Abstract:
In a video conferencing system, camera position means are used to point the camera to a speaking person. To find the correct direction for the camera, a system is required that determines the position from which the sound is transmitted. This can be done by using at least two microphones receiving the speech signal. By measuring the transmission delay between the signals received by the microphones, the position of the speaker can be determined. According to the present invention, the delay is determined by first determining the impulse responses (h 1 ) and (h 2 ) and subsequently calculating a cross correlation function between the impulse responses (h 1 ) and (h 2 ). From the main peak in the cross correlation function, the delay value is determined.

Description:
BACKGROUND OF THE INVENTION 
     The present invention relates to a signal source localization arrangement comprising a plurality of receivers having different positions, the signal source localization arrangement comprising delay estimation means for estimating a delay difference between the signals received by at least two receivers, and position determining means for determining from the delay difference a signal source location. 
     The present invention relates also to a delay estimation arrangement, a video communication system and a signal source localization method. 
     An arrangement according to the preamble is known from the article “Voice source localization for automatic camera pointing system in videoconferencing” by Hong Wang and Peter Chu in IEEE, ASSP workshop on applications of signal processing to audio and acoustics, 1997. 
     Signal localization arrangements are used in several applications. A first example of such applications is automatic camera pointing in video conferencing systems or in security systems. Another application is the determination of the position of a user of an audio system, in order to be able to optimize the reproduction of the audio at said position. 
     Signal localization arrangements using a plurality of receivers are often based on the determination of a delay difference between the signals at the outputs of the receivers. If the position of the receivers and a delay difference between the propagation paths between the source and the different receivers are known, the position of the source can be determined. If two receivers are used, it is possible to determine the direction with respect to the baseline between the receivers. If three receivers are used, it becomes possible to determine a position of the source in a 2-D plane. If more than 3 receivers, being not placed in a single plane, are used, it becomes possible to determine the position of a source in three dimensions. 
     In the prior art signal localization arrangements, the delay difference is determined by calculating a cross-correlation function between the signals received by the different receivers. The delay difference is then equal to the delay value in the cross-correlation function at which the highest correlation value occurs. 
     A problem with the prior art signal localization arrangement is that its operation depends heavily on the properties of the signal generated by the source. Especially voiced speech signals in a reverberant environment can disturb the operation. To reduce this large influence of the signal properties, a long averaging time has to be used in determining the cross-correlation function of the received signals. 
     SUMMARY OF THE INVENTION 
     The object of the present invention is to provide a signal localization arrangement in which the adverse influence of the signal properties has been reduced. 
     To achieve said purpose, the signal localization arrangement is characterized in that the signal source localization arrangement comprises impulse response determining means for determining a plurality of functions representing the impulse responses of the paths between the signal source and the receivers, and in that the delay estimation means are arranged for determining the delay difference from said functions. 
     A function representing the impulse response is a function that represents an important aspect of the impulse response, but it may differ substantially in other aspects from the real impulse response of the paths between signal sources and receivers. 
     By determining the delay difference from functions representing the impulse responses of the paths between the signal source and the receivers instead of from the received signals themselves, the influence of the properties of the signals on the determination of the delay difference is strongly reduced. Experiments have shown that the averaging time to be used in the determination of the delay difference can be strongly reduced. 
     Preferably, the delay difference is determined by calculating a cross correlation function of the functions representing the impulse responses. 
     An embodiment of the invention is characterized in that the impulse response determining means comprise adjustable filters for deriving filtered signals from the signals provided by the receivers, the signal source localization arrangement comprising combining means for deriving a combined signal from the filtered signals, in that the impulse response determining means comprises control means for controlling the adjustable filters in order to maximize a power measure of the combined signal, and in that the control means are arranged for limiting a combined power gain measure of the filtered audio signals to a predetermined value. 
     By combining a plurality of filtered signals and adjusting the filters for maximizing a power of the combined signal under the constraint of a limited combined power gain measure, it is obtained that the filters converge to a transfer function leading to filtered signals having a maximum degree of coherence before they are added. This means that the delay differences between the impulse responses of the adjustable filters correspond to the delay difference between the signals at the outputs of the receivers. 
     A further embodiment of the invention is characterized in that the control means comprise a plurality of further adjustable filters having a transfer function being the conjugate of the transfer function of the adjustable filters, said further adjustable filters being arranged for deriving from the combined audio signal filtered combined audio signals, and in that the control means are arranged for maximizing the power measure of the combined audio signal, and for restricting a combined power gain measure of the processed audio signals to a predetermined value by controlling the transfer functions of the adjustable filters and the further adjustable filters in order to minimize a difference measure between the input audio signals and the filtered combined audio signal corresponding to said input audio signals. 
     Experiments have shown that by using two sets of adjustable filters, the quality of the speech signal can be further enhanced. By minimizing a difference measure between the input audio signal and the corresponding filtered combined audio signal, it is obtained that a power measure of the combined audio signal is maximized under the constraint that per frequency component the sum of the power gains of the adjustable filters is equal to a predetermined constant. The correspondence between the two criteria mentioned above will be shown in the detailed description of the drawings by using a simplified example. 
    
