Abstract:
Systems ( 200 ) and methods ( 100 ) for noise error amplitude reduction. The methods involve configuring a first microphone system ( 202 ) and a second microphone system ( 302 ) so that far field sound originating in a far field environment relative to the first and second microphone systems produces a difference in sound signal amplitude at the first and second microphone systems. The difference has a known range of values. The methods involve ( 128 ) dynamically identifying the far field sound based on the difference. The methods also involve ( 130, 132, 134 ) automatically reducing substantially to zero a gain applied to the far field sound responsive to the identifying step.

Description:
BACKGROUND OF THE INVENTION 
       [0001]    1. Statement of the Technical Field 
         [0002]    The invention concerns noise error amplitude reduction systems. More particularly, the invention concerns noise error amplitude reduction systems and methods for noise error amplitude reduction. 
         [0003]    2. Description of the Related Art 
         [0004]    In many communication systems, various noise cancellation techniques have been employed to reduce or eliminate unwanted sound from audio signals received at one or more microphones. Some conventional noise cancellation techniques generally use hardware and/or software for analyzing received audio waveforms for background aural or non-aural noise. The background non-aural noise typically degrades analog and digital voice. Non-aural noise can include, but is not limited to, diesel engines, sirens, helicopter noise, water spray and car noise. Subsequent to completion of the audio waveform analysis, a polarization reversed waveform is generated to cancel a background noise waveform from a received audio waveform. The polarization reversed waveform has an identical or directly proportional amplitude to the background noise waveform. The polarization reversed waveform is combined with the received audio signal thereby creating destructive interference. As a result of the destructive interference, an amplitude of the background noise waveform is reduced. 
         [0005]    Despite the advantages of the conventional noise cancellation technique, it suffers from certain drawbacks. For example, the conventional noise cancellation technique does little to reduce the noise contamination in a severe or non-stationary acoustic noise environment. 
         [0006]    Other conventional noise cancellation techniques generally use hardware and/or software for performing higher order statistic noise suppression. One such higher order statistic noise suppression method is disclosed by Steven F. Boll in “Suppression of Acoustic Noise in Speech Using Spectral Subtraction”, IEEE Transactions on Acoustics, Speech, and Signal Processing, VOL. ASSP-27, No. 2, April 1979. This spectral subtraction method comprises the systematic computation of the average spectra of a signal and a noise in some time interval and afterwards through the subtraction of both spectral representations. Spectral subtraction assumes (i) a signal is contaminated by a broadband additive noise, (ii) a considered noise is locally stationary or slowly varying in short intervals of time, (iii) the expected value of a noise estimate during an analysis is equal to the value of the noise estimate during a noise reduction process, and (iv) the phase of a noisy, pre-processed and noise reduced, post-processed signal remains the same. 
         [0007]    Despite the advantages of the conventional higher order statistic noise suppression method, it suffers from certain drawbacks. For example, the conventional higher order statistic noise suppression method encounters difficulties when tracking a ramping noise source. The conventional higher order statistic noise suppression method also does little to reduce the noise contamination in a ramping, severe or non-stationary acoustic noise environment. 
         [0008]    Other conventional noise cancellation techniques use a plurality of microphones to improve speech quality of an audio signal. For example, one such conventional multi-microphone noise cancellation technique is described in the following document B. Widrow, R. C. Goodlin, et al.,  Adaptive Noise Cancelling: Principles and Applications , Proceedings of the IEEE, vol. 63, pp. 1692-1716, December 1975. This conventional multi-microphone noise cancellation technique uses two (2) microphones to improve speech quality of an audio signal. A first one of the microphones receives a “primary” input containing a corrupted signal. A second one of the microphones receives a “reference” input containing noise correlated in some unknown way to the noise of the corrupted signal. The “reference” input is adaptively filtered and subtracted from the “primary” input to obtain a signal estimate. 
         [0009]    Despite the advantages of the multi-microphone noise cancellation technique, it suffers from certain drawbacks. For example, analog voice is typically severely degraded by high levels of background non-aural noise. Although the conventional noise cancellation techniques reduce the amplitude of a background non-aural waveform contained in an audio signal input, the amount of the amplitude reduction is insufficient for certain applications, such as military applications, law enforcement applications and emergency response applications. 
         [0010]    In view of the forgoing, there is a need in the art for a system and method to improve the intelligibility and quality of speech in the presence of high levels of background noise. There is also a need in the art for a system and method to improve the intelligibility and quality of speech in the presence of non-stationary background noise. 
       SUMMARY OF THE INVENTION 
       [0011]    Embodiments of the present invention concern methods for noise error amplitude reduction. The method embodiments generally involve configuring a first microphone system and a second microphone system so that far field sound originating in a far field environment relative to the first and second microphone systems produces a difference in sound signal amplitude at the first and second microphone systems. The difference has a known range of values. The method embodiments also involve dynamically identifying the far field sound based on the difference. The identifying step comprises determining if the difference falls within the known range of values. The method embodiments further involve automatically reducing substantially to zero a gain applied to the far field sound responsive to the identifying step. 
         [0012]    The reducing step comprises dynamically modifying the sound signal amplitude level for at least one component of the far field sound detected by the first microphone system. The dynamically modifying step further comprises setting the sound signal amplitude level for the component to be substantially equal to the sound signal amplitude of a corresponding component of the far field sound detected by the second microphone system. A gain applied to the component is determined based on a comparison of the relative sound signal amplitude level for the component and the corresponding component. The gain value is selected for the output audio signal based on a ratio of the sound signal amplitude level for the component and the corresponding component. The gain value is set to zero if the sound signal amplitude level for the component and the corresponding component are approximately equal. 
