Patent Publication Number: US-10771660-B2

Title: Automatically determining a wet microphone condition in a camera

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a continuation of U.S. application Ser. No. 15/674,355, filed on Aug. 10, 2017, now U.S. Pat. No. 10,362,999, which is a continuation of U.S. application Ser. No. 15/083,266, filed Mar. 28, 2016, now U.S. Pat. No. 9,769,364, which application claims the benefit of U.S. Provisional Application No. 62/188,450, filed on Jul. 2, 2015, the contents of which are incorporated by reference in their entirety. 
    
    
     BACKGROUND 
     Technical Field 
     This disclosure relates to audio capture, and more specifically, to the selecting between multiple available microphones in an audio capture system. 
     Description of the Related Art 
     In a camera designed to operate both in and out of water, the audio subsystem can be stressed to the point where the resulting signal captured by the microphone is distorted and unnatural. The transition between the two environments can be particularly challenging due to the impulse of splashing water. During certain activities such as surfing, swimming, or other water sports, transition in and out of water may occur frequently over an extended period of time. 
    
    
     
       BRIEF DESCRIPTIONS OF THE DRAWINGS 
       The disclosed embodiments have other advantages and features which will be more readily apparent from the following detailed description of the invention and the appended claims, when taken in conjunction with the accompanying drawings, in which: 
       Figure ( FIG. 1  is a block diagram illustrating an example embodiment of an audio capture system. 
         FIG. 2  is a flowchart illustrating a first embodiment of a process for selecting between audio signals from different microphones in an audio capture system with multiple microphones. 
         FIG. 3  is a flowchart illustrating a second embodiment of a process for selecting between audio signals from different microphones in an audio capture system with multiple microphones. 
         FIG. 4  is a flowchart illustrating an embodiment of a process for detecting a wet microphone condition. 
         FIG. 5  is a flowchart illustrating an embodiment of a process for selecting a subset of microphones out of a group of microphones. 
         FIG. 6A  is first perspective view of an example camera system. 
         FIG. 6B  is second perspective view of an example camera system. 
         FIG. 7  illustrates an example of a drainage enhancement feature for an enhanced microphone in a camera system. 
     
    
    