    
     BRIEF DESCRIPTION OF THE DRAWING 
     The present invention will now be explained with reference to the drawings. 
     FIG. 1 shows a block diagram of a video communication system using a signal source localization means according to the invention. 
     FIG. 2 shows a general block diagram of impulse response determining means according to the present invention. 
     FIG. 3 shows a more detailed impulse response determining means according to the invention in which frequency domain adaptive and frequency domain programmable filters are used; 
     FIG. 4, shows an embodiment of the normalization means  73  used in the arrangement according to FIG.  2 . 
     FIG. 5 shows an implementation of the frequency domain adaptive filters  62 ,  66  and  68  used in FIG. 3; 
     FIG. 6 shows an implementation of the frequency domain programmable filters  44 ,  46  and  50  used in FIG. 3; 
     FIG. 7 shows an implementation of the impulse response determining means according to the invention in which time domain adaptive filters and time domain programmable filters are used. 
    
    
     DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     In the video communication system according to FIG. 1 a microphone  1  is connected to impulse response determining means  5 , and a microphone  2  is connected to impulse response determining means  6 . Additional microphones  3  and  4  can be added to corresponding impulse response determining means in order to be able to determine, besides the direction, the exact position of the signal source in two or three dimensions. The impulse response determining means  5  and  6  determine a function representing the impulse response from the signal source to the respective microphones. 
     The outputs of the impulse response determining means  5  and  6 , carrying the functions representing the impulse responses, are connected to inputs of correlation calculation means  7 . 
     If the impulse response determining means  5  and  6  operate in the frequency domain, they will provide Fourier transforms W 1 * and W 2 * of the estimates of the impulse responses h 1  and h 2 . The crosscorrelation function can now be easily determined by first determining the cross power spectrum according to 
     
       
         Φ w   1 ,w 2 ( f )= W   1   ·W   2 *  (1) 
       
     
     In (1) W 2  is the complex conjugate of the function W 2 * provided by the impulse response determining means. From the function Φw 1 ,w 2  (f) the cross-correlation function ρw 1 ,w 2  (k) can be determined by performing an IFFT on the function 
     In the impulse response determining means  5  and  6  operate in the time domain, the functions h 1  and h 2  will be provided by these impulse response determining means. In that case, the cross-correlation function ρw 1 ,w 2  (k) can be calculated according to:                        ρ       w   1          w   2              (   k   )       =       ∑     n   =   0       n   =   N                           h   1          (   k   )       ·       h   2          (     n   -   k     )             ;                k   =   0       ,   1   ,   ⋯              ,     N   -   1            
                  ρ       w   1          w   2              (   k   )       =       ∑     n   =     -   k         N   -   1                           h   1          (   k   )       ·       h   2          (     n   -   k     )             ;                k   =     -     (     N   -   1     )           ,   ⋯              ,     -   1               (   2   )                                
     In (2) N is the length of h 1  and h 2 . 
     After the function ρw 1 ,w 2  (k) has been determined, the resolution of this function can be improved by upsampling the function ρw 1 ,w 2  (k) by introducing samples with value zero between the non-zero samples, followed by an interpolation. Useful interpolation factors are in the range from 4 to 8. 
     The (upsampled and interpolated) cross correlation function is passed by the correlation function determining means  7  to delay difference calculating means  8 . These delay difference calculation means  8  determine the value of k having the largest correlation value. The corresponding delay difference Δ is then equal to k·T s  in which T s  is the sampling period. 
     The output of the delay calculating means  8  is connected to the input of position calculating means. If two receivers are used, the direction θ defined as the angle between the connection line between the receivers and the direction of the source can be calculated according to:              θ   =     arccos        (       c   ·   k   ·     T   s       d     )               (   3   )                                
     In (3) c is the propagation speed of the signal to be received and d is the distance between the receivers. A signal representing the angle θ is passed to camera positioning means  10  which rotates the position of the camera over an angle θ with respect to the baseline between the receivers  1  and  2 . 
     In the impulse response determining means according to FIG. 2, an output of a first receiver, being here a microphone  1 , is connected to a first input of the impulse response determining means  5 , 6  and an output of a second receiver, being here a microphone  2 , is connected to a second input of the impulse response determining means  5 , 6 . 
     If it is assumed that the microphones  4  and  6  receive a signal V IN  via propagation paths with impulse responses H 1  and H 2  respectively, the output signal of microphone  1  is equal H 1 ·V IN  and the output signal of microphone  2  is equal to H 2 ·V IN . The output of the microphone  1  is connected to an input of a filter  10  with transfer function W 1 , and the output of the microphone  2  is connected to an input of a filter  12  with transfer function W 2 . At the output of the filters  10  and  12  the processed signals V P  and V Q  are available. For these processed signals can be written: 
     