         [0013]    The first microphone system and second microphone system are configured so that near field sound originating in a near field environment relative to the first and second microphone systems produces a second difference in the sound signal amplitude at the first and second microphone systems exclusive of the known range of values. The far field environment comprises locations at least three feet distant from the first and second microphone systems. The microphone configuration is provided by selecting at least one parameter of a first microphone associated with the first microphone system and a second microphone associated with the second microphone system. The parameter is selected from the group consisting of a distance between the first and second microphone, a microphone field pattern, a microphone orientation, and acoustic feed system. 
         [0014]    Embodiments of the present invention also concern noise error amplitude reduction systems implementing the above described method embodiments. The system embodiments comprise the first microphone system, the second microphone system and at least one signal processing device. The first and second microphone systems are configured so that far field sound originating in a far field environment relative to the first and second microphone systems produces a difference in sound signal amplitude at the first and second microphone systems. The difference has a known range of values. The signal processing device is configured to dynamically identify the far field sound based on the difference. If the far field noise is identified, then the signal processing device is also configured to automatically reduce substantially to zero a gain applied to the far field sound. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0015]    Embodiments will be described with reference to the following drawing figures, in which like numerals represent like items throughout the figures, and in which: 
           [0016]      FIGS. 1A-1C  collectively provide a flow diagram of an exemplary method for noise error amplitude reduction that is useful for understanding the present invention. 
           [0017]      FIG. 2  is a front perspective view of an exemplary communication device implementing the method of  FIGS. 1A-1C  that is useful for understanding the present invention. 
           [0018]      FIG. 3  is a back perspective view of the exemplary communication device shown in  FIG. 2 . 
           [0019]      FIG. 4  is a cross-sectional view of a portion of the exemplary communication device taken along line  4 - 4  of  FIG. 3 . 
           [0020]      FIG. 5  is a block diagram illustrating an exemplary hardware architecture of the communication device shown in  FIGS. 2-4  that is useful for understanding the present invention. 
           [0021]      FIG. 6  is a more detailed block diagram of the Digital Signal Processor shown in  FIG. 5  that is useful for understanding the present invention. 
       
    
    
     DETAILED DESCRIPTION 
       [0022]    The present invention is described with reference to the attached figures, wherein like reference numbers are used throughout the figures to designate similar or equivalent elements. The figures are not drawn to scale and they are provided merely to illustrate the instant invention. Several aspects of the invention are described below with reference to example applications for illustration. It should be understood that numerous specific details, relationships, and methods are set forth to provide a full understanding of the invention. One having ordinary skill in the relevant art, however, will readily recognize that the invention can be practiced without one or more of the specific details or with other methods. In other instances, well-known structures or operation are not shown in detail to avoid obscuring the invention. The present invention is not limited by the illustrated ordering of acts or events, as some acts may occur in different orders and/or concurrently with other acts or events. Furthermore, not all illustrated acts or events are required to implement a methodology in accordance with the present invention. 
         [0023]    Embodiments of the present invention generally involve implementing systems and methods for noise error amplitude reduction. The method embodiments of the present invention overcome certain drawbacks of conventional noise error reduction techniques. For example, the method embodiments of the present invention provide a higher quality of speech in the presence of high levels of background noise as compared to conventional methods for noise error amplitude reduction. Also, the method embodiments of the present invention provide a higher quality of speech in the presence of non-stationary background noise as compared to conventional methods for noise error amplitude reduction. 
         [0024]    The method embodiments of the present invention will be described in detail below in relation to  FIGS. 1A-1C . However, it should be emphasized that the method embodiments implement modified spectral subtraction techniques for noise error amplitude reduction. The method embodiments produce a noise signal estimate from a noise source rather than from one or more incoming speech sources (as done in conventional spectral subtraction techniques). In this regard, the method embodiments generally involve receiving at least one primary mixed input signal and at least one secondary mixed input signal. The primary mixed input signal has a higher speech-to-noise ratio as compared to the secondary mixed input signal. A plurality of samples are produced by processing the secondary mixed input signal. The samples represent a Frequency Compensated Noise Signal Estimate (FCNSE) at different sample times. Thereafter, the FCNSE samples are used to reduce the amplitude of a noise waveform contained in the primary mixed input signal. 
         [0025]    More particularly, the method embodiments involve receiving at least one primary mixed input signal at a first microphone system and at least one secondary mixed input signal at a second microphone system. The second microphone system is spaced a distance from the first microphone system. The microphone systems can be configured so that a ratio between a first signal level of far field noise arriving at the first microphone and a second signal level of far field noise arriving at the second microphone falls within a pre-defined range. For example, the distance between the microphone systems can be selected so that the ratio falls within the pre-defined range. The secondary mixed input signal has a lower speech-to-noise ratio as compared to the primary mixed input signal. The secondary mixed input signal is processed at a processor to produce the FCNSE. The primary mixed input signal is processed at the processor to reduce sample amplitudes of a noise waveform contained therein. The sample amplitudes are reduced using the FCNSE. 
         [0026]    The FCNSE is generated by evaluating a magnitude level of the primary and secondary mixed input signal to identify far field noise components contained therein. This evaluation can involve comparing the magnitude of the secondary mixed input signal to the magnitude level of the primary mixed input signal. The magnitude of the secondary mixed input signal is compared to the magnitude level of the primary mixed input signal for determining if the magnitude levels satisfy a power ratio. The values of the far field noise components of the secondary mixed input signal are set equal to the far field noise components of the primary mixed input signal if the far field noise components fall within the pre-defined range. A least means squares algorithm is used to determine an average value for far field noise effects occurring at the first and second microphone systems. 
         [0027]    The method embodiments of the present invention can be used in a variety of applications. For example, the method embodiments can be used in communication applications and voice recording applications. An exemplary communications device implementing a method embodiment of the present invention will be described in detail below in relation to  FIGS. 2-6 . 
