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JPWO2014024248

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DESCRIPTION JPWO2014024248
Abstract: A first target sound blocker 103 that removes target signals having correlation with
each other from the first audio signal x and the second audio signal x that are converted into
audio signals by the first and second microphones 101 and 102. And the second target sound
blocker 104 and the information acquired when the first target sound blocker 103 removes the
target signal, the phases of the first audio signal x and the second audio signal x are calculated.
The noise component included in the output signal of the phasing unit 105 is learned from the
signal from which the target signal has been removed by the phasing unit 105 to be combined
and synthesized, and the first target sound blocking unit 103 and the second target sound
blocking unit 104. And a noise learning unit 106.
Beam forming device
[0001]
The present invention relates to a beamforming apparatus that performs beamforming to obtain
a signal in which a target signal is enhanced from a plurality of microphone signals.
[0002]
A technology that separates and extracts only the signal of a specific signal source (speaker) in
order to construct an on-vehicle hands-free communication system in a noisy environment or an
environment in which multiple signal sources exist Is required.
03-05-2019
1
One of the techniques is a beam former. Beamformers emphasize signals in a target direction by
adding together signals of a plurality of channels by a microarray, and include fixed beamformers
and adaptive beamformers.
[0003]
The simplest fixed beamformer is the delay and sum method, and as shown in FIG. 6, it comprises
microphones 901 and 902 of two channels, a signal delay unit 903 and a delay and sum unit
904. Although this delay-and-sum method generally requires less computational complexity,
when it is difficult to use a large number of microphones, such as for in-vehicle purposes, the
side lobe is large, it is weak in a reverberant environment, for low frequency regions. There was a
problem that sufficient directivity could not be obtained. In order to improve directivity in the
low frequency region, it is necessary to increase the overall array length of the microphone array.
For example, in order to obtain directivity of about ± 10 ° in the main lobe for a sound of 1000
Hz, an array length of about 2 m is required. In addition, when the array length is increased
simply by increasing the distance between the microphone arrays, grating lobes are generated in
directions other than the target direction, and there is a problem that the directivity is lowered
(see Non-Patent Document 1). Therefore, in order to suppress grating lobes and maintain
directivity in a low frequency region, it is necessary to closely arrange a large number of
microphones, which is very costly.
[0004]
On the other hand, the adaptive beamformer is a method of forming directivity so that the noise
source becomes a dead angle while keeping the sensitivity in the target direction constant, and is
effective even in the low frequency region and in a reverberant environment Noise suppression
can also be performed. There are various methods for adaptive beamformers, but one of the
methods that can be regarded as an extension of the delay-and-sum method is the Generalized
Sidelobe Canceller (GSC). The generalized sidelobe canceller is a beamformer that suppresses
noise with a fixed beamformer and an adaptive filter, and a general Griffith-Jim type GSC with a
two-channel microphone is configured as shown in FIG. The target sound blocking unit 905
performs subtraction-type beam forming by subtraction of microphone signals. The noise
component is estimated in the adaptive filter 906 using the output of the target sound blocking
unit 905, and the difference with the output of the delay summing unit 904 is obtained.
[0005]
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2
It is considered that only the noise component from which the target signal has been subtracted
remains in the output result of the subtractive beamformer, and the noise component can be
removed from the delay-and-sum result by applying it as the input of the adaptive filter. .
However, in many cases the target signal can not be removed sufficiently by simple subtraction,
and there is a problem that the target signal can not be removed sufficiently by the adaptive
filter, and the target signal is removed. As a countermeasure against this, according to Patent
Document 1, the target sound blocking unit is configured by an output of a fixed beam former
and an adaptive filter using a microphone input, and configured to remove a target signal from
each microphone input. Since a signal from which the target sound has been removed can be
obtained more than a simple subtraction-type beam former, the performance of noise
suppression in the subsequent adaptive filter can be improved.
[0006]
Japanese Patent Application Publication No. 08-122424
[0007]
Oga Juro, Yamazaki Yoshio, Kanada Yutaka, "Sound System and Digital Processing", First Edition,
The Institute of Electronics, Information and Communication Engineers, March 25, 1995, p 181186
[0008]
However, the technique disclosed in Patent Document 1 mentioned above improves the signal to
noise ratio by aligning the phases of a plurality of input signals with a fixed FIR (Finite Impulse
Response) filter or the like in a fixed beam former. There is a problem that the phase alignment
can not be performed with high accuracy if the phase shift or intensity differs or varies
depending on the environment of the sound field depending on the environment of the sound
field, and the phase alignment performance is degraded. .
