EP3065417B1 - Method for suppressing interference noise in an acoustic system - Google Patents

Method for suppressing interference noise in an acoustic system Download PDF

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EP3065417B1
EP3065417B1 EP16151092.0A EP16151092A EP3065417B1 EP 3065417 B1 EP3065417 B1 EP 3065417B1 EP 16151092 A EP16151092 A EP 16151092A EP 3065417 B1 EP3065417 B1 EP 3065417B1
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signal
filter
microphone
output signal
input
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French (fr)
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EP3065417A1 (en
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Tobias Daniel Rosenkranz
Tobias Wurzbacher
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Sivantos Pte Ltd
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Sivantos Pte Ltd
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    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10KSOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K11/00Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/002Devices for damping, suppressing, obstructing or conducting sound in acoustic devices
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04RLOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R25/00Deaf-aid sets, i.e. electro-acoustic or electro-mechanical hearing aids; Electric tinnitus maskers providing an auditory perception
    • H04R25/45Prevention of acoustic reaction, i.e. acoustic oscillatory feedback
    • H04R25/453Prevention of acoustic reaction, i.e. acoustic oscillatory feedback electronically
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10KSOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K2210/00Details of active noise control [ANC] covered by G10K11/178 but not provided for in any of its subgroups
    • G10K2210/30Means
    • G10K2210/301Computational
    • G10K2210/3026Feedback
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10KSOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K2210/00Details of active noise control [ANC] covered by G10K11/178 but not provided for in any of its subgroups
    • G10K2210/30Means
    • G10K2210/301Computational
    • G10K2210/3028Filtering, e.g. Kalman filters or special analogue or digital filters
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04RLOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R3/00Circuits for transducers, loudspeakers or microphones
    • H04R3/02Circuits for transducers, loudspeakers or microphones for preventing acoustic reaction, i.e. acoustic oscillatory feedback