       Method for Noise Error Amplitude Reduction 
       [0028]    Referring now to  FIGS. 1A-1C , there is provided an exemplary method  100  for noise error amplitude reduction that is useful for understanding the present invention. The goal of method  100  is: (a) to equalize a noise microphone signal input to match the phase and frequency response of a primary microphone input; (b) to adjust amplitude levels to exactly cancel the noise in the primary microphone input in the time domain; and (c) to zero filter taps that are “insignificant” so that audio Signal-to-Noise Ratio (SNR) is not degraded by a filtering process. Zeroing weak filter taps results in a better overall noise cancellation solution with improved speech SNR. The phrase “filter taps”, as used herein, refers to the terms on the right-hand side of a mathematical equation defining how an input signal of a filter is related to an output signal of the filter. For example, if the mathematical equation y[n]=b 0 x[n]+b 1 x[n−1]+ . . . +b N x[n−N] defines how an input signal of an N th -order filter is related to an output signal of the an N th -order filter, then the (N+1) terms on the right-hand side represent the filter taps. 
         [0029]    As shown in  FIG. 1A , method  100  begins with step  102  and continues with step  104 . In step  104 , a first frame of “H” samples is captured from a primary mixed input signal. “H” is an integer, such as one hundred and sixty (160). The primary mixed input signal can be, but is not limited to, a signal received at a first microphone and/or processed by front end hardware of a noise error amplitude reduction system. The front end hardware can include, but is not limited to, Analog-to-Digital Convertors (ADCs), filters, and amplifiers. Step  104  also involves capturing a second frame of “H” samples from a secondary mixed input signal. The secondary mixed input signal can be, but is not limited to, a signal that is received at a second microphone and/or processed by the front end hardware of the noise error amplitude reduction systems. The second microphone can be spaced a distance from the first microphone. The microphones can be configured so that a ratio between a first signal level of far field noise arriving at the first microphone and a second signal level of far field noise arriving at the first microphone falls within a pre-defined range (e.g., +/−0.3 dB). For example, the distance between the microphones can be configured so that ratio falls within the pre-defined range. Alternatively or additionally, one or more other parameters can be selected so that a ratio between a first signal level of far field noise arriving at the first microphone and a second signal level of far field noise arriving at the first microphone falls within a pre-defined range (e.g., +/−0.3 dB). The other parameters can be selected from the group consisting of a microphone field pattern, a microphone orientation, and acoustic feed system. The far field sound can be, but is not limited to, sound emanating from a source residing a distance of greater than three (3) or six (6) feet from the communication device  200 . 
         [0030]    The primary mixed input signal can be defined by the following mathematical equation (1). The secondary mixed input signal can be defined by the following mathematical equation (2). 
         [0000]        Y   P ( m )= x   P ( m )+ n   P ( m )  (1) 
         [0000]        Y   S ( m )= x   S ( m )+ n   S ( m )  (2) 
         [0000]    where Y P (m) represents the primary mixed input signal. x P (m) is a speech waveform contained in the primary mixed input signal. n P (m) is a noise waveform contained in the primary mixed input signal. Y S (m) represents the secondary mixed input signal. x S (m) is a speech waveform contained in the secondary mixed input signal. n S (m) is a noise waveform contained in the secondary mixed input signal. The primary mixed input signal Y P (m) has a relatively high speech-to-noise ratio as compared to the speech-to-noise ratio of the secondary mixed input signal Y S (m). 
         [0031]    After capturing a frame of “H” samples from the primary and secondary mixed input signals, the method  100  continues with step  106 . In step  106 , filtration operations are performed. Each filtration operation uses a respective one of the captured first and second frames of “H” samples. The filtration operations are performed to compensate for mechanical placement of the microphones on an object (e.g., a communications device). The filtration operations are also performed to compensate for variations in the operations of the microphones. 
         [0032]    Each filtration operation can be implemented in hardware and/or software. For example, each filtration operation can be implemented via an FIR filter. The FIR filter is a sampled data filter characterized by its impulse response. The FIR filter generates a discrete time sequence which is the convolution of the impulse response and an input discrete time input defined by a frame of samples. The relationship between the input samples and the output samples of the FIR filter is defined by the following mathematical equation (3). 
         [0000]        V   o   [n]=A   0   V   i   [n]+A   1   V   i   [n− 1 ]+A   2   V   i   [n− 2 ]+ . . . +A   N-1   V   i   [n−N+ 1]  (3) 
         [0000]    where V o [n] represents the output samples of the FIR filter. A 0 , A 1 , A 2 , . . . A N-1  represent filter tap weights. N is the number of filter taps. N is an indication of the amount of memory required to implement the FIR filter, the number of calculations required to implement the FIR filter, and the amount of “filtering” the filter can provide. V i [n], V i [n−1], V i [n−2], . . . , V i [n−N+1] each represent input samples of the FIR filter. In the FIR filter, there is no feedback, and thus it is an all zero (0) filter. The phrase “all zero (0) filter”, as used herein, means that the response of an FIR filter is shaped by placement of transmission zeros (0s) in a frequency domain. 
         [0033]    Referring again to  FIG. 1A , the method  100  continues with steps  108  and  110 . In step  108 , a first Overlap-and-Add operation is performed using the “H” samples captured from the primary mixed input signal Y P (m) to form a first window of “M” samples. In step  110 , a second Overlap-and-Add operation is performed using the “H” samples captured from the secondary mixed input signal Y S (m) to form a second window of “M” samples. The first and second Overlap-and-Add operations allow a frame size to be different from a Fast Fourier Transform (FFT) size. During each Overlap-and-Add operation, at least a portion of the “H” samples captured from the input signal Y P (m) or Y S (m) may be overlapped and added with samples from a previous frame of the signal. Alternatively or additionally, one or more samples from a previous frame of the signal Y P (m) or Y S (m) may be appended to the front of the frame of “H” samples captured in step  104 . 
