(12) United States Patent
`Elko
`
`(10) Patent No.:
`(45) Date of Patent:
`
`US 8,098,844 B2
`*Jan. 17, 2012
`
`USOO809884.4B2
`
`(54) DUAL-MICROPHONESPATIAL NOISE
`SUPPRESSION
`
`(75) Inventor: Gary W. Elko, Summit, NJ (US)
`
`(73) Assignee: MH Acoustics, LLC, Summit, NJ (US)
`(*) Notice:
`Subject to any disclaimer, the term of this
`patent is extended or adjusted under 35
`U.S.C. 154(b) by 887 days.
`This patent is Subject to a terminal dis-
`claimer.
`
`(21) Appl. No.:
`
`12/089,545
`
`Nov. 5, 2006
`PCT/US2O06/044427
`
`(22) PCT Filed:
`(86). PCT No.:
`S371 (c)(1)
`Apr. 8, 2008
`(2), (4) Date:
`(87) PCT Pub. No.: WO2007/059255
`PCT Pub. Date: May 24, 2007
`O
`O
`Prior Publication Data
`US 2008/O26O175A1
`Oct. 23, 2008
`
`(65)
`
`Related U.S. Application Data
`(63) Continuation-in-part of application No. 10/193,825,
`filed on Jul. 12, 2002, now Pat. No. 7,171,008.
`(60) Provisional application No. 60/737,577, filed on Nov.
`17, 2005
`isional
`lication No. 60/354,650
`fil s d F. fy appl1cauon No.
`swall ws
`ed on Feb. ),
`51) Int. C
`(51) Int. Cl.
`(2006.01)
`H04B I5/00
`f
`(9) f
`(52) H04R 3/00
`52) U.S. C. ....... 381/94.1: 381/92: 381/94.2: 381/94.3:
`381/122
`
`(58) Field of Classification Search .................... 381/92,
`381/94.1, 122,942, 94.3, 313
`See application file for complete search history.
`
`(56)
`
`Ref
`Cited
`eeees e
`U.S. PATENT DOCUMENTS
`3,626,365 A 12, 1971 Press ............................... 340/34
`4,281,551 A
`8, 1981 Gaudriot et al.
`4,741,038 A
`4, 1988 Elko et al. ....................... 381/92
`5,325,872 A
`7/1994 Westermann ................. 128/897
`5,473,701 A 12, 1995 Cezanne et al.
`(Continued)
`
`JP
`
`FOREIGN PATENT DOCUMENTS
`10O23590 A
`1, 1998
`(Continued)
`Primary Examiner — Vivian Chin
`Assistant Examiner — Douglas Suthers
`. E"S.S.C. S. AG Mendelsohn. Drucker &
`SSoc1ales, F.U.; Sleve Mendelso
`(57)
`ABSTRACT
`Spatial noise Suppression for audio signals involves generat
`p
`9.
`pp
`9.
`ing a ratio of powers of difference and Sum signals of audio
`signals from two microphones and then performing noise
`suppression processing e.g., on the Sum signal where the
`Suppression is limited based on the power ratio. In certain
`embodiments, at least one ofthe signal powers is filtered (e.g.,
`the Sum signal power 1s equalized) prior to generating the
`power ratio. In a Subband implementation, Sum and differ
`ence signal powers and corresponding the power ratio are
`generated for different audio signal subbands, and the noise
`Suppression processing is performed independently for each
`different Subband based on the corresponding subband power
`ratio, where the amount of Suppression is derived indepen
`dently for each subband from the corresponding subband
`power ratio. In an adaptive filtering implementation, at least
`one of the audio signals can be adaptively filtered to allow for
`array self-calibration and modal-angle variability.
`35 Claims, 10 Drawing Sheets
`
`
`
`
`
`i Subbard
`I
`noise
`analysis
`
`Compute
`short-terr
`power
`
`
`
`Sibband
`nois
`analysis
`
`co-au--ms--
`r
`Compute
`Equalize is short-term
`power
`
`
`
`
`
`Compute
`and imit
`surron
`and Subband T suppression
`Syrithesis
`
`
`
`Output
`
`Page 1 of 22
`
`GOOGLE EXHIBIT 1002
`
`