     DETAILED DESCRIPTION 
     The figures and the following description relate to preferred embodiments by way of illustration only. It should be noted that from the following discussion, alternative embodiments of the structures and methods disclosed herein will be readily recognized as viable alternatives that may be employed without departing from the principles of what is claimed. 
     Reference will now be made in detail to several embodiments, examples of which are illustrated in the accompanying figures. It is noted that wherever practicable similar or like reference numbers may be used in the figures and may indicate similar or like functionality. The figures depict embodiments of the disclosed system (or method) for purposes of illustration only. One skilled in the art will readily recognize from the following description that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles described herein. 
     Configuration Overview 
     In a first embodiment, an output audio signal is generated in an audio capture system having multiple microphones including at least a first microphone and a second microphone. The first microphone includes a drainage enhancement feature structured to drain liquid more quickly than the second microphone lacking the drainage enhancement feature. A first audio signal is received from the first microphone representing ambient audio captured by the first microphone during a time interval. A second audio signal is received from the second microphone representing ambient audio captured by the second microphone during the time interval. A correlation metric is determined between the first audio signal and the second audio signal representing a similarity between the first audio signal and the second audio signal. Responsive to the correlation metric exceeding a predefined threshold, the first audio signal is outputted for the time interval. Responsive to the correlation metric not exceeding the first predefined threshold, a first noise metric is determined for the first audio signal and a second noise metric is determined for the second audio signal. Responsive to the sum of the first noise metric and a bias value being less than the second noise metric, the first audio signal is output for the time interval. Responsive to the sum of the first noise metric and the bias value being greater than the second noise metric, the second audio signal is output for the time interval. 
     In a second embodiment, an output audio signal is generated in an audio capture system having multiple microphones including at least a first microphone and a second microphone. The first microphone includes a drainage enhancement feature structured to drain liquid more quickly than the second microphone lacking the drainage enhancement feature. A first audio signal is received from the first microphone representing ambient audio captured by the first microphone during a time interval. A second audio signal is received from the second microphone representing ambient audio captured by the second microphone during the time interval. A correlation metric is determined between the first audio signal and the second audio signal representing a similarity between the first audio signal and the second audio signal. Responsive to the correlation metric exceeding a first predefined threshold, the first audio signal is output for the time interval. Responsive to the correlation metric not exceeding the first predefined threshold, it is determined whether the microphones are submerged in liquid. If the microphones are not submerged, it is determined whether the first microphone is wet. If the first microphone is wet, the second microphone signal is output for the time interval. Responsive to determining that first microphone is not wet or that the microphones are submerged, a first noise metric is determined for the first audio signal and a second noise metric is determined for the second audio signal. Responsive to the sum of the first noise metric and a bias value being less than the second noise metric, the first audio signal is output for the time interval. Responsive to the sum of the first noise metric and the bias value being greater than the second noise metric, the second audio signal is output for the time interval. 
     In another embodiment, a method determines if a first microphone is wet in an camera system having a first microphone and a second microphone, where the first microphone is positioned in a recess of an inner side of a face of the camera, where the recess is coupled to a channel coupled to a lower drain below the channel to drain water from the recess away from the microphone via the channel, and where the second microphone is positioned away from the channel and the drain. A first average signal level of the first audio signal and a second average signal level of the second audio signal are determined over a predefined time interval. A ratio of the first average signal level to the second average signal level is determined. Responsive to the ratio of the first average signal level to the second average signal level exceeding a first threshold or detecting a wind condition, it is determined that a wet microphone condition is not detected. Responsive to the ratio of the first average signal level to the second average signal level not exceeding the first threshold and not detecting the wind condition, it is determined that the wet microphone condition is detected. 
     In another embodiment, a camera comprises a lens assembly, a substantially cubic camera housing, a first microphone, a lower drain, an upper drain, a channel, and a second microphone. The lens assembly directs light received through a lens window to an image sensor. The substantially cubic camera housing encloses the lens assembly and comprises a bottom face, left face, right face, back face, top face, and front face. The first microphone is integrated with the front face of the camera and positioned within a recess on an interior facing portion of the front face. The lower drain is below the first microphone and comprises an opening in the substantially cubic camera housing near the front face. The lower drain allows water that collects in the recess housing the first microphone to drain. The upper drain is above the first microphone and comprises an opening in the substantially cubic housing near the front face. The upper drain allows air to enter the recess as the water drains. The channel through the interior facing portion of the front face couples the recess to the lower drain. The second microphone is integrated with a rear portion of the substantially cubic camera housing. 
     In yet another embodiment, an audio capture system comprises a substantially cubic housing including a bottom face, left face, right face, back face, top face, and front face. A first microphone is integrated with the front face of the audio capture system and positioned within a recess on an interior facing portion of the front face. A lower drain below the first microphone comprises an opening in the substantially cubic housing near the front face to allow water that collects in the recess housing the first microphone to drain. An upper drain above the first microphone comprises an opening in the substantially cubic housing near the front face to allow air to enter the recess as the water drains. A channel through the interior facing portion of the front face couples the recess to the lower drain. A second microphone is integrated with a rear portion of the substantially cubic housing. 