       
           V   P   =H   1   ·W   1   ·V   IN   (4) 
       
     
     and 
       V   Q   =H   2   ·W   2   ·V   IN   (5) 
     At the output of the combination means  18  the sum V SUM  of the processed signals V P  and V Q  is available. This signal V SUM  is equal to: 
     
       
           V   SUM =( H   1   ·W   1   +H   2   ·W   2 ) V   IN   (6) 
       
     
     The output of the adder  18  is connected to the input of two further adjustable filters  14  and  16 . The further adjustable filters  14  and  16  derive filtered combined signals from the combined signal using transfer functions W 1 * and W 2 *. The first filtered combined signal is equal to 
     
       
           V   FC1 =( H   1   ·W   1   +H   2   ·W   2 )· W   1   *·V   IN   (7) 
       
     
     and the second filtered combined signal is equal to: 
     
       
           V   FC2 =( H   1   ·W   1   +H   2   ·W   2 )· W   2   *·V   IN   (8) 
       
     
     A first difference measure between the first input audio signal and the first filtered combined audio signal is determined by a subtractor  24 . For the output signal of the subtractor  24  can be written: 
     
       
           V   DIFF1   ={H   1 −( H   1   ·W   1   +H   2   ·W   2 )· W   1   *}·V   IN   (9) 
       
     
     A second difference measure between the second input audio signal and the second scaled combined audio signal is determined by a subtractor  26 . For the output signal of the subtractor  26  can be written: 
     
       
           V   DIFF2   ={H   2 −( H   1   ·W   1   +H   2   ·W   2 )· W   2   *}·V   IN   (10) 
       
     
     The arrangement according to FIG. 2 comprises a control element  20  for adjusting the coefficients of filter  10  and  14  to make the power of the output signal of V DIFF1  of the subtractor  24  equal to 0. The arrangement further comprises a control element  22  for adjusting the coefficients of filter  12  and  16  to make the power of the output signal V DIFF2  of the subtractor  26  equal to 0. In order to find the values for x and y to make both difference signals equal to 0, the following set of equations has to be solved: 
     
       
         ( H   1   ·W   1   +H   2   ·W   2 )· W   1   *=H   1   (11) 
       
     
     
       
         ( H   1   ·W   1   +H   2   ·W   2 )· W   2   *=H   2   (12) 
       