`

`US 8,098.844 B2
`Page 2
`
`U.S. PATENT DOCUMENTS
`5,515,445. A
`5/1996 Baumhauer, Jr. et al. ...... 381/92
`5,524,056 A
`6/1996 Killion et al. .........
`... 381 (68.2
`5,602,962 A
`2f1997 Kellermann
`395/235
`5,610,991 A
`3, 1997 Janse ..........
`... 381/92
`5,687.241 A 1 1/1997 Ludvigsen .
`381 (68.4
`5,878,146 A
`3, 1999 Andersen ...................... 381,312
`5,982,906 A 1 1/1999 Ono
`6,041,127 A
`3, 2000 Eko
`6,272.229 B1
`8/2001 Baekgaard .................... 381 313
`6.292,571 B1
`9/2001 Sjursen ..........
`381 312
`6,339,647 B1
`1/2002 Andersen et al. ............. 381/312
`6,584,203 B2
`6/2003 Elko et al.
`2003, OO31328 A1
`2/2003 Elko et al.
`
`
`
`8, 2003 Elko
`2003/014.7538 A1
`2003/0206640 A1 11/2003 Malvaret al.
`2004/0022397 A 2.2004 Warren
`2004O165736 A1
`8/2004 Hetherington et al.
`2005/0276423 A1 12/2005 Aubauer et al. ................ 381/92
`2009,0175466 A1
`7, 2009 Elko et al.
`2009.0323982 A1 12/2009 Solbach et al.
`2010/03294.92 A1 12/2010 Derleth et al.
`FOREIGN PATENT DOCUMENTS
`
`JP
`WO
`WO
`
`10 126878 A
`WOO1,56328 A
`WOO1? 69.968 A2
`
`5, 1998
`8, 2001
`9, 2001
`
`Page 2 of 22
`
`

`

`U.S. Patent
`
`Jan. 17, 2012
`
`Sheet 1 of 10
`
`US 8,098,844 B2
`
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`Page 3 of 22
`
`

`

`U.S. Patent
`
`Jan. 17, 2012
`
`Sheet 2 of 10
`
`US 8,098,844 B2
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`Page 4 of 22
`
`

`

`U.S. Patent
`
`Jan. 17, 2012
`
`Sheet 3 of 10
`
`US 8,098,844 B2
`
`
`
`1.
`
`to
`Frequency (Hz)
`
`Fig. 3:
`
`10
`
`Page 5 of 22
`
`

`

`U.S. Patent
`
`Jan. 17, 2012
`
`Sheet 4 of 10
`
`US 8,098,844 B2
`
`4-(Smin Rmin)
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`
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`
`Page 6 of 22
`
`

`

`U.S. Patent
`
`Jan. 17, 2012
`
`Sheet 5 of 10
`
`US 8,098,844 B2
`
`
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`-- Short-terrn i-, --
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`suppression
`
`Fig. 7:
`
`Page 7 of 22
`
`

`

`U.S. Patent
`
`Jan. 17, 2012
`
`Sheet 6 of 10
`
`US 8,098,844 B2
`
`
`
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`
`Output
`
`Fig. 9:
`
`Page 8 of 22
`
`

`

`U.S. Patent
`
`Jan. 17, 2012
`
`Sheet 7 of 10
`
`US 8,098,844 B2
`
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`
`---------------
`
`Page 9 of 22
`
`

`

`U.S. Patent
`
`Jan. 17, 2012
`
`Sheet 8 of 10
`
`US 8,098,844 B2
`
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`
`Page 10 of 22
`
`