         [0034]    Referring again to  FIG. 1A , the method  100  continues with steps  112  and  114 . In step  112 , a first filtration operation is performed over the first window of “M” samples. The first filtration operation is performed to ensure that erroneous samples will not be present in the FCNSE. In step  110 , a second filtration operation is performed over the window including “M” samples of the secondary mixed input signal Y S (m). The second filtration operation is performed to ensure that erroneous samples will not be present in an estimate of the FCNSE. “M” is an integer, such as two hundred fifty-six (256). 
         [0035]    The first and second filtration operations can be implemented in hardware and/or software. For example, the first and second filtration operation are implement via RRC filters. In such a scenario, each RRC filter is configured for pulse shaping of a signal. The frequency response of each RRC filter can generally be defined by the following mathematical equations (4)-(6). 
         [0000]        F (ω)=1 for ω&lt;ω c (1−α)  (4) 
         [0000]        F (ω)=0 for ω&gt;ω c (1−α)  (5) 
         [0000]        F (ω)= sqrt [(1+cos((π(ω−ω c (1−α)))/2αω c ))/2] for ω c (1−α)&lt;ω&lt;ω c (1+α)  (6) 
         [0000]    where F(ω) represents the frequency response of an RRC filter. ω represents a radian frequency. ω c  represents a carrier frequency. α represents a roll off factor constant. Embodiments of the present invention are not limited to RRC filters having the above defined frequency response. 
         [0036]    Referring again to  FIG. 1A , the method  100  continues with step  116  and  118 . In step  116 , a first windowing operation is performed using the first window of “M” samples formed in step  108  to obtain a first product signal. The first product signal is zero-valued outside of a particular interval. Similarly, step  118  involves performing a second windowing operation using the second window of “M” samples to obtain a second product signal. The second product signal is zero-valued outside of a particular interval. Each windowing operation generally involves multiplying “M” samples by a “window” function thereby producing the first or second product signal. The first and second windowing operations are performed so that accurate FFT representations of the “M” samples are obtained during subsequent FFT operations. 
         [0037]    After completing step  118 , the method  100  continues with step  120  of  FIG. 1B . Step  120  involves performing first FFT operations for computing first Discrete Fourier Transforms (DFTs) using the first product signal. The first FFT operation generally involves applying a Fast Fourier transform to the real and imaginary components of the first product signal samples. A next step  122  involves performing second FFT operations for computing second DFTs using the second product signal. The second FFT operation generally involves applying a Fast Fourier transform to the real and imaginary components of the second product signal samples. 
         [0038]    Upon computing the first and second DFTs, step  124  and  126  are performed. In step  124 , first magnitudes are computed using the first DFTs computed in step  120 . Second magnitudes are computed in step  126  using the second DFTs computed in step  122 . The first and second magnitude computations can generally be defined by the following mathematic equation (7). 
         [0000]      magnitude[ i]=sqrt (real[ i ]·real[ i ]+imag[ i ]·imag[ i ])  (7) 
         [0000]    where magnitude[i] represents a first or second magnitude. real[i] represents the real components of a first or second DFT. imag[i] represents an imaginary component of a first or second DFT. Embodiments of the present invention are not limited in this regard. For example, steps  124  and/or  126  can alternatively or additionally involve obtaining pre-stored magnitude approximation values from a memory device. Steps  124  and/or  126  can also alternatively or additionally involve computing magnitude approximation values rather than actual magnitude values as shown in  FIG. 1B . 
         [0039]    Thereafter, a decision step  128  is performed for determining if signal inaccuracies occurred at one or more microphones and/or for determining the differences in far field noise effects occurring at the first and second microphones. This determination can be made by evaluating a relative magnitude level of the primary and secondary mixed input signal to identify far field noise components contained therein. As shown in  FIG. 1B , signal inaccuracies and far field noise effects exist if magnitudes of respective first and second magnitudes are within “K” decibels (e.g., within +/−6 dB) of each other. If the magnitudes of the respective first and second magnitudes are not within “K” decibels of each other [128:NO], then method  100  continues with step  134 . Step  134  will be described below. If the magnitudes of the respective first and second magnitudes are within “K” decibels of each other [128:NO], then method  100  continues with step  130 . 
         [0040]    Step  130  involves optionally performing a first order Least Mean Squares (LMS) operation using an LMS algorithm, the first magnitude(s), and the second magnitude(s). The first order LMS operation is generally performed to compensate for signal inaccuracies occurring in the microphones and to drive far field noise effects occurring at the first and second microphones to zero (i.e., to facilitate the elimination of a noise waveform from the primary mixed input signal). The LMS operation determines an average value for far field noise effects occurring at the first and second microphone systems. The first order LMS operation is further performed to adjust an estimated noise level for level differences in signal levels between fair field noise levels in the two (2) signal Y P (m) and Y S (m) channels. In this regard, the first order LMS operation is performed to find filter coefficients for an adaptive filter that relate to producing a least mean squares of an error signal (i.e., the difference between the desired signal and the actual signal). LMS algorithms are well known to those having ordinary skill in the art, and therefore will not be described herein. Embodiments of the present invention are not limited in this regard. For example, if a Wiener filter is used to produce an error signal (instead of an adaptive filter), then the first order LMS operation need not be performed. Also, the LMS operation need not be performed if frequency compensation of the adaptive filter is to be performed automatically using pre-stored filter coefficients. 
