Patent Publication Number: US-7716044-B2

Title: Sound collecting method and sound collecting device

Description:
TECHNICAL FIELD 
   The present invention relates to a sound acquisition method and a sound acquisition apparatus and, more particularly, to a sound acquisition method and a sound acquisition apparatus that acquire speech sounds from a plurality of speech sound sources and adjust their volume before outputting. 
   PRIOR ART 
   For example, in a teleconference in which persons at different remote locations participate, if a single microphone is used at each location to acquire speech sounds of plural participants sitting at different positions at each remote location, received signal levels greatly differ because of different distances from the participants to the microphone and different volumes of their speech sounds. At the remote receiving side the reproduced speech sounds greatly differ in volume with the participants at the transmitting side and, in some cases, they are hard to distinguish one participant from another. 
     FIG. 20  illustrates in block form the basic configuration of a conventional sound acquisition apparatus disclosed, for example, in Japanese Patent Application Kokai Publication 8-250944. The conventional sound acquisition apparatus is made up of a microphone  41 , a power calculating part  42 , an amplification factor setting part  43 , and an amplifier  44 . The power calculating part  42  calculates a long-time mean power P ave  of the signal received by the microphone  41 . The long-time mean power can be obtained by squaring the signal and time-integrating the squared output. Next, the amplification factor setting part  43  sets an amplification factor G based on the long-time mean power P ave  of the received signal calculated by the power calculating part  42  and a preset desired sending level P opt . The amplification factor G can be calculated, for example, by the following equation (1).
   G =( P   opt   /P   ave ) 1/2   (1) 
   The amplifier  44  amplifies the microphone received signal by the set amplification factor G and outputs the amplified signal. 
   By the processing described above, the output signal power is put to the desired sending level P opt , by which the volume is automatically adjusted. With the conventional sound acquisition method, however, since the amplification factor is determined based on the long-time mean power, a delay of several to tens of seconds develops in the setting of an appropriate amplification factor. Accordingly, in the case where plural speakers are present and their speech sounds are acquired by the microphone at different levels, there arises a problem that whenever the speakers changes from one to another, setting of an appropriate amplification factor delays, resulting in an the speech sound being reproduced at an inappropriate volume. 
   An object of the present invention is to provide a sound acquisition apparatus and a sound acquisition method that, even where plural speakers are present and their speech sounds are picked up by a microphone at different levels, automatically adjust the volume of each speech sound to an appropriate value, and a program for implementing the method. 
   DISCLOSURE OF THE INVENTION 
   A sound acquisition method for acquiring sound from each sound source by microphones of plural channels according to the present invention, comprises: 
   (a) a state deciding step including an utterance deciding step of deciding an utterance period from signals received by said plural-channel microphones; 
   (b) a sound source position detecting step of detecting the position of said each sound source from said received signals when the utterance period is decided in said utterance deciding step; 
   (c) a frequency domain converting step of converting said received signals to frequency domain signals; 
   (d) a covariance matrix calculating step of calculating a covariance matrix of said frequency domain received signals; 
   (e) a covariance matrix storage step of storing said covariance matrix for each sound source based on the result of detection in said sound position detecting step; 
   (f) a filter coefficient calculating step of calculating filter coefficients of said plural channels based on said stored covariance matrix and a predetermined output level; 
   (g) a filtering step of filtering the received signals of said plural channels by filter coefficients of said plural channels, respectively; and 
   (h) an adding step of adding together the results of filtering in said plural channels, and providing the added output as a send signal. 
   According to the present invention, a sound acquisition apparatus which acquires sound from each sound source by microphones of plural channels placed in an acoustic space, comprises: 
   a state decision part including an utterance deciding part for deciding an utterance period from signals received by said plural-channel microphones; 
   a sound source position detecting part for detecting the position of said each sound source from said received signals when the utterance period is decided by said utterance deciding part; 
   a frequency domain converting part for converting said received signals to frequency domain signals; a covariance matrix calculating part for calculating a covariance matrix of said frequency domain received signals of said plural channels; 
   a covariance matrix storage part for storing said covariance matrix for said each sound source based on the result of detection by said sound position detecting part; 
   a filter coefficient calculating part for calculating filter coefficients of said plural channels by use of said stored covariance matrix so that the send signal level for said each sound source becomes a desired level; 
   filters of said plural channels for filtering the received signals from said microphones by use of the filter coefficients of said plural channels, respectively; and 
   an adder for adding together the outputs from said filters of said plural channels and for providing the added output as a send signal. 
   According to a second aspect of the present invention, a sound acquisition method for acquiring speech sound from at least one sound source by a microphone of at least one channel in an acoustic space in which a received signal is reproduced by a loudspeaker, comprises: 
   (a) a state deciding step of deciding an utterance period and a receiving period from the sound acquired by said microphone of said at lest one channel and said received signal; 
   (b) a frequency domain converting step of converting said acquired signal and said received signal to frequency domain signals; 
   (c) a covariance matrix calculating step of calculating a covariance matrix in said utterance period and a covariance in said receiving period from said frequency domain acquired signal and received signal; 
   (d) a covariance matrix storage step of storing said covariance matrices for said utterance period and for said receiving period, respectively; 
   (e) a filter coefficient calculating step of calculating filter coefficients for said acquired signal of said at least one channel and filter coefficients for said received signal based on said stored covariance matrices in said utterance period and said receiving period so that an acoustic echo, which is a received signal component contained in said received signal is cancelled; 
   (f) a filtering step of filtering said received signal and said acquired signal by use of said filter coefficients for said received signal and filter coefficients for said acquired signal of said at least one channel; and 
   (g) an adding step of adding together said filtered signals and providing the added output as a send signal. 
   A sound acquisition apparatus according to the second aspect of the present invention comprises: 
   a microphone of at least one channel for acquiring speech sound from a sound source and for outputting an acquired signal; 
   a loudspeaker for reproducing a received signal; 
   a state decision part for deciding an utterance period and a receiving period from said acquired signal and said received signal; 
   a frequency domain converting part for converting said acquired signal and said received signal to frequency domain signals; 
   a covariance matrix calculating part for calculating covariance matrices of said acquired and received signals of said frequency domain for said utterance period and for said receiving period, respectively; 
   a covariance matrix storage part for storing said covariance matrices for said utterance period and for said receiving period, respectively; 
   a filter coefficient calculating part for calculating filter coefficients for said acquired signal of said at least one channel and filter coefficients for said received signal based on said stored covariance matrices so that an acoustic echo of said received signal is cancelled; 
   an acquired signal filter and a received signal filter having set therein said filter coefficients for said acquired signal and said filter coefficients for said received signal, for filtering said acquired signal and for filtering said received signal; and 
   an adder for adding together the outputs from said acquired signal filter and said received signal filter, and for providing the added output as a send signal. 
   According to the present invention, even when plural speakers are present ad their speech sounds are acquired by a plurality of microphones at different levels, the directivity of the microphones is appropriately controlled to automatically adjust the volume of the speech sound to an appropriate value for each speaker. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
       FIG. 1  is a block diagram illustrating a sound acquisition apparatus according to a first embodiment of the present invention. 
       FIG. 2  is a block diagram showing an example of the configuration of a state decision part  14  in  FIG. 1 . 
       FIG. 3  is a block diagram showing an example of the configuration of a sound source position detecting part  15  in  FIG. 1 . 
       FIG. 4  is a block diagram showing an example of the configuration of a filter coefficient calculating part  21  in  FIG. 1 . 
       FIG. 5  is a flowchart showing a first example of a sound acquisition method using the sound acquisition apparatus of  FIG. 1 . 
       FIG. 6  is a flowchart showing a second example of a sound acquisition method using the sound acquisition apparatus of  FIG. 1 . 
       FIG. 7  is a flowchart showing a third example of a sound acquisition method using the sound acquisition apparatus of  FIG. 1 . 
       FIG. 8  is a block diagram illustrating a sound acquisition apparatus according to a second embodiment of the present invention. 
       FIG. 9  is a block diagram showing an example of the configuration of the state decision part  14  in  FIG. 8 . 
       FIG. 10  is a block diagram illustrating a sound acquisition apparatus according to a third embodiment of the present invention. 
       FIG. 11  is a block diagram showing an example of the configuration of the state decision part  14  in  FIG. 7 . 
       FIG. 12  is a block diagram illustrating a sound acquisition apparatus according to a fourth embodiment of the present invention. 
       FIG. 13  is a block diagram illustrating a sound acquisition apparatus according to a fifth embodiment of the present invention. 
       FIG. 14  is a block diagram showing an example of the configuration of a weighting factor setting part  21 H in  FIG. 4 . 
       FIG. 15  is a block diagram showing another example of the configuration of a weighting factor setting part  21 H in  FIG. 4 . 
       FIG. 16  is a block diagram showing an example of the configuration of a whitening part  21 J in  FIG. 4 . 
       FIG. 17  is a block diagram an example of a covariance matrix storage part  18  that is used when each embodiment is equipped with a covariance matrix averaging function. 
       FIG. 18A  is a diagram showing simulated speech waveforms of speakers A and B before processing by the first embodiment. 
       FIG. 18B  is a diagram showing simulated speech waveforms of speakers A and B after processing by the first embodiment. 
       FIG. 19  is a diagram showing received and send speech waveform by simulation, which show acoustic echo and noise cancellation according to a third embodiment. 
       FIG. 20  is a block diagram illustrating a conventional sound acquisition apparatus. 
   