`

`U.S. Patent
`U.S. Patent
`
`Jan. 17, 2012
`Jan. 17, 2012
`
`Sheet 9 of 10
`Sheet 9 of 10
`
`US 8,098,844 B2
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`US8,098,844 B2
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`
`Page 11 of 22
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`Page 11 of 22
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`Jan. 17, 2012
`Jan. 17, 2012
`
`Sheet 10 of 10
`Sheet 10 of 10
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`US 8,098,844 B2
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`US8,098,844 B2
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`U.S. Patent
`U.S. Patent
`
`
`
`Page 12 of 22
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`Page 12 of 22
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`

`

`1.
`DUAL-MCROPHONE SPATAL NOISE
`SUPPRESSION
`
`CROSS-REFERENCE TO RELATED
`APPLICATIONS
`
`This application claims the benefit of PCT patent applica
`tion no. PCT/US2006/044427 filed on Nov. 15, 2006, which
`is a continuation-in-part of U.S. patent application Ser. No.
`10/193,825, filed on Jul. 12, 2002 and issued as U.S. Pat. No.
`7,171,008 on Jan. 30, 2007, which claimed the benefit of the
`filing date of U.S. provisional application No. 60/354,650,
`filed on Feb. 5, 2002, the teachings of all three of which are
`incorporated herein by reference. PCT patent application no.
`PCT/US2006/044427 also claims the benefit of the filing date
`of U.S. provisional application No. 60/737,577, filed on Nov.
`17, 2005, the teachings of which are incorporated herein by
`reference.
`
`10
`
`15
`
`BACKGROUND OF THE INVENTION
`
`1. Field of the Invention
`The present invention relates to acoustics, and, in particu
`lar, to techniques for reducing room reverberation and noise
`in microphone systems, such as those in laptop computers,
`cellphones, and other mobile communication devices.
`2. Description of the Related Art
`Interest in simple two-element microphone arrays for
`speech input into personal computers has grown due to the
`fact that most personal computers have stereo input and out
`put. Laptop computers have the problem of physically locat
`ing the microphone so that disk drive and keyboard entry
`noises are minimized. One obvious solution is to locate the
`microphone array at the top of the LCD display. Since the
`depth of the display is typically very small (laptop designers
`strive to minimize the thickness of the display), any direc
`tional microphone array will most likely have to be designed
`to operate as a broadside design, where the microphones are
`placed next to each other along the top of the laptop display
`and the main beam is oriented in a direction that is normal to
`the array axis (the display top, in this case).
`It is well known that room reverberation and noise are
`typical problems when using microphones mounted on laptop
`or desktop computers that are not close to the talker's mouth.
`Unfortunately, the directional gain that can be attained by the
`use of only two acoustic pressure microphones is limited to
`first-order differential patterns, which have a maximum gain
`of 6 dB in diffuse noise fields. For two elements, the micro
`phone array built from pressure microphones can attain the
`maximum directional gain only in an endfire arrangement.
`For implementation limitations, the endfire arrangement dic
`tates microphone spacing of more than 1 cm. This spacing
`might not be physically desired, or one may desire to extend
`the spatial filtering performance of a single endfire directional
`microphone by using an array mounted on the display top
`edge of a laptop PC.
`Similar to the laptop PC application is the problem of noise
`pickup by mobile cell phones and other portable communi
`cation devices such as communication headsets.
`
`SUMMARY OF THE INVENTION
`
`Certain embodiments of the present invention relate to a
`technique that uses the acoustic output signal from two micro
`phones mounted side-by-side in the top of a laptop display or
`on a mobile cellphone or other mobile communication device
