WO2007059255A1 - Suppression de bruit spatial dans un microphone double - Google Patents

Suppression de bruit spatial dans un microphone double Download PDF

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Publication number
WO2007059255A1
WO2007059255A1 PCT/US2006/044427 US2006044427W WO2007059255A1 WO 2007059255 A1 WO2007059255 A1 WO 2007059255A1 US 2006044427 W US2006044427 W US 2006044427W WO 2007059255 A1 WO2007059255 A1 WO 2007059255A1
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signal
audio
sum
difference
microphones
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PCT/US2006/044427
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English (en)
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Gary W. Elko
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Mh Acoustics, Llc
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Priority to US12/089,545 priority Critical patent/US8098844B2/en
Application filed by Mh Acoustics, Llc filed Critical Mh Acoustics, Llc
Priority to US12/281,447 priority patent/US8942387B2/en
Publication of WO2007059255A1 publication Critical patent/WO2007059255A1/fr
Priority to US13/596,563 priority patent/US9301049B2/en
Priority to US15/073,754 priority patent/US10117019B2/en

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R3/00—Circuits for transducers, loudspeakers or microphones
    • H04R3/005—Circuits for transducers, loudspeakers or microphones for combining the signals of two or more microphones
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R2201/00—Details of transducers, loudspeakers or microphones covered by H04R1/00 but not provided for in any of its subgroups
    • H04R2201/40—Details of arrangements for obtaining desired directional characteristic by combining a number of identical transducers covered by H04R1/40 but not provided for in any of its subgroups
    • H04R2201/403—Linear arrays of transducers
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R2410/00—Microphones
    • H04R2410/05—Noise reduction with a separate noise microphone
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R2430/00—Signal processing covered by H04R, not provided for in its groups
    • H04R2430/20—Processing of the output signals of the acoustic transducers of an array for obtaining a desired directivity characteristic
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R2499/00—Aspects covered by H04R or H04S not otherwise provided for in their subgroups
    • H04R2499/10—General applications
    • H04R2499/11—Transducers incorporated or for use in hand-held devices, e.g. mobile phones, PDA's, camera's
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R25/00—Deaf-aid sets, i.e. electro-acoustic or electro-mechanical hearing aids; Electric tinnitus maskers providing an auditory perception
    • H04R25/40—Arrangements for obtaining a desired directivity characteristic
    • H04R25/407—Circuits for combining signals of a plurality of transducers