[0009]
The present invention has been made to solve the problems as described above, and its object is
to improve the accuracy of phasing of a plurality of input signals and to obtain an output signal
having an improved SN ratio.
[0010]
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3
A beam forming apparatus according to the present invention is composed of two microphones,
and an audio input unit that converts collected voice into a first audio signal and a second audio
signal; and a first audio signal converted by the audio input unit. When the first target sound
blocking unit and the first target sound blocking unit remove the target signal from the first and
second audio signals, the first target sound blocking unit and the second target sound blocking
unit remove the target signals having correlation with each other. A phase matching unit that
combines the phases of the first audio signal and the second audio signal using the acquired
information and combines them, and removes the target signal in the first target sound blocking
unit and the second target sound blocking unit And a noise learning unit for learning a noise
component included in the output signal of the phasing unit from the received signal.
[0011]
According to the present invention, it is possible to perform phase alignment of a plurality of
input signals with high accuracy and to obtain an output signal with an improved SN ratio,
without being affected by changes in the sound field environment.
[0012]
FIG. 1 is a diagram showing a configuration of a beam forming device according to Embodiment
1.
FIG. 7 is a diagram showing a configuration of a beam forming device according to Embodiment
2.
FIG. 8 is a diagram showing a configuration of a beam forming device according to Embodiment
3.
FIG. 16 is a diagram showing the configuration of a target sound cutoff pair of the beamforming
device according to the third embodiment.
FIG. 16 is a diagram showing a configuration of a beam forming device according to Embodiment
4.
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4
It is a figure which shows the structure of the fixed type beamformer by the delay sum method.
It is a figure which shows the structure of a generalization side lobe canceller.
[0013]
Hereinafter, in order to explain the present invention in more detail, a mode for carrying out the
present invention will be described according to the attached drawings. Embodiment 1 FIG. 1 is a
diagram showing the configuration of a beam forming apparatus according to a first embodiment
of the present invention. The beam forming apparatus according to the first embodiment
includes a first microphone 101, a second microphone 102, a first target sound blocking unit
103, a second target sound blocking unit 104, a phasing unit 105, and a noise learning unit 106.
It is configured. The first microphone 101 and the second microphone 102 convert an external
sound into an electrical signal (a first audio signal and a second audio signal). The first target
sound blocking unit 103 performs processing for blocking the target sound from the signal of
the first microphone 101 using the signal of the second microphone 102. The second target
sound blocker 104 uses the signal of the first microphone 101 to block the target sound from
the signal of the second microphone 102. The phasing unit 105 phasing the input signals input
from the first microphone 101 and the second microphone 102 using the processing result input
from the first target sound blocking unit 103. The noise learning unit 106 learns the noise
component from the output signal of the phasing unit 105 using the mixed signal of the signals
output from the first target sound blocking unit 103 and the second target sound blocking unit
104.
[0014]
Next, the operation of the beam forming apparatus according to the first embodiment will be
described. In the following, the case where an adaptive filter by LMS (Least Mean Squares filter)
is used as the first target sound blocker 103 and the second target sound blocker 104 will be
described as an example. As shown in FIG. 1, the first target sound blocker 103 receives the
signal x 1 of the first microphone 101 to the signal x 2 of the second microphone 102, and
obtains a residual signal by the LMS adaptive filter. Thereby, it is possible to remove a correlated
signal (target signal) included in both the first microphone 101 and the second microphone 102
from the signal x 1 of the first microphone 101.
03-05-2019
5
[0015]
The signal of the first microphone 101 at time n is x 1 (n), the signal of the second microphone
102 is x 2 (n), the output of the first target sound blocker 103 is y 1 (n), the first Assuming that
the filter coefficients of the LMS adaptive filter of the target sound blocking unit 103 are F (n) =
[h 0 (n), h 1 (n), ..., h p-1 (n)] <T> The signal e 1 (n) after speech removal is determined using
equations (1) to (3). X 2 (n) = [x 2 (n), x 2 (n-1), ..., x 2 (np-1)] <T> (1) e 1 (n) = x 1 (n )-y 1 (n) = x
1 (n)-F <T> (n) · X 2 (n) (2) F (n + 1) = F (n) + μ · e 1 ( n) · X 2 (n) · · · (3)
[0016]
In equation (3), μ is a constant for obtaining the learning speed and is a positive value smaller
than 1. In equation (1), p is the length of the LMS adaptive filter, and in equations (1) and (2), T is
a transposed matrix Indicates The length p of the LMS adaptive filter is such that the speech
signal has a correlation. The LMS adaptive filter facilitates the learning of the filter coefficient
when the power is strong, so the learning progresses in the voice section and the voice signal is
easily removed from the signal x 1 of the first microphone 101.
