Patent Publication Number: US-8116474-B2

Title: System for suppressing ambient noise in a hands-free device

Description:
CLAIM OF PRIORITY 
     This patent application is a continuation of U.S. patent application Ser. No. 10/497,748 filed Feb. 9, 2005 now U.S. Pat. No. 7,315,623, which is hereby incorporated by reference. 
    
    
     FIELD OF THE INVENTION 
     The invention relates to suppressing ambient noise in a hands-free device having two microphones spaced a predetermined distance apart. 
     RELATED ART 
     Ambient noise represents a significant interference factor for the use of hands-free devices, which interference factor can significantly degrade the intelligibility of speech. Car phones are equipped with hands-free devices to allow the driver to concentrate fully on driving the vehicle and on traffic. However, particularly loud and interfering ambient noise is encountered in a vehicle. 
     There is a need for a technique of suppressing ambient noise for a hands-free device. 
     SUMMARY 
     A hands-free device is equipped with two microphones spaced a predetermined distance apart. The distance selected for the speaker relative to the microphones is smaller than the so-called diffuse-field distance, so that the direct sound components from the speaker at the location of the microphones predominate over the reflective components occurring within the space. 
     From the microphone signals supplied by the microphones, the sum and difference signal is generated from which the Fourier transform of the sum signal and the Fourier transform of the difference signal are generated. 
     From these Fourier transforms, the speech pauses are detected, for example, by determining their average short-term power levels. During speech pauses, the short-term power levels of the sum and difference signal are approximately equal, since for uncorrelated signal components it is unimportant whether these are added or subtracted before the calculation of power, whereas, based on the strongly correlated speech component, when speech begins the short-term power within the sum signal rises significantly relative to the short-term power in the difference signal. This rise is easily detected and exploited to reliably detect a speech pause. As a result, a speech pause can be detected with great reliability even in the case of loud ambient noise. 
     The spectral power density is determined from the Fourier transform of the sum signal and from the Fourier transform of the difference signal, from which the transfer function for an adaptive transformation filter is calculated. By multiplying the power density of the Fourier transform of the difference signal by its transfer function, this adaptive transformation filter generates the interference power density. From the spectral power density of the Fourier transform of the sum signal and from the interference power density generated by the adaptive transformation filter, the transfer function of an analogous adaptive spectral subtraction filter is calculated that filters the Fourier transform of the sum signal and supplies an audio signal essentially free of ambient noise at its output in the frequency domain, which signal is transformed back to the time domain using an inverse Fourier transform. At the output of this inverse Fourier transform, an audio or speech signal essentially free of ambient noise can be picked up in the time domain and then processed further. 
     These and other objects, features and advantages of the present invention will become more apparent in light of the following detailed description of preferred embodiments thereof, as illustrated in the accompanying drawing. 
    
    
     
       DESCRIPTION OF THE DRAWING 
       The FIGURE is a block diagram illustration of a device for suppressing ambient noise in a hands-free device. 
     
    
    
     DETAILED DESCRIPTION 
     The output of a first microphone  100  is provided on a line  102  to an adder  104  and a subtracter  106 , while a second microphone  108  provides a sensed signal on a line  110  to the adder  104  and the subtracter  106 . The adder  104  provides an output on a line  112  to a first Fourier transformer  114 , the output of which on a line  116  is input to a speech pause detector  118 , to a first arithmetic unit  120  to calculate the spectral power density S rr  of the Fourier transform R(f) of the sum signal, and to an adaptive spectral subtraction filter  122 . 
     The subtracter  106  provides a difference signal on line  124  to a second Fourier transformer  126 , the output of which on a line  128  is connected to the speech pause detector  118  and to a second arithmetic unit  130  to calculate the spectral power density S DD  of the Fourier transform D(f) of the difference signal on the line  124 . The first arithmetic unit  120  provides an output on a line  129  to a third arithmetic unit  132  to calculate the transfer function of an adaptive transformation filter  140 , and to the adaptive spectral subtraction filter  122 , the output of which is connected to an inverse Fourier transformer  160 . The second arithmetic unit  130  provides a signal on line  133 , indicative of the spectral power density S DD , to the third arithmetic unit  132 , and to an adaptive transformation filter  140 , the output of which is connected to the adaptive spectral subtraction filter  122 . The output of the speech pause detector  118  is also connected to the third arithmetic unit  132 , that provides an output which is connected to the control input of the adaptive transformation filter  140 . 
     As mentioned above, the two microphones  100  and  108  are separated a distance which is smaller than the so-called diffuse-field distance. For this reason, the direct sound components of the speaker predominate at the site of the microphone over the reflection components occurring within a closed space, such as the interior of a vehicle. 
     The short-term power of the Fourier transform R(f) on the line  116  of the sum signal and of the Fourier transform D(f) on the line  128  of the difference signal is determined in the speech pause detector  118 . During pauses in speech, the two short-term power levels differ hardly at all since it is unimportant for the uncorrelated speech components whether they are added or subtracted before the power calculation. When speech begins, on the other hand, the short-term power within the sum signal rises significantly relative to the short-term power in the difference signal due to the strongly correlated speech component. This rise thus indicates the end of a speech pause and the beginning of speech. 
     The first arithmetic unit  120  uses time averaging to calculate the spectral power density S rr  of the Fourier transform R(f) on the line  116 . Similarly, the second arithmetic unit  130  calculates the spectral power density S DD  of the Fourier transform D(f) on the line  128 . From the power density S rrp (f) and the spectral power density S DDp (f) during the speech pauses, the third arithmetic unit  132  calculates the transfer function H T (f) of the adaptive transformation filter  140  using the following equation:
 