   BEST MODE FOR CARRYING OUT THE INVENTION 
   First Embodiment 
     FIG. 1  is a block diagram of a sound acquisition apparatus according to a first embodiment of the present invention. The sound acquisition apparatus of this embodiment comprises microphones  11   1  to  11   M  of M channels disposed in an acoustic space, filters  12   1  to  12   M , an adder  13 , a state decision part  14 , a sound source position detecting part  15 , a frequency domain converting part  16 , a covariance matrix calculating part  17 , a covariance matrix storage part  18 , an acquired sound level estimating part  19 , and a filter coefficient calculating part  21 . 
   In this embodiment, the positions of speech sound sources  9   1  to  9   K  in an acoustic space are detected, then covariance matrices of acquired signals in the frequency domain for the respective speech sound sources are calculated and stored, and these covariance matrices are used to calculate filter coefficients. These filter coefficients are used to filter the signals acquired by the microphones, thereby controlling the signals from the respective speech sound sources to have a constant volume. In this embodiment, let it be assumed that the output signals from the microphones  11   1  to  11   M  are digital signals into which the signals acquired by the microphones are converted by a digital-to-analog converter at a predetermined sampling frequency, though not shown in particular. This applies to other embodiments of the present invention. 
   In the first place, the state decision part  14  detects an utterance period from each of the received signals by the microphones  11   1  to  11   M . For example, as shown in  FIG. 2 , in the state decision part  14  all the received signals from the microphones  11   1  to  11   M  are added together by an adding part  14 A, then the added output is applied to a short-time mean power calculating part  14 B and a long-time mean power calculating part  14 C to obtain a shirt-time mean power (approximately in the range of 0.1 to 1 s, for instance) P avS  and a long-time mean power (approximately in the range of 1 to 100 s, for instance) P avL , respectively, then the ratio between the short-time mean power and the long-time mean power, R p =P avS /P avL , is calculated in a division part  14 D, and in an utterance decision part  14 E the power ratio R p  is compared with a predetermined utterance threshold value R thU ; if the power ratio exceeds the threshold value, then the former is decided as indicating the utterance period. 
   When the decision result by the state decision part  14  is the utterance period, the sound source position detecting part  15  estimates the position of the sound source. A method for estimating the sound source position is, for example, a cross-correlation method. 
   Let M (M being an integer equal to or greater than 2) represent the number of microphones and τij represent a measured value of the delay time difference between signals acquired by i-th and j-th microphones  11   i  and  11   j . The measured value of the delay time difference between the acquired signals can be obtained by calculating the cross-correlation between the acquired signals and detecting its maximum peak position. Next, let the sound acquisition position of an m-th (where m=1, . . . , M) microphone be represented by (xm, ym, zm) and an estimated sound source position by ({circumflex over (X)}, Ŷ, {circumflex over (Z)}). An estimated value {circumflex over (τ)} ij  of the delay time difference between the acquired signals, which is available from these positions, is expressed by Eq. (2). 
                     τ   ^       i   ⁢           ⁢   j       =         1   c     ⁢           (       x   i     -     X   ^       )     2     +       (       y   i     -     Y   ^       )     2     +       (       z   i     -     Z   ^       )     2           -       1   c     ⁢           (       x   j     -     X   ^       )     2     +       (       y   j     -     Y   ^       )     2     +       (       z   j     -     Z   ^       )     2                     (   2   )               
where c is sound velocity.
 
   Next, measured and estimated value τ ij  and {circumflex over (τ)} ij  of the delay time difference between the acquired signals are multiplied by the sound velocity c for conversion into distance values, which are used as measured and estimated values d ij  and {circumflex over (d)} ij  of the difference in the distance to the uttering sound source between the positions of microphones acquiring the speech sound therefrom, respectively; a mean square error e(q) of these values is given by Eq. (3). 
                         e   ⁡     (   q   )       =       ⁢       ∑     i   =   1       M   -   1       ⁢           ⁢       ∑     j   =     i   +   1       M     ⁢           ⁢              d     i   ⁢           ⁢   j       -       d   ^       i   ⁢           ⁢   j              2                     =       ⁢       ∑     i   =   1       M   -   1       ⁢           ⁢       ∑     j   =     i   +   1       M     ⁢           ⁢            d     i   ⁢           ⁢   j       -           (       x   i     -     X   ^       )     2     +       (       y   i     -     Y   ^       )     2     +       (       z   i     -     Z   ^       )     2         +                             ⁢           (       x   j     -     X   ^       )     2     +       (       y   j     -     Y   ^       )     2     +       (       z   j     -     Z   ^       )     2              2               =       ⁢       ∑     i   =   1       M   -   1       ⁢           ⁢       ∑     j   =     i   +   1       M     ⁢           ⁢                d     i   ⁢           ⁢   j       -     r   i     +     r   j            2     .                       (   3   )               
where q=({circumflex over (X)}, Ŷ, {circumflex over (Z)}). r i  and r j  represent the distances between the estimated sound source position q=({circumflex over (X)}, Ŷ, {circumflex over (Z)}) and the microphones  11   i  and  11   j .
 
   By obtaining a solution that minimizes the mean square error e(q) of Eq. (3), it is possible to obtain estimated sound source position that minimizes the error between the measured and estimated values of the delay time difference between the acquired signals. In this instance, however, since Eq. (3) is nonlinear simultaneous equations and is difficult to solve analytically, the estimated sound source position is obtained by a numerical analysis using successive correction. 
   To obtain the estimated sound source position ({circumflex over (X)}, Ŷ, {circumflex over (Z)}) that minimizes Eq. (3), the gradient at a certain point in Eq. (3) is calculated, then the estimated sound source position is corrected in the direction in which to reduce the error until the gradient becomes zero; accordingly, the estimated sound source position is corrected by repeatedly calculating the following equation (4) for u=0, 1, . . . .
 
 q   (u+1)   =q   (u) −α·grad  e ( q )| q=q     (u)     (4)
 
where α is a step size of correction, and it is set at a value α&gt;0. q (u)  represents q corrected u times, and q (0) =({circumflex over (X)} 0 , Ŷ 0 , {circumflex over (Z)} 0 ) is a predetermined arbitrary initial value when u=0. grad represents the gradient, which is expressed by the following equations (5) to (10).
 
   
     
       
         
           
             
               
                 
                   grad 
                   ⁢ 
                   
                       
                   
                   ⁢ 
                   
                     e 
                     ⁡ 
                     
                       ( 
                       q 
                       ) 
                     
                   
                 
                 = 
                 
                   ( 
                   
                     
                       
                         ∂ 
                         
                           e 
                           ⁡ 
                           
                             ( 
                             q 
                             ) 
                           
                         
                       
                       
                         ∂ 
                         
                           X 
                           ^ 
                         
                       
                     
                     , 
                     
                       
                         ∂ 
                         
                           e 
                           ⁡ 
                           
                             ( 
                             q 
                             ) 
                           
                         
                       
                       
                         ∂ 
                         
                           Y 
                           ^ 
                         
                       
                     
                     , 
                     
                       
                         ∂ 
                         
                           e 
                           ⁡ 
                           
                             ( 
                             q 
                             ) 
                           
                         
                       
                       
                         ∂ 
                         
                           Z 
                           ^ 
                         
                       
                     
                   
                   ) 
                 
               
             
             
               
                 ( 
                 5 
                 ) 
               
             
           
           
             
               
                 
                   
                     ∂ 
                     
                       e 
                       ⁡ 
                       
                         ( 
                         q 
                         ) 
                       
                     
                   
                   
                     ∂ 
                     
                       X 
                       ^ 
                     
                   
                 
                 = 
                 
                   2 
                   ⁢ 
                   
                     
                       ∑ 
                       
                         i 
                         = 
                         1 
                       
                       
                         M 
                         - 
                         1 
                       
                     
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     
                       
                         ∑ 
                         
                           j 
                           = 
                           
                             i 
                             + 
                             1 
                           
                         
                         M 
                       
                       ⁢ 
                       
                           
                       
                       ⁢ 
                       
                         
                           { 
                           
                             
                               d 
                               
                                 i 
                                 ⁢ 
                                 
                                     
                                 
                                 ⁢ 
                                 j 
                               
                             
                             - 
                             
                               r 
                               i 
                             
                             + 
                             
                               r 
                               j 
                             
                           
                           } 
                         
                         · 
                         
                           { 
                           
                             
                               
                                 
                                   x 
                                   i 
                                 
                                 - 
                                 
                                   X 
                                   ^ 
                                 
                               
                               
                                 r 
                                 i 
                               
                             
                             - 
                             
                               
                                 
                                   x 
                                   j 
                                 
                                 - 
                                 
                                   X 
                                   ^ 
                                 
                               
                               
                                 r 
                                 j 
                               
                             
                           
                           } 
                         
                       
                     
                   
                 
               
             
             
               
                 ( 
                 6 
                 ) 
               
             
           
           
             
               
                 
                   
                     ∂ 
                     
                       e 
                       ⁡ 
                       
                         ( 
                         q 
                         ) 
                       
                     
                   
                   
                     ∂ 
                     
                       Y 
                       ^ 
                     
                   
                 
                 = 
                 
                   2 
                   ⁢ 
                   
                     
                       ∑ 
                       
                         i 
                         = 
                         1 
                       
                       
                         M 
                         - 
                         1 
                       
                     
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     
                       
                         ∑ 
                         
                           j 
                           = 
                           
                             i 
                             + 
                             1 
                           
                         
                         M 
                       
                       ⁢ 
                       
                           
                       
                       ⁢ 
                       
                         
                           { 
                           
                             
                               d 
                               
                                 i 
                                 ⁢ 
                                 
                                     
                                 
                                 ⁢ 
                                 j 
                               
                             
                             - 
                             
                               r 
                               i 
                             
                             + 
                             
                               r 
                               j 
                             
                           
                           } 
                         
                         · 
                         
                           { 
                           
                             
                               
                                 
                                   y 
                                   i 
                                 
                                 - 
                                 
                                   Y 
                                   ^ 
                                 
                               
                               
                                 r 
                                 i 
                               
                             
                             - 
                             
                               
                                 
                                   y 
                                   j 
                                 
                                 - 
                                 
                                   Y 
                                   ^ 
                                 
                               
                               
                                 r 
                                 j 
                               
                             
                           
                           } 
                         
                       
                     
                   
                 
               
             
             
               
                 ( 
                 7 
                 ) 
               
             
           
           
             
               
                 
                   
                     ∂ 
                     
                       e 
                       ⁡ 
                       
                         ( 
                         q 
                         ) 
                       
                     
                   
                   
                     ∂ 
                     
                       Z 
                       ^ 
                     
                   
                 
                 = 
                 
                   2 
                   ⁢ 
                   
                     
                       ∑ 
                       
                         i 
                         = 
                         1 
                       
                       
                         M 
                         - 
                         1 
                       
                     
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     
                       
                         ∑ 
                         
                           j 
                           = 
                           
                             i 
                             + 
                             1 
                           
                         
                         M 
                       
                       ⁢ 
                       
                           
                       
                       ⁢ 
                       
                         
                           { 
                           
                             
                               d 
                               
                                 i 
                                 ⁢ 
                                 
                                     
                                 
                                 ⁢ 
                                 j 
                               
                             
                             - 
                             
                               r 
                               i 
                             
                             + 
                             
                               r 
                               j 
                             
                           
                           } 
                         
                         · 
                         
                           { 
                           
                             
                               
                                 
                                   z 
                                   i 
                                 
                                 - 
                                 
                                   Z 
                                   ^ 
                                 
                               
                               
                                 r 
                                 i 
                               
                             
                             - 
                             
                               
                                 
