System for suppressing ambient noise in a hands-free device
View Patent ↗In order to suppress as much noise as possible in a hands-free device in a motor vehicle, for example, two microphones (M 1 , M 2 ) are spaced a certain distance apart, the output signals (MS 1 , MS 2 ) of which are added in an adder (AD) and subtracted in a subtracter (SU). The sum signal (S) of the adder (AD) undergoes a Fourier transform in a first Fourier transformer (F 1 ), and the difference signal (D) of the subtracter (SU) undergoes a Fourier transform in a second Fourier transformer (F 2 ). From the two Fourier transforms R(f) and D(f), a speech pause detector (P) detects speech pauses, during which a third arithmetic unit (R) calculates the transfer function H T of an adaptive transformation filter (TF). The transfer function of a spectral subtraction filter (SF), at the input of which the Fourier transform R(f) of the sum signal (S) is applied, is generated from the spectral power density S rr of the sum signal (S) and from the interference power density S nn generated by the adaptive transformation filter (TF). The output of the spectral subtraction filter (SF) is connected to the input of an inverse Fourier transformer (IF), at the output of which an audio signal (A) can be picked up in the time domain which is essentially free of ambient noise.
1. A noise reduction system, comprising:
an adder that sums first and second input audio signals to provide a sum signal;
a subtractor that subtracts the first input audio signal from the second input audio signal to provide a difference signal;
a speech pause detector that compares the sum and the difference signals to generate a speech pause signal;
first and second arithmetic units, each of which respectively determines a spectral power density of the sum signal or the difference signal;
an adaptive transformation filter that processes the spectral power density of the difference signal, as a function of the speech pause signal, to estimate an interference power density; and
an adaptive spectral subtraction filter that filters the sum signal, as a function of the spectral power density of the sum signal and the interference power density, to provide a filtered output signal.
2. The system of claim 1 , further comprising first and second microphones, where first microphone generates the first input audio signal, and where the second microphone generates the second input audio signal.
3. The system of claim 1 , further comprising:
a first time-to-frequency domain transformation unit that receives the sum signal in a time domain, and provides the sum signal to the speech pause detector, the first arithmetic unit and the adaptive spectral subtraction filter in a frequency domain; and
a second time-to-frequency domain transformation unit that receives the difference signal in the time domain, and provides the difference signal to the speech pause detector and the second arithmetic unit in the frequency domain.
4. The system of claim 3 , further comprising a frequency-to-time domain transformation unit that provides the filtered output signal in a time domain.
5. The system of claim 1 , further comprising a third arithmetic unit that processes the spectral power densities of the sum and the difference signals, as a function of the speech pause signal, to update a transfer function H T of the adaptive transformation filter.
6. The system of claim 1 , where the speech pause detector compares the sum and the difference signals by comparing short-term power levels of the sum and the difference signals.
7. The system of claim 1 , where the first and the second arithmetic units use time averaging to determine the spectral power densities of the sum and the difference signals.
8. A method for reducing signal noise, comprising:
processing first and second input audio signals to provide sum and difference signals;
detecting a speech pause by comparing the sum and the difference signals;
respectively determining spectral power densities of the sum and the difference signals;
processing the spectral power density of the difference signal, as a function of the speech pause signal, to estimate an interference power density; and
reducing signal noise in the sum signal with an adaptive filter, as a function of the spectral power density of the sum signal and the interference power density, to provide an audio signal.
9. The method of claim 8 , where the processing the first and the second input audio signals comprises:
summing first and second input audio signals to provide the sum signal; and
subtracting the first input audio signal from the second input audio signal to provide the difference signal.
10. The method of claim 8 , where the signal noise is reduced in the sum signal to suppress ambient noise for a hands-free device.
11. The method of claim 8 , further comprising respectively generating the first and the second input audio signals with first and second microphones.
12. The method of claim 8 , where
the processing of the first and the second input audio signals is performed in a time domain; and
the detecting of the speech pause, the determining of the spectral densities, the adaptively processing of the spectral power density of the difference signal, and the reducing of the signal noise are performed in a frequency domain.
13. The method of claim 12 , further comprising transforming the audio signal from the frequency domain to the time domain.
14. The method of claim 8 , further comprising processing the spectral power densities of the sum and the difference signals, as a function of the speech pause signal, to update a transfer function H T of a transformation filter, where the interference power density is estimated using the transformation filter with the updated transfer function H T .
15. The method of claim 8 , where the comparing of the sum and the difference signals comprises comparing a difference between short-term power levels of the sum and the difference signals.
16. The method of claim 8 , where the spectral power densities of the sum and the difference signals are determined using time averaging.