Definitions

  • the invention relates to a method for suppressing a noise in an acoustic system, wherein the acoustic system comprises at least one microphone and at least one speaker, and wherein the at least one microphone generates an input signal, wherein the at least one loudspeaker generates an acoustic signal, which partially the at least one microphone feeds back.
  • noise may occur due to feedback.
  • Acoustic feedback may result from the fact that the acoustic signal generated by the speaker is partially perceived by the microphone, and thereby re-entry into the acoustic system.
  • the input signal generated by the microphone is amplified in the acoustic system, so that within the closed loop, which is formed by the speaker, the acoustic signal generated by this, the microphone, and the signal processing within the acoustic system, a signal component by the feedback continues is amplified to a whistling noise when the gain in the signal processing within the acoustic system exceeds a certain limit.
  • k is the discrete time index
  • x is the input to the feedback cancellation system
  • is the step size over which the speed of adaptation or convergence is controlled, and * denotes the complex conjugation.
  • the input signal m is often first digitized with a comparatively high sampling rate and thereby converted into time-discrete sampled values. Subsequently, in each case a multiplicity, for example 128, of consecutive samples is combined to form a so-called frame.
  • a spectral analysis of the input signal can now be carried out on the basis of the samples forming the frame by means of Fourier transformation.
  • the window to be considered is shifted in the direction of the time axis by a few sample values, for example 32, so that the windows of the respective samples to be taken into account for one frame overlap partially for adjacent frames.
  • the time index can in this case be understood as a frame index, whereby the adaptive filter can also be used in the frequency domain.
  • the filter coefficients h are vectors whose entries each correspond to a spectral subband.
  • the application is not limited to this case. Details can be found for example in S. Haykin, "Adaptive Filter Theory” (Englewood Cliffs, NJ: Prentice-Hall, 1996 ) or T. v. Waterschoot & M. Moonen, "Fifty years of acoustic feedback control: state of the art and future challenges "(Proc. IEEE, Vol. 99, No. 2, Feb. 2011, pages 288-327 ).
  • correlated input signals such as may be generated by the recording of music or spoken language
  • an adaptive filter which may result in at least partial cancellation of a target signal.
  • This can produce noticeable signal artifacts in the output signal, resulting in a significant deterioration of the sound quality.
  • the whistling noise generated by acoustic feedback also has a high correlation in the signals concerned, particularly when there is a correlated target signal which is picked up and fed back through a loudspeaker after playback. If an adaptive filter is to be used to suppress the interference noise generated thereby, signal components of the target signal can also be at least partially extinguished in the suppression of the interference signal of the feedback, which has a negative effect on the sound quality of the output signal.
  • the EP 2 736 271 A1 discloses a system for estimating a feedback noise signal in which an output signal is shifted in frequency. The frequency-shifted output signal is then supplied as an input to an adaptive filter for rejecting a noise signal and to an algorithm for adjusting the filter parameters of the adaptive filter.
  • the invention is therefore based on the object of mentioning a method for suppressing an acoustic noise caused by noise, which allows the use of an adaptive filter, and at the same time has the highest possible sound quality in the output signal.
  • the acoustic system comprises at least one microphone and at least one speaker, wherein the at least one microphone generates an input signal and wherein the at least one loudspeaker generates an acoustic signal, which partially feeds back to the at least one microphone, wherein along a main signal path in response to the input signal, a first intermediate signal and from the first intermediate signal by a frequency distortion an output signal is formed, wherein the output signal is coupled out of the main signal path in a signal feedback path, wherein in the signal Feedback path from the output signal by decorrelation a second intermediate signal is formed, which is used as an input to an adaptive filter, which generates a compensation signal, and wherein the Kompensat ion signal is supplied to the input signal for compensation, wherein from the input signal and / or from the compensated input signal, a third intermediate signal is formed, which is used as an input to the adaptive filter, and wherein the output signal is supplied to the at
  • the output signal can also be used as a further input variable for the adaptive filter, wherein the second intermediate signal and the third intermediate signal are used in the adaptive filter for determining filter coefficients, by means of which the output signal is filtered and the compensation signal is thereby generated.
  • the invention is based on the following considerations: A reduction in the step size p of an adaptive filter used would result in the filter diverging much more slowly in the case of a correlated input signal, so that undesired artifacts in the output signal could be reduced or become inaudible.
  • the reduction of the step size could, for example, always take place when a correlated or tonal input signal is registered.
  • a disadvantage of such a procedure is that any change in the acoustic feedback path while the correlated signal is being registered can not be tracked fast enough to avoid feedback noise, because of the reduced step size p limitations on the adaptability of the filter be placed.
  • the step size is therefore always to be seen as a trade-off between sound quality and the ability to respond to changes in the acoustic feedback path.
  • Another way to solve the problems of an adaptive filter for a strongly correlated input signal is a possible decorrelation of the input signal (so-called "pre-whitening"). Since only correlated input signals cause matching problems in the adaptive filter, such decorrelation could first solve the problem.
  • Such decorrelation is often implemented by a linear predictor. For a correlated input signal, a prediction is made for one or more future samples of the signal as a function of past observed samples of the signal. This prediction then becomes the actual input signal subtracted. The result of this subtraction is called the prediction error signal ("residual signal"). For example, a sinusoidal signal is completely deterministic and therefore perfectly predictable. In this case, for a corresponding prediction order, the residual signal would be zero.
  • s (k) represents the sample of the input signal for the prediction at time k
  • a (i) denotes the filter coefficient of decorrelation
  • P the order of prediction.
  • the prediction error signal thus generated is generally of complex value.
  • Interference caused by feedback also has significantly correlated signal components. If a decorrelation is applied to such a signal, the signal strength of the resulting prediction error signal is very low. For reuse in an adaptive filter, this would mean that the adaptive filter is not excited at the frequency of the noise generated by the feedback. Thus, the filter can not adapt to the acoustic feedback path at this frequency, whereby the noise remains until the acoustic feedback path changes.
  • the autocorrelation values are time-dependent, and therefore preferred to be repeatedly determined.
  • most non-stationary signals can be considered nearly stationary within a time window of a certain duration. The length of this time window depends on the degree to which the signal is not stationary.
  • the adaptation speed of a filter or estimator which calculates the autocorrelation values of an input signal, plays an important role in this case: the faster the estimator, the better it is not possible to track stationary signals, which improves the decorrelation of an input signal.
  • the adaptation speed and thus the ability to decorrelate nonstationary signals is regulated by the step size.
  • a correlated target signal for the adaptive filter for canceling out a feedback-related noise is preferably decorrelated beforehand, but that a decorrelation of the adaptive filter at the frequencies of the feedback-induced noise no longer stimulates, could now be avoided, that in a first step, such a noise is detected, and in response to such detection in a second step in this case, the decorrelation omitted.
  • this has several practical disadvantages: First, such a detection in practice is always faulty. In particular, if the acoustical feedback stimulates a plurality of closely spaced frequencies, these may not be sufficiently suppressed due to insufficient spectral resolution in the detection.
  • Another possibility could be to determine the filter coefficients for the decorrelation in another acoustic system, and to transmit these filter coefficients continuously between the participating acoustic systems for adaptation. This possibility would be given in particular in a binaural hearing aid system.
  • the above idea would be based on the assumption that the sound signals from the environment recorded by the respective acoustic systems have a high degree of similarity, but that noise caused by feedback in a single system affects only the individual acoustic system. Since feedback noise at a given frequency will most likely only occur in one acoustic system, the filter coefficients for decorrelation determined in another acoustic system may be considered a good estimate for the decorrelation of a target signal in the feedback acoustic system are used.
  • the presence of a further acoustic system is first required, which is often not the case.
  • the filter coefficients occur so that they are no longer up-to-date when receiving in the other acoustic system, or due to the spatial arrangement of the acoustic systems involved, the respective filter coefficients are not a sufficiently good estimate for the other system. This may, for example, in a binaural hearing aid system caused by the head of the user shading effects occur.
  • the invention proposes to first subject an output signal of the acoustic system, which is to be fed into a signal feedback path, to frequency distortion, and then to decorrelate it.
  • a time-dependent frequency distortion can be used here.
  • Noise caused by feedback usually has a nearly perfectly sinusoidal signal. Due to the frequency distortion, this form is lost. If, for example, a time-dependent frequency shift is selected for the frequency distortion, the signals of the noise follow this frequency shift.
  • the autocorrelation values of frequency-distorted signals decrease as the time interval increases, so that the window of time during which the feedback-induced noise can be considered stationary is shortened.
  • a decorrelator such that it does not adapt to the interference signal of the feedback.
  • the time window in which signals can be considered stationary is preferably to be chosen so that the interference signal of the feedback is not considered stationary by the frequency distortion, the actually non-stationary signal components of a target signal already.
  • the decorrelation is not adapted to the interference signal, but only to the signal components of the target signal, which are decorrelated.
  • the decorrelated signal the non-stationary correlated signal components are removed, as they occur in the recording of spoken speech, but not caused by the feedback Signal components.
  • the decorrelated signal is now supplied as an intermediate signal to the adaptive filter, which can generate a compensation signal based on the feedback caused by feedback, which is fed back to the main signal path for the suppression of the noise.
  • the input signal is favorably time-discretized, whereby a "least mean square” algorithm (LMS) is used as the adaptive filter.
  • LMS least mean square algorithm
  • the output signal is preferably used as the reference signal, and the error signal of the LMS filter is formed by the difference between the input signal and the compensation signal.
  • the specified method is particularly advantageous in the use of an LMS algorithm in the adaptive filter, since the frequency distortion of the output signal solves the divergence problems which occur when using an LMS algorithm for the adaptive filtering of feedback-related interference signals.
  • the step size in the LMS algorithm is normalized via the second intermediate signal.
  • This procedure is also called “normalized least mean square” (NLMS).
  • NLMS normalized least mean square
  • Such normalization improves the convergence properties of the algorithm.
  • the optimal filter coefficients are generally given by the solution of the filter equation by means of a Wiener filter. However, due to the static properties and the limited conversion time, this can usually not be used, which is why estimates are used for the filter coefficients given by the Wiener filter, the estimates converging ideally against the Wiener solution.
  • the frequency distortion to form the output signal from the first intermediate signal is achieved by a frequency shift.
  • a frequency shift is used.
  • This provides the ability to tune the decorrelator's adaptation speed to the frequency offset, and thus effectively exclude the frequency-shifted signal components of the acoustic feedback noise from the decorrelation.
  • frequency distortion may also be by phase modification, frequency transposition, or non-linear transformation.
  • the adaptation speed of the decorrelator is preferably to be tuned to the respective degree of frequency distortion.
  • the output signal for decoding the second intermediate signal is decorrelated by means of a linear prediction filter.
  • the filter coefficients of the linear prediction filter are preferably to be determined by means of a Levinson-Durbin recursion or by means of an LMS or NLMS algorithm.
  • the advantage of a linear prediction filter is that only linear systems of equations have to be solved, which limits the numerical complexity for the respective filter problem.
  • the input signal or the compensated input signal can also be decorrelated by means of a linear prediction filter, and used to form the third intermediate signal, which is supplied as an input variable to the adaptive filter.
  • time-dependent autocorrelation values of the output signal and / or of a signal based on the input signal are preferred for the filter coefficients of the linear prediction filter Error signal used.
  • the autocorrelation values can be used for a Levinson-Durbin algorithm. Taking into account the time dependence of the autocorrelation values allows the decorrelation to be adjusted to the degree of frequency distortion via the appropriate choice of a corresponding time window, after which the autocorrelation values are again determined.
  • the filter coefficients of, in particular, each linear prediction filter are adapted as a function of the decorrelation strength of the frequency distortion.
  • the time window in which signals can be regarded as stationary depends on the decorrelation strength of the frequency distortion.
  • this can be done, for example, via a repeated adaptation of the autocorrelation values in the mentioned time intervals, from which the filter coefficients are to be determined again.
  • the step size can instead be adjusted accordingly in the time intervals specified.
  • the described functional dependence of the time intervals or of the stationary time window can influence which signal components are still perceived as stationary by the decorrelator, so that the signal components of the interference signal affected by the frequency distortion are not decorrelated.
  • a decorrelator which has too short a "stationary time window", could also perceive signal components of a frequency-distorted originally monofrequency signal as stationary and therefore decorrelate it. This is circumvented by adapting the rate of adaptation of the decorrelation to the degree of frequency distortion, in particular to that of its own decorrelation strength. If, for example, a time-dependent frequency shift is selected, then this is preferably carried out more quickly than signals are considered to be stationary in the time window for the decorrelation.
  • the filter coefficients of the, in particular each linear prediction filter are adapted in dependence on a transfer function of a model of the acoustic system, which comprises the at least one microphone and at least one speaker reproducing the corrected output signal.
  • the time intervals for the adaptation of the filter coefficients may additionally depend on the decorrelation strength of the frequency distortion.
  • the transfer function may hereby contain the specific characteristics of the acoustic system, e.g. Gain values in individual sub-bands. In such a model, it is also possible, at least implicitly via coefficients of the transfer function, to enter into the probability that a feedback causes noise at a certain frequency.
  • the decorrelation adaptation rate may be reduced to ensure that the frequency-distorted components of the original monofrequency noise are not considered stationary and decorrelated. If feedback is unlikely, the time window for the decorrelator adaptation can be shortened so that tonal signal components, e.g. generated by voice recording, are quickly detected, and decorrelated.
  • the invention further provides an acoustic system comprising at least one microphone for generating an input signal, at least one loudspeaker for reproducing an output signal, and a control unit which is adapted to generate a noise by feedback of the output signal reproduced via the at least one loudspeaker is caused in the input signal generated by the at least one microphone, suppress by the above-described method.
  • the acoustic system is here as a hearing aid, and advantageous as a Hearing aid formed.
  • FIG. 1 3 shows a schematic block diagram of the sequence of a method 1 for suppressing a noise g in an acoustic system 2.
  • the acoustic system 2 which is given here by a hearing device 3, for example a hearing aid device, comprises a microphone 4 and a loudspeaker 6.
  • the microphone signal m recorded by the microphone 4 is fed to a signal processing unit 10 in a main signal path 8 where it amplifies, among other things becomes.
  • an output signal xs is output to the microphone 4, which generates an acoustic signal p from the output signal xs.
  • a part of the acoustic signal p generated by the loudspeaker 6 is again recorded by the microphone 4 as feedback fb, and thus finds its way into the microphone signal m.
  • the feedback fb signal components of the acoustic signal p in the microphone signal m are fed again to the signal processing unit 10 and further amplified there.
  • the repeated amplification, playback and recording in a closed process produces noise g in the form of almost monofrequente whistling sounds.
  • the signal feedback path 16 is provided.
  • the output signal x s is coupled out of the main signal path 8 and fed to a decorrelator 18.
  • the decorrelator 18 is formed by a linear prediction filter 20.
  • the signal processing unit 10 outputs a first intermediate signal x, which is converted by a frequency distortion 22 in the output signal xs.
  • the frequency distortion 22, which is achieved in the present case by a frequency shift 23, has the consequence that the linear prediction filter 20 does not decorrelate the signal components corresponding to the noise g, but only signal components of a target signal.
  • a second intermediate signal xw is output as an input to an adaptive filter 24.
  • the adaptive filter 24 generates from the output signal xs a compensation signal c, which is subtracted from the microphone signal m to compensate for the noise g. As a result, the signal feedback path 16 is closed.
  • the adaptive filter 24 is supplied with an additional intermediate signal ew as an input signal.
  • This third intermediate signal ew is formed from the error signal e, which results from the microphone signal m compensated for the compensation signal, c.
  • the error signal e is now likewise decorrelated by a linear prediction filter 26, and the decorrelated error signal ew is supplied as a second input variable to the adaptive filter 24.
  • the coefficients h are calculated in a filter block 28 of the adaptive filter 24, from which a signal block 30 of the adaptive filter together with the output signal xs generates the compensation signal c.
  • the frequency shift 23 ensures that the linear prediction filter 20 does not decorrelate any signal components associated with the noise g, whereby the adaptive filter 24 would no longer compensate for these with the compensation signal c.
  • the length of the stationary time window T of the linear prediction filters 20, 26, and thus their adaptation speed, is thereby controlled as a function of the frequency shift 23.
  • a control unit 32 in the hearing aid 3 performs all specified method steps.
  • FIG. 2 is in a block diagram a slight modification of the in FIG. 1 shown method 1 shown.
  • the decorrelated error signal ew which is supplied as an input to the adaptive filter, is formed from an input signal mw decorrelated in the linear prediction filter 26 and a decorrelated compensation signal cw.
  • the decorrelated compensation signal cw is formed in the filter block 28 of the adaptive filter from the error signal ew decorrelated in the linear prediction filter 26 and the second intermediate signal xw, which is given by the output signal xs decorrelated in the linear prediction filter 20.
  • the length of the stationary time window T of the linear prediction filters 20, 26, and thus their adaptation speed is hereby determined by an adaptation control 34, in which the degree df of the frequency shift 23, the gain n of the signal processing unit 10 in individual sub-bands, and a non find more detailed transfer function of the acoustic system 2 input and used to determine the time window T.
  • an adaptation control 34 in which the degree df of the frequency shift 23, the gain n of the signal processing unit 10 in individual sub-bands, and a non find more detailed transfer function of the acoustic system 2 input and used to determine the time window T.
  • a model of the acoustic feedback path fb determined by the filter coefficients h can also be used, so that the adaptation speed of the decorrelation in the linear prediction filters 20, 26 is also determined as a function of the feedback estimated by this model.
  • the use of such an adjustment control 34 is thereby not on the in FIG. 2 illustrated form of the signal feedback path 16 is limited, but can in principle in various embodiments, in particular