     Example Audio Capture System 
       FIG. 1  illustrates an example of an audio capture system  100  including multiple microphones. The audio capture system  100  includes at least one “enhanced” microphone  110 , at least one “reference” microphone  120 , a microphone selection controller  130 , and an audio encoder  140 . The enhanced microphone  110  includes a drainage enhancement feature to enable water to drain from the microphone more quickly than the reference microphone  120 . The drainage enhancement feature may be accomplished utilizing gravity and/or surface tension forces. In various embodiments, the drainage enhancement feature may be implemented using an inner surface energy coating or particular hole dimensions, shapes, density, patterns, or interior curvature or a combination of features that affect that drainage profile of the enhanced microphone  110 . The enhanced microphone  110  can therefore recover relatively quickly when moved from in water to out of water and therefore mitigates the frequency response distortion leading to muffled, unnatural sound when water is trapped on the membrane over the microphone or obscures the acoustic pathways to the microphone. In contrast, the reference microphone  120  includes a physical barrier between the splashing water and a waterproof membrane over the microphone to mitigate the impulses from splashing water. For example, in one embodiment, the barrier comprises a plastic barrier that absorbs some of the water impact impulse. In another embodiment, an air buffer may exist between the barrier and the waterproof membrane over the microphone. In another embodiment, a porting structure traps a buffer layer of water on the outside of a waterproof membrane over the microphone, thus creating a protective layer that blocks splashing water from directly impacting the waterproof membrane. Additionally, the muffling quality of water pooled on the waterproof membrane reduces some high frequency content of the splashing water. 
     In operation, both the enhanced microphone  110  and reference microphone  120  capture ambient audio  105  and pass the captured audio to the microphone selection controller  130 . The audio captured by the enhanced microphone  110  and the reference microphone  120  may have varying audio characteristics due to the different structural features of the microphones  110 ,  120 . Typically, the enhanced microphone  110  will have more spectral artifacts both in open air and when operating under water due to the drainage enhancement feature. Furthermore, the enhanced microphone  110  may have degraded signal-to-noise in windy conditions due to the drainage enhancement feature. However, the enhanced microphone  110  will generally have better signal-to-noise ratio performance out of water in non-windy conditions relative to the reference microphone  120 . Therefore, a different selection between the enhanced microphone  110  and the reference microphone  120  may be desirable under different audio capture conditions. 
     The microphone selection controller  130  processes the audio captured from the enhanced microphone  110  and the reference microphone  120  and selects, based on the audio characteristics, which of the audio signals to pass to the audio encoder  140 . In one embodiment, the microphone selection controller  130  operates on a block-by-block basis. In this embodiment, for each time interval, the microphone selection controller  130  receives a first block of audio data from the enhanced microphone and a second block of audio data from the reference microphone  120 , each corresponding to ambient audio  105  captured by the respective microphones  110 ,  120  during the same time interval. The microphone selection controller  130  processes the pair of blocks to determine which block to pass the audio encoder  140 . 
     In one embodiment, the microphone selection controller  130  generally operates to select the enhanced microphone  110  directly after transitioning out of water since the enhanced microphone  110  tends to drain the water faster and has better out of water audio quality. Furthermore, the microphone selection controller  130  generally operates to select the reference microphone  120  when in the water and when transitioning between air and water because it better mitigates the unnatural impulses caused by splashing water. 
     The audio encoder  140  encodes the blocks of audio received from the microphone selection controller  130  to generate an encoded audio signal  145 . 
     In an embodiment, the microphone selection control  130  and/or the audio encoder  140  are implemented as a processor and a non-transitory computer-readable storage medium storing instructions that when executed by the processor carry out the functions attributed to the microphone selection controller  130  and/or audio encoder  140  described herein. The microphone selection controller  130  and audio encoder  140  may be implemented using a common processor or separate processors. In other embodiments, the microphone selection controller  130  and/or audio encoder  140  may be implemented in hardware, (e.g., with an FPGA or ASIC), firmware, or a combination of hardware, firmware and software. 
     In an embodiment, the audio capture system  100  is implemented within a camera system such as the camera  500  described below with respect to  FIG. 5 . Such a camera may use the encoded audio  145  captured by the audio capture system  100  as an audio channel for video captured by the camera. Thus, the audio capture system  100  may capture audio in a manner that is concurrent and synchronized with corresponding frames of video. 
       FIG. 2  is a flowchart illustrating an embodiment of a process for selecting between an enhanced microphone  110  and a reference microphone  120 . A correlation metric is determined  202  between signal levels of audio blocks captured by the enhanced microphone  110  and reference microphone  120  respectively. The correlation metric represents a similarity between a first audio signal captured from the enhanced microphone  110  during a time interval and a second audio signal captured from the reference microphone  120  during the same time interval. Generally, the signals will be well-correlated in the absence of wind noise, but will be poorly correlated when wind noise is present. Thus, the correlation metric may operate as a wind detector. In one embodiment, the correlation metric comprises a value from 0 to 1 where a correlation metric of 1 represents a situation where there is no wind, and a correlation metric of 0 means that the captured audio is entirely wind noise. In one embodiment, the correlation metric is determined using a correlation function that includes a regularization term γ to handle low level signals. For example, in one embodiment, the correlation function is given by:
 