`Such as a communication headset. These two microphones
`
`25
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`30
`
`35
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`40
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`US 8,098,844 B2
`
`2
`may themselves be directional microphones such as cardioid
`microphones. The maximum directional gain for a simple
`delay-sum array is limited to 3 dB for diffuse sound fields.
`This gain is attained only at frequencies where the spacing of
`the elements is greater than or equal to one-half of the acous
`tic wavelength. Thus, there is little added directional gain at
`low frequencies where typical room noise dominates. To
`address this problem, certain embodiments of the present
`invention employ a spatial noise Suppression (SNS) algo
`rithm that uses a parametric estimation of the main signal
`direction to attain higher Suppression of off-axis signals than
`is possible by classical linear beam forming for two-element
`broadside arrays. The beam former utilizes two omnidirec
`tional or first-order microphones, such as cardioids, or a com
`bination of an omnidirectional and a first-order microphone
`that are mounted next to each other and aimed in the same
`direction (e.g., towards the user of the laptop or cell phone).
`Essentially, the SNS algorithm utilizes the ratio of the
`power of the differenced array signal to the power of the
`Summed array signal to compute the amount of incident sig
`nal from directions other than the desired front position. A
`standard noise Suppression algorithm, Such as those
`described by S. F. Boll, “Suppression of acoustic noise in
`speech using spectral Subtraction.” IEEE Trans. Acoust. Sig
`nal Proc., vol. ASSP-27, April 1979, and E. J. Diethorn,
`“Subband noise reduction methods. Acoustic Signal Pro
`cessing for Telecommunication, S. L. Gay and J. Benesty,
`eds. Kluwer Academic Publishers, Chapter 9, pp. 155-178,
`March 2000, the teachings of both of which are incorporated
`herein by reference, is then adjusted accordingly to further
`Suppress undesired off-axis signals. Although not limited to
`using directional microphone elements, one can use cardioid
`type elements, to remove the front-back symmetry and mini
`mizes rearward arriving signals. By using the power ratio of
`the two (or more) microphone signals, one can estimate when
`a desired source from the broadside of the array is operational
`and when the input is diffuse noise or directional noise from
`directions off of broadside. The ratio measure is then incor
`porated into a standard Subband noise Suppression algorithm
`to affect a spatial Suppression component into a normal
`single-channel noise-suppression processing algorithm. The
`SNS algorithm can attain higher levels of noise Suppression
`for off-axis acoustic noise sources than Standard optimal lin
`ear processing.
`In one embodiment, the present invention is a method for
`processing audio signals, comprising the steps of (a) gener
`ating an audio difference signal; (b) generating an audio Sum
`signal; (c) generating a difference-signal power based on the
`audio difference signal; (d) generating a Sum-signal power
`based on the audio Sum signal; (e) generating a power ratio
`based on the difference-signal power and the Sum-signal
`power, (f) generating a Suppression value based on the power
`ratio; and (g) performing noise Suppression processing for at
`least one audio signal based on the Suppression value to
`generate at least one noise-suppressed output audio signal.
`In another embodiment, the present invention is a signal
`processor adapted to perform the above-reference method. In
`yet another embodiment, the present invention is a consumer
`device comprising two or more microphones and Such a sig
`nal processor.
`
`BRIEF DESCRIPTION OF THE DRAWINGS
`
`Other aspects, features, and advantages of the present
`invention will become more fully apparent from the following
`
`Page 13 of 22
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`