Definitions

  • the present invention relates to acoustics, and, in particular, to techniques for reducing room ⁇ reverberation and noise in microphone systems, such as those in laptop computers, cell phones, and other mobile communication devices.
  • the microphone array built from pressure microphones can attain the maximum directional gain only in an endfire arrangement.
  • the endfire arrangement dictates 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 communication devices such as communication headsets.
  • Certain embodiments of the present invention relate to a technique that uses the acoustic output signal from two microphones mounted side-by-side in the top of a laptop display or on a mobile cell phone or other mobile communication device such as a communication headset.
  • These two microphones 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 acoustic wavelength. Thus, there is little added directional gain at low frequencies where typical room noise dominates.
  • certain embodiments of the present invention employ a spatial noise suppression (SNS) algorithm that uses a parametric estimation of the main signal direction to attain higher suppression of off-axis signals than is possible by classical linear bean ⁇ forming for two-element broadside arrays.
  • the beamformer utilizes two omnidirectional or first-order microphones, such as cardioids, or a combination 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).
  • 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 signal 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. SigttalProc, vol. ASSP-27, Apr. 1979, and EJ. Diethorn, "Subband noise reduction methods,” Acoustic Signal Processing for Telecommunication, S.L. Gay and J. Benesty, eds., Kluwer Academic Publishers, Chapter 9, pp. 155-178, Mar.
  • the present invention is a method for pxOcessing audio signals, comprising the steps of (a) generating 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.
  • the present invention is a signal processor adapted to perform the above- reference method.
  • the present invention is a consumer device comprising two or more microphones and such a signal processor.
  • 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 SR as a function of first-order microphone type when the first-order microphone level variation is normalized
  • Fig. 4 shows the general SNS suppression level as a function of SR ;
  • Fig. 5 shows one suppression function for various values of IR ;
  • Fig. 6 shows a block diagram of a two-element microphone array spatial noise suppression system according to one embodiment of the present invention
  • Fig 7 shows a block diagram of three-element microphone 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 microphone array spatial noise suppression system according to another embodiment of the present invention.
  • Fig. 10 shows a block diagram of a two-element microphone array spatial noise suppression system according to yet another embodiment of the present invention.
  • Fig. 11 shows a block diagram of a two-element microphone 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 independent 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 cardioid 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;
  • 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.
  • Equation (1) The magnitude array response S of the array formed by summing the two microphone signals is given by Equation (1) as follows:
  • Equation (2) the array magnitude response D can be written as Equation (2) as follows:
  • 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 SR for a plane-wave impinging at an angle ⁇ relative to the array axis is given by Equation (3) as follows:
  • Equations (1) and (2) can be reduced to Equations (4) and (5), respectively, as follows:
  • Equation (3) can be expressed by Equation (6) as follows:
  • 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.
  • the first option was chosen, namely to multiply the sum array output by a filter whose gain is ⁇ )d/(2c) .
  • the difference array can be filtered or both the sum and difference arrays can be appropriately filtered.
  • Equation (7) After applying a filter to the sum array with the first-order high-pass response kd/2 , the ratio of the powers of the difference and sum arrays yields Equation (7) as follows:
  • Equation (7) is the main desired result.
  • 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).
  • any angular suppression function could be created by using 91(6?) to estimate ⁇ and then applying a desired suppression scheme.
  • 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 SR .
  • a good model for typical spatial noise is a diffuse field, which is an idealized field that has uncorrelated signals coming from all directions with equal probability.
  • a diffuse field is also sometimes referred to as a spherically isotropic acoustic field.
  • the diffuse-field power ratio can be computed by integrating the SR function 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:
  • Fig. 2 is a plot of Equation (3) integrated over all incident angles of uncorrelated noise (the diffuse field assumption).
  • Fig. 2 shows the output powers of the difference array and the filtered sum array (filtered by kd/2 ) and the corresponding ratio SR for a 2-cm spaced array in a diffuse sound field.
  • curve 202 is the spatial average of SR 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 SR is the inverse of the directivity factor of a dipole microphone, which is the effective beampattern of the difference between both microphones.
  • the desired source direction is not broadside 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.