                                   z 
                                   j 
                                 
                                 - 
                                 
                                   Z 
                                   ^ 
                                 
                               
                               
                                 r 
                                 j 
                               
                             
                           
                           } 
                         
                       
                     
                   
                 
               
             
             
               
                 ( 
                 8 
                 ) 
               
             
           
           
             
               
                 
                   r 
                   i 
                 
                 = 
                 
                   
                     
                       
                         ( 
                         
                           
                             x 
                             i 
                           
                           - 
                           
                             X 
                             ^ 
                           
                         
                         ) 
                       
                       2 
                     
                     + 
                     
                       
                         ( 
                         
                           
                             y 
                             i 
                           
                           - 
                           
                             Y 
                             ^ 
                           
                         
                         ) 
                       
                       2 
                     
                     + 
                     
                       
                         ( 
                         
                           
                             z 
                             i 
                           
                           - 
                           
                             Z 
                             ^ 
                           
                         
                         ) 
                       
                       2 
                     
                   
                 
               
             
             
               
                 ( 
                 9 
                 ) 
               
             
           
           
             
               
                 
                   r 
                   j 
                 
                 = 
                 
                   
                     
                       
                         ( 
                         
                           
                             x 
                             j 
                           
                           - 
                           
                             X 
                             ^ 
                           
                         
                         ) 
                       
                       2 
                     
                     + 
                     
                       
                         ( 
                         
                           
                             y 
                             j 
                           
                           - 
                           
                             Y 
                             ^ 
                           
                         
                         ) 
                       
                       2 
                     
                     + 
                     
                       
                         ( 
                         
                           
                             z 
                             j 
                           
                           - 
                           
                             Z 
                             ^ 
                           
                         
                         ) 
                       
                       2 
                     
                   
                 
               
             
             
               
                 ( 
                 10 
                 ) 
               
             
           
         
       
     
   
   As described above, by repeatedly calculating Eq. (4), it is possible to obtain the estimated sound source position q=({circumflex over (X)}, Ŷ, {circumflex over (Z)}) where the error is minimized. 
     FIG. 3  illustrates in block form the functional configuration of the sound source position detecting part  15 . In this example, the sound source position detecting part is comprises a delay time difference measuring part  15 A, a multiplier  15 B, a distance calculating part  15 C, a mean square error calculating part  15 D, a gradient calculating part  15 E, a relative decision part  15 F, and an estimated position updating part  15 G The delay time difference measuring part  15 A measures, during utterance from one speech sound source  9   k , the delay time difference τ ij  by the cross-correlation scheme for every pair (i, j) of
   i= 1, 2 , . . . , M− 1;   j=i+ 1 , i+ 2 , . . . , M    
based on the received signals by the microphones  11   i  and  11   j . The multiplier  15 B multiplies each measured delay time difference τ ij  by the sound velocity c to obtain the difference in distance, d ij , between the sound source and the microphones  11   i  and  11   j . The distance calculating part  15 C calculates, by Eqs. (9) and (10), the distances r i  and r j  between the estimated sound source position ({circumflex over (X)}, Ŷ, {circumflex over (Z)}) fed from the estimated position updating part  15 G and the microphones  11   i  and  11   j . In this case, however, the estimated position updating part  15 G provides an arbitrary initial value ({circumflex over (X)} 0 , Ŷ 0 , {circumflex over (Z)} 0 ) as a first estimated sound source position to the distance calculating part  15 C. The mean square error calculating part  15 D uses d ij , r i  and r j  to calculate the mean square error e(q) by Eq. (3) for all of the above-mentioned pairs (i, j). The gradient calculating part  15 F uses the current estimate sound source position and d ij , r i , r j  to calculate the gradient grad e(q) of the mean square error e(q) by Eqs. (6), (7) and (8).
 
   The relative decision part  15 F compares each element of the gradient grad e(q) of the mean square error with a predetermined threshold value e th  to decide whether every element is smaller than the threshold value e th , and if so, then outputs the estimated sound source position ({circumflex over (X)}, Ŷ, {circumflex over (Z)}) at that time. If every element is not smaller than e th , then the estimated position updating part  15 G uses the gradient grad e(q) and the current estimated position q=({circumflex over (X)}, Ŷ, {circumflex over (Z)}) to update the estimated position by Eq. (4), and provides th updated estimated position q u+1 =({circumflex over (X)}, Ŷ, {circumflex over (Z)}) to the distance calculating part  15 C. The distance calculating part  15 C uses the updated estimated position ({circumflex over (X)}, Ŷ, {circumflex over (Z)}) and d ij  to calculate r i  and r j  updated in the same manner as referred to previously; thereafter, the mean square error calculating part  15 D updates e(q), then the gradient calculating part  15 E calculates the updated grad e(q), and the relative decision part  15 F decides whether the updated mean square error e(q) is smaller than the threshold value e th . 
   In this way, updating of the estimated position ({circumflex over (X)}, Ŷ, {circumflex over (Z)}) is repeated until every element of the gradient grad e(q) of the mean square error becomes sufficiently small (smaller than e th ), thereby estimating the position ({circumflex over (X)}, Ŷ, {circumflex over (Z)}) of the sound source  9   k . Similarly, positions of other sound sources are estimated. 
   The frequency domain converting part  16  converts the signal acquired by each microphone to a frequency domain signal. For example, the sampling frequency of the acquired signal is 16 kHz, and acquired signal samples from each microphone  11   m  (m=1, . . . , M) are subjected to FFT (Fast Fourier Transform) processing every frame of 256 samples to obtain the same number of frequency domain signal samples X m (ω). 
   Next, the covariance matrix calculating part  17  calculates the covariance of the microphone acquired signals and generates a covariance matrix. Letting X 1 (ω) to X M (ω) represent the frequency domain converted signals of the microphone acquired signals obtained by the frequency domain converting part  16  for each sound source  9   k , an M×M covariance matrix R XX (ω) of these signals is generally expressed by the following equation (11). 
                     R   XX     ⁡     (   ω   )       =       (             X   1     ⁡     (   ω   )               ⋮               X   M     ⁡     (   ω   )             )     ⁢     (           X   1     ⁡     (   ω   )       *     ,           ⁢   ⋯   ⁢           ,           ⁢         X   M     ⁡     (   ω   )       *       )               (   11   )                       ⁢     =     (                 X   1     ⁡     (   ω   )       ⁢         X   1     ⁡     (   ω   )       *       ,                 X   1     ⁡     (   ω   )       ⁢         X   2     ⁡     (   ω   )       *       ,         ⋯         ,         X   1     ⁡     (   ω   )       ⁢         X   M     ⁡     (   ω   )       *                         X   2     ⁡     (   ω   )       ⁢         X   1     ⁡     (   ω   )       *       ,                 X   2     ⁡     (   ω   )       ⁢         X   2     ⁡     (   ω   )       *       ,         ⋯         ,         X   2     ⁡     (   ω   )       ⁢         X   M     ⁡     (   ω   )       *                 ⋮       ⋮       ⋰       ⋮                   X   M     ⁡     (   ω   )       ⁢         X   1     ⁡     (   ω   )       *       ,                 X   M     ⁡     (   ω   )       ⁢         X   2     ⁡     (   ω   )       *       ,         ⋯         ,         X   M     ⁡     (   ω   )       ⁢         X   M     ⁡     (   ω   )       *               )                               
where * represents a complex conjugate.
 
   Next, the covariance matrix storage part  18  stores, based on the result of detection by the sound source position detecting part  15 , the covariance matrix R XX (ω) as an M×M covariance matrix R SkSk (ω) for each sound source  9   k . 
   Letting A k (ω)=(a k1 (ω), . . . , a kM (ω)) represent the weighted mixing vectors for M-channel acquired signals for each sound source  9   k , the acquired sound level estimating part  19  calculates the acquired sound level  Sk  for each sound source by the following equation (12) using the covariance matrix R SkSk (ω) of the acquired signal for each sound source  9   k  stored in the covariance matrix storage part  18 . 
                   P   Sk     =       1   W     ⁢       ∑     ω   =   0     W     ⁢           ⁢           A   k     ⁡     (   ω   )       H     ⁢       R   SkSk     ⁡     (   ω   )       ⁢       A   k     ⁡     (   ω   )                     (   12   )               
In the above, the weighted mixing vector is expressed as a vector A k (ω)=(a k1 (ω), . . . , a kM (ω)) that has a controllable frequency characteristics, but if no frequency characteristics control is effected, the elements of the vector A k  may be preset values a k1 , a k2 , . . . , a kM . For example, the elements of the weighted mixing vector A k  for each sound source  9   k  are given greater values as the microphones corresponding to the elements become closer to the sound source  9   k . In the extreme, it is possible to set 1 for only the element corresponding to the microphone  11   m  closest to the sound source  9   k  and set 0 for all the other elements like A k =(0, . . . 0, a km =1, 0, . . . , 0). In the following description, a k1 (ω), . . . , a kM (ω) will be expressed simply as a k1 , . . . , a kM , for the sake of brevity.
 
     H  in Eq. (12) represents a complex conjugate transpose, and A k (ω) H R SkSk (ω)A k (ω) can be expanded as given by the following equation. 
                               A   k     ⁡     (   ω   )       H     ⁢       R   SkSk     ⁡     (   ω   )       ⁢       A   k     ⁡     (   ω   )         =                     a   k1     *     ⁡     (         a   k1     ⁢       X   1     ⁡     (   ω   )       ⁢         X   1     ⁡     (   ω   )       *       +       a   k2     ⁢       X   2     ⁡     (   ω   )       ⁢         X   1     ⁡     (   ω   )       *       +   …   +       a   kM     ⁢       X   M     ⁡     (   ω   )       ⁢         X   1     ⁡     (   ω   )       *         )       +                   a   k2   *     ⁡     (         a   k1     ⁢       X   1     ⁡     (   ω   )       ⁢         X   2     ⁡     (   ω   )       *       +       ⁢       a   k2     ⁢       X   2     ⁡     (   ω   )       ⁢         X   2     ⁡     (   ω   )       *       +   …   +       a   kM     ⁢       X   M     ⁡     (   ω   )       ⁢         X   2     ⁡     (   ω   )       *         )       +                       ⁢     ⋮   ⁢           ⁢   ⋮                     a   kM   *     ⁡     (         a   k1     ⁢       X   1     ⁡     (   ω   )       ⁢         X   M     ⁡     (   ω   )       *       +       a   k2     ⁢       X   2     ⁡     (   ω   )       ⁢         X   M     ⁡     (   ω   )       *       +   …   +       a   kM     ⁢       X   M     ⁡     (   ω   )       ⁢         X   M     ⁡     (   ω   )       *         )       =               Ω   ⁡     (   ω   )                   (   13   )               
Eq. (12) means that the mean power P sk  of the acquired signal is calculated by adding the power spectrum sample value represented by Ω(ω) given by Eq. (13) for bands 0 to W (sample number) of the frequency domain signal generated by the frequency domain converting part  16  and then dividing the added value by W.
 
