Electrical audio signal processing systems and devices – Hearing aids – electrical
Reexamination Certificate
1999-07-30
2002-08-13
Tran, Sinh (Department: 2743)
Electrical audio signal processing systems and devices
Hearing aids, electrical
C381S071110
Reexamination Certificate
active
06434247
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to apparatus and methods for feedback cancellation adapted to the detection of changes in the feedback path in audio systems such as hearing aids.
2. Prior Art
Mechanical and acoustic feedback limits the maximum gain that can be achieved in most hearing aids. System instability caused by feedback is sometimes audible as a continuous high frequency tone or whistle emanating from the hearing aid. Mechanical vibrations from the receiver in a high power hearing aid can be reduced by combining the outputs of two receivers mounted back to back so as to cancel the net mechanical moment; as much as 10 dB additional gain can be achieved before the onset of oscillation (or whistle) when this is done. But in most instruments, venting the BTE earmold or ITE shell establishes an acoustic feedback path that limits the maximum possible gain to less than 40 dB for a small vent and even less for large vents. The acoustic feedback path includes the effects of the hearing aid amplifier, receiver, and microphone as well as the vent acoustics.
The traditional procedure for increasing the stability of a hearing aid is to reduce the gain at high frequencies. Controlling feedback by modifying the system frequency response, however, means that the desired high frequency response of the instrument must be sacrificed in order to maintain stability. Phase shifters and notch filters have also been tried, but have not proven to be very effective.
A more effective technique is feedback cancellation, in which the feedback signal is estimated and subtracted from the microphone signal. Feedback cancellation typically uses an adaptive filter that models the dynamically changing feedback path within the hearing aid. Particularly effective feedback cancellation schemes are disclosed in patent application Ser. No. 08/972,265, entitled “Feedback Cancellation Apparatus and Methods,” incorporated herein by reference and patent application Ser. No. 09/152,033 entitled “Feedback Cancellation Improvements,” incorporated herein by reference (by the present inventors). Adaptive feedback cancellation systems, however, can generate a large mismatch between the feedback path and the adaptive filter modeling the feedback path when the input signal is narrow band or sinusoidal. Thus some adaptive feedback cancellation systems have combined an adaptive filter for feedback cancellation with a mechanism for reducing the hearing aid gain when a periodic input signal is detected (Wyrsch, S., and Kaelin, A., “A DSP implementation of a digital hearing aid with recruitment of loudness compensation and acoustic echo cancellation”, Proc. 1997 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, New Paltz, N.Y., Oct. 19-22, 1997). This approach, however, may reduce the hearing aid gain even if the adaptive filter is behaving correctly, thus reducing the audibility of desired sounds.
A feedback cancellation system should satisfy several performance objectives: The system should respond quickly to a sinusoidal input signal so that “whistling” due to hearing aid instability is stopped as soon as it occurs. The system adaptation should be constrained so that steady state sinusoidal inputs are not canceled and audible processing artifacts and coloration effects are prevented from occurring. The system should be able to adapt to large changes in the feedback path that occur, for example, when a telephone handset is placed close to the aided ear. And the system should provide an indication when significant changes have occurred in the feedback path and are not just due to the characteristics of the input signal.
The preferred feedback cancellation system satisfies the above objectives. The system uses constrained adaptation to limit the amount of mismatch that can occur between the hearing aid feedback path and the adaptive filter being used to model it. The constrained adaptation, however, allows a limited response to a sinusoidal signal so that the system can eliminate “whistling” when it occurs in the hearing aid. The constraints greatly reduce the probability that the adaptive filter will cancel a sinusoidal or narrow band input signal, but still allow the system to track the feedback path changes that occur in daily use. The constrained adaptation uses a set of reference filter coefficients that describe the most accurate available model of the feedback path.
Two procedures have been developed for LMS adaptation with a constraint on the norm of the adaptive filter used to model the feedback path. Both approaches are designed to prevent the adaptive filter coefficients from deviating too far from the reference coefficients. In the first approach, the distance of the adaptive filter coefficients from the reference coefficients is determined, and the norm of the adaptive filter coefficient vector is clamped to prevent the distance from exceeding a preset threshold. In the second approach, a cost function is used in the adaptation to penalize excessive deviation of the adaptive filter coefficients from the reference coefficients.
Adaptation with Clamp: The feedback cancellation uses LMS adaptation to adjust the FIR filter that models the feedback path (
FIGS. 3 and 7
illustrate the LMS adaptation). The processing is most conveniently implemented in block time domain form, with the adaptive coefficients updated once for each block of data.
Conventional LMS adaptation adapts the filter coefficients w
k
(m) over the block of data to minimize the error signal given by
ϵ
(
m
)
=
∑
n
=
0
N
-
1
e
n
2
(
m
)
=
∑
n
=
0
N
-
1
(
(
[
s
n
(
m
)
-
v
n
(
m
)
]
)
)
2
,
(
1
)
where s
n
(m) is the microphone input signal and v
n
(m) is the output of the FIR filter modeling the feedback path for data block m, and there are N samples per block. The LMS coefficient update is given by
w
k
(
m
+
1
)
=
w
k
(
m
)
+
2
μ
∑
n
=
0
N
-
1
e
n
(
m
)
g
n
-
k
(
m
)
,
(
2
)
where g
n−k
(m) is the input to the adaptive filter, delayed by k samples, for block m.
In general, one wants the tightest bound on the adaptive filter coefficients that still allows the system to adapt to expected changes in the feedback path such as those caused by the proximity of a telephone handset. The bound is needed to prevent coloration artifacts or temporary instability in the hearing aid which can often result from unconstrained growth of the adaptive filter coefficients in the presence of a sinusoidal or narrow band input signal. The measurements of the feedback path indicate that the path response changes by about 10 dB in magnitude when a telephone handset is placed near the aided ear, and that this relative change is independent of the type of earmold used. The constraint on the norm of the adaptive filter coefficients can thus be expressed as
∑
k
=
0
K
-
1
&LeftBracketingBar;
w
k
(
m
)
-
w
k
(
0
)
&RightBracketingBar;
∑
K
=
0
K
-
1
&LeftBracketingBar;
w
k
(
0
)
&RightBracketingBar;
<
γ
,
(
3
)
where w
k
(m) are the current filter coefficients, W
k
(0) are the filter coefficients determined during initialization in the hearing aid dispenser's office, the FIR filter consists of K taps, and &ggr;~2 to give the desired headroom above the reference condition. The clamp given by Eq (3) allows the adaptive filter coefficients to adapt freely when they are close to the initial values, but prevents the filter coefficients from growing beyond the clamp boundary.
Adaptation with Cost Function: The cost function algorithm minimizes the error signal combined with a cost function based on the magnitude of the adaptive coefficient vector:
ϵ
(
m
)
=
∑
n
=
0
N
-
1
[
s
n
(
m
)
-
v
n
(
m
)
]
2
+
β
∑
k
=
0
K
-
1
[
w
k
(
m
)
-
w
k
(
0
)
]
2
,
(
4
)
where &bgr; is a weighting factor. The new constraint
Kates James Mitchell
Melanson John Laurence
Bales Jennifer L.
GN ReSound A/S
Macheledt Bales LLP
Tran Sinh
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