     
     Eliminating the term (H 1 ·W 1 +H 2 ·W 2 ) from (11) and (12) by dividing (11) by (12) results in:                  W   1   *       W   2   *       =           H   1       H   2       ⇒     W   1   *       =         H   1     ·     W   2   *         H   2                 (   13   )                                
     By conjugating the left-hand side and the right-hand side of (13) for W 1  can be written:                  W   1               W   2               =           H   1   *       H   2   *       ⇒     W   1       =         H   1   *     ·     W   2         H   2   *                 (   14   )                                
     Substituting (14) into (12) gives the following expression:                  (                  H   1          2     ·     W   2         H   2   *       +       H   2     ·     W   2         )     ·     W   2   *       =     H   2             (   15   )                                
     Rearranging (15) gives for |W 2 | 2 :                       W   2          2     =              H   2          2                H   1          2     +            H   2          2                 (   16   )                                
     For |W 1 | 2  can be found in the same way:                       W   1          2     =              H   1          2                H   1          2     +            H   2          2                 (   17   )                                
     From (16) and (17) it is clear that the value of |W 1 | 2  increases when |H 1 | 2  increases (or |H 2 | 2  decreases) and that the value of |W 2 | 2  increases when |H 2 | 2  increases (or |H 1 | 2  decreases). In such a way the strongest input signal is pronounced. This is of use to enhance a speech signal of a speaker over background noise and reverberant components of the speech signal without needing to know the frequency dependence of the paths from the speaker to the microphones as was needed in the prior art arrangement. 
     Below will be demonstrated that maximizing the power of the combined audio signal under the constraint that the sum of the power gains of the processing means is limited, results in the same values for |H 1 | 2  and |H 2 | 2  as making the output signals of the subtractors  24  and  26  equal to 0. 
     For the power measure P SUM  of the combined audio signal V SUM  can be written: 
       P   SUM   =V   SUM   2   =|H   1   ·W   1   +H   2   ·W   2 | 2   ·V   IN   2   (18) 
     For the boundary condition that the sum of the power gains of the scaling means is limited to a constant value can be stated: 
     
       
           G   P   =|W   1 | 2   +|W   2 | 2 =1  (19) 
       
     
     Consequently, the term |H 1 ·W 1 +H 2 ·W 2 | 2  has to be maximized under the boundary condition |W 1 | 2 +|W 2 | 2 −1=0. This can be done by using the well-known Lagrange multiplier method. According to said method, the following expression has to be maximized: 
     
       
         (| H   1   ·W   1   +H   2   ·W   2 | 2 +λ·(| H   1 | 2   +|H   2 | 2 −1)  (20) 
       
