MICROPHONE MIXING FOR WIND NOISE REDUCTION

Abstract

Wind noise reduction in microphone signals. A first microphone signal is obtained from a first omnidirectional microphone and, contemporaneously, a second microphone signal is obtained from a second omnidirectional microphone. The first and second microphone signals are mixed to produce an output signal. Mixing involves weighting the first and second microphone signals by respective first and second signal weights to produce respective first and second weighted microphone signals, and summing the first and second weighted microphone signals together to produce the output signal. The first and second signal weights are calculated to minimise the power of the output signal.

Claims

1. A method of wind noise reduction, the method comprising obtaining a first microphone signal from a first omnidirectional microphone; contemporaneously obtaining a second microphone signal from a second omnidirectional microphone; and mixing the first and second microphone signals to produce an output signal, by: weighting the first and second microphone signals by respective first and second signal weights to produce respective first and second weighted microphone signals; and summing the first and second weighted microphone signals together to produce the output signal, wherein the first and second signal weights are calculated to minimise the power of the output signal.

2. The method of claim 1, wherein the first signal weight a takes a value in the range of 0 to 1 inclusive, and is calculated by the processor as follows: $\begin{array}{cc}a=\frac{.Math..Math.y^2-.Math..Math.\mathrm{xy}}{.Math..Math.x^2-2.Math..Math..Math..Math.\mathrm{xy}+.Math..Math.y^2}& \left(1\right)\end{array}$ where: x=signal sample of the first microphone signal, and y=signal sample of the second microphone signal, and wherein the second signal weight is (1−a).

3. (canceled)

4. (canceled)

5. The method of claim 1 wherein weights are calculated continuously for each first signal sample and second signal sample, by calculating x.sup.2, y.sup.2 and xy for each sample and adding them to a respective appropriate running sum.

6. The method of claim 5 wherein a leaky integrator is used to perform the running sum in order to prevent overflows.

7. The method of claim 1 wherein the first and second signals are frequency domain samples.

8. The method of claim 7 wherein a weighting factor a, is calculated for each subband i, and the a.sub.i are applied on a subband—by—subband basis to give different mixing ratios at different frequencies.

9. The method of claim 8 wherein frequencies deemed to be more important for wind noise suppression are given a higher weighting.

10. The method of claim 9 wherein the frequencies deemed to be more important are given a higher weighting by calculating the weighting factor a in respect of such frequencies before applying a for mixing across a wider band.

11. The method of claim 9, wherein the frequencies deemed to be more important are given a higher weighting by performing mixing only in the important subbands.

12. The method of claim 1 wherein complex inputs are utilised and the weighting factor is calculated as being: $a=\frac{.Math..Math.{.Math.y.Math.}^2-\mathrm{real}.Math..Math.\left(.Math..Math.x*\stackrel{\_}{y}\right)}{.Math..Math.{.Math.x.Math.}^2-2*\mathrm{real}.Math..Math.\left(.Math..Math.x*\stackrel{\_}{y}\right)+.Math..Math.{.Math.y.Math.}^2}$ where y is the complex conjugate of y, |y| is the absolute value of y and real( ) is a function that takes the real part of the complex input.

13. The method of claim 1 when applied to signals produced from more than two microphones.

14. The method of claim 13 wherein the processor is configured to calculate the required number of signal weights in a manner to minimise the power of the output signal.

15. The method of claim 14 wherein, when a signal z from a third omnidirectional microphone is obtained, the output signal Y is calculated as follows:
Y=a*primary_mic+b*secondary_mic+(1−a−b)*tertiary_mic where $a=\frac{{\left(.Math..Math.x^2\right)}^{-1}}{{\left(.Math..Math.x^2\right)}^{-1}+{\left(.Math..Math.y^2\right)}^{-1}+{\left(.Math..Math.z^2\right)}^{-1}},\mathrm{and}$ $b=\frac{{\left(.Math..Math.y^2\right)}^{-1}}{{\left(.Math..Math.x^2\right)}^{-1}+{\left(.Math..Math.y^2\right)}^{-1}++.Math.{\left(.Math..Math.z^2\right)}^{-1}}.$

16. The method of claim 1 wherein, prior to mixing, the first and second microphone signals are matched for a level of a signal of interest.

17. The method of claim 1 wherein, prior to mixing, the first and second microphone signals are matched for phase.

18. The method of claim 1 further comprising activating the wind noise reduction only at times when a wind noise detector indicates that wind noise is present.

19. The method of claim 1 when utilised to produce from a plurality of left-side microphones a wind-noise-reduced left side output signal, and to produce from a plurality of right-side microphones a wind-noise-reduced right side output signal.