         [0041]    Upon completing step  130 , step  132  is performed to frequency compensate for any signal inaccuracies that occurred at the microphones. Step  132  is also performed to drive far field noise effects occurring at the first and second microphones to zero (i.e., to facilitate the elimination of a noise waveform from the primary mixed input signal) by setting the values of the far field noise components of the secondary mixed input signal equal to the far field noise components of the primary mixed input signal. Accordingly, step  132  involves using the filter coefficients to adjust the second magnitude(s). Step  132  can be implemented in hardware and/or software. For example, the magnitude(s) of the second DFT(s) can be adjusted at an adaptive filter using the filter coefficients computed in step  130 . Embodiments of the present invention are not limited in this regard. 
         [0042]    Subsequent to completing step  128  or steps  128 - 132 , step  134  of  FIG. 1B  and step  136  of  FIG. 1C  are performed for reducing the amplitude of the noise waveform n P (m) of the primary mixed input signal Y P (m) or eliminating the noise waveform n P (m) from the primary mixed input signal Y P (m). In a step  134 , a plurality of gain values are computed using the first magnitudes computed in step  120  for the first DFTs. The gain values are also computed using the second magnitude(s) computed in step  122  for the second DFTs and/or the adjusted magnitude(s) generated in step  132 . 
         [0043]    The gain value computations can generally be defined by the following mathematical equation (8). 
         [0000]      gain[ i ]=1.0−noise_mag[ i ]÷primary_mag[ i]   (8) 
         [0000]    where gain[i] represents a gain value. noise_mag[i] represent a magnitude of a second DFT computed in step  122  or an adjusted magnitude of the second DFT generated in step  132 . primary_mag[i] represents a magnitude for the a first DFT computed in step  120 . 
         [0044]    Step  134  can also involve limiting the gain values so that they fall within a pre-selected range of values (e.g., values falling within the range of 0.0 to 1.0, inclusive of 0.0 and 1.0). Such gain value limiting operations can generally be defined by the following “if-else” statement. 
         [0000]    if (gain[i]&gt;psv 1 ), then gain[i]=psv 1 ;
 
else if (gain[i]&lt;psv 2 ), then gain[i]=psv 2 .
 
psv 1  represents a first pre-selected value defining a high end of a range of gain values. psv 2  represents a second pre-selected value defining a low end of a range of gain values. Embodiments of the present invention are not limited in this regard.
 
         [0045]    In step  136  of  FIG. 1C , scaling operations is performed to scale the first DFTs computed in step  120 . The scaling operations involves using the gain values computed in step  134  of  FIG. 1B . The scaling operations can generally be defined by mathematical equations (9) and (10). 
         [0000]        x ′( i ).real= x ( i ).real·gain[ i]   (9) 
         [0000]        x ′( i ).imag= x ( i ).imag·gain[ i]   (10) 
         [0000]    where x′(i).real represents a real component of a scaled first DFT. x′(i).imag represents an imaginary component of the scaled first DFT. x(i).real represents a real component of a first DFT computed in step  120 . x(i).imag represents an imaginary component of the first DFT. 
         [0046]    After completing step  136 , the method  100  continues with step  138 . In step  138 , an Inverse FFT (IFFT) operation is performed using the scaled DFTs obtained in step  136 . The IFFT operation is performed to reconstruct a noise reduced speech signal X P (m). The results of the IFFT operation are Inverse Discrete Fourier transforms of the scaled DFTs. Subsequently, step  140  is performed where the samples of the noise reduced speech signal X P (m) are multiplied by the RRC values obtained in steps  112  and  114  of  FIG. 1A . The outputs of the multiplication operations illustrate an anti-symmetric filter shape between the current frame samples and the previous frame samples overlapped and added thereto in steps  108  and  110  of  FIG. 1A . The results of the multiplication operations performed in step  140  are herein referred to as an output product samples. The output product samples computed in step  140  are then added to previous output product samples in step  142 . In effect, the fidelity of the original samples are restored. Thereafter, step  144  is performed where the method  100  returns to step  104  or subsequent processing is resumed. 
       Exemplary Communications Device Implementing Method  100   
       [0047]    Referring now to  FIGS. 2-3 , there are provided front and back perspective views of an exemplary communication device  200  implementing method  100  of  FIGS. 1A-1C . The communication device  200  can be, but is not limited to, a radio, a mobile phone, a cellular phone, or other wireless communication device. 
         [0048]    According to embodiments of the present invention, communication device  200  is a land mobile radio system intended for use by terrestrial users in vehicles (mobiles) or on foot (portables). Such land mobile radio systems are typically used by military organizations, emergency first responder organizations, public works organizations, companies with large vehicle fleets, and companies with numerous field staff. The land mobile radio system can communicate in analog mode with legacy land mobile radio systems. The land mobile radio system can also communicate in either digital or analog mode with other land mobile radio systems. The land mobile radio system may be used in: (a) a “talk around” mode without any intervening equipment between two land mobile radio systems; (b) a conventional mode where two land mobile radio systems communicate through a repeater or base station without trunking; or (c) a trunked mode where traffic is automatically assigned to one or more voice channels by a repeater or base station. The land mobile radio system  200  can employ one or more encoders/decoders to encode/decode analog audio signals. The land mobile radio system can also employ various types of encryption schemes from encrypting data contained in audio signals. Embodiments of the present invention are not limited in this regard. 
         [0049]    As shown in  FIGS. 2-3 , the communication device  200  comprises a first microphone  202  disposed on a front surface  204  thereof and a second microphone  302  disposed on a back surface  304  thereof. The microphones  202 ,  302  are arranged on the surfaces  204 ,  304  so as to be parallel with respect to each other. The presence of the noise waveform x S (m) in a signal generated by the second microphone  302  is controlled by its “audio” distance from the first microphone  202 . Accordingly, each microphone  202 ,  302  can be disposed a distance from a peripheral edge  208 ,  308  of a respective surface  204 ,  304 . The distance can be selected in accordance with a particular application. For example, microphone  202  can be disposed ten (10) millimeters from the peripheral edge  208 ,  308  of surface  204 . Microphone  302  can be disposed four (4) millimeters from the peripheral edge  208 ,  308  of surface  304 . Embodiments of the present invention are not limited in this regard. 
