Noise reduction method
A noise reduction method partitions frequency band into multiple sub-bands and estimates the signal-to-noise ratio (SNR) value for each sub-band. An over-subtraction factor of each sub-band is determined based on the estimated SNR value. Then, the clean speech spectrum estimate is determined by performing spectral over-subtraction on each sub-band, so as to determine the clean speech signal from the estimated clean speech spectrum.
1. A noise reduction method for dividing input noise speech into a plurality of continuous frames, determining a noisy speech spectrum for each frame, and partitioning a frequency band into multiple sub-bands to determine a clean speech spectrum from the noisy speech spectrum on each sub-band, the method comprising:
(A) estimating a noise spectrum |W r (k)| 2 of an r-th frame at a k-th frequency component from the noisy speech y r (k) of the r-th frame by silence detection and noise spectrum estimation;
(B) estimating a signal-to-noise ratio (SNR) value SNR r (i) of an i-th sub-band for the r-th frame by applying a regression process to the SNR of the i-th sub-band for the (r−1)-th frame after noise reduction, the noisy speech spectrum, and the noise spectrum of the i-th sub-band for the r-th frame;
(C) determining an over-subtraction factor α r (i) of sub-band i based on the estimated SNR r (i); and
(D) determining a clean speech spectrum estimate by performing, on each sub-band, a spectral subtraction |Ŝ r (i,k)| 2 =|Y r (i,k)| 2 −α r (i)·|W r (i,k)| 2 ,
wherein Y r (i,k)| 2 is the noisy speech spectrum of the r-th frame at the k-th frequency component of the i-th sub-band, |W r (i,k)| 2 is the corresponding noise spectrum and |Ŝ r (i,k)| 2 is the clean speech spectrum at sub-band i for the r-th frame.
2. The noise reduction method as claimed in claim 1 , wherein in step (C), the over-subtraction factor of the i-th sub-band for the r-th frame is:
α
r
(
i
)
=
α
0
(
i
)
+
SNR
r
(
i
)
·
1
-
α
0
(
i
)
SNR
1
(
i
)
,
where α 0 (i) is a pre-selected over-subtraction factor when the actual SNR r (i)=0 at sub-band i, SNR 1 (i) represents a pre-selected SNR value when α r (i)=1.
3. The noise reduction method as claimed in claim 2 , wherein, the over-subtraction factor α r (i) of the sub-band is modified by the SNR value SNR r of the frame as:
α r (i)=α max if SNR r <SNR min ,
where SNR min is a pre-selected minimum value of SNR.
4. The noise reduction method as claimed in claim 1 wherein SNR r (i) is obtained by a regression process:
SNR
r
(
i
)
=
μ
·
SNR
r
-
1
o
(
i
)
+
(
1
-
μ
)
·
10
·
log
10
(
∑
k
∈
sub
-
band
i
Y
r
(
i
,
k
)
2
∑
k
∈
sub
-
band
i
W
r
(
i
,
k
)
2
-
1
)
where μis a predetermined weight in a range of 0<μ<1, and SNR r-1 o (i) is the SNR of the sub-band i for the previous frame after noise reduction.
5. The noise reduction method as claimed in claim 4 , wherein SNR r-1 o (i) is determined by:
SNR
r
-
1
o
(
i
)
=
10
·
log
10
∑
k
∈
sub
-
band
i
S
^
r
(
i
,
k
)
2
∑
k
∈
sub
-
band
i
W
r
(
i
,
k
)
2
.