 H   T ( f )= S   rrp ( f )/ S   DDp ( f )  (1)
 
     Preferably, an additional time averaging—that is, a smoothing—of the coefficients of the transfer function thus obtained is used to significantly improve the suppression of ambient noise by preventing the occurrence of so-called artifacts, often called “musical tones.” 
     The spectral power density S rr (f) is obtained from the Fourier transform R(f) of the sum signal on the line  116  by time averaging, while in analogous fashion the spectral power density S DD (f) is calculated by time averaging from the Fourier transform D(f) of the difference signal on the line  128 . 
     For example, the spectral power density S rr  is calculated using the following equation (2):
 
 S   rr ( f,k )= c*|R ( f )| 2 +(1− c )* S   rr ( f,k− 1)  (2)
 
     In analogous fashion, the spectral power density S DD (f) is, for example, calculated using the equation (3):
 
 S   DD ( f,k )= c*|D ( f )| 2 +(1− c )* S   DD ( f,k− 1)  (3)
 
The term c is a constant between 0 and 1 which determines the averaging time period. When c=1, no time averaging takes place; instead the absolute squares of the Fourier transforms R(f) and D(f) are taken as the estimates for the spectral power densities. The calculation of the residual spectral power densities required to implement the method according to the invention is preferably performed in the same manner.
 
     The adaptive transformation filter  140  uses its transfer function H T (f) to generate the interference power density S nn  on line  152  from the spectral power density S DD (f) on the line  154  using the following equation (4):
 
 S   nn ( f )= H   T   *S   DD ( f )  (4)
 
Using the interference power density S nn  on the line  152  and the spectral power density S rr  on the line  156  the transfer function H sub  of the spectral subtraction filter  122  is calculated as specified by equation (5):
 
 H   sub ( f )=1− a*S   nn ( f )/ S   rr ( f ) for 1− a*S   nn ( f )/ S   rr ( f )&gt; b  
 
 H   sub ( f )= b  for 1− a*S ( f )/ S   rr ( f )≦ b  
 
The parameter a represents the so-called overestimate factor, while b represents the so-called “spectral floor.”
 
     The interference components picked up by the microphones  100  and  108 , which strike the microphones as diffuse sound waves, can be viewed as virtually uncorrelated for almost the entire frequency range of interest. However, there does exist for low frequencies a certain correlation dependent on the relative spacing of the two microphones, which correlation results in the interference components contained in the reference signal appearing to be high-pass-filtered to a certain extent. In order to prevent a faulty estimation of the low-frequency interference components in the spectral subtraction, a spectral boost of the low-frequency components of the reference signal is performed by the adaptive transformation filter  140 . 
     The method according to the invention and the hands-free device according to the invention, which are particularly suitable for a car phone, are distinguished by excellent speech quality and intelligibility since the estimated value for the interference power density S nn  on the line  152  is continuously updated independently of the speech activity. As a result, the transfer function of the spectral subtraction filter  122  is also continuously updated, both during speech activity and during speech pauses. As was mentioned above, speech pauses are detected reliably and precisely, this detection being necessary to update the transformation filter  140 . 
     The audio signal at the output on line  158  of the spectral subtraction filter  122 , which signal is essentially free of ambient noise, is fed to the inverse Fourier transformer  160  which transforms the audio signal back to the time domain. 
     Although the present invention has been illustrated and described with respect to several preferred embodiments thereof, various changes, omissions and additions to the form and detail thereof, may be made therein, without departing from the spirit and scope of the invention.