   For example, assuming that the microphone  11   1  is the closest to the sound source  9   1 , the value of the weighting factor a k1  is so determined as to assign the maximum weight to the acquired signal by the microphone  11   1  (a first channel) and the values of weighting factors a k2 , a k3 , . . . , a kM  for the acquired signals of the other channels are determined smaller than a k1 . With such weighting scheme, it is possible to increase S/N (Signal to Noise ratio) of the acquired signal from the sound source  9   1  or lessen the influence of room reverberation more than in the case where such weighting is not performed. That is, the optimum value of the weighting factor of the weighted mixing vector A k (ω) for each sound source  9   k  is predetermined experimentally by the directivity and layout of microphones and the layout of sound sources in such a manner as to increase S/N of the output speech signal corresponding to the sound source  9   k , for example, and decrease the room reverberation. According to the present invention, however, even when equal weighting is done in all the channels, acquired signals from the respective sound sources can be controlled to a desired level. 
   Next, the filter coefficient calculating part  21  calculates filter coefficients for acquiring speech sound from each sound source in a desired volume. In the first place, let H 1 (ω) to H M (ω) represent frequency domain converted versions of filter coefficients of the filters  12   1  to  12   M  each connected to one of the microphones. Next, let H(ω) represent a matrix of these filter coefficients by the following equation (14). 
   
     
       
         
           
             
               
                 
                   H 
                   ⁡ 
                   
                     ( 
                     ω 
                     ) 
                   
                 
                 = 
                 
                   ( 
                   
                     
                       
                         
                           
                             
                               
                                 
                                   H 
                                   1 
                                 
                                 ⁡ 
                                 
                                   ( 
                                   ω 
                                   ) 
                                 
                               
                             
                           
                           
                             
                               ⋮ 
                             
                           
                         
                       
                     
                     
                       
                         
                           
                             H 
                             M 
                           
                           ⁡ 
                           
                             ( 
                             ω 
                             ) 
                           
                         
                       
                     
                   
                   ) 
                 
               
             
             
               
                 ( 
                 14 
                 ) 
               
             
           
         
       
     
   
   Further, let X Sk,1  to X Sk,M  represent frequency domain converted signals of the signals acquired by respective microphones during utterance of the k-th sound source  9   k . 
   In this case, the condition that the filter coefficient matrix H(ω) needs to satisfy is that when the microphone acquired signals are subjected to filtering with the filter coefficient matrix H(ω) and the filtered signals are added together, the signal component from each sound source has a desired level P opt . Accordingly, the following equation (15) is an ideal condition by which the signal obtained by adding the filtered signals from the sound source  9   k  becomes equivalent to a signal obtained by multiplying the weighted mixing vector A k (ω)) for the acquired signals from the microphones  11   1  to  11   M  by a desired gain. 
                     (         X     Sk   ,   1       ⁡     (   ω   )       ⁢           ,   ⋯   ⁢           ,       X     Sk   ,   M       ⁡     (   ω   )         )     ⁢     H   ⁡     (   ω   )         =           P   opt       P   Sk         ⁢     (         X     Sk   ,   1       ⁡     (   ω   )       ⁢           ,   ⋯   ⁢           ,       X     Sk   ,   M       ⁡     (   ω   )         )     ⁢       A   k     ⁡     (   ω   )                 (   15   )               
where k=1, . . . , K, K representing the number of sound sources.
 
   Next, solving the condition of Eq. (15) by the least square method for the filter coefficient matrix H(ω) gives the following equation (16). 
                   H   ⁡     (   ω   )       =         {       ∑     k   =   1     K     ⁢           ⁢       C   Sk     ⁢       R   SkSk     ⁡     (   ω   )           }       -   1       ⁢       ∑     k   =   1     K     ⁢           ⁢       C   Sk     ⁢         P   opt       P   Sk         ⁢       R   SkSk     ⁡     (   ω   )       ⁢       A   k     ⁡     (   ω   )                     (   16   )               
where C Sk  is a weighting factor that imposes a sensitivity restraint on the k-th sound source position. The sensitivity restraint mentioned herein means flattening the frequency characteristics of the present sound acquisition apparatus with respect to the sound source position. An increase in this value increases the sensitivity restraint on the sound source concerned, permitting sound acquisition with flatter frequency characteristics but increasing deterioration of frequency characteristics for other sound source positions. Hence, it is preferable that C Sk  be normally set at a value approximately in the range of 0.1 to 10 to impose well-balances restraints on all the sound sources.
 
     FIG. 4  illustrates in block form the functional configuration of the filter coefficient calculating part  21  for calculating the filter coefficients expressed by Eq. (16). In this example, the covariance matrices R S1S1  to R SKSK  corresponding to the respective sound sources  9   1  to  9   K , provided from the covariance matrix storage part  18 , are applied to multipliers  21 A 1  to  21 Ak, wherein they are multiplied by weighting factors C S1  to C SK  set by a weighting factor setting part  21 H, respectively. The acquired sound levels P S1  to P SK  for the sound sources  9   1  to  9   K , estimated by the acquired sound level estimating part  19 , are provided to square ratio calculating parts  21 B 1  to  21 BK, wherein square ratios, (P opt /P S1 ) 1/2  to (P opt /P SK ) 1/2 , between them and the predetermined desired output level P opt  are calculated, and the calculated values are provided to multipliers  21 C 1  to  21 CK for multiplication by the outputs from multipliers  21 A 1  to  21 AK, respectively. The outputs from the multipliers  21 C 1  to  21 CK are fed to multipliers  21 D 1  to  21 DK, where they are further multiplied by weighted mixing vectors A 1 (ω) to A K (ω), and a matrix of the total sum of the multiplied outputs is calculated by an adder  21 E. On the other hand, a matrix of the sum total of the outputs from the multipliers  21 A 1  to  21 AK is calculated by an adder  21 F, and by an inverse matrix multiplier  21 G, an inverse matrix of the matrix calculated by the adder  21 F and the output from the adder  21 E are multiplied to calculate the filter coefficient H(ω). 
   Next, the filter coefficients H 1 (ω), H 2 (ω), . . . , H M (ω) calculated by the filter coefficient calculating part  21  are set in the filters  12   1  to  12   M  for filtering the acquired signals from the microphones  11   1  to  11   M , respectively. The filtered signals are added together by the adder  13 , from which the added output is provided as an output signal. 
   A description will be given below of three examples of the usage of the sound acquisition apparatus according to the present invention. 
   A first method begins, as shown in  FIG. 5 , with initial setting of the number K of sound sources at K=0 in step S 1 . This is followed by step S 2  in which the state decision part  14  periodically makes a check for utterance, and if utterance is detected, the sound source position detecting part  15  detects the position of the sound source concerned in step S 3 . In step S 4  it is decided whether the detected sound source position matches any one of those previously detected, and if a match is found, the covariance matrix R XX (ω) corresponding to that sound source position is newly calculated in the covariance matrix calculating part  17  in step S 5 , and in step S 6  the covariance matrix in the corresponding area of the covariance matrix storage part  18  is updated with the newly calculated covariance matrix. 
   When no match is found with the previously detected sound source position in step S 4 , K is incremented by 1 in step S 7 , then in step S 8  the covariance matrix R XX (ω) corresponding to that sound source position is newly calculated in the covariance matrix calculating part  17 , and in step S 9  the covariance matrix is stored in a new area of the covariance matrix storage part  18 . 
   Next, in step S 10  the acquired sound level is estimated from the stored covariance matrix in the acquired sound level estimating part  19 , then in step S 11  the estimated acquired sound level and the covariance matrix are used to calculate the filter coefficients H 1 (ω) to H M (ω) by the filter coefficient calculating part  17 , and in step S 12  the filter coefficients set in the filters  12   1  to  12   M  are updated with the newly calculated ones. 
   A second method begins, as shown in  FIG. 6 , with presetting the maximum value of the sound source number at K max  and presetting the initial value of the sound source number K at 0 in step S 1 . The subsequent steps S 2  to S 6  are the same as in the case with  FIG. 5 ; that is, the microphone output signals are checked for utterance, and if utterance is detected, then its sound source position is detected, then it is decided whether the detected sound source position matches any one of those previously detected, and if a match is found, the covariance matrix corresponding to that sound source position is calculated and stored as a newly updated matrix in the corresponding storage area. 
   When it is found in step S 4  that the detected sound source position does not match any one of previously detected positions, K is incremented by 1 in step S 7 , and in step S 8  a check is made to see if K is larger than the maximum value K max . If it does not exceed the maximum value K max , then the covariance matrix for the detected position is calculated in step S 9 , and in step S 10  the covariance matrix is stored in a new area. When it is found that in step S 8  that K exceeds the maximum value K max , K=K max  is set in step S 11 , then in step S 12  the most previously updated one of the covariance matrices stored in the covariance matrix storage part  18  is erased, and a new covariance matrix calculated by the covariance matrix calculating part  17  in step S 13  is stored in that area in step S 14 . The subsequent steps S 15 , S 16  and S 17  are the same as in steps S 10 , S 11  and S 12  in  FIG. 5 ; that is, the estimated acquired sound level for each sound source is calculated from the covariance matrix, and filter coefficients are calculated and set in the filters  12   1  to  12   M . This method is advantageous over the  FIG. 5  method in that the storage area of the covariance matrix storage part  18  can be reduced by limiting the maximum value of the sound source number K to K max . 
   In the first and second methods, described above, each detection of speech sound is always accompanied by the calculation and storage of a covariance matrix and updating of the filter coefficients, but the third method described below does not involve updating of the filter coefficients when the position of the sound source of the detected utterance matches any one of the already detected sound source positions.  FIG. 7  illustrates the procedure of the third method. In step S 1  the initial value of the sound source number k is set to 0, then in step S 2  the state detecting part  14  periodically makes a check for utterance, and if utterance is detected, the sound source position detecting part  15  detects the position of the sound source of the detected utterance in step S 3 . In step S 4  it is decided whether the detected sound source position matches any one of the already detected sound source positions, and if a match is found, the procedure returns to step S 2  without updating. If no match is found with any one of the already detected sound source positions in step S 4 , that is, if the sound source  9   k  moves to a position different from that where it was previously, or if a new sound source is added, K is incremented by 1 in step S 5 , then in step S 6  the covariance matrix R SkSk (ω) corresponding to the sound source is newly calculated in the covariance calculating part  17 , and in step S 7  it is stored in the corresponding new area MA k  of the covariance storage part  18 , then in step S 8  the covariance matrix is used to estimate the acquired sound level by the acquired sound level estimating part  19 , then in step S 9  all the covariance matrices and estimated acquired sound levels to calculate updated filter coefficients by the filter coefficient calculating part  21 , and in step S 10  the updated filter coefficients are set in the filters  12   1  to  12   M , followed by a return to step S 2 . 
   As described above, according to the present invention, the sound source positions are estimated from the acquired signals of a plurality of microphones, then a covariance matrix of the acquired signal is calculated for each sound source, then filter coefficients for adjusting the sound volume for each sound source position are calculated, and the filter coefficients are used to filter the acquired signals of the microphones, by which it is possible to obtain an output signal of a volume adjusted for each speaker&#39;s position. 
   While the  FIG. 1  embodiment has been described with reference to the case where the sound source position detecting part  15  estimates the coordinate position of each sound source  9   k , it is also possible to calculate the sound source direction, that is, the angular position of each sound source  9   k  to the arrangement of the microphones  11   1  to  11   M . A method for estimating the sound source direction is set forth, for example, in Tanaka, Kaneda, and Kojima, “Performance Evaluation of a Sound Source Direction Estimating Method under Room Reverberation,” Journal of the Society of Acoustic Engineers of Japan, Vol. 50, No. 7, 1994, pp. 540-548. In short, a covariance matrix of acquired signals needs only to be calculated for each sound source and stored. 
   Second Embodiment 
     FIG. 8  is a functional block diagram of a sound acquisition apparatus according to a second embodiment of the present invention. 
   The sound acquisition apparatus of this embodiment comprises microphones  11   1  to  11   M , filters  12   1  to  12   M , an adder  13 , a state decision part  14 , a sound source position detecting part  15 , a frequency domain converting part  16 , a covariance matrix calculating part  17 , a covariance matrix storage part  18 , an acquired sound level estimating part  19 , and a filter coefficient calculating part  21 . 
   This embodiment adds an effect of noise reduction to the acquired sound level adjustment of the sound acquisition apparatus according to the first embodiment of the present invention. 
   In the first place, the state decision part  14  detects an utterance period and a noise period from the power of the received signals from the microphones  11   1  to  11   M . The state decision part  14  includes, as shown in  FIG. 9 , a noise decision part  14 F added to the state decision part  14  of  FIG. 2 . For example, as is the case with the first embodiment, a short-time mean power P avS  and a long-time mean power P avL  are calculated by the short-time mean power calculating part  14 B and the long-time mean power calculating part  14 C for the acquired signals from the respective microphones, then the ratio, R p =P avS /P avL , between the short-time mean power and the long-time mean power is calculated in the division part  14 D, then the ratio is compared with an utterance threshold value P thU  in the utterance decision part  14 E, and if the power ratio exceeds the threshold value, it is decided as indicating the presence of the utterance period. The noise decision part  14 F compares the power ratio R p  with a noise threshold value P thN , and if the power ratio is smaller than the threshold value, it is decided as indicating the presence of the noise period. 
   When the result of decision by the utterance decision part  14 E is indicative of the utterance period, the sound source position detecting part  15  detects the position of the sound source concerned in the same way as in the first embodiment of the present invention. 
   Next, the frequency domain converting part  16  converts acquired signals from the microphones  11   1  o  11   M  in the utterance period and in the noise period of each sound source  9   k  into frequency domain signals, and provides them to the covariance matrix calculating part  17 . The covariance matrix calculating part  17  calculates a covariance matrix R SkSk (ω) of the frequency domain acquired signals for the sound source  9   k  in the same manner as in the first embodiment of the present invention. Further, the covariance matrix calculating part calculates a covariance matrix R NN (ω) of the frequency domain acquired signals in the noise period. 
   The covariance matrix storage part  18  stores, based on the result of detection by the sound source position detecting part  15  and the result of decision by the state decision part  14 , the covariance matrices R SkSk (ω) in the utterance period and the covariance matrices R NN (ω) in the noise period for the sound sources  9   1 , . . . ,  9   K  in areas MA 1 , . . . , MA K , MA K+1 . 
   The acquired sound level estimating part  19  estimates the acquired sound level P Sk  for each sound source in the same manner as in the first embodiment of the present invention. 
   Next, the filter coefficient calculating part  21  calculates filter coefficients for acquiring sound from each sound source  9   k  at a desired volume and for reducing noise. In the first place, the condition for noise reduction is calculated. Let the frequency domain converted signals of the microphone acquired signals in the noise period be represented by X N,1 (ω) to X N,M (ω). If the microphone acquired signals X N,1 (ω) to X N,M (ω) in the noise period become zero after passing through the filters  12   1  to  12   M  and the adder  13 , this means that noise could be reduced; hence, the condition for noise reduction is given by the following equation (17).
 