 X =max(0,Σ n=0   N-1 ( L [ n ]+γ)*( R [ n ]+γ))  (1)
 
where (*) represents a scalar multiplication, N is the block size, γ is the regularization term (e.g., γ=0.001), and L[n] and R[n] are the samples from the enhanced microphone and reference microphone respectively. The max operator constrains the correlation metric X to be in the range 0 and +1. In one embodiment, the correlation metric is calculated over a predefined spectral range (e.g., 600-1200 Hz). Using a restricted range beneficially eliminates or reduces artifacts caused by vibration (which typically occur at low frequencies) and reduces the amount of processing relative to calculating the metric over the full frequency spectrum. In one embodiment, the correlation metric is updated at a frequency based on the audio sample rate and sample block size. For example, if a 32 kHz sampling rate is used with a block size of 1024 samples, the correlation metric may be updated approximately every 32 milliseconds. In one embodiment, the correlation metric is smoothed over time.
 
     The correlation metric is compared  204  to a predefined threshold. In one embodiment, the predefined threshold may changes between two or more predefined thresholds depending on the previous state (e.g., whether the reference microphone or enhanced microphone was selected) to include a hysteresis effect. For example, if for the previously processed block, the correlation metric exceeded the predefined threshold (e.g., a predefined threshold of 0.8) indicating that low wind noise detected, then the predefined threshold is set lower for the current block (e.g. 0.7). If for the previously processed block, the correlation metric did not exceed the predefined threshold (e.g., a predefined threshold of 0.8), indicating that high wind noise was detected, then the predefined threshold for the current block is set higher (e.g., to 0.8). 
     If the correlation metric exceeds  204  a predefined threshold, then the enhanced microphone  110  is selected because it typically has better signal-to-noise ratio. If the correlation metric does not exceed  204  the predefined threshold, noise metrics are determined for the audio signals captured by the enhanced microphone  110  and the reference microphone  120 . Under some conditions, it may be reasonably presumed that both microphones  110 ,  120  pick up the desired (noiseless) signal at approximately, the same level and if one of the microphones is slightly blocked, then the correlation metric will still be relatively high indicating that there is low wind. Furthermore, it may be reasonably presumed that noise from the effects of wind or water is local to each microphone and that the noise will not destructively cancel out the signal. Based on these assumptions, the microphone that is louder during a low correlation condition is determined to be the microphone that has the noise. Thus, in one embodiment, the noise metrics simply comprise root-mean-squared amplitude levels of the enhanced and reference microphones over a predefined time period. For example, the predefined time period may include a sliding time window that includes the currently processed block and a fixed number of blocks prior to the current block (e.g., an approximately 4 second window). In another embodiment, a recursive-based RMS value is used (e.g., with a time constant of approximately 4 seconds). In one embodiment, the noise metric is based on equalized amplitude levels of the microphones. The equalization levels are set so that the microphones have similar amplitude characteristics under normal conditions (e.g., non-windy and non-watery conditions). In one embodiment, the noise metric is measured across substantially the entire audible band (e.g., between 20 Hz and 16 kHz). 
     If the sum of the noise metric for the enhanced microphone  110  and a bias value is less than the noise metric for the reference microphone  120 , then the microphone selection controller  130  selects  212  the enhanced microphone. On the other hand, if the sum of the noise metric for the enhanced microphone  110  and the bias value is not less than (e.g., greater than) the noise metric for the reference microphone  120 , then the microphone selection controller  130  selects  212  the reference microphone  120 . 
     In one embodiment, the bias value may comprise either a positive or negative offset that is dynamically adjusted based on the correlation metric. For example, if the correlation metric is below a lower threshold (e.g., 0.4), then a first bias value is used which may be a positive bias value (e.g., 10 dB). If the correlation metric is above an upper threshold (e.g., 0.8), then a second bias value is used which may be a negative bias value (e.g., −6 dB). If the correlation metric is between the lower threshold (e.g., 0.4) and the upper threshold (e.g., 0.8), the bias value is a linear function of the correlation metric X For example, in one embodiment, the bias value is given by: 
                   bias   =     {             bias   1     ,           X   ≤     Th   L                           bias   1     -     bias   2           Th   L     -     Th   U         ⁢     (     X   -     Th   L       )       +     bias   1       ,             Th   L     &lt;   X   &lt;     Th   U                   bias   2     ,           X   ≥     Th   U                       (   2   )               
where bias 1  is the first bias value used when the correlation metric X is below the lower threshold Th L  and bias 2  is the second bias value used when the correlation metric X is above the upper threshold Th U .
 
