Telephonic communications – Subscriber line or transmission line interface – Network interface device
Reexamination Certificate
1997-09-11
2001-06-12
Woo, Stella (Department: 2643)
Telephonic communications
Subscriber line or transmission line interface
Network interface device
C379S406010
Reexamination Certificate
active
06246760
ABSTRACT:
BACKGROUND OF THE INVENTION
The present invention relates to an echo cancellation method for cancelling room echoes which would otherwise cause howling and give rise to psychoacoustic problems in a teleconferencing system using a multi-receive-system and, more particularly, to a subband echo cancellation method and apparatus for a multichannel audio teleconference which updates or corrects an estimated impulse response of an echo path for each subband through utilization of a projection algorithm or the like.
ONE-CHANNEL ECHO CANCELLATION
An echo canceller is used to offer a hands-free telecommunication system that has an excellent double-talk function and is virtually free from echoes.
A description will be given first, with reference to
FIG. 1
, of a one-channel echo canceller. In hands-free communication, speech uttered by a person at a remote place is provided as a received signal to a received signal terminal
11
and is radiated from a loudspeaker
12
directly or after being subjected to some processing by a received signal processing part
13
that automatically adjusts the gain of the received signal according to its amplitude, power or similar magnitude. For this reason, the received signal x
1
(k) herein mentioned is not limited specifically to the received signal itself but shall refer to a processed received signal as well when the received signal processing part
13
is employed. In
FIG. 1
, k indicates discrete time. An echo canceller
14
cancels an echo y(k) which is produced when the received signal x
1
(k) radiated from the loudspeaker
12
is picked up by a microphone
16
after propagating over an echo path
15
. The echo y
1
(k) can be modeled by such a convolution as follows:
y
1
(
k
)
=
∑
l
=
0
L
-
1
h
11
(
k
,
1
)
x
1
(
k
-
1
)
(
1
)
where &Sgr; indicates a summation from 1=0 to L−1, h
11
(k,n) is the impulse response indicating the transfer function of the echo path
15
at time k and L is the number of taps, which is a constant preset corresponding to the reverberation time of the echo path
15
. In the first place, received signals x
1
(k) from the current time to L−1 are stored in a received signal storage and vector generating part
17
. The L received signals thus stored are outputted as a received signal vector x
1
(k), that is, as
x
1
(k)=[x
1
(k), x
1
(k−1), . . . , x
1
(k−L+1)]
T
(2)
where *
T
indicates a transposition. In an estimated echo generating part
18
, the inner product of the received signal vector x
1
(k) of Eq. (2) and an estimated echo path vector ĥ
11
(k), which is provided from an echo path estimating part
19
, is calculated as follows:
ŷ
1
(k)=ĥ
11
T
(k)x
1
(k) (3)
As a result, an estimated echo or echo replica ŷ
1
(k) is generated. This inner product calculation is equivalent to such a convolution as Eq. (1). In the echo path estimating part
19
, the estimated echo path vector ĥ
11
(k) is generated which is used in the estimated echo generating part
18
.
Since the impulse response h
11
(k,1) of the echo path
15
from the loudspeaker
12
to the microphone
16
varies with a sound field variation by a movement of a person or object, for instance, the estimated echo path vector ĥ
11
(k) needs to be varied following the time-varying impulse response of the echo path
15
. In this example, the echo canceller
14
is formed by an adaptive FIR (Finite Impulse Response) filter. The most common algorithm for the echo path estimation is an NLMS (Normalized Least Mean Square) algorithm. With the NLMS algorithm, the received signal vector x
1
(k) at time k and a residual echo e
1
(k), i.e. the following error, obtained by subtracting the estimated echo signal ŷ
1
(k) from the output y
1
(k) of the microphone
16
by a subtractor
21
,
e
1
(k)=y
1(k)−ŷ
1
(k) (4)
are used to calculate an estimated echo path vector ĥ
11
(k+1) which is used at time k+1, by the following equation:
ĥ
11
(k+1)=ĥ
11
(k)+&mgr;e
1
(k)x
1
(k)/(x
1
T
(k)x
1
(k)) (5)
where &mgr; is called a step size parameter, which is used to adjust adaptation within the range of 0<&mgr;<2. By repeating the above processing, the estimated echo path vector ĥ
11
(k) in the echo path estimating part
19
can be gradually brought into agreement with a true echo path vector h
11
(k) whose elements are impulse response sequences h
11
(k, 1) of the true echo path
15
, that is, the following echo path vector:
h
11
(k)=[h
11
(k,0), h
11
(k,1), . . . , h
11
(k,L−1)]
T
(6)
As the result of this, the residual echo e
1
(k) given by Eq. (4) can be reduced.