`US 8,098,844 B2
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`10
`
`15
`
`25
`
`30
`
`35
`
`3
`detailed description, the appended claims, and the accompa
`nying drawings in which like reference numerals identify
`similar or identical elements.
`FIG. 1 is a plot of the ratio of Equation (3) for a microphone
`spacing of d=2.0 cm, of the output powers of the difference
`array relative to the filtered sum array for frequencies from
`100 Hz to 10 kHz for a 2-cm spaced array for various angles
`of incidence of a farfield planewave;
`FIG. 2 is a plot of Equation (3) integrated over all incident
`angles of uncorrelated noise (the diffuse field assumption);
`FIG.3 shows the variation in the power ratio
`as a func
`tion of first-order microphone type when the first-order
`microphone level variation is normalized;
`FIG. 4 shows the general SNS suppression level as a func
`tion of:
`FIG. 5 shows one suppression function for various values
`of SR;
`FIG. 6 shows a block diagram of a two-element micro
`phone array spatial noise Suppression system according to
`one embodiment of the present invention:
`FIG. 7 shows a block diagram of three-element micro
`phone array spatial noise Suppression system according to
`another embodiment of the present invention;
`FIG. 8 shows a block diagram of stereo microphone array
`spatial noise Suppression system according to yet another
`embodiment of the present invention;
`FIG. 9 shows a block diagram of a two-element micro
`phone array spatial noise Suppression system according to
`another embodiment of the present invention;
`FIG. 10 shows a block diagram of a two-element micro
`phone array spatial noise suppression system according to yet
`another embodiment of the present invention;
`FIG. 11 shows a block diagram of a two-element micro
`phone array spatial noise Suppression system according to yet
`another embodiment of the present invention;
`FIG. 12 shows sum and difference powers from a simulated
`diffuse sound field using 100 random directions of indepen
`dent white noise sources;
`FIG. 13 is a plot that shows the measured magnitude
`squared coherence for 200 randomly incident uncorrelated
`noise sources onto a 2-cm spaced microphone;
`FIG. 14 shows spatial Suppression for 4-cm spaced car
`dioid microphones with a maximum suppression level of 10
`dB at 1 kHz, while FIG. 15 shows simulated polar response
`for the same array and maximum suppression; and
`FIGS. 16 and 17 show computer-model results for the same
`4-cm spaced cardioid array and the same 10-dB maximum
`Suppression level at 4 kHz.
`
`ideo)
`
`(2)
`
`An important design feature that can impact the design of
`any beam former design is that both of these functions are
`periodic in frequency. This periodic phenomenon is also
`referred to as spatial aliasing in beam forming literature. In
`order to remove frequency ambiguity, the distanced between
`the microphones is typically chosen so that there is no aliasing
`up to the highest operating frequency. The constraint that
`occurs here is that the microphone element spacing should be
`less than one wavelength at the highest frequency. One may
`note that this value is twice the spacing that is typical in
`beam forming design. But the sum and difference array do not
`both incorporate steering, which in turn introduces the one
`wavelength spacing limit. However, if it is desired to allow
`modal variation of the array relative to the desired source,
`then some time delay and amplitude matching would be
`employed. Allowing time-delay variation is equivalent to
`“steering the array and therefore the high-frequency cutoff
`will be lower. However, off-axis nearfield sources would not
`exhibit these phenomena due to the fact that these source
`locations result in large relative level differences between the
`microphones.
`As stated in the Summary, the detection measure for the
`spatial noise Suppression (SNS) algorithm is based on the
`ratio of powers from the differenced and summed closely
`spaced microphones. The power ratio is for a plane-wave
`impinging at an angle 0 relative to the array axis is given by
`Equation (3) as follows:
`
`kdcos(8) ).
`
`(3)
`
`For small values of k.d. Equations (1) and (2) can be reduced
`to Equations (4) and (5), respectively, as follows:
`S(C),0)-s2
`
`(4)
`
`(5)
`D(c),0)-skid cos(0)|
`and therefore Equation (3) can be expressed by Equation (6)
`as follows:
`
`(co, 8) as
`
`(kd)cos(0)
`4
`
`(6)
`
`These approximations are valid over a fairly large range of
`frequencies for arrays where the spacing is below the one
`wavelength spacing criterion. In Equation (5), it can be seen
`that the difference array has a first-order high-pass frequency
`response. Equation (4) does not have frequency dependence.
`In order to have a roughly frequency-independent ratio, either
`the sum array can be equalized with a first-order high-pass
`response or the difference array can be filtered through a
`first-order low-pass filter with appropriate gain. For the
`implementation of the SNS algorithm described in this speci
`fication, the first option was chosen, namely to multiply the
`Sum array output by a filter whose gain is (Od/(2c). In other
`implementations, the difference array can be filtered or both
`the sum and difference arrays can be appropriately filtered.
`After applying a filter to the sum array with the first-order
`high-pass responsekd/2, the ratio of the powers of the differ
`ence and Sum arrays yields Equation (7) as follows:
`Si(0)-cos(0)
`
`(7)
`
`40
`
`45
`
`DETAILED DESCRIPTION
`
`Derivation
`To begin, assume that two nondirectional microphones are
`spaced a distance of d meters apart. The magnitude array
`response S of the array formed by Summing the two micro
`phone signals is given by Equation (1) as follows:
`
`50
`
`55
`
`S(co, 8) = also de 2
`
`(1)
`
`60
`
`where k=()/c is the wavenumber, () is the angular frequency,
`and c is the speed of Sound (m/s), and Ois defined as the angle
`relative to the array axis. If the two elements are subtracted,
`then the array magnitude response D can be written as Equa
`tion (2) as follows:
`
`65
`
`Page 14 of 22
`
`