     In one embodiment, a hysteresis component is additionally included in the bias value. In this embodiment, the bias value is adjusted up or down depending on whether the reference microphone  120  or the enhanced microphone  110  was selected for the previous block, so as to avoid switching between the microphones  110 ,  120  too frequently. For example, in one embodiment, if the enhanced microphone  110  was selected for the previous block, an additional hysteresis bias (e.g., 5 db) is subtracted from the bias value to make it more likely that the enhanced microphone  110  will be selected again as shown in the equation below: 
                   bias   =     {               bias   1     -     bias   H       ,           X   ≤     Th   L                           bias   1     -     bias   2           Th   L     -     Th   U         ⁢     (     X   -     Th   L       )       +     bias   1     -     bias   H       ,             Th   L     &lt;   X   &lt;     Th   U                     bias   2     -     bias   H       ,           X   ≥     Th   U                       (   3   )               
where bias H  is the hysteresis bias.
 
     On the other hand, if the reference microphone  120  was selected for the previous block, the additional hysteresis bias (e.g, 5 dB) is added to the bias value to make it more likely that the reference microphone is selected again as shown in the equation below: 
     
       
         
           
             
               
                 
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     The bias value takes into account that not all wind level is created equal. It is possible to have wind that is softer, but generates more perceptive noise, than a louder wind. With high amounts of wind (low correlation metric), the enhanced microphone  110  tends to generate more perceptive noise than the reference microphone  120  during high wind condition due to the drainage enhancement feature. Thus, the bias value is used to penalize the enhanced microphone  110  for low correlation metrics. 
       FIG. 3  is a flowchart illustrating another embodiment of a process for selecting between an enhanced microphone  110  and a reference microphone  120 . A correlation metric is determined  302  between signal levels of audio blocks captured by the enhanced microphone  110  and reference microphone  120  respectively. If the correlation metric exceeds  304  a predefined threshold, then the enhanced microphone  110  is selected because it typically has better signal-to-noise ratio. If the correlation metric does not exceed  304  the threshold, it is determined  306  if the microphones are submerged in liquid (e.g., water). The predefined threshold may be determined in the same manner described above. 
     In one embodiment, a water submersion sensor may be used to determine if the microphones are submerged. In other embodiment (in which the audio capture system is integrated with a camera), an image analysis may be performed to detect features representative of the camera being submerged in water. For example, detecting color loss may be indicative of the camera being submerged because it causes exponential loss of light intensity depending on wavelength. Furthermore, crinkle patterns may be present in the image when the camera is submerged because the water surface can form small concave and convex lenses that create patches of light and dark. Additionally, light reflecting off particles in the water creates scatter and diffusion that can be detected to determine if the camera is submerged. In yet another embodiment, water pressure on the microphone&#39;s waterproof membrane may be detected because the waterproof membrane will deflect under external water pressure. This causes increased tension which shifts the waterproof membrane&#39;s resonance higher from its nominal value and can be detected in the microphone signal. Furthermore, the deflection of the waterproof membrane will results in a positive pressure on and deflection of the microphone membrane which could manifest itself as a shift in microphone bias. Additionally, a sensor could be placed near the waterproof membrane to detect an increase in shear force caused by deflection of the waterproof membrane that is indicative of the microphone being submerged. 
     If the microphones are not submerged, then it is determined  316  whether the enhanced microphone  110  is wet (e.g., not sufficiently drained after being removed from water). In one embodiment, the wet microphone condition can be detected by observing spectral response changes over a predefined frequency range (e.g., 2 kHz-4 kHz) or by detecting the sound pattern known to be associated with a wet microphone as compared to a drained microphone. For example, in one embodiment the spectral features associated with a wet (undrained) microphone can be found through empirical means. In general, when a microphone membrane is wet, higher frequency sounds are attenuated because the extra weight of the water on the membrane reduces the vibration of the membrane. Thus, the water generally acts as a low pass filter. An example of a process for detecting wet microphones is described in  FIG. 4  below. In one embodiment, spectral changes can be monitored based on the measured known drain time constant differences between the microphone geometries. If the enhanced microphone  110  is wet (e.g., not sufficiently drained), then the reference microphone  120  is selected  320 . Otherwise, if the microphones are submerged or if the enhanced microphone  110  is not wet, then noise metrics are determined  310  for the audio blocks captured by the enhanced microphone  110  and the reference microphone  120 . The noise metrics may be determined in the same manner as described above in  FIG. 2 . If the sum of the noise metric for the enhanced microphone  110  and a bias value is less than the noise metric for the reference microphone  120 , then the microphone selection controller  130  selects  314  the enhanced microphone. On the other hand, if the sum of the noise metric for the enhanced microphone  110  and the bias value is not less than the noise metric for the reference microphone  120 , then the microphone selection controller  130  selects  320  the reference microphone  120 . The bias value may be determined based on equations (2)-(4) described above. 