The most effective algorithm now in use for the echo path estimation is a projection algorithm or ES projection algorithm (hereinafter referred to as an ESP algorithm). The projection algorithm is based on an idea of improving the convergence speed for correlated signals such as speech by removing the auto-correlation between input signals in the algorithm. The removal of auto-correlated components means whitening of signals in the time domain. The projection algorithm is described in detail in K. Ozeki and T. Umeda, “An Adaptive filtering Algorithm Using an orthogonal Projection to an Affine Subspace and Its Properties,” T rans.(A), IEICE Japan, vol.J67-A, No.2, pp.126-132, February, 1984.
In general, the p-order projection algorithm updates the estimated echo path vector ĥ(k) in such a manner as to obtain correct outputs y(k), y(k−1), . . . , y(k−p+1) for the last p input signal vectors x(k), x(k−1), . . . , x(k−p+1). That is, ĥ(k+1) is computed which satisfies the following equations:
x
T
(k)ĥ(k+1)=y(k)
x
T
(k−1)ĥ(k+1)=y(k−1)
x
T
(k−p+1)ĥ(k+1)=y(k−p+1) (7)
where
x(k)=[x(k),x(k−1), . . . ,x(k−L+1)]
T
(8)
When the number p of equations is smaller than the number of unknown numbers (the number of taps) L, the solution ĥ(k+1) of the simultaneous equations (7) is indeterminate. Hence, the estimated echo path vector is updated to minimize the value or magnitude of the updating ∥ĥ(k+1)−ĥ(k)∥. The p-order projection algorithm in such an instance is expressed by the following equation:
ĥ(k+1)=ĥ(k)+&mgr;[X
T
(k)]
+
e(k) =ĥ(k)+&mgr;X(k)[X
T
(k)X(k)]
−1
e(k) =ĥ(k)+&mgr;X(k)&bgr;(k) =ĥ(k)+&mgr;[&bgr;
1
x(k)+&bgr;
2
x(k−1)+. . . +&bgr;
p
x(k−p+1)] (9)
where
X(k)=[x(k),x(k−1), . . . ,x(k−p+1)] (10)
e(k)=[e(k),(1−&mgr;)e(k−1), . . . ,(1−&mgr;)
P−1
e(k−p+1)]
T
(11)
e(k)=y(k)−ŷ(k) (12)
ŷ(k)=ĥ(k)
T
X(k) (13)
&bgr;(k)=[&bgr;
1
, &bgr;
2
, . . . , &bgr;
P
]
T
(14)
+
: generalized inverse matrix
−
1
: inverse matrix.
In the above, &bgr;(k) is the solution of the following simultaneous linear equation with p unknowns:
[X
T
(k)X(k)]&bgr;(k)=e(k) (15)
To avoid instability in the inverse matrix operation, a small positive constant &dgr; may be used as follows:
[X
T
(k)X(k)+&dgr;I]&bgr;(k)=e(k) (15)′
where I is a unit matrix. The second term on the right-hand side of Eq. (9) is an updated vector, with which the estimated echo path vector is iteratively updated. X(k)&bgr;(k) in Eq. (9) represents processing for removing the auto-correlation of the input signal. The removal of auto-correlation means suppression of input signal variations in the time domain, and hence it means whitening of the signals in the
Haneda Yoichi
Kojima Junji
Makino Shoji
Nakagawa Akira
Shimauchi Suehiro
Connolly Bove & Lodge & Hutz LLP
Nippon Telegraph & Telephone Corporation
Woo Stella
LandOfFree
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