primarily on the SNR of each system  118 ,  119 , and thresholds can be determined as part of a tuning process. In one implementation, the threshold can be tuned based on user preference. In other implementations, a manual switch can be provided to allow the user to force the inner microphone system to switch during high noise or wind. In certain implementations, to minimize artifacts, changes in the mixing ratio should only happen when near end speech is absent. The SNR can be accurately determined using VAD system  130 , which is another benefit of using an inner microphone. 
     As shown, VAD  130  operates in the time domain, which provides a slight look ahead capability, but the system can be equally implemented in the frequency domain as well if desired. In some implementations, the internal signal  106  is bandpass filtered by the VAD  130  to where the voice signal has the highest SNR (typically from 400 Hz to 1600 Hz) squared to emphasize further high amplitude events (i.e., speech) versus low amplitude events (i.e., noise), appropriately processed with time constants to derive threshold-able metrics for very reliable voice activity detection. If accelerometer  112  is also present, the signal information from accelerometer  112  can also be utilized by the VAD  130  to enhance the accuracy and/or simplify the VAD  130  tuning. It is noted that such an enhanced VAD  130  benefits even a traditional external microphone based system, and hence can help to extend the operating range of the external microphone system. Detecting voice activity using only an external microphone can become unreliable under high noise or wind conditions, or if the noise source is in front of the user (i.e., same direction as the user speech). 
     An additional issue that may arise when using the inner microphone signal  106  is that during voice calls the inner microphone pickup will have a very high receive voice coupling due to proximity with the driver. Fortunately, this ‘closeness’ also means the driver to inner microphone transfer path is short and not expected to deviate much, resulting in a simple, low cost setup. In various implementations, an echo canceller with some amount of output signal attenuation can be used to provide an echo free output to the far end for full duplex communication. The driver to microphone signal transfer coefficients can be a pre-initialized measurement from ANR (e.g., using factory tuning or calculated in-situ), thus further simplifying the required adaptive filter design in adaptive canceller  120 . In one approach, the average precomputed driver to inner microphone transfer function (e.g., a dummy ear or an average of several users) is measured and pre-initialize. Alternatively, the coefficients can be determined in-situ when wearer puts on the ear bud by playing a tune and measuring it. 
     Finally, if binaural signals are available, the overall system can be combined binaurally to provide an even more superior voice pickup system. For the inner microphone, two independent inner microphone voice pickups are utilized, and each may have some mutually exclusive information that can be combined to enhance the final output. Since the residual noise is likely to be uncorrelated between the two ears, the combination process can also further reduce noise. If audio signals cannot be communicated between the ears, then a control algorithm can determine which side has the best SNR for a given environment and use that side for communication. 
       FIGS. 4-6  depict additional aspect that can be incorporated into the system  100  of  FIG. 3 .  FIG. 4  depicts a first aspect for use when the user is speaking and only the noise reduced internal signal  123  is present in the output  125  of the intelligent mixer  124  (see  FIG. 3 ), e.g., due extreme acoustic noise and wind conditions. In this case, the noise reduced external signal is unavailable due to the detected environmental noise. The internal noise reduced signal  123  provides reasonable sound quality up to about 2 kHz, but lacks higher frequency components, which results in a low quality sound for the listener. Under such conditions, a flag F is triggered and activates a bandwidth extension signal extractor  150 , which processes the output  154  of the STSA speech enhancement system  126  to create high frequency components that are mixed with the output  154  to create a more pleasing sound quality. A signal  116  (see  FIG. 3 ) obtained from the external microphone may also be utilized as reference signal by the bandwidth extension signal extractor  150  to help generate the high frequency components and maintain speech spectral balance to provide naturalness and intelligibility. 
       FIG. 5  depicts a second additional aspect for use when the user is speaking and there is low to moderate acoustic noise (e.g., caused by wind) that is interfering with the speech signal. In this case, e.g., when wind sensor  131  detects such conditions, the time domain signal  104  from one of the external microphones is processed with a delay  170  (to synch with the internal noise reduced signal  123 ) and a high pass filter  172  to extract high frequency components  174  from the external microphone signal  104 . Wind noise generally comprises primarily low frequency components, so any existing high frequency components from the external microphone signal  104  can be captured for use. The resulting high frequency components  174  are fed to the intelligent mixer  124 , along with the internal noise reduced signal  123 , and mixed together to provide a robust signal  125  that includes both low and high frequency components. 
       FIG. 6  depicts a third additional aspect for improving voice activity detection. In this case, a VAD processor  162  is deployed that utilizes signals from both the internal microphone VAD  130  (described above) and an external microphone VAD  160 . Whereas the internal microphone VAD  130  detects speech based on signals from the internal microphone, external microphone VAD  160  detects speech based on signals from the external microphone. While the internal microphone VAD  130  performs well under most conditions, certain conditions can result in errors in which speech is not detected (i.e., false negatives may occur). To address this, a failure detector  164  compares the two signals, which under ideal conditions, should have similar responses. In one approach, the internal microphone VAD  130  output is considered to be the “golden” reference. If the external microphone VAD  160  output deviates from the internal microphone VAD  130  signal beyond a predetermined threshold, it indicates that the conditions for using the external microphone are deteriorating and the VAD processor  162  can send a signal to the intelligent mixer  124  to use the internal microphone signal  123 . 
     It is noted that the implementations described herein are particularly useful for two way communications such as phone calls, especially when using ear buds. However, the benefits extend beyond phone call applications in that these approaches can potentially provide SNR that rival boom microphones with just a single ear bud. These technologies are also applicable to aviation and military use where high nose pick up with ear buds is desired. Further potential uses include peer-to-peer applications where the voice pickup is shielded from echo issues normally present. Other use cases may involve automobile ‘car wear’ like applications, wake word or other human machine voice interfaces in environments where external microphones will not work reliably, self-voice recording/analysis applications that provide discreet environments without picking up external conversations, and any application in which multiple external microphones are not feasible. Further, the implementations may be useful in work from home or call center applications by avoiding picking up nearby conversations, thus providing privacy for the user. 
     It is understood that one or more of the functions of the described systems may be implemented as hardware and/or software, and the various components may include communications pathways that connect components by any conventional means (e.g., hard-wired and/or wireless connection). For example, one or more non-volatile devices (e.g., centralized or distributed devices such as flash memory device(s)) can store and/or execute programs, algorithms and/or parameters for one or more described devices. Additionally, 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, 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. All or part of the functions can be implemented as, special purpose logic circuitry, e.g., an FPGA (field programmable gate array) and/or an ASIC (application-specific integrated circuit). 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 may 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. 
     It is noted that while the implementations described herein utilize microphone systems to collect input signals, it is understood that any type of sensor can be utilized separately or in addition to a microphone system to collect input signals. e.g., accelerometers, thermometers, optical sensors, cameras, etc. 
     Additionally, actions associated with implementing all or part of the functions described herein can be performed by one or more networked computing devices. Networked computing devices can be connected over a network, e.g., one or more wired and/or wireless networks such as a local area network (LAN), wide area network (WAN), personal area network (PAN). Internet-connected devices and/or networks and/or a cloud-based computing (e.g., cloud-based servers). 
     In various implementations, electronic components described as being “coupled” can be linked via conventional hard-wired and/or wireless means such that these electronic components can communicate data with one another. Additionally, sub-components within a given component can be considered to be linked via conventional pathways, which may not necessarily be illustrated. 
     A number of implementations have been described. Nevertheless, it will be understood that additional modifications may be made without departing from the scope of the inventive concepts described herein, and, accordingly, other implementations are within the scope of the following claims.