       FIG. 4  is a flowchart illustrating an embodiment of a process for detecting a wet microphone. Generally, water on a microphone has a transfer function approximating a low pass filter. The amount of attenuation and the cutoff frequency of the wet microphone transfer function is dependent on how much water is on the microphone. Particularly, the more water on the microphone membrane, the greater the attenuation and the lower the cutoff frequency. This phenomenon is due to the added mass of the water on the microphone membrane dampening the movement of the membrane. In one embodiment, root-mean-squared (RMS) signal levels of the audio blocks captured by the enhanced microphone  110  and reference microphone  120  are calculated  402  across a predefined frequency range (e.g., 2 kHz-4 kHz). A smoothing filter may be applied  404  to smooth the a ratio of the enhanced microphone RMS signal level to the reference microphone RMS signal level over time. If it is determined  406  that the ratio of the enhanced microphone RMS signal level to the reference microphone RMS signal level is above a predefined threshold, then the wet microphone is not detected  412 . Otherwise, if it is determined  406  that the ratio of the RMS signal levels is not above the predefined threshold, it is determined  408  if wind is present since the presence of wind can result in similar RMS ratios. The presence of wind can be determined based on, for example, a detection signal from a wind detector that determines the presence of wind based on a correlation metric X as described above. If it is determined  408  that wind noise threshold is met (i.e., the correlation metric is less than a predefined threshold), then the wet microphone is not detected  412 . Otherwise, if the wind noise threshold is not met (i.e., the correlation metric is greater than a predefined threshold), then the wet microphone condition is detected  410 . 
     In embodiments where there are two or more enhanced microphones  110  and two or more reference microphones  120 , the selection algorithm described above may be applied to a group of enhanced microphones  110  and group of reference microphones  120  instead of a single enhanced microphone  110  and single reference microphone  120 . In this embodiment, the enhanced microphone signal and reference microphone signal inputted to the processes above may comprise, for example, an average of all of the enhanced microphones and the reference microphones respectively. Then the processes described above select either the enhanced microphone group or the reference group. Furthermore in one embodiment, once either the enhanced microphones  110  or reference microphones  120  are selected, a separate selection algorithm may be applied to select an audio block from one of the microphones in the selected group to provide to the audio encoder  140  (e.g., the signal with the lowest noise). 
     In another embodiment, a process selects a subset of microphones out of a group of microphones that may include reference microphones or enhanced microphones.  FIG. 5  illustrates an embodiment of a process performed by the microphone selection controller  130  for choosing N microphones out of a group of M microphones. Audio signals are received  502  from each of the microphones in the group. Adverse conditions such as wind (e.g., low correlation value) or wet microphone (e.g., using the process of  FIG. 4 ) are detected  504  if present. If no adverse conditions (e.g., wind, water, etc.) are detected, the microphone selection controller  130  selects  506  N microphones in the group of M microphones that are pre-identified as being preferred microphones. If adverse conditions are detected (e.g., wind or water) the RMS levels of each of the M microphones are measured  508  and a bias value is added to each microphone. In one embodiment, the bias value is determined based on the bias equations (2)-(4) described above. In alternative embodiments, the bias value for each microphone may be different depending on the configuration of each microphone. For example, in one embodiment, the bias function can be a function of the correlation metric, the RMS values of all other microphones and the determination of whether or not the microphone is under water. Then, the N microphones having the lowest sums of their respective bias values and RMS levels are selected  510 . Mathematically, the process described above can be represented by the following equations: 
                                     J   →     =                                                                       ⁡     [           J   1               J   2             …             J   M           ]       ⁢                       =                                                                     ⁡     [             f   1     ⁡     (     X   ,     R   1     ,     R   2     ,   …   ⁢           ,     R   M       )                   f   2     ⁡     (     X   ,     R   1     ,     R   2     ,   …   ⁢           ,     R   M       )               …               f   M     ⁡     (     X   ,     R   1     ,     R   2     ,   …   ⁢           ,     R   M       )             ]             
where the microphone selection controller  130  picks the N microphones having the smallest cost value of J and where Ji is a cost value associated with the ith microphone, X is the correlation metric, R is the RMS value of the ith microphone, and ƒ i  is a predefined cost function.
 