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Description

Die Erfindung betrifft ein Verfahren zur Unterdrückung eines Störgeräusches in einem akustischen System, wobei das akustische System wenigstens ein Mikrofon und wenigstens einen Lautsprecher umfasst, und wobei das wenigstens eine Mikrofon ein Eingangssignal erzeugt, wobei der wenigstens eine Lautsprecher ein akustisches Signal erzeugt, welches teilweise auf das wenigstens eine Mikrofon rückkoppelt.The invention relates to a method for suppressing a noise in an acoustic system, wherein the acoustic system comprises at least one microphone and at least one speaker, and wherein the at least one microphone generates an input signal, wherein the at least one loudspeaker generates an acoustic signal, which partially the at least one microphone feeds back.

In einem akustischen System der oben beschriebenen Art, wie es beispielsweise durch ein Hörgerät gegeben sein kann, können durch Rückkopplung bedingte Störgeräusche auftreten. Eine akustische Rückkopplung kann dadurch entstehen, dass das durch den Lautsprecher erzeugte akustische Signal teilweise vom Mikrofon wahrgenommen wird, und hierdurch erneut Eingang in das akustische System findet. Das vom Mikrofon erzeugte Eingangssignal wird im akustischen System verstärkt, so dass innerhalb der geschlossenen Schleife, welche durch den Lautsprecher, das durch diesen erzeugte akustische Signal, das Mikrofon, und die Signalverarbeitung innerhalb des akustischen Systems gebildet wird, ein Signalanteil durch die Rückkopplung immer weiter zu einem pfeifenden Störgeräusch verstärkt wird, wenn die Verstärkung bei der Signalverarbeitung innerhalb des akustischen Systems einen bestimmten Grenzwert übersteigt.In an acoustic system of the type described above, such as may be provided by a hearing aid, noise may occur due to feedback. Acoustic feedback may result from the fact that the acoustic signal generated by the speaker is partially perceived by the microphone, and thereby re-entry into the acoustic system. The input signal generated by the microphone is amplified in the acoustic system, so that within the closed loop, which is formed by the speaker, the acoustic signal generated by this, the microphone, and the signal processing within the acoustic system, a signal component by the feedback continues is amplified to a whistling noise when the gain in the signal processing within the acoustic system exceeds a certain limit.