[0017]
Similarly, the second target sound blocking unit 104 receives the signal x 1 of the first
microphone 101 from the signal x 2 of the second microphone 102 and obtains a residual signal
by the LMS adaptive filter. Thereby, it is possible to remove a correlated signal (target signal)
included in both the second microphone 102 and the first microphone 101 from the signal x 2 of
the second microphone 102.
[0018]
On the other hand, the phasing unit 105 combines the signal x 1 of the first microphone 101 and
the signal x 2 of the second microphone 102 through an FIR filter. Here, the filter coefficient F
(n) of the LMS adaptive filter learned by the first target sound blocker 103 is set as the
coefficient of the FIR filter. The filter coefficient F (n) learned by the first target sound blocking
unit 103 is a coefficient obtained by learning so that the signal x 2 of the second microphone
102 is in phase with the signal x 1 of the first microphone 101. Therefore, by convolving the
03-05-2019
6
signal x 2 of the second microphone 102, a signal in phase with the signal x 1 of the first
microphone 101 can be obtained. That is, the signal x 1 of the first microphone 101 and the
signal x 2 of the second microphone 102 are added with the signal obtained by convolving the
filter coefficient F (n) learned by the first target sound blocking unit 103, Average. The output
signal z (n) of the phasing unit 105 at time n is expressed by the following equation (4). z (n) =
(x1 (n) + F <T> (n) x 2 (n)) 2 ... (4) By the processing of the phase matching unit 105, according to
the delay addition shown in the conventional example Also, it is possible to realize speechenhanced beamforming.
[0019]
Further, the output signal y 1 of the first target sound blocker 103 and the output signal y 2 of
the second target sound blocker 104 are added to form a noise signal noise, which is input to the
noise learning unit 106. The noise learning unit 106 is included in an output signal z of the
phasing unit 105 by an NLMS (Normalized Least Mean Squares filter) adaptive filter having the
noise signal noise as an input and the output signal z of the phasing unit 105 as a target signal.
Learn the noise component. By subtracting the output signal of the noise learning unit 106 from
the output signal z of the phasing unit 105, a signal e from which noise is removed can be
obtained.
[0020]
The addition signal of the output signal y 1 (n) of the first target sound blocker 103 and the
output signal y 2 (n) of the second target sound blocker 104 at time n is noise (n) and the filter
coefficient is FN ( n) = [hn 0 (n), hn 1 (n), ..., hn p-1 (n)] <T>, the signal e (n) after noise removal is
expressed by the following equation (5) Calculated based on (7). N (n) = [noise (n), noise (n-1), ...,
noise (np-1)] <T> (5) e (n) = z (n)-FN <T> (n) · N (n) (6) FN (n + 1) = FN (n) + μ · ne (n) · N (n) / N
<T> (n) N (n) · (7)
[0021]
In the above description, the LMS is used as an adaptive filter of the first target sound blocker
103 and the second target sound blocker 104, and the NLMS is used as an adaptive filter of the
noise learning unit 106. Other adaptive filters such as (Recursive Least Squares) and affine
projection filters may be used.
03-05-2019
7
[0022]
As described above, according to the first embodiment, since the filter coefficient learned by the
first target sound blocking unit 103 is applied as the filter coefficient of the phasing unit 105, the
generalized side lobe canceller A signal with a better SN ratio compared to (GSC) or a fixed beam
former can be obtained from the phasing unit 105.
In addition, since the coefficient obtained in the process of the arithmetic processing of the first
target sound blocking unit 103 can be applied as the filter coefficient of the phasing unit 105,
the phasing process can be performed efficiently.