     In the case of only a single reference microphone  120  and a single enhanced microphone  120 , ƒ 1  (X, R 1 , R 2 )=R 1 +g(X) and ƒ 2  (X, R 1 , R 2 )=R 2  where g(X) is the piecewise linear function described in the bias equations above, ƒ 1  is the cost function for the enhanced microphone  110  and ƒ 2  is the cost function for the reference microphone  120 . In one embodiment, a hysteresis bias may also be included as described above, except with potentially different thresholds, depending on the configuration. 
     Example Camera System Configuration 
       FIGS. 6A-6B  illustrate perspective views of an example camera  600  in which the audio capture system  100  may be integrated. The camera  600  comprises at least one cross-section having four approximately equal length sides in a two-dimensional plane. Although the cross-section is substantially square, the corners of the cross-section may be rounded in some embodiments (e.g., a rounded square or squircle). The exterior of the square camera  600  includes 6 surfaces (i.e. a front face, a left face, a right face, a back face, a top face, and a bottom face). In the illustrated embodiment, the exterior surfaces substantially conform to a rectangular cuboid, which may have rounded or unrounded corners. In one example embodiment, all camera surfaces may also have a substantially square (or rounded square) profile, making the square camera  600  substantially cubic. In alternate embodiments, only two of the six faces (e.g., the front face  610  and back face  640 ) have equal length sides and the other faces may be other shapes, such as rectangles. The camera  600  can have a small form factor (e.g. a height of 2 cm to 9 cm, a width of 2 cm to 9 cm, and a depth of 2 cm to 9 cm) and is made of a rigid material such as plastic, rubber, aluminum, steel, fiberglass, or a combination of materials. In other embodiments, the camera  600  may have a different form factor. 
     In an embodiment, the camera  600  includes a camera lens window  602  surrounded by a front face perimeter portion  608  on a front face  610 , an interface button  604  and a display  614  on a top face  620 , an I/O door  606  on a side face  630 , and a back door  612  on a back face  640 . The camera lens window  602  comprises a transparent or substantially transparent material (e.g., glass or plastic) that enables light to pass through to an internal lens assembly. In one embodiment, the camera lens window  602  is substantially flat (as opposed to a convex lens window found in many conventional cameras). The front face  610  of the camera  600  furthermore comprises a front face perimeter portion  608  that surrounds the lens window  602 . In one embodiment, the front face perimeter portion  608  comprises a set of screws to secure the front face perimeter portion  608  to the remainder of the housing of the camera  600  and to hold the lens window  602  in place. 
     The interface button  604  provides a user interface that when activated enables a user to control various functions of the camera  600 . For example, pressing the button  604  may control the camera to power on or power off, take pictures or record video, save a photo, adjust camera settings, or perform any other action relevant to recording or storing digital media. In one embodiment, the interface button  604  may perform different functions depending on the type of interaction (e.g., short press, long press, single tap, double tap, triple tap, etc.) In alternative embodiments, these functions may also be controlled by other types of interfaces such as a knob, a switch, a dial, a touchscreen, voice control, etc. Furthermore, the camera  600  may have more than one interface button  604  or other controls. The display  614  comprises, for example, a light emitting diode (LED) display, a liquid crystal display (LCD) or other type of display for displaying various types of information such as camera status and menus. In alternative embodiments, the interface button  604 , display  606 , and/or other interface features may be located elsewhere on the camera  600 . 
     The I/O door  606  provides a protective cover for various input/output ports of the camera  600 . For example, in one embodiment, the camera  600  includes a Universal Serial Bus (USB) port and/or a High-Definition Media Interface (HDMI) port, and a memory card slot accessible behind the I/O door  606 . In other embodiments, additional or different input/output ports may be available behind the I/O door  606  or elsewhere on the camera  600 . 