Derartige Störgeräusche können durch sog. Rückkopplungs-Unterdrückungsverfahren ("feedback cancellers") reduziert oder sogar eliminiert werden. Hierfür werden nach Stand der Technik oftmals adaptive feedback-cancellation-Methoden verwendet, in welchen ein adaptives Filter mit Filterkoeffizienten h die zeitabhängige Impulsantwort des akustischen Rückkopplungspfades modelliert. Ein oft verwendetes Beispiel für eine Vorschrift zur Anpassung der Filterkoeffizienten h ist durch den "normalized least mean square" Algorithmus (NLMS) gegeben: h k + 1 = h k + μ e * k x k / | x k | 2 .

Figure imgb0001
Such noise can be reduced or even eliminated by so-called feedback cancellers. For this purpose, the prior art often uses adaptive feedback cancellation methods in which an adaptive filter with filter coefficients h models the time-dependent impulse response of the acoustic feedback path. An often used example of a rule for adjusting the filter coefficients h is given by the "normalized least mean square" algorithm (NLMS): H k + 1 = H k + μ e * k x k / | x k | 2 ,
Figure imgb0001

Hierbei ist k der diskrete Zeitindex, x der Input in das System zur Auslöschung der Rückkopplung, e = m-c das Fehlersignal, welches definiert ist als die Differenz zwischen dem vom Mikrofon erzeugten Eingangssignal m und dem Kompensationssignal c zur Kompensation der Rückkopplung. µ ist die Schrittweite, über welche die Geschwindigkeit der Anpassung bzw. der Konvergenz gesteuert wird, und * bezeichnet die komplexe Konjugation.Where k is the discrete time index, x is the input to the feedback cancellation system, e = m-c is the error signal, which is defined as the difference between the microphone-generated input m and the compensation signal c to compensate for the feedback. μ is the step size over which the speed of adaptation or convergence is controlled, and * denotes the complex conjugation.

In einem realistischen akustischen System wird dabei das Eingangssignal m oftmals zunächst mit einer vergleichsweise hohen Abtastrate digitalisiert und hierdurch in zeitdiskrete Abtastwerte umgewandelt. Anschließend wird jeweils eine Vielzahl, beispielsweise 128, von aufeinander folgenden Abtastwerten zu einem sogenannten Frame zusammengefasst. Innerhalb eines Frames kann nun anhand der den Frame bildenden Abtastwerte mittels Fouriertransformation eine spektrale Analyse des Eingangssignals durchgeführt werden. Für die Erzeugung bzw. die Analyse eines nächsten Frames wird das zu betrachtende Fenster um einige Abtastwerte, beispielsweise 32, in Richtung der Zeitachse verschoben, sodass die Fenster der jeweils für einen Frame zu berücksichtigenden Abtastwerte sich für benachbarte Frames teilweise deutlich überlappen. Der Zeitindex kann in diesem Fall als ein Frame-Index aufgefasst werden, wobei das adaptive Filter auch im Frequenzraum verwendet werden kann. In diesem Fall sind die Filterkoeffizienten h Vektoren, deren Einträge jeweils einem spektralen Subband entsprechen. Die Anwendung ist jedoch nicht auf diesen Fall beschränkt. Einzelheiten hierzu finden sich beispielsweise in S. Haykin, "Adaptive Filter Theory" (Englewood Cliffs, NJ: Prentice-Hall, 1996 ) oder T. v. Waterschoot & M. Moonen, "Fifty years of acoustic feedback control: state of the art and future challenges" (Proc. IEEE, Bd. 99, Nr. 2, Feb. 2011, Seiten 288-327 ).In a realistic acoustic system, the input signal m is often first digitized with a comparatively high sampling rate and thereby converted into time-discrete sampled values. Subsequently, in each case a multiplicity, for example 128, of consecutive samples is combined to form a so-called frame. Within a frame, a spectral analysis of the input signal can now be carried out on the basis of the samples forming the frame by means of Fourier transformation. For the generation or the analysis of a next frame, the window to be considered is shifted in the direction of the time axis by a few sample values, for example 32, so that the windows of the respective samples to be taken into account for one frame overlap partially for adjacent frames. The time index can in this case be understood as a frame index, whereby the adaptive filter can also be used in the frequency domain. In this case, the filter coefficients h are vectors whose entries each correspond to a spectral subband. However, the application is not limited to this case. Details can be found for example in S. Haykin, "Adaptive Filter Theory" (Englewood Cliffs, NJ: Prentice-Hall, 1996 ) or T. v. Waterschoot & M. Moonen, "Fifty years of acoustic feedback control: state of the art and future challenges "(Proc. IEEE, Vol. 99, No. 2, Feb. 2011, pages 288-327 ).

Es ist nun ein bekanntes Problem, dass korrelierte Eingangssignale, wie sie beispielsweise durch die Aufnahme von Musik oder auch von gesprochener Sprache erzeugt werden können, in einem adaptiven Filter zu einer Divergenz führen können, was zu einer mindestens teilweisen Auslöschung eines Zielsignals führen kann. Dies kann im Ausgangssignal deutlich wahrnehmbare Signal-Artefakte produzieren, was zu einer erheblichen Verschlechterung der Klangqualität führt. Die durch eine akustische Rückkopplung erzeugten pfeifenden Störgeräusche weisen in den betreffenden Signalen ebenfalls eine hohe Korrelation auf, insbesondere, wenn ein korreliertes Zielsignal vorliegt, welches aufgenommen und nach der Wiedergabe durch einen Lautsprecher rückgekoppelt wird. Soll nun zur Unterdrückung der hierdurch erzeugten Störgeräusche ein adaptives Filter verwendet werden, so können bei der Unterdrückung des Störsignals der Rückkopplung auch Signalanteile des Zielsignals zumindest teilweise ausgelöscht werden, was sich negativ auf die Klangqualität des Ausgangssignals auswirkt.It is now a known problem that correlated input signals, such as may be generated by the recording of music or spoken language, may result in divergence in an adaptive filter, which may result in at least partial cancellation of a target signal. This can produce noticeable signal artifacts in the output signal, resulting in a significant deterioration of the sound quality. The whistling noise generated by acoustic feedback also has a high correlation in the signals concerned, particularly when there is a correlated target signal which is picked up and fed back through a loudspeaker after playback. If an adaptive filter is to be used to suppress the interference noise generated thereby, signal components of the target signal can also be at least partially extinguished in the suppression of the interference signal of the feedback, which has a negative effect on the sound quality of the output signal.

Aus der EP 2 503 795 A2 ist ein Verfahren zum Betreiben einer binauralen Hörvorrichtung mit einer Rückkopplungsunterdrückungseinrichtung bekannt, bei welchem ein Pre-Whitening-Filter eines ersten Hörgeräts in Abhängigkeit eines Signals eines zweiten Hörgeräts gesteuert wird.From the EP 2 503 795 A2 a method for operating a binaural hearing device with a feedback suppression device is known, in which a pre-whitening filter of a first hearing device is controlled in response to a signal of a second hearing device.

In der DE 2013 207 403 B3 ist ein Verfahren zur Steuerung einer Adaptionsschrittweite eines adaptiven Filters einer Hörvorrichtung beschrieben, bei welchem ein Ausgangssignal zur Ansteuerung eines adaptiven Filters frequenzverschoben wird. Hierbei wird ein Autokorrelationswert eines Eingangssignals in Abhängigkeit der Frequenzverschiebung zur Ansteuerung der Adaptionsschrittweite verwendet.In the DE 2013 207 403 B3 a method for controlling an adaptation step size of an adaptive filter of a hearing device is described in which an output signal for driving an adaptive filter is frequency-shifted. In this case, an autocorrelation value of an input signal is used as a function of the frequency shift for controlling the adaptation step size.