  • the amplitude response from the preferred direction increases.
  • the difference array output along the endfire increases by 6 dB.
  • the value for SR will increase from -4.8 dB to 1.2 dB as the microphone moves from dipole to cardioid.
  • the spatial average of SR for this more-general case for diffuse sound fields can reach a minimum of -4.8 dB.
  • Fig. 3 shows the variation in the power ratio SR N as a function of first-order microphone type when the first-order microphone level variation is normalized.
  • 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 kd/2 ) for a 2-cm spaced array in a diffuse sound field for different values of first-order parameter ⁇ .
  • Equation (11) Another approach that bounds the minimum of SR ⁇ 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 12 (r,r) for stationary random acoustic pressure processes p x and p 2 is defined by Equation (11) as follows:
  • Equation (11) can be expressed as Equation (13) as follows:
  • R l2 (r, ⁇ ) R( ⁇ +k T r) (13)
  • R is the spatio-temporal autocorrelation function of the acoustic pressure p .
  • the cross-spectral density is the Fourier transform of the cross-correlation function given by Equation (14) as follows:
  • Equation (14) can be expressed as Equation (15) as follows:
  • N 0 ( ⁇ )sm.(kd) kd N 0 ( ⁇ )sm.(kd) kd
  • Equations (18) and (19) The output power spectral densities of the sum signal (S aa (c ⁇ )) and the minimized difference signal (S dd (a>) ), where the minimized difference signal contains all uncorrelated signal components between the microphone channels, can be written as Equations (18) and (19) as follows:
  • Equation (20) Taking the ratios of Equation (18) and Equation (19) normalized by kd/2 yields Equation (20) as follows:
  • Equation (21) As follows: min ⁇ 5H w ( ⁇ , d) ⁇ « -4.8 dB , (21) which is the same result obtained previously. Similar equations can be written if one allows the single first-order differential null to move to any first-order pattern. Since it was shown that Sft w for diffuse fields is equal to minus the directivity index, the minimum value of SR ⁇ is equal to the negative of the maximum directivity index for all first-order patterns, i.e., min ⁇ SR M ( ⁇ , d) ⁇ « -6.0 dB .
  • 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 propagating wave sound field.
  • 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.
  • a more-flexible suppression algorithm would allow algorithm tuning to allow a general suppression function that limits that suppression to certain preset bounds and trajectories. Thus, one has to find a mapping that allows one to tailor the suppression preferences.
  • Fig. 1 shows the ratio of powers as a function of incident angle.
  • there would be noise and mismatch between the microphones that would place a physical limit on the minimum of SR for broadside.
  • the actual limit would also be a function of frequency since microphone self-noise typically has a ⁇ lf 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 electronics).
  • 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 electronics.
  • FIG. 5 shows one suppression function for various values of SR .
  • Fig. 5 shows suppression level S versus power ratio SR for 20-dB maximum suppression (-20 dB gain in the figure) with a suppression level of 0 dB (unity gain) when SR ⁇ 0.1.
  • SR power ratio
  • subband implementations one could also have the ability to use unique suppression functions as a function of frequency. This would allow for a much more general implementation and would probably be the preferred mode of implementation for subband designs.
  • Fig. 6 shows a block diagram of a two-element microphone array spatial noise suppression system 600, according to one embodiment of the present invention.
  • the signals from two ⁇ microphones 602 are differenced (604) and summed (606).
  • the sum signal is equalized by convolving the sum signal with a (kd/2) high-pass filter (608), and the short-term powers of the difference signal (610) and the equalized sum signal (612) are calculated.
  • the sum signal is equalized by multiplying the frequency components of the sum signal by (kd/2).
  • the difference signal power and the equalized sum signal power are used to compute the power ratio SR (614), which is then used to determine (e.g., compute and limit) the suppression level (616) used to perform (e.g., conventional) subband noise suppression (618) on the sum signal to generate a noise-suppressed, single- channel output signal.
  • the suppression level e.g., conventional
  • subband noise suppression processing can be applied to the difference signal instead of or in addition to being applied to the sum signal.
  • difference and sum blocks 604 and 606 can be eliminated by using a directional (e.g., cardioid) microphone to generate the difference signal applied to power block 610 and a non-directional (e.g., omni) microphone to generate the sum signal applied to equalizer block 608.
  • a directional microphone e.g., cardioid
  • a non-directional microphone e.g., omni
  • Fig 7 shows a block diagram of three-element microphone array spatial noise suppression system 700, according to another embodiment of the present invention.
  • SNS system 700 is similar to SNS system 600 of Fig. 6 with analogous elements performing analogous functions, except that, in SNS system 700, two sensing microphones 702 are used to compute the suppression level that is then applied to a separate third microphone 703.
  • the third microphone is of high-quality and the two sensing microphones are either of lower quality and/or less expensive.