[0023]
Further, according to the first embodiment, since the noise learning unit 106 learns the noise
component included in the output signal of the phasing unit 105 and subtracts the learned noise
component, the noise is suppressed. A signal with an improved SN ratio can be obtained.
[0024]
Second Embodiment
FIG. 2 is a diagram showing the configuration of a beam forming apparatus according to a
second embodiment of the present invention. In the second embodiment, a first target sound
blocker 103 'and a second target sound blocker 104' using an adaptive filter are used, and the
phasing unit 105 shown in the first embodiment is a gain adjustment unit 107a. And the
synthesizing unit 107 b. In the following, parts that are the same as or correspond to the
constituent elements of the beamforming apparatus according to Embodiment 1 will be assigned
the same reference numerals as those used in Embodiment 1 to omit or simplify the description.
[0025]
The first target sound blocking unit 103 ′ is configured by an adaptive filter, and noises
included in the signal x 1 of the first microphone 101 from the signal x 1 of the first microphone
101 and the signal x 2 of the second microphone 102 Estimate the component y 1. By removing
03-05-2019
8
the estimated noise component y 1 from the signal x 1 of the first microphone 101, a signal e 1
after speech removal is obtained. The second target sound blocking unit 104 ′ is configured by
an adaptive filter, and noises included in the signal x 2 of the second microphone 102 from the
signal x 1 of the first microphone 101 and the signal x 2 of the second microphone 102 Estimate
the component y 2 By removing the estimated noise component y 2 from the signal x 2 of the
second microphone 102, a signal e 2 after speech removal is obtained.
[0026]
The gain adjustment unit 107 a adjusts the gain of the output signal y 1 of the first target sound
blocking unit 103 ′, and the combining unit 107 b subtracts the gain-adjusted signal from the
signal x 1 of the first microphone 101. Thus, the same signal as the output signal z of the phase
matching unit 105 of the first embodiment is obtained. The noise learning unit 106 uses the
addition signal of the signal e 1 after the voice removal of the first target sound blocking unit
103 ′ and the signal e 2 after the voice removal of the second target sound blocking unit 104
′. A noise component is learned from the output signal z after gain adjustment. By subtracting
the output signal of the noise learning unit 106 from the output signal z after gain adjustment,
the signal e from which noise has been removed can be obtained.
[0027]
In the first embodiment described above, an example in which the convolution operation is
performed using the FIR filter in the phase matching unit 105 has been described, but as
described in the second embodiment, the first target sound blocking unit 103 ′ and the second
target sound blocking unit 103 ′ When an adaptive filter is used for the target sound blocking
unit 104 ′ of the above, the convolution operation by the FIR filter becomes unnecessary, and
the following Equation (8) and Equation calculated based on the above Equation (2) and Equation
(4) By (9), the output of the first target sound blocker 103 ′ and the gain adjustment unit 107a
can obtain the output signal z (n). First, the following equation (8) is obtained from the abovedescribed equation (2). F <T> (n) x 2 (n) = x 1 (n)-e 1 (n) (8)
[0028]
As shown in the following equation (9) using the equation (4) and the equation (8) described
above, the output signal z (n) can be used to adjust the signal x 1 (n) of the first microphone 101
03-05-2019
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and the gain adjustment. It is represented by the signal e 1 (n) after the performed speech
removal. z (n) = (x1 (n) + F <T> (n) x 2 (n)) 2 ... (9) = (x 1 (n) + x 1 (n)-e 1 (n) / 2 = x 1 (n)-e 1 (n) /
2
[0029]
As shown in equation (9), after the signal e 1 (n) after speech removal is output to the gain
adjustment unit 107 a and the gain adjustment unit 107 a adjusts the gain of the signal e 1 (n) to
1⁄2, By subtracting the signal x 1 (n) of the first microphone 101, an output signal z (n) is
obtained. Although the case where the gain in the gain adjustment part 107a is set to 1/2 in
order to obtain the same result as Embodiment 1 mentioned above was shown in Formula (9), the
1st microphone 101 and the 2nd microphone 102 are shown. The values may be changed as
appropriate according to the gain balance of
[0030]
As described above, according to the second embodiment, the signal of the first microphone 101
and the second target signal using the adaptive filter as the first target sound blocker 103 ′ and
the second target sound blocker 104 ′. The noise component contained in the signal of the
microphone 102 is estimated, and the gain adjustment unit 107a adjusts the gain of the signal
after the speech removal and subtracts it from the signal of the first microphone 101. It is not
necessary to provide an FIR filter, and the amount of computation can be reduced.