Die EP 2 736 271 A1 offenbart ein System zur Schätzung eines Rückkopplungs-Störsignals, bei welchem ein Ausgangssignal frequenzverschoben wird. Das frequenzverschobene Ausgangssignal wird anschließend als eine Eingangsgröße für ein adaptives Filter zur Unterdrückung eines Störsignals und an einen Algorithmus zur Einstellung der Filterparameter des adaptiven Filters zugeführt.The EP 2 736 271 A1 discloses a system for estimating a feedback noise signal in which an output signal is shifted in frequency. The frequency-shifted output signal is then supplied as an input to an adaptive filter for rejecting a noise signal and to an algorithm for adjusting the filter parameters of the adaptive filter.

Der Erfindung liegt daher die Aufgabe zugrunde, ein Verfahren zur Unterdrückung eines durch akustische Rückkopplung bedingten Störgeräusches zu nennen, welches die Verwendung eines adaptiven Filters erlaubt, und gleichzeitig eine möglichst hohe Klangqualität im Ausgangssignal aufweist.The invention is therefore based on the object of mentioning a method for suppressing an acoustic noise caused by noise, which allows the use of an adaptive filter, and at the same time has the highest possible sound quality in the output signal.

Die genannte Aufgabe wird erfindungsgemäß gelöst durch ein Verfahren zur Unterdrückung eines Störgeräusches in einem akustischen System, wobei das akustische System wenigstens ein Mikrofon und wenigstens einen Lautsprecher umfasst, wobei das wenigstens eine Mikrofon ein Eingangssignal erzeugt und wobei der wenigstens eine Lautsprecher ein akustisches Signal erzeugt, welches teilweise auf das wenigstens eine Mikrofon rückkoppelt, wobei entlang eines Hauptsignalpfades in Abhängigkeit vom Eingangssignal ein erstes Zwischensignal und aus dem ersten Zwischensignal durch eine Frequenzverzerrung ein Ausgangssignal gebildet wird, wobei aus dem Hauptsignalpfad das Ausgangssignal in einen Signal-Rückkopplungspfad ausgekoppelt wird, wobei im Signal-Rückkopplungspfad aus dem Ausgangssignal durch eine Dekorrelierung ein zweites Zwischensignal gebildet wird, das als Eingangsgröße für ein adaptives Filter herangezogen wird, welches ein Kompensationssignal erzeugt, und wobei das Kompensationssignal dem Eingangssignal zur Kompensation zugeführt wird, wobei aus dem Eingangssignal und/oder aus dem kompensierten Eingangssignal ein drittes Zwischensignal gebildet wird, welches als Eingangsgröße für das adaptive Filter herangezogen wird, und wobei das Ausgangssignal dem wenigstens einen Lautsprecher zur Wiedergabe zugeführt wird. Vorteilhafte und teils für sich gesehen erfinderische Ausgestaltungsformen sind in den Unteransprüchen und der nachfolgenden Beschreibung dargelegt.The above object is achieved by a method for suppressing a noise in an acoustic system, wherein the acoustic system comprises at least one microphone and at least one speaker, wherein the at least one microphone generates an input signal and wherein the at least one loudspeaker generates an acoustic signal, which partially feeds back to the at least one microphone, wherein along a main signal path in response to the input signal, a first intermediate signal and from the first intermediate signal by a frequency distortion an output signal is formed, wherein the output signal is coupled out of the main signal path in a signal feedback path, wherein in the signal Feedback path from the output signal by decorrelation a second intermediate signal is formed, which is used as an input to an adaptive filter, which generates a compensation signal, and wherein the Kompensat ion signal is supplied to the input signal for compensation, wherein from the input signal and / or from the compensated input signal, a third intermediate signal is formed, which is used as an input to the adaptive filter, and wherein the output signal is supplied to the at least one speaker for playback. Advantageous and partly inventive in themselves inventive embodiments are set forth in the dependent claims and the description below.

Insbesondere kann auch das Ausgangssignal als weitere Eingangsgröße für das adaptive Filter herangezogen werden, wobei das zweite Zwischensignal und das dritte Zwischensignal im adaptiven Filter zur Bestimmung von Filterkoeffizienten herangezogen werden, mittels derer das Ausgangssignal gefiltert und hierdurch das Kompensationssignal erzeugt wird.In particular, the output signal can also be used as a further input variable for the adaptive filter, wherein the second intermediate signal and the third intermediate signal are used in the adaptive filter for determining filter coefficients, by means of which the output signal is filtered and the compensation signal is thereby generated.

Die Erfindung geht dabei von folgenden Überlegungen aus: Eine Verringerung der Schrittweite p eines verwendeten adaptiven Filters hätte zur Folge, dass im Fall eines korrelierten Eingangssignals das Filter deutlich langsamer divergiert, so dass ungewünschte Artefakte im Ausgangssignal reduziert werden könnten bzw. unhörbar werden. Die Reduktion der Schrittweite könnte hierbei beispielsweise immer dann erfolgen, wenn ein korreliertes bzw. tonales Eingangssignal registriert wird. Ein Nachteil eines solchen Vorgehens ist jedoch, dass jede Veränderung des akustischen Rückkopplungspfades, während das korrelierte Signal registriert wird, nicht schnell genug verfolgt werden kann, um durch die Rückkopplung hervorgerufene Störgeräusche zu vermeiden, da infolge der verringerten Schrittweite p Beschränkungen an die Anpassungsfähigkeit des Filters gelegt werden. Die Schrittweite ist daher immer zu sehen als ein Trade-off zwischen der Klangqualität und der Fähigkeit, auf Veränderungen im akustischen Rückkopplungspfad zu reagieren.The invention is based on the following considerations: A reduction in the step size p of an adaptive filter used would result in the filter diverging much more slowly in the case of a correlated input signal, so that undesired artifacts in the output signal could be reduced or become inaudible. The reduction of the step size could, for example, always take place when a correlated or tonal input signal is registered. However, a disadvantage of such a procedure is that any change in the acoustic feedback path while the correlated signal is being registered can not be tracked fast enough to avoid feedback noise, because of the reduced step size p limitations on the adaptability of the filter be placed. The step size is therefore always to be seen as a trade-off between sound quality and the ability to respond to changes in the acoustic feedback path.

Eine andere Möglichkeit, die Probleme eines adaptiven Filters für ein stark korreliertes Eingangssignal zu beheben, liegt in einer möglichen Dekorrelierung des Eingangssignals (sog. "pre-whitening"). Da im adaptiven Filter nur korrelierte Eingangssignale Probleme mit der Anpassung hervorrufen, könnte eine derartige Dekorrelierung zunächst das Problem lösen. Eine solche Dekorrelierung wird oftmals durch eine lineare Prädiktion ("linear predictor") implementiert. Für ein korreliertes Eingangssignal wird dabei eine Vorhersage für ein oder mehrere zukünftige Samples des Signals in Abhängigkeit von vergangenen beobachteten Samples des Signals getroffen. Diese Vorhersage wird anschließend vom eigentlichen Eingangssignal subtrahiert. Das Resultat dieser Subtraktion wird Prädiktions-Fehlersignal ("residual signal") genannt. So ist beispielsweise ein Sinussignal vollständig deterministisch und daher perfekt vorhersagbar. In diesem Fall wäre für eine entsprechende Prädiktions-Ordnung das residuale Signal null.Another way to solve the problems of an adaptive filter for a strongly correlated input signal is a possible decorrelation of the input signal (so-called "pre-whitening"). Since only correlated input signals cause matching problems in the adaptive filter, such decorrelation could first solve the problem. Such decorrelation is often implemented by a linear predictor. For a correlated input signal, a prediction is made for one or more future samples of the signal as a function of past observed samples of the signal. This prediction then becomes the actual input signal subtracted. The result of this subtraction is called the prediction error signal ("residual signal"). For example, a sinusoidal signal is completely deterministic and therefore perfectly predictable. In this case, for a corresponding prediction order, the residual signal would be zero.