     The back door  612  provides a protective cover that when removed enables access to internal components of the camera  600 . For example, in one embodiment, a removable battery is accessible via the back door  612 . 
     In some embodiments, the camera  600  described herein includes features other than those described below. For example, instead of a single interface button  604 , the square camera  600  can include additional buttons or different interface features such as a speakers and/or various input/output ports. 
     In one embodiment, the reference microphone  110  is integrated with or near the back door  612  of the camera  600  such that it is positioned near the rear of the camera  600 , and the enhanced microphone is integrated with the front face  610  of the camera  600  such that it is positioned near the front of the camera  600 . 
       FIG. 7  illustrates an example of a front face perimeter portion  608  of a camera  600  with an integrated drain enhancement feature in the form of a channel  702  between a recess  704  where the enhanced microphone  110  (not shown) is positioned, and one or more drains (e.g, an upper drain structure  708  and a lower drain structure  706 , each of which may comprise a single drain or multiple drains) to enable liquid to drain. Microphone ports  710  provide openings to let sound reach the microphone(s) housed in recess  704 . In one embodiment, the upper drain structure  708  is positioned above the channel  702  and the lower drain structure  706  is positioned below the channel  702 . The lower drain structure  706  is generally much larger than the upper drain structure  708 . 
     When the camera  600  is submerged the entire channel  702  generally fills with water. When the camera  600  emerges from the water, the large mass of water in the channel  702  flows out through the lower drain structure  706  through the force of gravity. This pulls air in through upper drain structure  708  and clears water from the recess  704 , the upper drain structure  708 , and/or the microphone ports  710 , thus allowing the microphone to resume normal acoustic performance. 
     Additional Configuration Considerations 
     Throughout this specification, some embodiments have used the expression “coupled” along with its derivatives. The term “coupled” as used herein is not necessarily limited to two or more elements being in direct physical or electrical contact. Rather, the term “coupled” may also encompass two or more elements are not in direct contact with each other, but yet still co-operate or interact with each other, or are structured to provide a drainage path between the elements. 
     Likewise, as used herein, the terms “comprises,” “comprising,” “includes,” “including,” “has,” “having” or any other variation thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, article, or apparatus that comprises a list of elements is not necessarily limited to only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. 
     In addition, use of the “a” or “an” are employed to describe elements and components of the embodiments herein. This is done merely for convenience and to give a general sense of the invention. This description should be read to include one or at least one and the singular also includes the plural unless it is obvious that it is meant otherwise. 
     Finally, as used herein any reference to “one embodiment” or “an embodiment” means that a particular element, feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment. The appearances of the phrase “in one embodiment” in various places in the specification are not necessarily all referring to the same embodiment. 
     Upon reading this disclosure, those of skill in the art will appreciate still additional alternative structural and functional designs as disclosed from the principles herein. Thus, while particular embodiments and applications have been illustrated and described, it is to be understood that the disclosed embodiments are not limited to the precise construction and components disclosed herein. Various modifications, changes and variations, which will be apparent to those skilled in the art, may be made in the arrangement, operation and details of the method and apparatus disclosed herein without departing from the spirit and scope defined in the appended claims.