[0031]
Third Embodiment
Although the first embodiment and the second embodiment described above show the
configuration including two microphones, the first microphone 101 and the second microphone
102, in the third embodiment, the number of microphones is three or more. The beam forming
apparatus in the case of being expanded to N will be described.
[0032]
03-05-2019
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FIG. 3 is a diagram showing the configuration of a beam forming apparatus according to a third
embodiment of the present invention. The beam forming apparatus according to the third
embodiment includes an array microphone unit 108, a target sound blocking pair collecting unit
109, a phasing unit 105, and a noise learning unit 106. The array microphone unit 108 includes
N microphones of a first microphone 108A, a second microphone 108B, ..., and an N-th
microphone 108N. Each of the microphones 108A, 108B,..., 108N converts an external sound
into an electrical signal. The target sound blocking pair collecting unit 109 includes N−1 target
sound blocking pairs with respect to the number N of microphones. In the example of FIG. 3, the
first target sound block pair 109A, the second target sound block pair 109B,..., And the N-1th
target sound block pair 109 (N-1) are configured. Each of the target sound blocking pairs 109A,
109B,..., 109 (N-1) is a signal of the first microphone 108A (representative audio signal) and
other signals of the microphones 108B,. A voice signal is used to remove signals (target signals)
having correlation with each other.
[0033]
FIG. 4 is a diagram showing the configuration of a target sound cutoff pair of a beamforming
device according to a third embodiment of the present invention. In FIG. 4, the first target sound
blocking pair 109A is shown as an example. The first target sound block pair 109A is composed
of a first input target sound blocker 111A and a second input target sound blocker 112A. The
first input target sound blocking unit 111A blocks the target sound from the signal x 1 of the
first microphone 108A, and the phase matching unit 105 outputs information for performing
phase matching. The second input target sound blocking unit 112A blocks the target sound from
the signal x 2 of the second microphone 108B, and the noise learning unit 106 outputs a signal
for learning noise.
[0034]
The phasing unit 105 uses the N microphones 108A, 108B,..., Using the results input from the N1 target sound blocking pairs 109A, 109B,. Perform phase alignment of the signal input from
108N. The noise learning unit 106 uses the summed signal of the signals output from the N-1
target sound blocking pairs 109A, 109B, ..., 109 (N-1) to generate noise from the output signal of
the phasing unit 105. Learn the ingredients.
[0035]
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In the first input target sound blocker 111K in the Kth target sound block pair 109K (1 ≦ K ≦
N−1), the signal x 1 of the first microphone 108A is a teacher signal, and the signal x K of the (K
+ 1) th microphone Assuming that +1 is an input signal, the adaptive filter by NLMS is used as
shown in the following equations (10) to (12) in the same manner as the above equations (1) to
(3). A learning is performed to remove the target signal from the signal x 1. XK (n) = [x K (n), x K
(n-1), ..., x K (np-1)] <T> (10) e 1 K (n) = x 1 (n) -y 1K (n) = x 1 (n)-FK <T> (n) · XK (n) (11) FK (n +
1) = FK (n) + μ · e 1K (n) XK (n) (12) In the above equations (10) to (12), X K is the signal of the
(K + 1) th microphone x K + 1, F K is the filter coefficient of NLMS, and y 1K is NLMS The
residual signal at
[0036]
On the other hand, the second input target sound blocker 112K in the Kth target sound block
pair 109K uses the signal x 1 of the first microphone 108A as an input signal and the signal x K
+ 1 of the (K + 1) th microphone as a teacher signal. The learning reverse to that of Equation (10)
to Equation (12) described above is performed based on Equation (13) to Equation (15) below. X
1 (n) = [x 1 (n), x 1 (n-1), ..., x 1 (np-1)] <T> (13) e K (n) = x K (n )-yK (n) = xK (n)-F1K <T> (n) · X1
(n) (14) F1K (n + 1) = F1K (n) + μ · · e K (n) · X 1 (n) (15) In the above equations (13) to (15), X 1
is the signal of the first microphone 101, F 1K is the filter coefficient of NLMS, y K is the output
signal of the Kth target sound block pair 109K, that is, the residual signal.