Im Fall einer linearen Prädiktion kann das Prädiktions-Fehlersignal geschrieben werden als r k = s k i = 1 P s k i a i ,

Figure imgb0002
wobei s(k) das Sample des Input-Signals für die Prädiktion zum Zeitpunkt k darstellt, a(i) den Filterkoeffizienten der Dekorrelierung bezeichnet, und P die Ordnung der Prädiktion. Das so erzeugte Prädiktions-Fehlersignal ist dabei im Allgemeinen komplexwertig.In the case of linear prediction, the prediction error signal may be written as r k = s k - Σ i = 1 P s k - i a i .
Figure imgb0002
where s (k) represents the sample of the input signal for the prediction at time k, a (i) denotes the filter coefficient of decorrelation, and P the order of prediction. The prediction error signal thus generated is generally of complex value.

Durch eine Rückkopplung verursachte Störgeräusche weisen ebenfalls erheblich korrelierte Signalanteile auf. Wendet man nun eine Dekorrelierung auf ein solches Signal an, so ist die Signalstärke des daraus resultierenden Prädiktions-Fehlersignals sehr gering. Für eine Weiterverwendung in einem adaptiven Filter würde dies bedeuten, dass das adaptive Filter an der Frequenz des durch die Rückkopplung erzeugten Störgeräusches nicht angeregt ist. Somit kann das Filter an dieser Frequenz keine Anpassung an den akustischen Rückkopplungspfad vornehmen, wodurch das Störgeräusch solange verbleibt, bis der akustische Rückkopplungspfad sich verändert.Interference caused by feedback also has significantly correlated signal components. If a decorrelation is applied to such a signal, the signal strength of the resulting prediction error signal is very low. For reuse in an adaptive filter, this would mean that the adaptive filter is not excited at the frequency of the noise generated by the feedback. Thus, the filter can not adapt to the acoustic feedback path at this frequency, whereby the noise remains until the acoustic feedback path changes.

Zum Abschätzen der Filterkoeffizienten für die Dekorrelierung mittels linearer Prädiktion existieren verschiedene Methoden, beispielsweise der NLMS-Algorithmus und die Lewinson-Durbin-Rekursion. Bei letzterer wird folgende matrixwertige Gleichung rekursiv gelöst: a = R 1 r ,

Figure imgb0003
wobei der Vektor a die Koeffizienten a(i) enthält, und die Matrix R und der Vektor r die Autokorrelationsmatrix bzw. den Autokorrelationsvektor bezeichnet. Beide Größen werden gebildet durch die Autokorrelationen r j = E s k s k j ,
Figure imgb0004
wobei für stationäre Signale der Erwartungswert E nur von der Zeitverschiebung j abhängt. Der Erwartungswert kann dabei z.B. durch rekursives Mitteln approximiert werden.For estimating the filter coefficients for decorrelation by means of linear prediction, various methods exist, for example the NLMS algorithm and the Lewinson-Durbin recursion. In the latter, the following matrix-valued equation is recursively solved: a = R - 1 r .
Figure imgb0003
wherein the vector a contains the coefficients a (i), and the matrix R and the vector r the autocorrelation matrix or the Autocorrelation vector called. Both sizes are formed by the autocorrelations r j = e s k s k - j .
Figure imgb0004
for stationary signals, the expected value E depends only on the time shift j. The expected value can be approximated, for example, by recursive means.

Für nicht stationäre Signale, wie z.B. Sprache, sind die Autokorrelationswerte zeitabhängig, und daher bevorzugt wiederholt zu ermitteln. Die meisten nicht stationären Signale können jedoch innerhalb eines Zeitfensters einer bestimmten Dauer als nahezu stationär betrachtet werden. Die Länge dieses Zeitfensters hängt dabei vom Grad ab, in welchem das Signal nicht stationär ist. Die Anpassungsgeschwindigkeit eines Filters bzw. Schätzers, welcher die Autokorrelationswerte eines Input-Signals berechnet, spielt hierbei eine wichtige Rolle: Je schneller der Schätzer, desto besser können nicht stationäre Signale verfolgt werden, wodurch sich eine Dekorrelierung eines Input-Signals verbessert. Um also ein nicht stationäres Signal für eine Dekorrelierung innerhalb eines kurzen Zeitfensters als stationär behandeln zu können, bedarf es eines möglichst schnellen Schätzers. Dies gilt auch für jene Dekorrelierungen, welche sich eines anderen Verfahrens bedienen. So wird beispielsweise im NLMS-Algorithmus die Anpassungsgeschwindigkeit und damit die Fähigkeit, nicht stationäre Signale zu dekorrelieren, über die Schrittweite geregelt.For non-stationary signals, e.g. Speech, the autocorrelation values are time-dependent, and therefore preferred to be repeatedly determined. However, most non-stationary signals can be considered nearly stationary within a time window of a certain duration. The length of this time window depends on the degree to which the signal is not stationary. The adaptation speed of a filter or estimator, which calculates the autocorrelation values of an input signal, plays an important role in this case: the faster the estimator, the better it is not possible to track stationary signals, which improves the decorrelation of an input signal. In order to be able to treat a non-stationary signal for a decorrelation within a short time window as stationary, it requires the fastest possible estimator. This also applies to those decorrelations which use a different method. In the NLMS algorithm, for example, the adaptation speed and thus the ability to decorrelate nonstationary signals is regulated by the step size.

Das Problem, dass ein korreliertes Zielsignal für das adaptive Filter zum Auslöschen eines durch Rückkopplung bedingten Störgeräusches vorher bevorzugt zu dekorrelieren ist, jedoch durch eine Dekorrelierung das adaptive Filter bei den Frequenzen des durch Rückkopplung hervorgerufenen Störgeräusches nicht mehr angeregt ist, könnte nun dadurch umgangen werden, dass in einem ersten Schritt ein derartiges Störgeräusch detektiert wird, und in Abhängigkeit einer solchen Detektion in einem zweiten Schritt in diesem Fall die Dekorrelierung unterbleibt. Dies hat jedoch mehrere praktische Nachteile: Zum einen ist eine solche Detektion in der Praxis stets fehlerbehaftet. Insbesondere, wenn durch die akustische Rückkopplung mehrere nahe beieinander liegende Frequenzen angeregt werden, können diese gegebenenfalls aufgrund einer unzureichenden spektralen Auflösung bei der Detektion nicht hinreichend unterdrückt werden. Überdies erfordert ein solches Vorgehen zunächst immer eine wenigstens ansatzweise Entwicklung eines durch die Rückkopplung bedingten Störgeräusches, um bei dessen Detektion den entsprechenden Signalverarbeitungsblock der Dekorrelierung zu umgehen. Dies bedeutet, dass ein internes Signal im akustischen System nie gänzlich rückkopplungsfrei ist, sondern Signalanteile des Störgeräusches bis zum Schwellwert der Detektion enthält. Dies ist jedoch aus Gründen der Klangqualität unerwünscht.The problem that a correlated target signal for the adaptive filter for canceling out a feedback-related noise is preferably decorrelated beforehand, but that a decorrelation of the adaptive filter at the frequencies of the feedback-induced noise no longer stimulates, could now be avoided, that in a first step, such a noise is detected, and in response to such detection in a second step in this case, the decorrelation omitted. However, this has several practical disadvantages: First, such a detection in practice is always faulty. In particular, if the acoustical feedback stimulates a plurality of closely spaced frequencies, these may not be sufficiently suppressed due to insufficient spectral resolution in the detection. Moreover, such a procedure initially always requires at least some development of a noise due to the feedback in order to bypass the corresponding signal processing block of the decorrelation when it is detected. This means that an internal signal in the acoustic system is never completely free from feedback, but contains signal components of the noise up to the threshold value of the detection. However, this is undesirable for reasons of sound quality.