20. A device for wind noise reduction, the device comprising: a first omnidirectional microphone and a second omnidirectional microphone; a processor for calculating first and second signal weights in a manner to minimise the power of an output signal; and a first multiplication block configured to apply the first signal weight to a first microphone signal from the first omnidirectional microphone, and a second multiplication block configured to apply the second signal weight to a second microphone signal from the second omnidirectional microphone; and a summation block configured to sum the weighted first and second microphone signals together to produce the output signal.

21. The device of claim 20 wherein the first and second signals are frequency domain samples, and wherein the processor is configured to calculate a weighting factor a, for each subband i, and to apply the a.sub.i on a subband—by—subband basis to give different mixing ratios at different frequencies, and wherein the processor is configured to give a higher weighting to frequencies deemed to be more important for wind noise suppression.

22. The device of claim 20 further comprising a third omnidirectional microphone, and wherein the processor is configured to calculate a third signal weight in a manner that the first to third signal weights when applied to the respective signals minimise the power of an output signal Y which is calculated by the processor as follows:
Y=a*primary_mic+b*secondary_mic+(1−a−b)*tertiary_mic where $a=\frac{{\left(.Math..Math.x^2\right)}^{-1}}{{\left(.Math..Math.x^2\right)}^{-1}+{\left(.Math..Math.y^2\right)}^{-1}+{\left(.Math..Math.z^2\right)}^{-1}},\mathrm{and}$ $b=\frac{{\left(.Math..Math.y^2\right)}^{-1}}{{\left(.Math..Math.x^2\right)}^{-1}+{\left(.Math..Math.y^2\right)}^{-1}++.Math.{\left(.Math..Math.z^2\right)}^{-1}}.$ and where x=signal sample of the first microphone signal, y=signal sample of the second microphone signal; and z=signal sample of the third microphone signal.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0035] An example of the invention will now be described with reference to the accompanying drawings, in which:

[0036] FIG. 1 illustrates the layout of microphones of a handheld device in accordance with one embodiment of the invention;

[0037] FIG. 2 is a schematic illustration of signal mixing for wind noise reduction in accordance with one embodiment of the invention;

[0038] FIG. 3 is a schematic illustration of sub-band signal mixing for wind noise reduction in accordance with another embodiment of the invention; and

[0039] FIG. 4 illustrates another embodiment in which the mixing procedure is performed in respect of three microphones, in subbands.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0040] FIG. 1 illustrates a handheld smartphone device 100 with touchscreen 110, button 120 and microphones 132, 134, 136, 138. The following embodiments describe the capture of audio using such a device, for example to accompany a video recorded by a camera (not shown) of the device or for use as a captured speech signal during a telephone call. Microphone 132 captures a first microphone signal, and microphone 134 captures a second microphone signal. Microphone 132 is mounted in a port on a front face of the device 100, while microphone 134 is mounted in a part on an end face of the device 100. Thus, the port configuration will give microphones 132 and 134 differing susceptibility to wind noise, based on the small scale device topography around each port and the resulting different effects in airflow past each respective port. Consequently, the signal captured by microphone 132 will suffer from wind noise in a different manner to the signal captured by microphone 134.

[0041] FIG. 2 illustrates the manner in which the signals from microphones 132 and 134 are mixed in order to produce an output signal carrying reduced wind noise. The signals from the first and second microphones are passed to an optimisation block 220. Block 220 calculates a weight a, and at 230 a value (1−a) is produced, which are the respective weights applied to the first and second microphone signals before producing the output signal at 240.

[0042] In the present embodiment, the weight a is calculated by the processor 220 as follows:

[00004]$a=\frac{.Math..Math.y^2-.Math..Math.\mathrm{xy}}{.Math..Math.x^2-2.Math..Math..Math..Math.\mathrm{xy}+.Math..Math.y^2}$

where:

[0043] x=signal sample of the first microphone signal, and

[0044] y=signal sample of the second microphone signal.

[0045] The derivation of the above formula is found by using the constraint that the total power of the output wind-noise-reduced signal is to be minimised. It is noted that:

Energy=Σ(ax(t)+(1−a)y(t)).sup.2

Thus, differentiating with respect to a to find the point of minimum energy gives:

[00005]$\begin{array}{c}\frac{\mathrm{dEnergy}}{\mathrm{da}}=.Math.0\\ =.Math.2.Math.a\left(.Math..Math.x^2-2.Math..Math..Math..Math.\mathrm{xy}+.Math..Math.y^2\right)+2.Math.\left(.Math..Math.\mathrm{xy}-.Math..Math.y^2\right)\end{array}$

Solving for a gives:

[00006]$a=\frac{.Math..Math.y^2-.Math..Math.\mathrm{xy}}{.Math..Math.x^2-2.Math..Math..Math..Math.\mathrm{xy}+.Math..Math.y^2}$

[0046] To implement this requirement, the primary mic and secondary mic signals are buffered and the buffer signals are used as the inputs to the optimization algorithm. The algorithm outputs the mixing coefficient ‘a’ within a range of 0 and 1, inclusive. The value of a is then smoothed with a leaky integrator and constrained to the range between 0 and 1, inclusive.