( X   N,1 (ω), . . . ,  X   N,M (ω)) H (ω)=0  (17)
 
   By satisfying both of Eq. (17) and Eq. (15) for adjusting the acquired sound level, mentioned previously in the first embodiment of the present invention, it is possible to implement both of the acquired sound level adjustment and the noise reduction. 
   Next, solving the conditions of Eqs. (15) and (17) by the least square method for the filter coefficient matrix H(ω) gives the following equation (18). 
                   H   ⁡     (   ω   )       =         {         ∑     k   =   1     K     ⁢           ⁢       C   Sk     ⁢       R   SkSk     ⁡     (   ω   )           +       C   N     ⁢       R   NN     ⁡     (   ω   )           }       -   1       ⁢       ∑     k   =   1     K     ⁢           ⁢       C   Sk     ⁢         P   opt       P   Sk         ⁢       R   SkSk     ⁡     (   ω   )       ⁢       A   k     ⁡     (   ω   )                     (   18   )               
C N  is a weight constant for the noise reduction rate; an increase in the value of the constant increases the noise reduction rate. But, since an increase in C N  decreases the sensitivity constraint for the sound source position and increases degradation of the frequency characteristics of the acquired sound signal, CN is normally set at an appropriate value approximately in the range of 0.1 to 10.0. The meanings of the other symbols are the same as in the first embodiment.
 
   Next, the filter coefficients calculated by Eq. (18) are set in the filters  12   1  to  12   M  and used to filter the microphone acquired signals. The filtered signals are added together by the adder  13 , from the added signal is provided as the output signal. 
   As described above, the second embodiment of the present invention permits reduction of noise in addition to the effect of acquired sound level adjustment in the first embodiment of the present invention. 
   The other parts of this embodiment are the same as in the first embodiment of the present invention, and hence they will not be described. 
   Third Embodiment 
     FIG. 10  is a functional block diagram of a sound acquisition apparatus according to a third embodiment of the present invention. 
   The sound acquisition apparatus of this embodiment comprises a loudspeaker  22 , microphones  11   1  to  11   M , filters  12   1  to  12   M  and  23 , an adder  13 , a state decision part  14 , a sound source position detecting part  15 , a frequency domain converting part  16 , a covariance matrix calculating part  17 , a covariance matrix storage part  18 , an acquired sound level estimating part  19 , and a filter coefficient calculating part  21 . 
   This embodiment adds, to the sound acquisition apparatus of the second embodiment of the present invention, the loudspeaker  22  for reproducing a received signal from a participating speaker at a remote location and the filter  23  for filtering the received signal, with a view to implementing, in addition to the acquired sound level adjustment and the noise reduction by the second embodiment, cancellation of acoustic echoes that are loudspeaker reproduced signal components which are acquired by the microphones  11   1  to  11   M . 
   The state decision part  14  has, in addition to the  FIG. 4  configuration of the state decision part  14  as shown in  FIG. 11 : a short-time mean power calculating part  14 B′ and a long-time mean power calculating part  14 C′ for calculating short-time mean power P′ avS  and long-time mean power P′ avL  of the received signal, respectively; a division part  14 D′ for calculating their ratio R′ p =P′ avS /P′ acL ; a receive decision part  14 G that compares the ratio R′ p  with a predetermined receive signal threshold value R thR  and, if the former is larger than the latter, decides the state as a receiving period; and a state determining part  14 H that determines the state based on the results of decision by the utterance decision part  14 E, the noise decision part  14 F and the receive decision part  14 G When the result of decision by the receive decision part  14 G is the receiving period, the state determining part  14 H determines the state as the receiving period, irrespective of the results of decision by the utterance decision part  14 E and the noise decision part  14 F, whereas when the receive decision part  14 G decides that the state is not the receiving period, the state determining part determines the state as the utterance or noise period according to the decisions by the utterance decision part  14 E and the noise decision part  14 F as in the case of  FIG. 4 . 
   When the result of decision by the state decision part  14  is the utterance period, the sound source position detecting part  15  detects the position of the sound source concerned in the same manner as in the first embodiment of the present invention. 
   Next, the frequency domain converting part  16  converts the microphone acquired signals and the received signal to frequency domain signals X 1 (ω), . . . , X M (ω) and Z(ω), and the covariance matrix calculating part  17  calculates covariance matrices of the frequency domain acquired signals and received signal. A covariance matrix R XX (ω) of the frequency domain converted signals X 1 (ω) to X M (ω) of the microphone acquired signals and the frequency domain converted signal Z(ω) is calculated by the following equation (19). 
                       R   XX     ⁡     (   ω   )       =       (           Z   ⁡     (   ω   )                   X   1     ⁡     (   ω   )               ⋮               X   M     ⁡     (   ω   )             )     ⁢     (       Z   ⁡     (   ω   )       *       X   1     ⁡     (   ω   )       *           ⁢   ⋯   ⁢           ⁢       X   M     ⁡     (   ω   )               ⁢   *)           (   19   )               
where * represents a complex conjugate.
 
   Next, in the covariance matrix storage part  18 , based on the result of detection by the sound source position detecting part  15  and on the result of decision by the state decision part  14 , the covariance matrix R XX (ω) is stored as covariance matrices R SkSk (ω) of the acquired signals and the received signal for each sound source  9   k  in the utterance period, as a covariance matrix R NN (ω) of the acquired signals and the received signal in the noise period, and as a covariance matrix R EE (ω) of the acquired signals and the received signal in the receiving period in areas MA 1 , . . . , MA K , MA K+1 , MA K+2 , respectively. 
   The acquired sound level estimating part  19  calculates the acquired sound level  Sk  for each sound source  9   k  by the following equation (20) based on the covariance matrices R S1S1 , . . . , R SKSK  for each sound source and predetermined weighted mixing vectors A 1 (ω), . . . , A K (ω) composed of M+1 elements for each sound source. 
   