  • the third microphone is a close-talking microphone, and wide-band suppression is applied to the audio signal generated by that close-talking microphone using a suppression level derived from the two sensing microphones.
  • Fig 8 shows a block diagram of stereo microphone array spatial noise suppression system 800, according to yet another embodiment of the present invention.
  • SNS system 800 is similar to SNS system 600 of Fig. 6 with analogous elements performing analogous functions, except that, in SNS system 800, the calculated suppression level is used to perform subband noise suppression 818 on two stereo channels from microphones 802.
  • the two microphones might themselves be directional microphones oriented to obtain a stereo signal.
  • a typical practical implementation would be to apply the same suppression level to both channels in order to preserve the true stereo signal.
  • Fig. 9 shows a block diagram of a two-element microphone array spatial noise suppression system 900, according to another embodiment of the present invention.
  • SNS system 900 is similar to SNS system 600 of Fig. 6 with analogous elements performing analogous functions, except that SNS system 900 employs frequency subband processing, in which the difference and sum signals are each separated into multiple subbands (905 and 907, respectively) using a dual-channel subband analysis and synthesis filterbank that independently computes and limits suppression level for each subband.
  • the noise suppression processing (918) is applied independently to different sum signal subbands. If the number of subbands is constrained to a reasonable value, then the additional computation should be minimal since the computation of the suppression values involves just adds and multiplies.
  • An added advantage of the dual-channel subband implementation of Fig. 9 is that suppression can simultaneously operate on reducing spatially separated signals that do not have shared, overlapping subbands. This added degree of freedom should enable better performance over the simpler single-channel implementation shown in Fig. 6.
  • Fig. 9 shows equalization being performed on the sum signal subbands prior to the power computation, in alternative subband implementations, equalization can be performed on the subband powers or even on the subband power ratios.
  • the basic detection algorithm relies on an array difference output, which implies that both microphones should be reasonably calibrated.
  • Another challenge for the basic algorithm is that there is an explicit assumption that the desired signal arrives from the broadside direction of the array. Since a typical application for the spatial noise algorithm is cell phone audio pickup, one should also handle the design issue of having a close-talking or nearf ⁇ eld source. Nearfield sources have high-wavenumber components, and, as such, the ratio of the difference and sum arrays is quite different from those that would be observed from farfield sources.
  • Fig. 10 shows a block diagram of a two-element microphone array spatial noise suppression system 1000, according to yet another embodiment of the present invention.
  • SNS system 1000 is similar to SNS system 600 of Fig. 6 with analogous elements performing analogous functions, except that SNS system 1000 employs adaptive filtering to allow for self-calibration of the array and modal-angle variability (i.e., flexibility in the position of the desired nearfield source).
  • SNS system 1000 has a short- length adaptive filter 1020 in series with one of the microphone channels. To allow for a causal filter that accounts for sound propagation from either direction relative the microphone axis, the unmodified channel is delayed (1022) by an amount that depends on the length of filter 1020 (e.g., one-half of the filter length).
  • a normalized least-mean-square (NLMS) process 1024 is used to adaptively update the taps of filter 1020 to minimize the difference between the two input signals in a minimum least-squares way.
  • NLMS process 1024 is preferably implemented with voice-activity detection (VAD) in order to update the filter tap values based only on suitable audio signals.
  • VAD voice-activity detection
  • One issue is that it might not be desirable to allow the adaptive filter to adapt during a noise-only condition, since this might result in a temporal variation in the outputs that might result in temporal distortion to the processed output signal. Whether this is a real problem or not has to be determined with real-world experimentation.
  • an adaptive filter also allows for the compensation of modal variation in the orientation of the array relative to the desired source. Flexibility in modal orientation of a handset would be enabled for any practical handset implementation. Also, as mentioned earlier, a close-talking handset application results in a significant change in the ratio of the sum and difference array signal powers relative to farfield sources. If one used the farfield model for suppression, then a nearfield source could be suppressed if the orientation relative to the array varied over a large incident angle variation. Thus, having an adaptive filter in the path allows for both self-calibration of the array as well as variability in close-talking modal handset position. For the case of a nearfield source, the adaptive filter will adjust the two microphones to form a spatial zero in the array response rather than a null. The spatial zero is adjusted by the adaptive filter to minimize the amount of desired nearfield signal from entering into the computed difference signal.
  • Fig. 10 could be combined with the subband processing of Fig. 9 to provide yet another embodiment of the present invention.
