Circuit and method for the adaptive suppression of an...

Electrical audio signal processing systems and devices – Dereverberators

Reexamination Certificate

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C381S093000, C381S318000, C379S406080

Reexamination Certificate

active

06611600

ABSTRACT:

FIELD OF THE INVENTION
The present invention relates to a circuit and a method for the adaptive suppression of an acoustic feedback. It is e.g. used in digital hearing aids.
BACKGROUND
In acoustic systems with a microphone, a loudspeaker or a receiver and an interposed electronic signal processing part, acoustic feedback can occur between the loudspeaker or receiver on the one hand and the microphone on the other. Acoustic feedback gives rise to undesired distortions and in extreme cases leads to an unstable behaviour of the system, e.g. an unpleasant whistling. As unstable operation is unacceptable, the signal amplification of the signal processing part must often be set lower than is effectively desired.
The suppression of acoustic feedback in digital hearing aids can be fundamentally combatted with different approaches. At present, the best results are obtained with the adaptive filtering method.
Various systems with adaptive filtering are known. In such systems an acoustic input signal is recorded, converted into a digital, electric signal and an echo estimate is deducted. The echo-compensated signal is transformed with a necessary hearing correcting means into a digital output signal, converted into an analog, electric signal and is emitted as an acoustic output signal. On its way back to the microphone the acoustic signal is shaped in accordance with a feedback characteristic and is superimposed on an acoustic signal from the outside to give a new, acoustic input signal. For calculating the echo estimate the fixed delays contained in the system are simulated and the unknown feedback characteristic is modelled.
Such generally known systems with adaptive filtering are unfortunately inadequate for obtaining in a realistic environment a low distortion transmission with satisfactory convergence behavior at the same time. The difficulties result from the fact that real signals, such as speech or music, have a not to be ignored autocorrelation function. The adaptive filter interprets the autocorrelation of the signal as a feedback effect and this leads to a partial extinction of the desired signal. In extreme cases this effect occurs with purely periodic signals (e.g. with alarm sounds). The system can be improved if the feedback characteristic is modelled using decorrelated signals. Different approaches exist for this and will be explained hereinafter.
A first approach involves the use of an artificial noise signal. Such a system is e.g. known from European patent applications EP-415 677, EP-634 084, EP-671 114 and corresponding U.S. Pat. Nos. 5,259,033, 5,680,467 and 5,619,580, respectively, of GN Danavox AS. The common characteristic of such systems is the use of an artificial noise signal for decorrelating the signals. The noise signal is either only connected in when required in place of the output signal or is continuously added to the output signal. The disadvantage of such systems is the necessary expenditure for the control of the noise signal power in such a way that the noise remains as inaudible as possible and despite this a sufficiently good convergence rate can be obtained.
A second approach involves the use of fixed, orthogonal transformations. Such a system of Phonak AG was e.g. published as European patent application EP585 976 and U.S. Pat. No. 5,661,814. The common characteristic of such systems is the use of fixed, orthogonal transformations for the decorrelation of signals. The filtering and updating of the coefficients does not take place directly in the time domain in such systems. Apart from the generally greater computing expenditure, the disadvantage of such systems is the additional delay in the signal processing path resulting from the blockwise processing.
A third approach involves the use of adaptive decorrelation filters. Such a system was e.g. described by Mamadou Mboup et al “Coupled Adaptive Prediction and System Identification: A Statistical Model and Transient Analysis”, Proc. 1992 IEEE ICASSP, 4; 1-4, 1992. The systems implementable on the basis of this approach differ through the different arrangement and implementation of the decorrelation filters. The disadvantage of this system is the use of relatively slow transversal (FIR) filter decorrelators which, as a result of their structure, cannot adapt particularly rapidly to the changing statistical characteristics of their input signals. The coefficients of both decorrelation filters are generally determined by the decorrelation of the output signal reaching the loudspeaker or receiver. This aims at making the convergence rate frequency-independent. Thus, there is no particular weighting of the frequencies particularly critical for the feedback behavior with high amplifications in the signal processing path.
SUMMARY OF THE INVENTION
The objective of the invention is to provide a circuit and a method for the adaptive suppression of an acoustic feedback, which do not suffer from the disadvantages of the known systems. In particular, with minimum expenditure, it is aimed at achieving an optimum convergence behaviour with minimum, inaudible distortions and without additional signal delay.
The present invention belongs to the group of systems with adaptive decorrelation filters. It makes use of the finding that lattice filter structures are particularly suitable for rapid decorrelation. Such lattice filter structures are known from speech signal processing and are used there for linear prediction. Algorithms for the decorrelation of a signal by means of lattice filters are known and can be gathered from the literature, cf. e.g. S. Thomas Alexander, “Adaptive Signal Processing”, Springer-Verlag, New York, 1986.
The present invention models the feedback path and follows its time changes adaptively by means of an optimized tracking. The fedback signal components are continuously removed from the input signal. Thus, there is a considerable increase in the signal amplification permitted for stable operation. This allows the use of higher amplifications (e.g. with severe hearing impairments) or a pleasant, more open supply (e.g. for slight hearing impairments).
The circuit according to the invention is used in an acoustic system with at least one microphone for producing an electric input signal, at least one loudspeaker or receiver and an interposed electronic signal processing part. It includes a filter for modelling a feedback characteristic, an updating unit for calculating current coefficients for the filter, a subtracter for calculating an echo-compensated input signal by means of the subtraction of an echo estimate supplied by the filter from a digital input signal, a delay element for calculating a delayed output signal and two adaptive lattice decorrelation filters. A first lattice decorrelation filter serves to decorrelate the echo-compensated input signal, while a second lattice decorrelation filter decorrelates the delayed output signal by means of coefficients from the first lattice decorrelation filter. Both lattice decorrelation filters are configured for calculating their lattice coefficients by means of adaptive decorrelation of the echo-compensated input signal.
The first decorrelation filter, a lattice decorrelator, extracts from the echo-compensated signal the noise-like components contained therein. Parallel thereto in the second decorrelation filter, a lattice filter, with the coefficients from the lattice decorrelator the delayed output signal is converted into a transformed signal. The special point about this arrangement is the transposing of the lattice decorrelator and the lattice filter compared with the conventional arrangement, where it is not the echo-compensated signal, but the delayed output signal which is decorrelated. The circuit according to the invention has the major advantage that the spectral maxima present in the hearing correcting means remain in the transformed signal. These maxima usually correspond to the most critical frequencies or feedback and they are to be taken into account with a correspondingly high weighting during the updating of the filter coef

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