     
     Differentiating (20) with respect to Re{W 1 }, Jm{W 1 }, Re{W 2 } and Jm{W 1 } and setting the derivatives to zero gives four equations with four variables. By solving these equations, and calculating the values of |W 1 | 2  and |W 2 | 2  (16) and (17) are found. Consequently it is clear that controlling W 1  and W 2  to make the difference signals equal to 0 is equivalent to maximizing the power of the combined signal under the boundary condition that the sum of the power gains of the different branches of the processing means is limited to a maximum value. The above can easily be generalized for N input signals each having a transfer factor H i  with 1≦i≦N. If it assumed that the processing means have N branches each corresponding to a signal i and having a power transfer factor |W i | 2 , for these values of |W i | 2  can be written:                       W   i          2     =              H   i          2         ∑     i   =   1     N                            H   i          2                 (   21   )                                
     It is observed that in general it is not possible to make the output signals of the subtractors exactly equal to zero, because the impulse response of the transmission paths cannot exactly be modeled by commonly used digital filters with reasonable complexity. In practice, the power of the output signals of the subtractors averaged over a given period in minimized. This way of operating the adaptive filters has turned out to be effective. In the present implementation, the functions representing the impulse response have the property that the differences of their phases is equal to the differences of the phases in the impulse responses of the transmission paths from the signal source to the receivers. This is one possibility for functions representing the impulse reponse of the transmission paths, but it is obvious that different functions could be used. 
     In the impulse response determining means  5 , 6  to FIG. 3, input signals from audio sources being here microphones  30 ,  32  and  34  are converted into digital signals which are converted into block of L samples by respective series to parallel converters  36 ,  38  and  40 . The output of the series to parallel converters  36 ,  38  and  40  are connected to corresponding inputs of the processing means  41 , and to input of respective block delay elements  54 ,  56  and  58 . 
     In the processing means  41  the output signal of the series to parallel converter  36  is applied to a block concatenation unit  42 . The block concatenating unit  42  constructs blocks of N+L samples from the present block of L samples and N samples from previous blocks of samples available at the output of the series to parallel converter  36 . The output of the block concatenation unit  42  is connected to an input of a frequency domain programmable filter  44 . The output of the frequency domain programmable filter  44 , carrying a processed audio signal, is connected to a first input of the combining means being here an adder  76 . The frequency domain programmable filter  44  presents blocks of N+L samples at its output. 
     In the same way the output signal of the series to parallel converter  38  is processed by a block concatenating unit  48  and a frequency domain programmable filter  46  and the output signal of the series to parallel converter  40  is processed by a block concatenating unit  52  and a frequency domain programmable filter  50 . Outputs of the frequency domain programmable filters  46  and  50 , carrying processed audio signals, are connected to corresponding inputs of the adder  76 . 
     The output of the adder  76  is connected to an input of an IFFT unit  77  which determines an Inverse Fast Fourier Transformed signal from the output signal of the adder  76 . The output of the IFFT unit  77  is connected to an input of a unit  79  which discards the last N samples of the N+L samples at the output of the IFFT unit  77 . 
     The output signal of the unit  79  is converted into a serial stream of samples by the parallel to series converter  78 . At the output of the parallel to series converter  78  the output signal of the audio processing arrangement is available. The output signal of the unit  79  is also applied to a block concatenating unit  74  which derives blocks of N+L samples from the present block of L samples at the output of the unit  79  and a block of N previous samples at the output of the unit  79 . The output of the block concatenating unit  74  is connected to an input of an Fast Fourier Transformer  72  which calculates a N+L points FFT from the N+L samples at its input. The output signal of the Fast Fourier Transformer  72  represents the frequency spectrum of the combined signal. This frequency spectrum is applied to inputs of frequency domain adaptive filters  62 ,  66  and  68 , and to an input of a normalizer  73 . An output of the normalizer  73  is connected to inputs of the frequency domain adaptive filters  62 ,  66  and  68 . 