         [0050]    According to embodiments of the present invention. each of the microphones  202 ,  302  is a MicroElectroMechanical System (MEMS) based microphone. More particularly, each of the microphones  202 ,  302  is a silicone MEMS microphone having a part number SMM310 which is available from Infineon Technologies North America Corporation of Milpitas, Calif. Embodiments of the present invention are not limited in this regard. 
         [0051]    The first and second microphones  202 ,  302  are placed at locations on surfaces  204 ,  304  of the communication device  200  that are advantageous to noise cancellation. In this regard, it should be understood that the microphones  202 ,  302  are located on surfaces  204 ,  304  such that they output the same signal for far field sound. For example, if the microphones  202  and  302  are spaced four (4) inches from each other, then an interfering signal representing sound emanating from a sound source located six (6) feet from the communication device  200  will exhibit a power (or intensity) difference between the microphones  204 ,  304  of less than half a decibel (0.5 dB). The far field sound is generally the background noise that is to be removed from the primary mixed input signal Y P (m). According to embodiments of the present invention, the microphone arrangement shown in  FIGS. 2-3  is selected so that far field sound is sound emanating from a source residing a distance of greater than three (3) or six (6) feet from the communication device  200 . Embodiments of the present invention are not limited in this regard. 
         [0052]    The microphones  202 ,  302  are also located on surfaces  204 ,  304  such that microphone  202  has a higher level signal than the microphone  302  for near field sound. For example, the microphones  202 ,  302  are located on surfaces  204 ,  304  such that they are spaced four (4) inches from each other. If sound is emanating from a source located one (1) inch from the microphone  202  and four (4) inches from the microphone  302 , then a difference between power (or intensity) of a signal representing the sound and generated at the microphones  202 ,  302  is twelve decibels (12 dB). The near field sound is generally the voice of a user. According to embodiments of the present invention, the near field sound is sound occurring a distance of less than six (6) inches from the communication device  200 . Embodiments of the present invention are not limited in this regard. 
         [0053]    The microphone arrangement shown in  FIGS. 2-4  can accentuate the difference between near and far field sounds. Accordingly, the microphones  202 ,  302  are made directional so that far field sound is reduced in relation to near field sound in one (1) or more directions. The microphone  202 ,  302  directionality is achieved by disposing each of the microphones  202 ,  302  in a tube  402  inserted into a through hole  206 ,  306  formed in a surface  204 ,  304  of the communication device&#39;s  200  housing  210 . The tube  402  can have any size (e.g., 2 mm) selected in accordance with a particular application. The tube  402  can be made from any material selected in accordance with a particular application, such as plastic, metal and/or rubber. Embodiments of the present invention are not limited in this regard. For example, the microphone  202 ,  302  directionality can be achieved using acoustic phased arrays. 
         [0054]    According to the embodiment shown in  FIG. 3 , the hole  206 ,  306  in which the tube  402  is inserted is shaped and/or filled with a material to reduce the effects of wind noise and “pop” from close speech. The tube  402  includes a first portion  406  formed from plastic or metal. The tube  402  also includes a second portion  404  formed of rubber. The second portion  404  provides an environmental seal around the microphone  202 ,  302  at locations where it passes through the housing  210  of the communication device  200 . The environmental seal prevents moisture from seeping around the microphone  202 ,  302  and into the communication device  200 . The second portion  404  also provides an acoustic seal around the microphone  202 ,  302  at locations where it passes through the housing  210  of the communication device  200 . The acoustic seal prevents sound from seeping into and out of the communication device  200 . In effect, the acoustic seal ensures that there are no shorter acoustic paths through the radio which will cause a reduction of performance. The tube  402  ensures that the resonant point of the through hole  206 ,  306  is greater than a frequency range of interest. Embodiments of the present invention are not limited in this regard. 
         [0055]    According to other embodiments of the present invention, the tube  402  is a single piece designed to avoid resonance which yields a band pass characteristic. Resonance is avoided by using a porous material in the tube  402  to break up the air flow. A surface finish is provided on the tube  402  that imposes friction on the layer of air touching a wall (not shown) thereof. Embodiments of the present invention are not limited in this regard. 
         [0056]    Referring now to  FIG. 5 , there is provided a block diagram of an exemplary hardware architecture  500  of the communication device  200 . As shown in  FIG. 5 , the hardware architecture  500  comprises the first microphone  202  and the second microphone  302 . The hardware architecture  500  also comprises a Stereo Audio Codec (SAC)  502  with a speaker driver, an amplifier  504 , a speaker  506 , a Field Programmable Gate Array (FPGA)  508 , a transceiver  501 , an antenna element  512 , and a Man-Machine Interface (MMI)  518 . The MMI  518  can include, but is not limited to, radio controls, on/off switches or buttons, a keypad, a display device, and a volume control. The hardware architecture  500  is further comprised of a Digital Signal Processor (DSP)  514  and a memory device  516 . 