Eine weitere Möglichkeit könnte darin bestehen, die Filterkoeffizienten für die Dekorrelierung in einem weiteren akustischen System zu bestimmen, und diese Filterkoeffizienten zwischen den beteiligten akustischen Systemen kontinuierlich zur Anpassung zu übermitteln. Diese Möglichkeit wäre insbesondere bei einem binauralen Hörgerätesystem gegeben. Der genannten Idee läge die Annahme zugrunde, dass die von den beteiligten akustischen Systemen jeweils aufgezeichneten Schallsignale aus der Umgebung eine hohe Ähnlichkeit aufweisen, durch Rückkopplung in einem einzelnen System hervorgerufene Störgeräusche jedoch nur das einzelne akustische System betreffen. Da ein durch Rückkopplung hervorgerufenes Störgeräusch bei einer bestimmten Frequenz unter hoher Wahrscheinlichkeit nur in einem akustischen System auftreten wird, können die Filterkoeffizienten für die Dekorrelierung, welche in einem anderen akustischen System ermittelt werden, als ein guter Schätzwert für die Dekorrelierung eines Zielsignals im von Rückkopplung betroffenen akustischen System herangezogen werden. Hierfür ist jedoch zunächst das Vorhandensein eines weiteren akustischen Systems erforderlich, was oft nicht gegeben ist. Überdies kann infolge der Übertragung auch eine Zeitverzögerung der Filterkoeffizienten auftreten, sodass diese beim Empfang im jeweils anderen akustischen System nicht mehr aktuell sind, oder aufgrund der räumlichen Anordnung der beteiligten akustischen Systeme stellen die jeweiligen Filterkoeffizienten keine hinreichend gute Abschätzung für das jeweils andere System dar. Dies kann beispielsweise bei einem binauralen Hörgerätesystem aufgrund von durch den Kopf des Anwenders bedingte Abschattungseffekte auftreten.Another possibility could be to determine the filter coefficients for the decorrelation in another acoustic system, and to transmit these filter coefficients continuously between the participating acoustic systems for adaptation. This possibility would be given in particular in a binaural hearing aid system. The above idea would be based on the assumption that the sound signals from the environment recorded by the respective acoustic systems have a high degree of similarity, but that noise caused by feedback in a single system affects only the individual acoustic system. Since feedback noise at a given frequency will most likely only occur in one acoustic system, the filter coefficients for decorrelation determined in another acoustic system may be considered a good estimate for the decorrelation of a target signal in the feedback acoustic system are used. For this, however, the presence of a further acoustic system is first required, which is often not the case. Moreover, as a result of the transmission also a time delay the filter coefficients occur so that they are no longer up-to-date when receiving in the other acoustic system, or due to the spatial arrangement of the acoustic systems involved, the respective filter coefficients are not a sufficiently good estimate for the other system. This may, for example, in a binaural hearing aid system caused by the head of the user shading effects occur.

Demgegenüber schlägt nun die Erfindung vor, ein Ausgangssignal des akustischen Systems, welches in einen Signal-Rückkopplungspfad einzuspeisen ist, zunächst einer Frequenzverzerrung zu unterziehen, und daraufhin zu dekorrelieren. Insbesondere kann hierbei eine zeitabhängige Frequenzverzerrung verwendet werden. Durch eine Rückkopplung hervorgerufene Störgeräusche weisen im Normalfall ein nahezu perfekt sinusförmiges Signal auf. Durch die Frequenzverzerrung geht diese Form verloren. Wird beispielsweise für die Frequenzverzerrung eine zeitabhängige Frequenzverschiebung gewählt, folgen die Signale der Störgeräusche dieser Frequenzverschiebung.In contrast, the invention proposes to first subject an output signal of the acoustic system, which is to be fed into a signal feedback path, to frequency distortion, and then to decorrelate it. In particular, a time-dependent frequency distortion can be used here. Noise caused by feedback usually has a nearly perfectly sinusoidal signal. Due to the frequency distortion, this form is lost. If, for example, a time-dependent frequency shift is selected for the frequency distortion, the signals of the noise follow this frequency shift.

Die Autokorrelationswerte von frequenzverzerrten Signalen nehmen mit zunehmendem Zeitabstand ab, sodass das Zeitfenster, währenddessen das durch Rückkopplung hervorgerufene Störsignal als stationär betrachtet werden kann, verkürzt wird. Somit ist es möglich, einen Dekorrelierer derart zu implementieren, dass sich dieser nicht an das Störsignal der Rückkopplung anpasst. Das Zeitfenster, in welchem Signale als stationär betrachtet werden können, ist dabei bevorzugt so zu wählen, dass durch die Frequenzverzerrung das Störsignal der Rückkopplung nicht als stationär betrachtet wird, die eigentlich nicht stationären Signalanteile eines Zielsignals schon. Somit wird die Dekorrelierung nicht an das Störsignal, sondern nur an die Signalanteile des Zielsignals angepasst, welche dekorreliert werden. Im dekorrelierten Signal sind nun die nicht stationären korrelierten Signalanteile entfernt, wie sie bei der Aufzeichnung von gesprochener Sprache auftreten, nicht jedoch die durch die Rückkopplung hervorgerufenen Signalanteile. Das dekorrelierte Signal wird nun als ein Zwischensignal dem adaptiven Filter zugeführt, welches basierend auf dem durch Rückkopplung hervorgerufenen Störsignal ein Kompensationssignal erzeugen kann, welches zur Unterdrückung der Störgeräusche in den Hauptsignalpfad zurückgeführt wird.The autocorrelation values of frequency-distorted signals decrease as the time interval increases, so that the window of time during which the feedback-induced noise can be considered stationary is shortened. Thus, it is possible to implement a decorrelator such that it does not adapt to the interference signal of the feedback. The time window in which signals can be considered stationary, is preferably to be chosen so that the interference signal of the feedback is not considered stationary by the frequency distortion, the actually non-stationary signal components of a target signal already. Thus, the decorrelation is not adapted to the interference signal, but only to the signal components of the target signal, which are decorrelated. In the decorrelated signal, the non-stationary correlated signal components are removed, as they occur in the recording of spoken speech, but not caused by the feedback Signal components. The decorrelated signal is now supplied as an intermediate signal to the adaptive filter, which can generate a compensation signal based on the feedback caused by feedback, which is fed back to the main signal path for the suppression of the noise.