  • Fig. 11 shows a block diagram of a two-element microphone array spatial noise suppression system 1100, according to yet another embodiment of the present invention.
  • SNS system 1100 is similar to SNS system 600 of Fig. 6 with analogous elements performing analogous functions, except that SNS system 1100 pre-processes signals from two omnidirectional microphones 1102 to remove the (kd/2) equalization filtering of the sum signal.
  • a delayed version (1126) of the corresponding omni signal is subtracted (1128) from the other microphone's omni signal to form front- facing and back-facing cardioids (or possible other first-order patterns).
  • delays 1126 and subtraction nodes 1128 can be eliminated by using opposite-facing first-order differential (e.g., cardioid) microphones in place of omni microphones 1102.
  • Fig. 11 allows modal variation and self-calibration of the microphone array.
  • One side benefit of generalizing the structure of SNS to include the adaptive filter in the front-end is that nearfield sources force the adaptive filter to match the large variations in level typical in nearfield applications.
  • farf ⁇ eld sources have a power ratio 9t that will be closer to 0 dB and therefore can be attenuated as undesired spatial noise.
  • This effect is similar to standard close-talking microphones, where, due to the proximity effect, a dipole microphone behaves like an omnidirectional microphone for nearfield sources and like a dipole for farfield sources, thereby potentially giving a ⁇ lf SNR increase.
  • SNR increase depends on the distance of the source to the close-talking microphone as well as the source frequency content.
  • a nearfield differential response also exhibits a sensitivity variation that is closer to I// *2 versus ⁇ lr for farf ⁇ eld sources.
  • SNR gain for nearfield sources relative to farfield sources for close-talking microphones has resulted in such microphones being commonly used for moderate and high background noise environments.
  • it is advantageous to use an "asymmetric" placement of the microphones where the desired source is close to the array such as in cellular phones and communication headsets. Since the endfire orientation is "asymmetrical" relative to the talker's mouth (each microphone is not equidistant), this would be a reasonable geometry since it also offers the possibility to use the microphones as a superdirectional beamformer for farfield pickup of sound (where the desired sound source is not in the nearfield of the microphone array).
  • Matlab programs were written to simulate the response of the spatial suppression algorithm for basic and NLMS implementations as well as for free and diffuse acoustic fields.
  • a diffuse field was simulated by choosing a variable number of random directions for uncorrelated noise sources. The angles were chosen from uniformly distributed directions over 4 ⁇ space.
  • Fig. 12 shows a result for 100 independent angles.
  • Fig. 12 shows sum and difference powers from a simulated diffuse sound field using 100 random directions of independent white noise sources.
  • the expected ratio is -4.8 dB for the case of the desired source impinging from the broadside direction, and the ratio shown in Fig. 9 is very close to the predicted value.
  • a rise in the ratio at low frequencies is most likely due to numerical error due to noise from simulation processing that uses a large up-and-down sample ratio to obtain the model results.
  • 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. For comparison purposes, the theoretical value sine 2 (kd) is also plotted in Fig. 10.
  • Two spacings of 2 cm and 4 cm were chosen to allow array operation up to 8 kHz in bandwidth.
  • two microphones were assumed to be ideal cardioid microphones oriented such that their maximum response was pointing in the broadside direction (normal to the array axis).
  • a second implementation used two omnidirectional microphones spaced at 2 cm with a desired single talking source contaminated by a wideband diffuse noise field.
  • An overall farfield beampattern can be computed by the Pattern Multiplication Theorem, which states that the overall beampattern of an array of directional transducers is the product of the individual transducer directivity and an array of nondirectional transducers having the same array geometry.
  • Figs. 14 and 15 show computer-model results for a two-element cardioid array at 1 kHz.
  • Fig. 14 shows spatial suppression for 4-cm spaced cardioid microphones with a maximum suppression level of 10 dB at 1 kHz
  • Fig. 15 shows simulated polar response for the same array and maximum suppression.
  • Fig. 14 shows the sin 2 (#) suppression function as given in Equation (23).
  • 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. At this frequency and above, the approximation used to equalize the sum array begins to deviate from the precise equalization that would be required using the exact expressions. One can also see the narrowing of the beampattern at this frequency where the sum array's spatial response begins to narrow the underlying cardioid pattern. A combination of these effects results in the changes in the computed beampatterns for the frequencies of 1 kHz and 4 kHz.
  • the directivity pattern was measured for a few cases.
  • a farfield source was positioned at 0.5 m from a 2-cm spaced omnidirectional array. The array was then rotated through 360 degrees to measure the polar response of the array. Since the source is within the critical distance of the microphone, 27