     
       
         
           
             
               
                 
                   P 
                   Sk 
                 
                 = 
                 
                   
                     1 
                     W 
                   
                   ⁢ 
                   
                     
                       ∑ 
                       
                         ω 
                         = 
                         0 
                       
                       W 
                     
                     ⁢ 
                     
                       
                         
                           
                             A 
                             k 
                           
                           ⁡ 
                           
                             ( 
                             ω 
                             ) 
                           
                         
                         H 
                       
                       ⁢ 
                       
                         
                           R 
                           SkSk 
                         
                         ⁡ 
                         
                           ( 
                           ω 
                           ) 
                         
                       
                       ⁢ 
                       
                         
                           A 
                           k 
                         
                         ⁡ 
                         
                           ( 
                           ω 
                           ) 
                         
                       
                     
                   
                 
               
             
             
               
                 ( 
                 20 
                 ) 
               
             
           
         
       
     
   
   Next, the filter coefficient calculating part  21  calculates filter coefficients for acquiring, at a desired volume, speech sound uttered from each sound source. Let H 1 (ω) to H M (ω) represent frequency domain converted versions of the filter coefficients of the filters  12   1  to  12   M  connected to the microphones, respectively, and let F(ω) represent a frequency domain converted version of the filter coefficient of the filter  23  for filtering the received signal. Then, let H(ω) represent a matrix of these filter coefficients given by the following equation (21). 
   
     
       
         
           
             
               
                 
                   H 
                   ⁡ 
                   
                     ( 
                     ω 
                     ) 
                   
                 
                 = 
                 
                   ( 
                   
                     
                       
                         
                           F 
                           ⁡ 
                           
                             ( 
                             ω 
                             ) 
                           
                         
                       
                     
                     
                       
                         
                           
                             H 
                             1 
                           
                           ⁡ 
                           
                             ( 
                             ω 
                             ) 
                           
                         
                       
                     
                     
                       
                         ⋮ 
                       
                     
                     
                       
                         
                           
                             H 
                             M 
                           
                           ⁡ 
                           
                             ( 
                             ω 
                             ) 
                           
                         
                       
                     
                   
                   ) 
                 
               
             
             
               
                 ( 
                 21 
                 ) 
               
             
           
         
       
     
   
   Further, let X E,1 (ω) to X E,M (ω) represent frequency domain converted signals of the microphone acquired signal in the receiving period; let Z E (ω) represent a frequency domain converted signal of the received signal; let X N,1 (ω) to X N,M (ω) represent frequency domain converted signals of the microphone acquired signals in the noise period; let Z N (ω) represent a frequency domain converted signal of the received signal; let X Sk,1 (ω) to X Sk,M (ω) represent frequency domain converted signals of the microphone acquired signals in the utterance period of the k-th sound source  9   k ; and let Z Sk (ω) represent a frequency domain converted signal of the received signal. 
   In this case, the condition that the filter coefficient matrix H(ω) needs to meet is that when the microphone acquired signals and the send signal are each subjected to filtering with the filter coefficient matrix H(ω) and the signals after filtering are added together, acoustic echo and noise signals are cancelled and only the send speech signal is sent at a desired level. 
   Accordingly, for the signals during the receiving period and the noise period, the following equations (22) and (23) are ideal conditions by which the filtered and added signals become 0.
 
( Z   E (ω),  X   E,1 (ω), . . . ,  X   E,M (ω)) H (ω)=0  (22)
 
( Z   N (ω),  X   N,1 (ω), . . . ,  X   N,M (ω)) H (ω)=0  (23)
 
For the signal during the utterance period, the following equation is an ideal condition by which the filtered and added signal becomes equivalent to a signal obtained by multiplying the microphone acquired signals and the received signal by the weighted mixing vector A k (ω) composed of predetermined M+1 elements and a desired gain.
 
                     (         Z   Sk     ⁡     (   ω   )       ,       X     Sk   ,   1       ⁡     (   ω   )       ,   ⋯   ⁢           ,       X     Sk   ,   M       ⁡     (   ω   )         )     ⁢     H   ⁡     (   ω   )         =           P   opt       P   Sk         ⁢     (         Z   Sk     ⁡     (   ω   )       ,       X     Sk   ,   1       ⁡     (   ω   )       ⁢           ,   ⋯   ⁢           ,       X     Sk   ,   M       ⁡     (   ω   )         )     ⁢       A   k     ⁡     (   ω   )                 (   24   )               
The element a 0 (ω) of the weighted mixing vector A k (ω)=(a 0 (ω),a k1 (ω), . . . , a kM (ω)) represents a weighting factor for the received signal; normally, it is set at a 0 (ω)=0.
 
   Next, solving the conditions of Eqs. (22) to (24) by the least square method for the filter coefficient matrix H(ω) gives the following equation: 
                   H   ⁡     (   ω   )       =         {         ∑     k   =   1     K     ⁢       C   Sk     ⁢       R   SkSk     ⁡     (   ω   )           +       C   N     ⁢       R   NN     ⁡     (   ω   )         +       C   E     ⁢       R   EE     ⁡     (   ω   )           }       -   1       ⁢       ∑     k   =   1     K     ⁢       C   Sk     ⁢         P   opt       P   Sk         ⁢       R   SkSk     ⁡     (   ω   )       ⁢           ⁢       A   k     ⁡     (   ω   )                     (   25   )               
C E  is a weight constant for acoustic echo return loss enhancement; the larger the value, the more the acoustic echo return loss enhancement increases. But, an increase in the value C E  accelerates deterioration of the frequency characteristics of the acquired signal and lowers the noise reduction characteristic. On this account, C E  is usually set at an appropriate value approximately in the range of 0.1 to 10.0. The meanings of the other symbols are the same as in the second embodiment.
 
   In this way, the filter coefficients can be determined in such a manner as to adjust volume and reduce noise. 
   Next, the filter coefficients, obtained by Eq. (25), are set in the filters  12   1  to  12   M  and  23 , which filter the microphone acquired signals and the received signal, respectively. The filtered signals are added together by the adder  13 , from which the added signal is output as the send signal. The other parts are the same as in the second embodiment of the present invention, and hence no description will be repeated. 
   As described above, the third embodiment of the present invention permits implementation of acoustic echo cancellation in addition to the effects of acquired sound level adjustment and noise reduction by the second embodiment of the present invention. While the third embodiment has been described as adding the acoustic echo cancellation capability to the second embodiment, the acoustic echo cancellation capability may also be added to the first embodiment. In such an instance, the noise decision part  14 F is removed in  FIG. 11  showing in detail the state decision part  14  in  FIG. 10 , and the covariance matrix calculating part  17  in  FIG. 10  does not calculate the covariance matrix R NN (ω) in the noise period. Accordingly, the calculation of filter coefficients in the filter coefficient calculating part  21  may be carried out by the following equation, which is evident from the foregoing description. 
   
     
       
         
           
             
               
                 
                   H 
                   ⁡ 
                   
                     ( 
                     ω 
                     ) 
                   
                 
                 = 
                 
                   
                     
                       { 
                       
                         
                           
                             ∑ 
                             
                               k 
                               = 
                               1 
                             
                             K 
                           
                           ⁢ 
                           
                             
                               C 
                               Sk 
                             
                             ⁢ 
                             
                               
                                 R 
                                 SkSk 
                               
                               ⁡ 
                               
                                 ( 
                                 ω 
                                 ) 
                               
                             
                           
                         
                         + 
                         
                           
                             C 
                             E 
                           
                           ⁢ 
                           
                             
                               R 
                               EE 
                             
                             ⁡ 
                             
                               ( 
                               ω 
                               ) 
                             
                           
                         
                       
                       } 
                     
                     
                       - 
                       1 
                     
                   
                   ⁢ 
                   
                     
                       ∑ 
                       
                         k 
                         = 
                         1 
                       
                       K 
                     
                     ⁢ 
                     
                       
                         C 
                         Sk 
                       
                       ⁢ 
                       
                         
                           
                             P 
                             opt 
                           
                           
                             P 
                             Sk 
                           
                         
                       
                       ⁢ 
                       
                         
                           R 
                           SkSk 
                         
                         ⁡ 
                         
                           ( 
                           ω 
                           ) 
                         
                       
                       ⁢ 
                       
                           
                       
                       ⁢ 
                       
                         
                           A 
                           k 
                         
                         ⁡ 
                         
                           ( 
                           ω 
                           ) 
                         
                       
                     
                   
                 
               
             
             
               
                 ( 
                 26 
                 ) 
               
             
           
         
       
     
   
   Fourth Embodiment 
   Though described above as an embodiment having added the acoustic echo cancellation capability to the acquired sound level adjustment and noise reduction capabilities of the second embodiment, the third embodiment of  FIG. 10  may also be configured as a sound acquisition apparatus equipped with only the noise reduction and acoustic echo cancellation capabilities. An example of such a configuration is shown in  FIG. 12 . 
   As illustrated in  FIG. 12 , this embodiment has a configuration in which the sound source position detecting part  15  and the acquired sound level estimating part  19  in the  FIG. 10  configuration are removed and the covariance matrix calculating part  17  calculates a covariance matrix R SS (ω) of the send signal, a covariance matrix R EE (ω) of the received signal, and a covariance matrix R NN (ω) of the noise signal, which are stored in storage areas MA S , MA E  and MA N  of the covariance storage part  18 , respectively. The acoustic echo cancellation capability can be implemented using at least one microphone, but an example using M microphones is shown. 
   The state decision part  14  decides, as in the  FIG. 10  embodiment, the utterance period, the receiving period, and the noise period from the signals acquired by the microphones  12   1  to  12   M  and the received signal; the state decision part is identical in concrete configuration and in operation with the counterpart depicted in  FIG. 11 . The acquired signals and the received signal are converted by the frequency domain converting part  16  to frequency domain acquired signals X 1 (ω) to X M (ω) and a frequency domain received signal Z(ω), which are provided to the covariance matrix calculating part  17 . 
   Next, the covariance matrix calculating part  17  generates a covariance matrix of the frequency domain acquired signals and received signal. The covariance matrix R XX (ω) of the frequency domain converted signals X(ω) to X M (ω) of the microphone acquired signals and the frequency domain converted signal Z(ω) of the received signal is calculated by the following equation (27). 
                       R   XX     ⁡     (   ω   )       =       (           Z   ⁡     (   ω   )                   X   1     ⁡     (   ω   )               ⋮               X   M     ⁡     (   ω   )             )     ⁢     (         Z   ⁡     (   ω   )       *     ,         X   1     ⁡     (   ω   )       *     ,   ⋯   ⁢           ,       X   M     ⁡     (   ω   )               ⁢   *)           (   27   )               
where * represents a complex conjugate.
 