[0037]
The phase matching unit 105 is a signal obtained by performing convolution with an output
signal of the first input target sound blocking unit 111A, that is, an output signal of the second
microphone 108B to an N-th microphone using FK as a coefficient. , To the signal x 1 of the first
microphone 108A. The noise learning unit 106 includes the first to (N-1) th target sound block
pairs 109A, 109B,..., 109 (N-1) second input target sound block units 112A, 112B,. The noise
signal noise obtained by adding the output signals y 1, y 2,..., Y N-1 cut off from the target sound
output from (N-1) is input, and the output signal z of the phasing unit 105 is a target The noise
component contained in the output signal z of the phasing unit 105 is learned by the NLMS
adaptive filter as a signal. By subtracting the output of the noise learning unit 106 from the
signal of the phase matching unit 105, the signal e after noise removal can be obtained.
[0038]
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As described above, according to the third embodiment, the target sound blocking pair assembly
section is configured of the array microphone unit 108 configured of three or more N
microphones and the N-1 target sound blocking pairs. 109. Each target sound block pair receives
the signal of the representative microphone and the signals of the other microphones as a first
input target sound blocker that removes the target signal from the signal of the representative
microphone, and each of the other microphones. Since the second input target sound blocker for
removing the target signal from the input signal of (1) is provided, the accuracy of phasing can
be improved even in an apparatus provided with three or more microphones. In addition,
efficient phase alignment can be performed.
[0039]
In the third embodiment described above, an example in which the target sound blocking pair
collecting unit 109 is configured using the signal of the first microphone 108A which is a
representative microphone and the signals of the other microphones 108B,. Although shown, the
representative microphone may be configured other than the first microphone 108A. For
example, the microphone with the highest S / N ratio may be selected as the representative
microphone, or may be switched according to the surrounding conditions. In the above-described
third embodiment, an example in which LMS is used as the adaptive filter is shown, but other
algorithms such as NLMS and affine projection filter may be used.
[0040]
Fourth Embodiment FIG. 5 is a diagram showing the configuration of a beam forming apparatus
according to a fourth embodiment of the present invention. In the fourth embodiment, the voice
section detection unit 120 is additionally provided to the beam forming apparatus shown in the
first embodiment described above. The voice section detection unit 120 receives the signal of the
first microphone 101 and the signal of the second microphone 102, and detects a voice section
of the input signal. A known technique can be applied to voice activity detection. For example,
the detection technology of the speech segment discrimination device disclosed in reference 1
described below can be applied. Reference 1 Japanese Patent Application Laid-Open No. 10171487
[0041]
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The first target sound blocking unit 103 and the second target sound blocking unit 104 refer to
the detection result of the voice section detection unit 120, and when the detection result
indicating that it is a voice section is input, The learning process can be performed, and the
learning process of the adaptive filter can not be performed when the detection result indicating
that the speech section is not input is input.
[0042]
As described above, according to the fourth embodiment, the voice segment detection unit 120
that detects the voice segment of the signal of the first and second microphones 101 and 102 is
provided, and the first and second target sound blockers are provided. Since the learning
processing of the adaptive filter is performed only when 103 and 104 detect the voice segment
by referring to the detection result of the voice segment detection unit 120, erroneous learning
of the adaptive filter is prevented, and The filter coefficients can be learned with high accuracy.
[0043]
In the fourth embodiment described above, an example is shown in which the voice section
detection unit 120 is applied to the beamforming apparatus shown in the first embodiment, but
the beamforming apparatus shown in the second embodiment and the third embodiment Is also
applicable.
[0044]
In the scope of the invention, the present invention allows free combination of each embodiment,
or modification of any component of each embodiment, or omission of any component in each
embodiment. .
[0045]
The beam forming apparatus according to the present invention can perform phase alignment in
a fixed beam former with high accuracy, and therefore an acoustic system having a function of
performing a beam former with high accuracy that is not affected by fluctuations in the sound
field environment. It is suitable.
[0046]
101 first microphone, 102 second microphone, 103, 103 'first target sound blocker, 104, 104'
second target sound blocker, 105 phase matching unit 106 noise learning unit 107a gain
adjustment unit 107b Synthesizing unit 108 Array microphone unit 109 Target sound blocking
pair collecting portion 109A First target sound blocking pair 111A First input target sound
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blocking portion 112A Second input target sound blocking portion 120 voice section Detection
unit.
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