`

`US 8,098,844 B2
`
`5
`where the “hat notation indicates that the sum array is mul
`tiplied (filtered) by k.d/2. (To be more precise, one could filter
`with sin(kd/2)/cos(kd/2).) Equation (7) is the main desired
`result. We now have a measure that can be used to decrease the
`off-axis response of an array. This measure has the desired
`quality of being relatively easy to compute since it requires
`only adding or subtracting signals and estimating powers
`(multiply and average).
`FIG. 1 is a plot of the ratio of Equation (3) for a microphone
`spacing of d=2.0 cm, of the output powers of the difference
`array relative to the filtered sum array for frequencies from
`100 Hz to 10 kHz for a 2-cm spaced array for various angles
`of incidence of a farfield planewave. The angle 0 is defined as
`the angle from endfire (i.e., the direction along the line that
`connects the two microphones). Such that 0–0 degrees corre
`sponds to endfire and 0=90 degrees corresponds to broadside
`incidence.
`In general, any angular suppression function could be cre
`ated by using Si(0) to estimate 0 and then applying a desired
`suppression scheme. Ofcourse, this is a simplified view of the
`problem since, in reality, there are many simultaneous signals
`impinging on the array, and the net effect will be an average
`St. A good model for typical spatial noise is a diffuse field,
`which is an idealized field that has uncorrelated signals com
`ing from all directions with equal probability. A diffuse field
`25
`is also sometimes referred to as a spherically isotropic acous
`tic field.
`Diffuse Spatial Noise
`The diffuse-field power ratio can be computed by integrat
`ing the Sifunction over the surface of a sphere. Since the
`two-element array is axisymmetric, this surface integral can
`be reduced to a line integral given by Equation (8) as follows:
`
`10
`
`15
`
`6
`One simple and straightforward way to reduce the range of
`Swould be to normalize the gain variation of the differential
`array when the null is steered from broadside to endfire to aim
`at a source that is not arriving from the broadside direction.
`Performing this normalization, Sican obtain only negative
`values of the directivity index for all first-order two-element
`differential microphones arrays. Thus one can write,
`(10)
`-6.0 dBsis 4.8 dB.
`as a func
`FIG.3 shows the variation in the power ratio
`tion of first-order microphone type when the first-order
`microphone level variation is normalized. In particular, FIG.
`3 shows the ratio of the output power of the difference array
`relative to the output power of the filtered sum array (filtered
`by k.d/2) for a 2-cm spaced array in a diffuse sound field for
`different values of first-order parameter C. The first-order
`parameter C. defines the directivity as T(0)=C+cos(0). Thus,
`C=0 is a dipole, C.-0.25 is a hypercardioid, and C=1 is a
`cardioid.
`Another approach that bounds the minimum of for a
`diffuse field is based on the use of the spatial coherence
`function for spaced omnidirectional microphones in a diffuse
`field. The space-time correlation function R (r,t) for sta
`tionary random acoustic pressure processes p and p is
`defined by Equation (11) as follows:
`
`where E is the expectation operator, s is the position of the