   Next, in the covariance matrix storage part  18 , based on the result of detection by the state decision part  14 , the covariance matrix R XX (ω) is stored as a covariance matrix R SS (ω) of the acquired signals and the received signal for each sound source  9   k  in the utterance period, as a covariance matrix R NN (ω) of the acquired signals and the received signal in the noise period, and as a covariance matrix R EE (ω) of the acquired signals and the received signal in the receiving period in areas MA S , MA N , and MA E , respectively. 
   Next, the filter coefficient calculating part  21  acquires speech sound uttered from sound sources, and calculates filter coefficients for canceling acoustic echo and noise. Let H 1 (ω) to H M (ω) represent frequency domain converted versions of the filter coefficients of the filters  12   1  to  12   M  connected to the microphones  11   1  to  11   M , respectively, and let F(ω) represent a frequency domain converted version of the filter coefficient of the filter  23  for filtering the received signal. Then, let H(ω) represent a matrix of these filter coefficients given by the following equation (28). 
   
     
       
         
           
             
               
                 
                   H 
                   ⁡ 
                   
                     ( 
                     ω 
                     ) 
                   
                 
                 = 
                 
                   ( 
                   
                     
                       
                         
                           F 
                           ⁡ 
                           
                             ( 
                             ω 
                             ) 
                           
                         
                       
                     
                     
                       
                         
                           
                             H 
                             1 
                           
                           ⁡ 
                           
                             ( 
                             ω 
                             ) 
                           
                         
                       
                     
                     
                       
                         ⋮ 
                       
                     
                     
                       
                         
                           
                             H 
                             M 
                           
                           ⁡ 
                           
                             ( 
                             ω 
                             ) 
                           
                         
                       
                     
                   
                   ) 
                 
               
             
             
               
                 ( 
                 28 
                 ) 
               
             
           
         
       
     
   
   Further, let X E,1 (ω) to X E,M (ω) represent frequency domain converted signals of the microphone acquired signals in the receiving period; let Z E (ω) represent a frequency domain converted signal of the received signal; let X N,1 (ω) to X N,M (ω) represent frequency domain converted signals of the microphone acquired signals in the noise period; let Z N (ω) represent a frequency domain converted signal of the received signal; let X Sk,1 (ω) to X Sk,M (ω) represent frequency domain converted signals of the microphone acquired signals in the utterance period; and let Z S (ω) represent a frequency domain converted signal of the received signal in the utterance period. 
   In this case, the condition that the filter coefficient matrix H(ω) needs to meet is that when the microphone acquired signals and the send signal are each subjected to filtering with the filter coefficient matrix H(ω) and the signals after filtering are added together, acoustic echo and noise signals are cancelled and only the send speech signal is sent at a desired level. 
   Accordingly, for the signals during the received signal period and the noise period, the following equations (29) and (30) are ideal conditions by which the filtered and added signals become 0.
 
( Z   E (ω),  X   E,1 (ω), . . . ,  X   E,M (ω),) H (ω)=0  (29)
 
( Z   N (ω),  X   N,1 (ω), . . . ,  X   N,M (ω)) H (ω)=0  (30)
 
For the signal during the utterance period, the following equation is an ideal condition by which the filtered and added signal becomes equivalent to a signal obtained by multiplying the microphone acquired signals and the received signal by the weighted mixing vector A(ω) composed of predetermined M+1 elements.
 
( Z   S (ω),  X   S,1 (ω), . . . ,  X   S,M (ω)) H (ω)=( Z   S (ω),  X   S,1 (ω), . . . ,  X   S,M (ω)) A (ω)  (31)
 
The first element a 0 (ω) of the weighted mixing vector A(ω)=(a 0 (ω),a k1 (ω), . . . , a kM (ω)) represents a weighting factor for the received signal; normally, it is set at a 0 (ω)=0.
 
   Next, solving the conditions of Eqs. (29) to (31) by the least square method for the filter coefficient matrix H(ω) gives the following equation:
 
 H (ω)={ R   SS (ω)+ C   N   R   NN (ω)+ C   E   R   EE (ω)} −1   R   SS (ω) A (ω)  (32)
 
C E  is a weight constant for acoustic echo return loss enhancement; the larger the value of the weight constant, the more the acoustic echo return loss enhancement increases. But, an increase in the value C E  accelerates deterioration of the frequency characteristics of the acquired signal and lowers the noise reduction characteristic. On this account, C E  is usually set at an appropriate value approximately in the range of 0.1 to 10.0. The meanings of the other symbols are the same as in the second embodiment.
 
   In this way, the filter coefficients can be determined in such a manner as to adjust volume and reduce noise. 
   Next, the filter coefficients, obtained by Eq. (32), are set in the filters  12   1  to  12   M  and  23 , which filter the microphone acquired signals and the received signal, respectively. The filtered signals are added together by the adder  13 , from which the added signal is output as the send signal. The other parts are the same as in the second embodiment of the present invention, and hence no description will be repeated. 
   As described above, the fourth embodiment of the present invention permits implementation of acoustic echo cancellation in addition to the effect of noise reduction. 
   Fifth Embodiment 
     FIG. 13  illustrates a fifth embodiment. According to the fifth embodiment, in the fourth embodiment of  FIG. 12 , sound source positions are detected during the utterance period, a covariance matrix is calculated for each sound source and stored and during the noise period a covariance matrix for noise is calculated and stored. Then, these stored covariance matrices are used to calculate filter coefficients for canceling noise and acoustic echo. The microphone acquired signals and the received signal are filtered using these filter coefficients to thereby obtain a send signal from which noise and acoustic echo have been cancelled. 
   The configuration of the fifth embodiment is common to the configuration of the third embodiment except the removal of the acquired sound level estimating part  19  in  FIG. 10 . 
   The state decision part  14  detects the utterance period, the receiving period and the noise period as in the third embodiment. When the result of decision by the state decision part  14  is the utterance period, the sound source position detecting part  15  estimates the position of each sound source  9   k . The sound source position estimating method is the same as that used in the first embodiment of  FIG. 1 , no description will be repeated. 
   Next, in the frequency domain converting part  16  the acquired signals and the received signal are converted to frequency domain signals, which are provided to the covariance matrix calculating part  17 . 
   The covariance matrix calculating part  17  calculates covariance matrices R S1S1 (ω) to R SKSK (ω) of the acquires signals for the respective sound sources  9   k  and the received signal, a covariance matrix R EE (ω) in the receiving period and a covariance matrix R NN (ω) in the noise period. The covariance matrix storage part  18  stores the covariance matrices R S1S1 (ω) to R SKSK (ω), R EE (ω) and R NN (ω) in the corresponding areas MA 1  to, MA K , MA K+1  and MA K+2 , respectively, based on the result of decision by the state decision part  14  and the results of position detection by the sound source position detecting part  15 . 
   Upon the send speech sound being acquired, the filter coefficient calculating part  21  calculates filter coefficients for canceling acoustic echo and noise. As is the case with the third embodiment, solving the conditional expression for the filter coefficient matrix H(ω) by the least square method gives the following equation: 
                   H   ⁡     (   ω   )       =         {         ∑     k   =   1     K     ⁢       C   Sk     ⁢       R   SkSk     ⁡     (   ω   )           +       C   N     ⁢       R   NN     ⁡     (   ω   )         +       C   E     ⁢       R   EE     ⁡     (   ω   )           }       -   1       ⁢       ∑     k   =   1     K     ⁢       C   Sk     ⁢       R   SkSk     ⁡     (   ω   )       ⁢           ⁢       A   k     ⁡     (   ω   )                     (   33   )               
In the above, C S1  to C SK  are weight constants of sensitivity constraints for the respective sound sources, C E  is a weight constant for the echo return loss enhancement, and C N  is a weight constant for the noise reduction rate.
 