         [0057]    The microphones  202 ,  302  are electrically connected to the SAC  502 . The SAC  502  is generally configured to sample input signals coherently in time between the first and second input signal d P (m) and d S (m) channels. As such, the SAC  502  can include, but is not limited to, a plurality of ADCs that sample at the same sample rate (e.g., eight or more kilo Hertz). The SAC  502  can also include, but is not limited to, Digital-to-Analog Convertors (DACs), drivers for the speaker  506 , amplifiers, and DSPs. The DSPs can be configured to perform equalization filtration functions, audio enhancement functions, microphone level control functions, and digital limiter functions. The DSPs can also include a phase lock loop for generating accurate audio sample rate clocks for the SAC  502 . According to an embodiment of the present invention, the SAC  502  is a codec having a part number WAU8822 available from Nuvoton Technology Corporation America of San Jose, Calif. Embodiments of the present invention are not limited in this regard. 
         [0058]    As shown in  FIG. 5 , the SAC  502  is electrically connected to the amplifier  504  and the FPGA  508 . The amplifier  504  is generally configured to increase the amplitude of an audio signal received from the SAC  502 . The amplifier  504  is also configured to communicate the amplified audio signal to the speaker  506 . The speaker  506  is generally configured to convert the amplifier audio signal to sound. In this regard, the speaker  506  can include, but is not limited to, an electro acoustical transducer and filters. 
         [0059]    The FPGA  508  is electrically connected to the SAC  502 , the DSP  514 , the MMI  518 , and the transceiver  510 . The FPGA  508  is generally configured to provide an interface between the components  502 ,  514 ,  518 ,  510 . In this regard, the FPGA  508  is configured to receive signals y S (m) and y P (m) from the SAC  502 , process the received signals, and forward the processed signals Y P (m) and Y S (m) to the DSP  514 . 
         [0060]    The DSP  514  generally implements method  100  described above in relation to  FIGS. 1A-1C . As such, the DSP  514  is configured to receive the primary mixed input signal Y P (m) and the secondary mixed input signal Y S (m) from the FPGA  508 . At the DSP  514 , the primary mixed input signals Y P (m) is processed to reduce the amplitude of the noise waveform n P (m) contained therein or eliminate the noise waveform n P (m) therefrom. This processing can involve using the secondary mixed input signal Y S (m) in a modified spectral subtraction method. The DSP  514  is electrically connected to memory  516  so that it can write information thereto and read information therefrom. The DSP  514  will be described in detail below in relation to  FIG. 6 . 
         [0061]    The transceiver  510  is generally a unit which contains both a receiver (not shown) and a transmitter (not shown). Accordingly, the transceiver  510  is configured to communicate signals to the antenna element  512  for communication to a base station, a communication center, or another communication device  200 . The transceiver  510  is also configured to receive signals from the antenna element  512 . 
         [0062]    Referring now to  FIG. 6 , there is provided a more detailed block diagram of the DSP  514  shown in  FIG. 5  that is useful for understanding the present invention. As noted above, the DSP  514  generally implements method  100  described above in relation to  FIGS. 1A-1C . Accordingly, the DSP  514  comprises frame capturers  602 ,  604 , FIR filters  606 ,  608 , Overlap-and-Add (OA) operators  610 ,  612 , RRC filters  614 ,  618 , and windowing operators  616 ,  620 . The DSP  514  also comprises FFT operators  622 ,  624 , magnitude determiners  626 ,  628 , an LMS operator  630 , and an adaptive filter  632 . The DSP  514  is further comprised of a gain determiner  634 , a Complex Sample Scaler (CSS)  636 , an IFFT operator  638 , a multiplier  640 , and an adder  642 . Each of the components  602 ,  604 , . . . ,  642  shown in  FIG. 6  can be implemented in hardware and/or software. 
         [0063]    Each of the frame capturers  602 ,  604  is generally configured to capture a frame  650   a ,  650   b  of “H” samples from the primary mixed input signal Y P (m) or the secondary mixed input signal Y S (m). Each of the frame capturers  602 ,  604  is also configured to communicate the captured frame  650   a ,  650   b  of “H” samples to a respective FIR filter  606 ,  608 . Each of the FIR filters  606 ,  608  is configured to filter the “H” samples from a respective frame  650   a ,  650   b . The FIR filters  606 ,  608  are provided to compensate for mechanical placement of the microphones  202 ,  302 . The FIR filters  606 ,  608  are also provided to compensate for variations in the operations of the microphones  202 ,  302 . The FIR filters  606 ,  608  are also configured to communicate the filtered “H” samples  652   a ,  652   b  to a respective OA operator  610 ,  612 . Each of the OA operators  610 ,  612  is configured to receive the filtered “H” samples  652   a ,  652   b  from an FIR filter  606 ,  608  and form a window of “M” samples using the filtered “H” samples  652   a ,  652   b . Each of the windows of “M” samples  652   s ,  652   b  is formed by: (a) overlapping and adding at least a portion of the filtered “H” samples  652   a ,  652   b  with samples from a previous frame of the signal Y P (m) or Y S (m); and/or (b) appending the previous frame of the signal Y P (m) or Y S (m) to the front of the frame of the filtered “H” samples  652   a ,  652   b.    
         [0064]    The windows of “M” samples  654   a ,  654   b  are then communicated from the OA operators  610 ,  612  to the RRC filters  614 ,  618  and windowing operators  616 ,  620 . Each of the RRC filters  614 ,  618  is configured to ensure that erroneous samples will not be present in the FCNSE. As such, the RRC filters  614 ,  618  perform RRC filtration operations over the windows of “M” samples  654   a ,  654   b . The results of the filtration operations (also referred to herein as the “RRC” values”) are communicated from the RRC filters  614 ,  618  to the multiplier  640 . The RRC values facilitate the restoration of the fidelity of the original samples of the signal Y P (m). 