`sensor measuring acoustic pressure p, and r is the displace
`ment vector to the sensor measuring acoustic pressure p. For
`a plane-wave incident field with wavevector k (where
`k-k=()/c where c is the speed of sound), p. can be written
`according to Equation (12) as follows:
`
`30
`
`dise
`
`(8)
`
`35
`
`where T is the transpose operator. Therefore, Equation (11)
`can be expressed as Equation (13) as follows:
`
`FIG. 2 is a plot of Equation (3) integrated over all incident
`angles of uncorrelated noise (the diffuse field assumption). In
`particular, FIG. 2 shows the output powers of the difference
`array and the filtered sum array (filtered by k.d/2) and the
`corresponding ratio
`for a 2-cm spaced array in a diffuse
`sound field. Note that curve 202 is the spatial average of at
`lower frequencies and is equal to -4.8 dB. It should not be a
`Surprise that the log of the integral is equal to -4.8 dB, since
`the spatial integral of Si is the inverse of the directivity factor
`of a dipole microphone, which is the effective beampattern of
`the difference between both microphones.
`It is possible that the desired source direction is not broad
`side to the array, and therefore one would need to steer the
`single null to the desired source pattern for the difference
`array could be any first-order differential pattern. However, as
`the first-order pattern is changed from dipole to other first
`order patterns, the amplitude response from the preferred
`direction (the direction in which the directivity index is maxi
`mum) increases. At the extreme end of steering the first-order
`pattern to endfire (a cardioid pattern), the difference array
`output along the endfire increases by 6 dB. Thus, the value for
`will increase from -4.8 dB to 1.2 dB as the microphone
`moves from dipole to cardioid. As a result, the spatial average
`of Si for this more-general case for diffuse sound fields can
`reach a minimum of -4.8 dB.
`Thus, one can write explicit limits for all far-field diffuse
`noise fields when the minimized difference signal is formed
`by a first-order differential pattern according to Equation (9)
`as follows:
`
`40
`
`45
`
`50
`
`55
`
`60
`
`65
`
`-48 dBsis 1.2 dB
`
`(9)
`
`where R is the spatio-temporal autocorrelation function of the
`acoustic pressure p. The cross-spectral density S is the Fou
`rier transform of the cross-correlation function given by
`Equation (14) as follows:
`
`If we assume that the acoustic field is spatially homoge
`neous (such that the correlation function is not dependent on
`the absolute position of the sensors) and also assume that the
`field is diffuse (uncorrelated signals from all direction), then
`the vector r can be replaced with a scalar variabled, which is
`the spacing between the two measurement locations. Thus,
`the cross-spectral density for an isotropic field is the average
`cross-spectral density for all spherical directions, 0, p. There
`fore, Equation (14) can be expressed as Equation (15) as
`follows:
`
`(15)
`
`N. (co)sin(codfc)
`codfic
`No (co)sin(kd)
`
`where N(CD) is the power spectral density at the measurement
`locations and it has been assumed without loss in generality
`that the vector r lies along the Z-axis. Note that the isotropic
`assumption implies that the power spectral density is the same
`
`Page 15 of 22
`
`