     The output of the block delay element  54  is connected to a first input of a subtractor  60 . The output of the block delay element  56  is connected to a first input of a subtractor  64  and the output of the block delay element  58  is connected to a first input of a subtractor  70 . The block delay elements  54 ,  56  and  58  are present to compensate the delay to which the audio signals are subjected in the frequency domain programmable filters  44 ,  46 . 
     An output of the frequency domain adaptive filter  62  is connected to a second input of the subtractor  60  and the output of the subtractor  60  is connected to a control input of the frequency domain adaptive filter. An output of the frequency domain adaptive filter  66  is connected to a second input of the subtractor  64  and the output of the subtractor  64  is connected to a control input of the frequency domain adaptive filter. An output of the frequency domain adaptive filter  68  is connected to a second input of the subtractor  70  and the output of the subtractor  70  is connected to a control input of the frequency domain adaptive filter. 
     The frequency domain adaptive filters  62 ,  66  and  68  are arranged to adjust their transfer function in order to minimize the power of the input signal at their control inputs. The frequency domain adaptive filters  62 ,  66  and  68  provide their N+L filter coefficients to the frequency domain programmable filters  44 ,  46  and  48 . These frequency domain adaptive filters determine the conjugate value of the N+L filter coefficients before using them to filter the signals received from the block concatenating units  42 ,  48  and  52 . 
     The functions representing the impulse response are here constituted by the sets of coefficients U 1 , U 2  . . . U M  for the frequency domain programmable filters  44 ,  46  and  50 . 
     In the frequency domain adaptive filters  62 ,  66  and  68  according to FIG. 4, a padding element  80  combines the L samples available at the control input of the respective frequency domain adaptive filter with N samples having a value of 0 to a block of data having N+L samples. This block of N+L samples is subjected to a N+L points Fast Fourier Transform executed by a FFT element  82 . The extension of blocks of L samples to blocks of N+L samples before executing the FFT is done to prevent distortion of the signal due to cyclic convolution effects. This measure is well known to those skilled in the art of (adaptive) digital filters. 
     At the output of the FFT element  82  the frequency spectrum of the signal at the control input of the frequency domain adaptive filter(=the output of the subtractor  60 ,  64  and  70  respectively) is available. The output signal of the FFT element  82  is multiplied with the output signal of the normalizer  73 . The N+L components of the output signal of the normalizer  73  represents adaptation speed values determining the speed of adaptation of the coefficients of the frequency domain adaptive filter. 
     The output signal of the multiplier  84  is added to the output signal of a block delay element  112  by an adder  86 . The output signal of the block delay element  112  represents the previous values of the filter coefficients of the frequency domain adaptive filter. The output signal of the adder  86  is subjected to an Inverse Fast Fourier Transform executed by an IFFT element  94 . From the N+L output samples of the IFFT element  94 , the value of the final L block is set to zero by the element  96 . Subsequently the N+L samples (of which L samples are zero) are subjected to an FFT operation executed by an FFT element  110 . The combination of the IFFT element  94 , the element  96  and the FFT element  110  constitutes a “constrained” FDAF where a time domain constraint is put on the FDAF coefficients to prevent cyclic convolution effects. 
     The output of the FFT element  110  is connected to an input of the block delay element  112 . At the output of the block delay element  112  N+L coefficients are available for use in the filter operation. These coefficients are also passed to the corresponding programmable filter. The combination of the adder  86 , the IFFT element  94 , the element  96 , the FFT element  110  and the block delay element  112  determine the filter coefficient according to the following expression. 
     