   The filter coefficients thus obtained are set in the filters  12   1  to  12   M  and  23 , which filter the microphone acquired sound signals and the received signal, respectively. The filtered signals are added together by the adder  13 , from which the added signal is output as the send signal. The other parts are the same as in the second embodiment of the present invention, and hence no description will be repeated. The fifth embodiment permits generation of a send signal having cancelled therefrom acoustic echo and noise as is the case with the third embodiment. Further, according to the fifth embodiment, sensitivity constraints can be imposed on a plurality of sound sources, and sensitivity can be held for a sound source having uttered speech sound previously as well. Accordingly, this embodiment is advantageous in that that even when the sound source moves, the speech quality does not deteriorate in the initial part of the speech sound since the sensitivity for the sound source is maintained if it has uttered speech sound in the past. 
   Sixth Embodiment 
   A sound acquisition apparatus according to a sixth embodiment of the present invention will be described. 
   In the sound acquisition apparatus of this embodiment, the weighting factors C S1  to C SK  of the sensitivity constraints for the sound source positions  9   k  in the sound acquisition apparatuses of the first to third and fifth embodiments are changed on a timewise basis. 
   The time-variant weighting factors C S1  to C SK  of the sensitivity constraints for the sound sources  9   1  to  9   K  are set smaller in order of utterance in the past. A first method is to reduce the weighting factor C Sk  with an increase in the elapsed time from the detection of each already detected sound source position to the detection of the most recently detected sound source position. A second method is to set the weighting factor C Sk  smaller in order of detection of K sound source positions. 
     FIG. 14  illustrates in block form the functional configuration of a weighting factor setting part  21 H for implementing the above-said first method. The weighting factor setting part  21 H is made up of: a clock  21 H 1  that outputs time; a time storage part  21 H 2  that upon each detection of sound source position, overwrites the time t of detection, using, as an address, the number k representing the detected sound source  9   k ; and a weighting factor determining part  21 H 3 . Based on the time of detection of the sound source position stored in the time storage part  21 H 2 , the weighting factor determining part  21 H 3  assigns a predetermined value C S  as the weighting factor S Ck  to the currently detected sound source of a number k(t), and assigns a value q (t−tk) C S  as the weighting factor C Sk  to each of the other sound sources of numbers k≠k(t) in accordance with the elapsed time t-tk after the detection time t k . q is a predetermined value in the range of 0&lt;q≦1. In this way, the weighting factors C S1  to C SK  of sensitivity constraints are determined for the respective sound sources, and they are provided to  21 A 1  to  21 AK. 
     FIG. 15  illustrates in block form the functional configuration of a weighting factor setting part  21 H for implementing the above-said second method; in this example, it is made up of a clock  21 H 1 , a time storage part  21 H 2 , an order decision part  21 H 4 , and a weighting factor determining part  21 H 5 . The order decision part  21 H 4  decides the order of detection of the positions of the sound sources  9   1  to  9   K  (the newest order) {k(t)}={k(1), . . . , k(K)} from the times stored in the time storage part  21 H 2 . The weighting factor determining part  21 H 5  assigns a predetermined value C S  as a weighting factor C Sk(1)  to the most recently detected sound source  9   k(1) . For the other sound sources, the weighting factor determining part calculates C Sk(t+1) ←qC Sk(t)  for t=1, 2, . . . , K−1 to obtain weighting factors C Sk(2) , . . . , C Sk(t) . These weighting factors C Sk(2)  to C Sk(t)  are rearranged following the order {k(1), . . . , k(K)}, thereafter being output as weighting factors C S1 , . . . , C SK . The value of q is a preset value in the range of 0&lt;q&lt;1. 
   By varying the weights of sensitivity constrains for the respective sound sources as described above, it is possible to reduce the sensitivity constrains for the sound source positions where utterance was made in the past. Thus, as compared with the sound acquisition apparatuses of the first to third embodiments, the apparatus of this embodiment reduces the number of sound sources to be subjected to sensitivity constraints, enhancing the acquired sound level adjustment capability and the noise and acoustic echo cancellation functions. 
   The other parts are the same as those in the first to third and fifth embodiments of the present invention, and hence no description will be repeated. 
   Seventh Embodiment 
   A sound acquisition apparatus according to a seventh embodiment of the present invention will be described. 
   The sound acquisition apparatus according to the seventh embodiment of the present invention features whitening the covariance matrix R XX (ω) in the filter coefficient calculating part  21  of the sound acquisition apparatus according to the first to sixth embodiments of the present invention.  FIG. 16  illustrates the functional configuration of a representative one of whitening parts  21 J 1  to  21 JK indicated by the broken lines in the filter coefficient calculating part  21  shown in  FIG. 4 . The whitening part  21 J comprises a diagonal matrix calculating part  21 JA, a weighting part  21 JB, an inverse operation part  21 JC and a multiplication part  21 JD. The diagonal matrix calculating part  21 JA generates a diagonal matrix diag(R XX (ω) of the covariance matrix R XX (ω) fed thereto. The weighting part  21 JB assign weights to the diagonal matrix by calculating the following equation based on a matrix D of a predetermined arbitrary M or M+1 rows.
 
 D   T diag( R   XX (ω)) D   (34)
 
The inverse calculation part  21 JC calculates an inverse of Eq. (34)
 
1/{ D   T diag( R   XX (ω)) D}   (35)
 
In the above  T  indicates a transpose of the matrix. In the multiplication part  21 JD the result of calculation by the inverse calculation part  21 JC is multiplied by each covariance matrix R XX (ω) input thereto to obtain a whitened covariance matrix.
 
   With the covariance matrix thus whitened, the filter coefficients obtained in the filter coefficient calculating part  21  no linger change with spectral changes of the send signal, acquired signal and the noise signal. As a result, the acquired sound level adjustment capability and the acoustic echo and noise cancellation capabilities do not change with the spectral changes—this makes it possible to achieve steady acquired sound level adjustment and acoustic echo and noise cancellation. 
   The other parts are the same as in the first to fourth embodiments of the present invention, and hence no description will be repeated. 
   Eighth Embodiment 
   A sound acquisition apparatus according to an eighth embodiment of the present invention will be described. 
   The sound acquisition apparatus of the eighth embodiment features that the covariance matrix storage part  18  of the sound acquisition apparatus according to the first to seventh embodiments of the present invention averages an already stored covariance matrix and a covariance matrix newly calculated by the covariance matrix calculating part  17  and stores the averaged covariance matrix as the current one. 
   The covariance matrices are averaged, for example, by the method described below. Letting the already stored covariance matrix be represented by R XX,old (c) and the covariance matrix newly calculated by the covariance matrix calculating part  17  by R xx,new (ω), the following equation is used to calculate an average covariance matrix R XX (ω).
 
 R   XX (ω)=(1− p ) R   XX,new (ω)+ pR   XX,old (ω)  (36)
 
where p is a constant that determines the time constant of the average and takes a value 0≦p&lt;1.
 
     FIG. 17  illustrates the functional configurations of the covariance matrix storage part  18  and an averaging part  18 A provided therein. The averaging part  18 A comprises a multiplier  18 A 1 , an adder  18 A 2 , and a multiplier  18 A 3 . The covariance matrix R SkSk (ω) corresponding to the sound source  9   k , calculated by the covariance matrix calculating part  17 , is provided as a new covariance matrix R SkSk,new (ω) to the multiplier  18 A 1  and is multiplied by (1−p), and the multiplied output is applied to the adder  18 A 2 . On the other hand, the covariance matrix R SkSk (ω) corresponding to the sound source  9   k  is read out of the storage area  18 B then provided as a old covariance matrix R SkSk,old (ω) to the multiplier  18 A 3  and multiplied by the constant p. The multiplied output is added by the adder  18 A 2  to the output (1−p)R SkSk,new (ω) from the multiplier  18 A 1 , and the thus obtained average covariance matrix R SkSk (ω) is overwritten in the storage area corresponding to the sound source  9   k . 
   By averaging covariance matrices and storing the averaged covariance matrix as described above, it is possible to lessen the influence of a circuit noise or similar disturbance as compared with that before averaging, hence providing an accurate covariance matrix—this makes it possible to determine filter coefficients that enhance the acquired sound level adjustment, noise cancellation or acoustic echo cancellation performance. 
   The other parts are the same as in the first to fifth embodiments of the present invention, and hence no description will be repeated. 
   Incidentally, the present invention can be implemented by dedicated hardware; alternatively, it is possible that a program for implementing the invention is recorded on a computer-readable recording medium and read into a computer for execution. The computer-readable recording medium refers to a storage device such as a floppy disk, an magneto-optical disk, CD-ROM, DVD-ROM, a nonvolatile semiconductor memory, or an internal or external hard disk. The computer-readable recording medium also includes a medium that dynamically holds a program for a short period of time (a transmission medium or transmission wave) as in the case of transmitting the program via the Internet, and a medium that holds the program for a fixed period of time, such as a volatile memory in the computer system serving as a server in that case. 
   EFFECT OF THE INVENTION 
   Next, to demonstrate the effectiveness of the first embodiment of the sound acquisition apparatus according to the present invention,  FIGS. 18A and 18B  show the results of simulations with microphones disposed at corners of a square measuring 20 cm by 20 cm. The simulation conditions are—number of microphones: 4, signal-to-noise ratio: about 20 dB, room reverberation time: 300 ms, and number of speakers: 2 (speaker A at a position 50 cm away from the center of the square in a direction at right angles to one side thereof, speaker B at a position 200 cm away from the center of the square in a direction at 90° to the speaker A).  FIG. 18A  shows microphone received signal waveforms obtained when the speakers A and B spoke alternately under the above-mentioned conditions. Comparison between the speech waveforms of the speakers A and B indicates that the speech waveform of the speaker B is small in amplitude.  FIG. 18B  shows waveforms processed by the present invention. The speech waveforms of the speakers A and B are nearly equal in amplitude, from which the effect of acquired sound level adjustment can be confirmed. 
     FIG. 19  shows simulation results obtained with the third embodiment shown in  FIG. 10 . The simulation conditions are—number M of microphones: 4, signal-to-noise ratio of send signal before processed: 20 dB, send signal-to-acoustic echo ratio: −10 dB, and room reverberation time: 300 msec.  FIG. 19  shows the send signal levels obtained when signal sending and receiving are repeated alternately under the above-mentioned conditions. 
   Row A shows the send signal level before processing, and Row B the send signal level after processing by the third embodiment. The above results indicate that the third embodiment reduces the acoustic echo about 40 dB and the noise signal about 15 dB, from which it can be confirmed that the embodiment of the invention is effective. 
   As described above, according to the first embodiment of the present invention, it is possible to obtain a send signal of a volume adjusted for each sound source position by: detecting the sound source position from signals picked up by a plurality of microphones; calculating filter coefficients based on a covariance matrix in the utterance period for each sound source position; filtering the microphone acquired signals by the filter coefficients; and adding the filtered signals. 
   According to the second embodiment of the present invention, it is possible to achieve noise cancellation as well as the acquired sound level adjustment by determining the filter coefficients by using a covariance matrix in the noise period in addition to the covariance in the utterance period in the first embodiment. 
   According to the third embodiment of the present invention, it is possible to achieve acoustic cancellation by determining the filter coefficients by using a covariance matrix in the receiving period in addition to the covariance matrix in the utterance period in the first or second embodiment. 
   According to the fourth embodiment of the present invention, it is possible to reproduce the received signal by a loudspeaker and cancel acoustic echo by determining the filter coefficients by using the covariance matrix in the utterance period and the covariance matrix in the receiving period. 
   According to the fifth embodiment of the present invention, it is possible to further cancel noise by determining the filter coefficients by using the covariance matrix in the noise period in addition to the covariance matrices in the utterance and receiving periods in the fourth embodiment. 
   According to the sixth embodiment of the present invention, it is possible to further enhance the acquired sound level adjustment, noise cancellation or acoustic echo cancellation performance by assigning a smaller weighting factor to the covariance matrix of older utterance at the time of calculating the filter coefficients in the first, second, third and fifth embodiments. 
   According to the seventh embodiment of the present invention, it is possible to implement acquired sound level adjustment, noise cancellation and acoustic echo cancellation not so susceptible to signal spectral changes by whitening the covariance matrix at the time of calculating the filter coefficients in the first to sixth embodiment. 
   According to the eighth embodiment of the present invention, when the covariance matrix is stored in the first to seventh embodiments, the covariance matrix and that already stored in the corresponding area are averaged and a weighted mean covariance matrix is stored, by which it is possible to obtain a more accurate covariance matrix and determine filter coefficients that provide increased performance in the acquired sound level adjustment, noise reduction and acoustic echo cancellation.