  • a second set of results was taken to compare the suppression obtained in a diffuse field, which is experimentally approximated by moving the source as far away as possible from the array, placing the bulk of the microphone input signal as the reverberant sound field. By comparing the power of a single microphone, one can obtain the amount of suppression that would be applied for this acoustic field.
  • a microphone array was mounted on the pinna of a Bruel & Kjaer HATS (Head and Torso Simulator) system with a Fostex 6301B speaker placed 50 cm from the HATS system, which was mounted on a Bruel & Kjaer 9640 turntable to allow for a full 360-degree rotation in the horizontal plane.
  • HATS Head and Torso Simulator
  • This specification has described a new dual-microphone noise suppression algorithm with computationally efficient processing to effect a spatial suppression of sources that do not arrive at the array from the desired direction.
  • the use of an NLMS adaptive calibration scheme was shown that allows for the desired flexibility of allowing for calibration of the microphones for effective operation.
  • Using an adaptive filter on one of the microphone array elements also allows for a wide variation in the modal position of close-talking sources, which would be common in cellular phone handset and headset applications.
  • the present invention is described in the context of systems having two or three microphones, the present invention can also be implemented using more than three microphones.
  • the microphones may be arranged in any suitable one-, two-, or even three-dimensional configuration.
  • the processing could be done with multiple pairs of microphones that are closely spaced and the overall weighting could be a weighted and summed version of the pair-weights as computed in Equation (24).
  • the multiple coherence function reference: Bendat and Piersol, "Engineering applications of correlation and spectral analysis", Wiley Interscience, 1993.
  • the use of the difference-to-sum power ratio can also be extended to higher-order differences. Such a scheme would involve computing higher- order differences between multiple microphone signals and comparing them to lower-order differences and zero-order differences (sums).
  • the maximum order is one less than the total number of microphones, where the microphones are preferably relatively closely spaced.
  • the term "power" in intended to cover conventional power metrics as well as other measures of signal level, such as, but not limited to, amplitude and average magnitude. Since power estimation involves some form of time or ensemble averaging, it is clear that one could use different time constants and averaging techniques to smooth the power estimate such as asymmetric fast-attack, slow- decay types of estimators. Aside from averaging the power in various ways, one can also average SR which is the ratio of sum and difference signal powers by various time-smoothing techniques to form a smoothed estimate of SR .
  • audio signals from a subset of the microphones could be selected for filtering to compensate for phase difference. This would allow the system to continue to operate even in the event of a complete failure of one (or possibly more) of the microphones.
  • the present invention can be implemented for a wide variety of applications having noise in audio signals, including, but certainly not limited to, consumer devices such as laptop computers, hearing aids, cell phones, and consumer recording devices such as camcorders. Notwithstanding their relatively small size, individual hearing aids can now be manufactured with two or more sensors and sufficient digital processing power to significantly reduce diffuse spatial noise using the present invention.
  • the present invention has been described in the context of air applications, the present invention can also be applied in other applications, such as underwater applications.
  • the invention can also be useful for removing bending wave vibrations in structures below the coincidence frequency where the propagating wave speed becomes less than the speed of sound in the surrounding air or fluid.
  • the present invention may be implemented as circuit-based processes, including possible implementation on a single integrated circuit.
  • various functions of circuit elements may also be implemented as processing steps in a software program.
  • Such software maybe employed in, for example, a digital signal processor, micro-controller, or general-purpose computer.
  • the present invention can be embodied in the form of methods and apparatuses for practicing those methods.
  • the present invention can also be embodied in the form of program code embodied in tangible media, such as floppy diskettes, CD-ROMs, hard drives, or any other machine-readable storage medium, wherein, when the program code is loaded into and executed by a machine, such as a computer, the machine becomes an apparatus for practicing the invention.
  • the present invention can also be embodied in the form of program code, for example, whether stored in a storage medium, loaded into and/or executed by a machine, or transmitted over some transmission medium or carrier, such as over electrical wiring or cabling, through fiber optics, or via electromagnetic radiation, wherein, when the program code is loaded into and executed by a machine, such as a computer, the machine becomes an apparatus for practicing the invention.
  • program code When implemented on a general-purpose processor, the program code segments combine with the processor to provide a unique device that operates analogously to specific logic circuits. Unless explicitly stated otherwise, each numerical value and range should be interpreted as being approximate as if the word "about” or “approximately” preceded the value of the value or range.