`

`7
`at each location. The complex spatial coherence function Y is
`defined as the normalized cross-spectral density according to
`Equation (16) as follows:
`
`US 8,098,844 B2
`
`8
`exceeds unity, which is used to detect and compute the Sup
`pression of wind-noise as in the electronic windscreen algo
`rithm described in U.S. patent application Ser. No. 10/193,
`825.
`From the above development, it was shown that the power
`ratio between the difference and sum arrays is a function of
`the incident angle of the signal for the case of a single propa
`gating wave sound field. For diffuse fields, the ratio is a
`function of the directivity of the microphone pattern for the
`minimized difference signal.
`The spatial noise Suppression algorithm is based on these
`observations to allow only signals propagating from a desired
`speech direction or position and Suppress signals propagating
`from other directions or positions. The main problem now is
`to compute an appropriate Suppression filter Such that desired
`signals are passed, while off-axis and diffuse noise fields are
`Suppressed, without the introduction of spurious noise or
`annoying distortion. As with any parametric noise Suppres
`sion algorithm, one cannot expect that the output signal will
`have increased speech intelligibility, but would have the
`desired effect to Suppress unwanted background noise and
`room reverberation. One suppression function would be to
`form the function C defined (for broadside steering) accord
`ing to Equation (23) as follows:
`(23)
`C(0)=1-Six(0)=sine.
`A practical issue is that the function Chas a minimum gain
`of 0. In a real-world implementation, one could limit the
`amount of Suppression to some maximum value defined
`according to Equation (24) as follows:
`
`y12 (d. (o) =
`
`S12 (d. (d)
`S1 (a)S22(a))]?
`
`16
`(16)
`
`For diffuse noise and omnidirectional receivers, the spatial
`coherence function is purely real. Such that Equation (17)
`results as follows:
`
`10
`
`sin(kd)
`
`(17)
`
`15
`
`The output power spectral densities of the Sum signal (S.
`(())) and the minimized difference signal (S(c))), where the
`minimized difference signal contains all uncorrelated signal
`components between the microphone channels, can be writ
`ten as Equations (18) and (19) as follows:
`
`Sad (d. co) = N (a)(1-y(d. (o)
`sin(kd),
`=N.(a)(1-2)
`
`and
`
`Sa(d. co) = No (a)(1+y(d, co)
`sin(kd),
`kd )
`
`N.(a)(1 --
`
`(18)
`
`25
`
`(19)
`
`30
`
`Taking the ratios of Equation (18) and Equation (19) nor
`malized by kd/2 yields Equation (20) as follows:
`
`35
`
`sin(kd)
`1--
`sin(kd)
`maxi (d. (o)} =
`(kd/2)(1 + "E)
`St. i
`
`(20)
`
`where the approximation is reasonable for kd/2< L. Convert
`ing to decibels results in Equation (21) as follows:
`(21)
`min{ivod)}-48 dB,
`which is the same result obtained previously. Similar equa
`tions can be written if one allows the single first-order differ
`ential null to move to any first-order pattern. Since it was
`shown that
`for diffuse fields is equal to minus the direc
`tivity index, the minimum value of Siis equal to the negative
`of the maximum directivity index for all first-order patterns,
`1.C.,
`
`40
`
`45
`
`50
`
`55
`
`(22)
`min{i(cod)}-6.0 dB.
`Although the above development has been based on the use of
`omnidirectional microphones, it is possible that some imple
`mentations might use first-order or even higher-order differ
`ential microphones. Thus, similar equations can be developed
`as above for directional microphones or even the combination
`of various orders of individual microphones used to form the
`array.
`Basic Algorithm Implementation
`From Equation (7), it can be seen that, for a propagating
`acoustic wave, Osis 1. For wind-noise, this ratio greatly
`
`60
`
`65
`
`A more-flexible Suppression algorithm would allow algo
`rithm tuning to allow a general Suppression function that
`limits that Suppression to certain preset bounds and trajecto
`ries. Thus, one has to find a mapping that allows one to tailor
`the Suppression preferences.
`As a starting point for the design of a practical algorithm, it
`is important to understand any constraints due to microphone
`sensor mismatch and inherent noise. FIG. 1 shows the ratio of
`powers as a function of incidentangle. In any practical imple
`mentation, there would be noise and mismatch between the
`microphones that would place a physical limit on the mini
`mum of for broadside. The actual limit would also be a
`function of frequency since microphone self-noise typically
`has a 1/f spectral shape due to electret preamplifier noise (e.g.,
`the FET used to transform the high output impedance of the
`electret to a low output impedance to drive external electron
`ics). Also, it would be reasonable to assume that the micro
`phones will have some amplitude and phase error. (Note that
`this problem is eliminated if one uses an adaptive filter to
`“match' the two microphone channel signals. This is
`described in more detail later in this specification.) Thus, it
`would be prudent to limit the expected value of the minimum
`power ratio from