[0047] The output signal produced at 240 is thus:

output=a*primary_mic+(1−a)*secondary_mic

[0048] If we assume the microphone signals are not correlated in wind, the equation can be simplified as

[00007]$a=\frac{{\left(.Math..Math.x^2\right)}^{-1}}{{\left(.Math..Math.x^2\right)}^{-1}+{\left(.Math..Math.y^2\right)}^{-1}}.$

However this simplified equation is less optimal if speech is present during wind.

[0049] The present invention can in other embodiments be extended to producing a wind-noise-reduced output from 3 or more microphone inputs. For three microphones, where z is the input from the tertiary microphone:

Y=a*primary_mic+b*secondary_mic+(1−a−b)*tertiary_mic

[0050] In one embodiment for reducing wind noise, involving the use of three input microphone signals:

[00008]$a=\frac{{\left(.Math..Math.x^2\right)}^{-1}}{{\left(.Math..Math.x^2\right)}^{-1}+{\left(.Math..Math.y^2\right)}^{-1}+{\left(.Math..Math.z^2\right)}^{-1}},\mathrm{and}$$b=\frac{{\left(.Math..Math.y^2\right)}^{-1}}{{\left(.Math..Math.x^2\right)}^{-1}+{\left(.Math..Math.y^2\right)}^{-1}++.Math.{\left(.Math..Math.z^2\right)}^{-1}}.$

[0051] In another embodiment for reducing wind noise, involving the use of three input microphone signals, the primary mic input and secondary mic input are mixed using equation (1) to determine a mixing factor A. Next, the mixed result produced by applying A and (1−A) weights to the primary and secondary signals is processed together with the tertiary input, to determine a mixing factor B. The mixing coefficient is then calculated as a=A*B and b=(1−A)*B.

[0052] FIG. 3 illustrates an embodiment in which the mixing procedure is performed in subbands. In subband processing, the mixing coefficient ‘a’ is calculated in each subband i. For complex inputs (for example, in the DFT domain):

[00009]$a=\frac{.Math..Math.{.Math.y.Math.}^2-\mathrm{real}.Math..Math.\left(.Math..Math.x*\stackrel{\_}{y}\right)}{.Math..Math.{.Math.x.Math.}^2-2*\mathrm{real}.Math..Math.\left(.Math..Math.x*\stackrel{\_}{y}\right)+.Math..Math.{.Math.y.Math.}^2},$ [0053] where y is the complex conjugate of y, |y| is the absolute value of y and real( ) is a function that takes the real part of the complex input.

[0054] The FIR filter 360 can be built from an inverse DFT of the array of the ‘a.sub.i’ values.

[0055] While the preceding describes the mixing of the signals from microphones 132 and 134 in order to produce a first wind-noise-reduced signal, it is to be noted that the signals from microphones 136 and 138 may also be similarly mixed in accordance with the present invention in order to produce a second wind-noise-reduced signal. Microphone 136 captures a first (primary) right signal R.sub.1, and microphone 138 captures a second (secondary) right signal R.sub.2. The first and second wind-noise-reduced signals may then be processed by subsequent stages as desired, and for example could be input to an adaptive directional microphone stage, or could be used for stereo processing to retain binaural cues, or could be used for other multi-channel audio functions as appropriate.

[0056] FIG. 4 illustrates an embodiment in which the mixing procedure is performed in respect of three microphones, in subbands. In this embodiment the third input is a beamforming output produced in a preceding stage (not shown) by using the signals from the primary mic and secondary mic. This arrangement is particularly advantageous because wind tends to dominate in the low frequency, and so in the low frequency bands the wind noise power is reduced by the mixing procedure of the present invention. In the other, higher, frequency bands where there is less wind noise impact, the beamforming reduces environmental noise. Thus in the high frequency bands the mixing procedure will weight strongly towards the beamforming output. In this scenario, both wind noise and environmental noise from certain directions will be reduced. In other embodiments the third input could simply be from another microphone or another signal processing stage, as appropriate.

[0057] It will be appreciated by persons skilled in the art that numerous variations and/or modifications may be made to the invention as shown in the specific embodiments without departing from the spirit or scope of the invention as broadly described. The present embodiments are, therefore, to be considered in all respects as illustrative and not limiting or restrictive.