Abstract

L'invention permet de supprimer le bruit spatial de signaux audio en produisant un rapport des puissances des signaux de différence et de somme des signaux audio en provenance de deux microphones et en effectuant un traitement de suppression du bruit spatial, p.ex. sur le signal de somme, la suppression étant limitée en fonction du rapport de puissance. Dans certains modes de réalisation, on filtre au moins l'une des puissances des signaux (p.ex., on égalise la puissance du signal de somme) avant de produire le rapport de puissance. Dans la mise en oeuvre en sous-bandes, on produit les puissances des signaux de somme et de différence et les rapports de puissance correspondants pour différentes sous-bandes des signaux audio, et l'on effectue le traitement de suppression du bruit pour chaque sous-bande différente, indépendamment des autres, sur la base du rapport de puissance de la sous-bande correspondante, la quantité de suppression étant dérivée du rapport de puissance de la sous-bande correspondante pour chaque sous-bande indépendamment. Dans un mode de réalisation de filtre adaptatif, on peut soumettre au moins l'un des signaux audio à un filtrage adaptatif afin de permettre un étalonnage automatique du réseau et une variabilité modale de l'angle.
PCT/US2006/044427 2002-02-05 2006-11-15 Suppression de bruit spatial dans un microphone double WO2007059255A1 (fr)

Priority Applications (4)

Application Number Priority Date Filing Date Title
US12/089,545 US8098844B2 (en) 2002-02-05 2006-11-05 Dual-microphone spatial noise suppression
US12/281,447 US8942387B2 (en) 2002-02-05 2007-03-09 Noise-reducing directional microphone array
US13/596,563 US9301049B2 (en) 2002-02-05 2012-08-28 Noise-reducing directional microphone array
US15/073,754 US10117019B2 (en) 2002-02-05 2016-03-18 Noise-reducing directional microphone array

Applications Claiming Priority (2)

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US73757705P 2005-11-17 2005-11-17
US60/737,577 2005-11-17

Related Parent Applications (1)

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US10/193,825 Continuation-In-Part US7171008B2 (en) 2002-02-05 2002-07-12 Reducing noise in audio systems

Related Child Applications (3)

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US12/281,447 Continuation-In-Part US8942387B2 (en) 2002-02-05 2007-03-09 Noise-reducing directional microphone array
PCT/US2007/006093 Continuation-In-Part WO2007106399A2 (fr) 2002-02-05 2007-03-09 Reseau de microphones directionnels reducteur de bruit
US28144708A Continuation-In-Part 2002-02-05 2008-09-02

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WO2009096958A1 (fr) * 2008-01-30 2009-08-06 Agere Systems Inc. Système et procédé de limitation de parasites
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JP2018014590A (ja) * 2016-07-20 2018-01-25 株式会社オーディオテクニカ マイクロホン
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WO2001069968A2 (fr) * 2000-03-14 2001-09-20 Audia Technology, Inc. Microphone adaptatif adapte a un systeme directionnel a plusieurs microphones
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TWI396189B (zh) * 2007-10-16 2013-05-11 Htc Corp 濾除聲音雜訊的方法
US7979487B2 (en) 2007-10-19 2011-07-12 Sennheiser Electronic Gmbh & Co. Kg Microphone device
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WO2009096958A1 (fr) * 2008-01-30 2009-08-06 Agere Systems Inc. Système et procédé de limitation de parasites
US8120993B2 (en) * 2008-06-02 2012-02-21 Kabushiki Kaisha Toshiba Acoustic treatment apparatus and method thereof
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WO2012091643A1 (fr) 2010-12-29 2012-07-05 Telefonaktiebolaget L M Ericsson (Publ) Procédé de suppression de bruit et suppresseur de bruit pour appliquer le procédé de suppression de bruit
US20130156221A1 (en) * 2011-12-15 2013-06-20 Fujitsu Limited Signal processing apparatus and signal processing method
US9271075B2 (en) * 2011-12-15 2016-02-23 Fujitsu Limited Signal processing apparatus and signal processing method
CN106328160A (zh) * 2015-06-25 2017-01-11 深圳市潮流网络技术有限公司 一种基于双麦克的降噪方法
CN106328160B (zh) * 2015-06-25 2021-03-02 深圳市潮流网络技术有限公司 一种基于双麦克的降噪方法
JP2018014590A (ja) * 2016-07-20 2018-01-25 株式会社オーディオテクニカ マイクロホン
CN112750447A (zh) * 2020-12-17 2021-05-04 云知声智能科技股份有限公司 一种去除风噪的方法

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