       
         ν i,k+1 =ν i,k +λ i,k   ·E   i,k   (22) 
       
     
     In (22) v i,k+1  represents the N+L filter coefficients at instant k+1, v i,k  represents the N+L filter coefficients at instant λ i,k  represents the adaptation coefficients provided by the normalizer  73  to the second input of the multiplier  84  and E k,i  represents the frequency spectrum of the error signal at the output of the subtractor  60 ,  64  or  70  in FIG.  2 . 
     In the normalizer  73  according to FIG. 4, the input signal provided by the FFT unit  72  in FIG. 2 a conjugating element  106  determines the conjugate value of said input signal. This conjugate value is multiplied with said input signal by a multiplier  104 . At the output of the multiplier  104  the power spectrum of the input signal is available. The output of the multiplier  104  is connected to an input of a multiplier  102 . 
     A low pass filter constituted by the multiplier  102 , an adder  100 , a multiplier  98  and a block delay element  92  determines a time average of the power spectrum of the input signal of the frequency domain adaptive filter as available at the output of the multiplier  104 . A suitable value for b is:              b   =     1   -       20   ·   L       f   sample                 (   23   )                                
     In (23) f sample  is the sample frequency with which the audio signals are sampled and processed. A value of 32 or 64 for L has proven to be a useful value when the sample rate is equal to 8 KHz. The output of the adder  100  carrying the time averaged power spectrum is connected to a first input of a divider  88 . The output signal of the conjugating element  106  is scaled with a scaling factor 2a by a scaling element  90 . A suitable value for a is 0.01. The output signal of the scaling element  90  is connected to a second input of the divider  88 . 
     The divider  88  determines the values of λ i,k  by calculating the ratio of the conjugated FFT transform (scaled with scaling factor 2a) of the input signal of the digital filter and the time averaged power spectrum of the input signal of the normalizer  73 . The value of λ i,k  increases proportional to the ratio between the k th  component of the spectrum of the input signal and the k th  component of the time averaged power spectrum. This results an adaptation speed that is the same for all frequency components irrespective of their strength. 
     In the frequency domain programmable filter  44 ,  46  and  50  according to FIG. 6, the input signal is applied to the input of an FFT element  120  which calculates a N+L points FFT from said input signal. A conjugating element  122  determines the conjugate value of the parameters received from the frequency domain adaptive filters  62 ,  66 ,  68 . A multiplier  124  calculates a filtered signal by multiplying the FFT of the input signal with the conjugated filter coefficients received from the frequency domain adaptive filters. 
     It is observed that a suitable choice for N is making it equal to L, but it is also possible to choose N smaller or larger than L. It is desirable to make N+L equal to a power of two in order to enable an easy implementation of the FFT and IFFT operations. 
     In the time domain implementation of the impulse response determining means according to FIG. 7 the outputs of microphones  30 ,  32  and  34  are connected to inputs of processing means  131  and to delay elements  186 ,  188  and  190 . The processing means  131  comprise time domain programmable filters  133 ,  135  and  137 . 
     The time domain programmable filter  133  comprises a plurality of cascaded delay elements  130 ,  132  and  134 , and an adder  146  which adds the output signals of the delay elements weighted with a weighting factor W 1,1  . . . W 1,N . The weighting is performed by the weighting elements  136 ,  138 ,  140 ,  142  and  144 . The time domain programmable filter  135  comprises a plurality of cascaded delay elements  148 ,  150  and  152 , and an adder  164  which adds the output signals of the delay elements weighted with a weighting factor W 2,1  . . . W 2,N . The weighting is performed by the weighting elements  154 ,  156 ,  158 ,  160  and  162 . The time domain programmable filter  137  comprises a plurality of cascaded delay elements  166 ,  168  and  170 , and an adder  182  which adds the output signals of the delay elements weighted with a weighting factor W M,1  . . . W M,N . 
     The outputs of the time domain programmable filters  133 ,  135  and  137 , carrying the processed audio signals, are connected to the combination means being here an adder  184 . At the output of the adder  184  an enhanced audio signal is available. The output of the adder  184  is connected to inputs of time domain adaptive filters  191 ,  193  and  195 . 
     The time domain adaptive filter  191  comprises a plurality of delay elements  194 ,  196  and  198 . The output signals of the delay elements  194 ,  196  and  198  are weighted with weighting factors W 1,1  . . . W 1,N  by weighting elements  200 ,  202 ,  204 ,  206  and  208 . The output signals of the weighting elements  200  . . .  208  are added by an adder  192  which provides the output signal of the adaptive filter  191 . 
     The time domain adaptive filter  193  comprises a plurality of delay elements  226 ,  228  and  230 . The output signals of the delay elements  226 ,  228  and  230  are weighted with weighting factors W 2,1  . . . W 2,N  by weighting elements  216 ,  218 ,  220 ,  222  and  224 . The output signals of the weighting elements  216  . . .  224  are added by an adder  210  which provides the output signal of the adaptive filter  193 . 
     The time domain adaptive filter  195  comprises a plurality of delay elements  236 ,  240  and  246 . The output signals of the delay elements  236 ,  240  and  246  are weighted with weighting factors W M,1  . . . W M,N  by weighting elements  234 ,  238 ,  242 ,  244  and  248 . The output signals of the weighting elements  234  . . .  248  are added by an adder  232  which provides the output signal of the time domain adaptive filter  195 . 
     The outputs of the delay elements  186 ,  188  and  190  are connected to first inputs of subtractors  212 ,  214  and  230 . The delay elements  186 ,  188  and  190  are present to make the impulse response of the programmable filters relatively anti-causal (earlier in time. Second inputs of the subtractors  212 ,  214  and  230  are coupled to outputs of the time domain adaptive filters  191 ,  193  and  195 . The outputs of the subtractors  212 ,  214  and  230  are connected to control means  231 ,  233  and  235  respectively. The control means are arranged to adjust the transfer function of the corresponding adaptive filter  191 ,  193  and  195  in order to minimize the power of the output signal of the corresponding subtractor. 
     The control means  231 ,  233  and  235  are arranged for adjusting the coefficients of the adaptive filters  191 ,  193  and  195  according to the following expression: 
     
       
           W   j,k ( n +1)= W   j,k ( n )=μ· y[n−k +1 ]·e   j   [n ]  (24) 
       
     
     In (24) W j,k (n) is the weight factor of the k th  (k=1, 2, . . . N) weighting element in the j th  adaptive filter, μ is a adaptation constant and e j [n] is the difference between the output signal of the j th  block delay element delaying the input signal and the output signal of the j th  adaptive filter. y j [n−k+1] is the over k−1 sample periods delayed output signal of the audio processing arrangement. These signals y[n−k+1] are available at the output of the delay elements of the adaptive filters. Because the adaptive filters all have the same input signals, the delay elements can be shared leading to a reduction of the required number of delay elements. 
     After the coefficients W j,k (n) have been determined, these coefficients are reversely passed to the time domain programmable filters  133 ,  135  and  137 . This means that the coefficients corresponding to the first taps in the adaptive filters are passed to coefficients of the last taps in the corresponding programmable filter. 
     The functions representing the impulse responses are here the sets of coefficients W 1,1 , . . . W 1,N ; . . . W M,1 , . . . W M,N . As explained before, these functions representing the impulse responses are passed to the correlation function correlation means  7 .