         [0065]    Each of the windowing operators  616 ,  620  is configured to perform a windowing operation using a respective window of “M” samples  654   a ,  654   b . The result of the windowing operation is a plurality of product signal samples  656   a  or  656   b . The product signal samples  656   a ,  656   b  are communicated from the windowing operators  616 ,  620  to the FFT operators  622 ,  624 , respectively. Each of the FFT operators  622 ,  624  is configured to compute DFTs  658   a ,  658   b  of respective product signal samples  656   a ,  656   b . The DFTs  658   a ,  658   b  are communicated from the FFT operators  622 ,  624  to the magnitude determiners  626 ,  628 , respectively. At the magnitude determiners  626 ,  628 , the DFTs  658   a ,  658   b  are processed to determine magnitudes  660   a ,  660   b  thereof. The magnitudes  660   a ,  660   b  are communicated from the magnitude determiners  626 ,  628  to the gain determiner  634 . The magnitudes  660   b  are also communicated to the LMS operator  630  and the adaptive filter  632 . 
         [0066]    The LMS operator  630  generates filter coefficients  662  for the adaptive filter  632 . The filter coefficients  662  are generated using an LMS algorithm and the magnitudes  660   a ,  660   b . LMS algorithms are well known to those having ordinary skill in the art, and therefore will not be described herein. However, any LMS algorithm can be used without limitation. At the adaptive filter  632 , the magnitudes  600   b  are adjusted. The adjusted magnitudes  664  are communicated from the adaptive filter  632  to the gain determiner  634 . 
         [0067]    The gain determiner  634  is configured to compute a plurality of gain values  670 . The gain value computations are defined above in relation to mathematical equation (9). The gain values  670  are computed using the magnitudes  660   a  and the unadjusted or adjusted magnitudes  660   b ,  664 . If the powers of the primary mixed input signal Y P (m) and the secondary mixed input signal Y S (m) are within “K” decibels (e.g., 6 dB) of each other, then the gain values  670  are computed using the magnitudes  660   a  and the unadjusted magnitudes  664 . However, if the powers of the primary mixed input signal Y P (m) and the secondary mixed input signal Y S (m) are not within “K” decibels (e.g., 6 dB) of each other, then the gain values  670  are computed using the magnitudes  660   a  and the adjusted magnitudes  660   b . The gain values  670  can be limited so as to fall within a pre-selected range of values (e.g., values falling within the range of 0.0 to 1.0, inclusive of 0.0 and 1.0). The gain values are communicated from the gain determiner  634  to the CSS  636 . 
         [0068]    At the CSS  636 , scaling operations are performed to scale the DFTs. The scaling operations generally involve multiplying the real and imaginary components of the DFTs by the gain values  670 . The scaling operations are defined above in relation to mathematical equations (10) and (11). The scaled DFTs  672  are communicated from the CSS  636  to the IFFT operator  638 . The IFFT operator  638  is configured to perform IFFT operations using the scaled DFTs  672 . The results of the IFFT operations are IDFTs  674  of the scaled DFTs  672 . The IDFTs  674  are communicated from the IFFT operator  638  to the multiplier  640 . The multiplier  640  multiplies the IDFTs  674  by the RRC values received from the RRC filters  614 ,  618  to produce output product samples  676 . The output product samples  676  are communicated from the multiplier  640  to the adder  642 . At the adder  642 , the output product samples  676  are added to previous output product samples  678 . The output of the adder  642  is a plurality of signal samples representing the primary mixed input signal Y P (m) having reduced noise signal n P (m) amplitudes. 
         [0069]    In light of the forgoing description of the invention, it should be recognized that the present invention can be realized in hardware, software, or a combination of hardware and software. A method for noise error amplitude reduction according to the present invention can be realized in a centralized fashion in one processing system, or in a distributed fashion where different elements are spread across several interconnected processing systems. Any kind of computer system, or other apparatus adapted for carrying out the methods described herein, is suited. A typical combination of hardware and software could be a general purpose computer processor, with a computer program that, when being loaded and executed, controls the computer processor such that it carries out the methods described herein. Of course, an application specific integrated circuit (ASIC), and/or a field programmable gate array (FPGA) could also be used to achieve a similar result. 
         [0070]    Applicants present certain theoretical aspects above that are believed to be accurate that appear to explain observations made regarding embodiments of the invention. However, embodiments of the invention may be practiced without the theoretical aspects presented. Moreover, the theoretical aspects are presented with the understanding that Applicants do not seek to be bound by the theory presented. 
         [0071]    While various embodiments of the present invention have been described above, it should be understood that they have been presented by way of example only, and not limitation. Numerous changes to the disclosed embodiments can be made in accordance with the disclosure herein without departing from the spirit or scope of the invention. Thus, the breadth and scope of the present invention should not be limited by any of the above described embodiments. Rather, the scope of the invention should be defined in accordance with the following claims and their equivalents. 
         [0072]    Although the invention has been illustrated and described with respect to one or more implementations, equivalent alterations and modifications will occur to others skilled in the art upon the reading and understanding of this specification and the annexed drawings. In addition, while a particular feature of the invention may have been disclosed with respect to only one of several implementations, such feature may be combined with one or more other features of the other implementations as may be desired and advantageous for any given or particular application. 
         [0073]    The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. Furthermore, to the extent that the terms “including”, “includes”, “having”, “has”, “with”, or variants thereof are used in either the detailed description and/or the claims, such terms are intended to be inclusive in a manner similar to the term “comprising.” 
         [0074]    The word “exemplary” is used herein to mean serving as an example, instance, or illustration. Any aspect or design described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other aspects or designs. Rather, use of the word exemplary is intended to present concepts in a concrete fashion. As used in this application, the term “or” is intended to mean an inclusive “or” rather than an exclusive “or”. That is, unless specified otherwise, or clear from context, “X employs A or B” is intended to mean any of the natural inclusive permutations. That is if, X employs A; X employs B; or X employs both A and B, then “X employs A or B” is satisfied under any of the foregoing instances. 
         [0075]    Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.