Günstigerweise wird das Eingangssignal zeitdiskretisiert, wobei als adaptives Filter ein "least mean square"-Algorithmus (LMS) verwendet wird. Bevorzugt wird dabei das Ausgangssignal als das Referenzsignal verwendet, und das Fehlersignal des LMS-Filters durch die Differenz aus dem Eingangssignal und dem Kompensationssignal gebildet. Das angegebene Verfahren ist insbesondere bei der Verwendung eines LMS-Algorithmus im adaptiven Filter vorteilhaft, da durch die Frequenzverzerrung des Ausgangssignals die Divergenz-Probleme, welche bei der Verwendung eines LMS-Algorithmus zur adaptiven Filterung von durch Rückkopplung bedingten Störsignalen auftreten, gelöst werden.The input signal is favorably time-discretized, whereby a "least mean square" algorithm (LMS) is used as the adaptive filter. In this case, the output signal is preferably used as the reference signal, and the error signal of the LMS filter is formed by the difference between the input signal and the compensation signal. The specified method is particularly advantageous in the use of an LMS algorithm in the adaptive filter, since the frequency distortion of the output signal solves the divergence problems which occur when using an LMS algorithm for the adaptive filtering of feedback-related interference signals.

Als weiter vorteilhaft erweist es sich hierbei, wenn die Schrittweite im LMS-Algorithmus über das zweite Zwischensignal normalisiert wird. Dieses Vorgehen wird auch bezeichnet als "Normalized least mean square" (NLMS). Durch eine solche Normalisierung werden die Konvergenzeigenschaften des Algorithmus verbessert. Die optimalen Filterkoeffizienten sind im Allgemeinen gegeben durch die Lösung der Filtergleichung mittels eines Wiener-Filters. Dieses kann jedoch aufgrund der statischen Eigenschaften und der begrenzten Umsetzungszeit meist nicht angewandt werden, weswegen Abschätzungen für die durch das Wiener-Filter gegebenen Filterkoeffizienten verwendet werden, wobei die Abschätzungen im Idealfall gegen die Wiener-Lösung konvergieren. Im Falle eines LMS-Algorithmus zur Abschätzung der im Sinne eines Wiener-Filters optimalen Filterkoeffizienten kann eine zu große Schrittweite p in der Nähe der optimalen Lösung die Konvergenz verschlechtern, da im Lösungsraum durch die Iterationsschritte eine relativ grobe Bewegung um die optimale Lösung stattfindet. Durch die Normalisierung der Schrittweite und damit durch den Übergang zum NLMS wird in der Nähe der optimalen Filterkoeffizienten die Bewegung verfeinert, wodurch in den einzelnen Iterationsschritten ein übermäßiges Entfernen von der optimalen Lösung im Lösungsraum unterbunden wird.It proves to be further advantageous if the step size in the LMS algorithm is normalized via the second intermediate signal. This procedure is also called "normalized least mean square" (NLMS). Such normalization improves the convergence properties of the algorithm. The optimal filter coefficients are generally given by the solution of the filter equation by means of a Wiener filter. However, due to the static properties and the limited conversion time, this can usually not be used, which is why estimates are used for the filter coefficients given by the Wiener filter, the estimates converging ideally against the Wiener solution. In the case of an LMS algorithm for estimating the optimum filter coefficient in the sense of a Wiener filter, too great a step size p in the vicinity of the optimal solution may worsen the convergence, since a relatively coarse movement around the optimal solution takes place in the solution space due to the iteration steps. By normalizing the step size and thus by the transition to the NLMS, the motion is refined near the optimal filter coefficients, thereby preventing excessive removal of the optimum solution in the solution space in the individual iteration steps.

Zweckmäßigerweise wird die Frequenzverzerrung zur Bildung des Ausgangssignals aus dem ersten Zwischensignal durch eine Frequenzverschiebung erreicht. Insbesondere wird dabei eine zeitabhängige Frequenzverschiebung verwendet. Dies bietet die Möglichkeit, die Anpassungsgeschwindigkeit des Dekorrelierers auf die Frequenzverschiebung abzustimmen, und somit die frequenzverschobenen Signalanteile des durch die akustische Rückkopplung hervorgerufenen Störgeräusches von der Dekorrelierung wirksam auszunehmen. Jedoch kann eine Frequenzverzerrung auch durch eine Phasenmodifikation, eine Frequenztransposition oder eine nicht-lineare Transformation erfolgen. Auch in diesem Fall ist die Anpassungsgeschwindigkeit des Dekorrelierers bevorzugt auf den jeweiligen Grad der Frequenzverzerrung abzustimmen.Conveniently, the frequency distortion to form the output signal from the first intermediate signal is achieved by a frequency shift. In particular, a time-dependent frequency shift is used. This provides the ability to tune the decorrelator's adaptation speed to the frequency offset, and thus effectively exclude the frequency-shifted signal components of the acoustic feedback noise from the decorrelation. However, frequency distortion may also be by phase modification, frequency transposition, or non-linear transformation. Also in this case, the adaptation speed of the decorrelator is preferably to be tuned to the respective degree of frequency distortion.

Als weiter vorteilhaft erweist sich, wenn das Ausgangssignal zur Bildung des zweiten Zwischensignals mittels eines linearen Prädiktionsfilters dekorreliert wird. Die Filterkoeffizienten des linearen Prädiktionsfilters sind dabei bevorzugt mittels einer Levinson-Durbin-Rekursion oder mittels eines LMS- bzw. NLMS-Algorithmus zu bestimmen. Der Vorteil eines linearen Prädiktionsfilters besteht darin, dass hierfür nur lineare Gleichungssysteme zu lösen sind, was die numerische Komplexität für das jeweilige Filterproblem begrenzt. Insbesondere kann auch das Eingangssignal oder das kompensierte Eingangssignal mittels eines linearen Prädiktionsfilters dekorreliert werden, und zur Bildung des dritten Zwischensignals herangezogen werden, welches als Eingangsgröße dem adaptiven Filter zugeführt wird.It proves to be further advantageous if the output signal for decoding the second intermediate signal is decorrelated by means of a linear prediction filter. The filter coefficients of the linear prediction filter are preferably to be determined by means of a Levinson-Durbin recursion or by means of an LMS or NLMS algorithm. The advantage of a linear prediction filter is that only linear systems of equations have to be solved, which limits the numerical complexity for the respective filter problem. In particular, the input signal or the compensated input signal can also be decorrelated by means of a linear prediction filter, and used to form the third intermediate signal, which is supplied as an input variable to the adaptive filter.

Bevorzugt werden dabei für die Filterkoeffizienten des linearen Prädiktionsfilters zeitabhängige Autokorrelationswerte des Ausgangssignals und/oder eines auf dem Eingangssignal basierenden Fehlersignals herangezogen. Insbesondere können die Autokorrelationswerte dabei für einen Levinson-Durbin-Algorithmus verwendet werden. Die Berücksichtigung der Zeitabhängigkeit der Autokorrelationswerte ermöglicht eine Abstimmung der Dekorrelierung an den Grad der Frequenzverzerrung über die geeignete Wahl eines entsprechenden Zeitfensters, nach welchem jeweils die Autokorrelationswerte erneut ermittelt werden.In this case, time-dependent autocorrelation values of the output signal and / or of a signal based on the input signal are preferred for the filter coefficients of the linear prediction filter Error signal used. In particular, the autocorrelation values can be used for a Levinson-Durbin algorithm. Taking into account the time dependence of the autocorrelation values allows the decorrelation to be adjusted to the degree of frequency distortion via the appropriate choice of a corresponding time window, after which the autocorrelation values are again determined.

Besonders bevorzugt werden die Filterkoeffizienten des, insbesondere jedes linearen Prädiktionsfilters in Abhängigkeit von der Dekorrelierungsstärke der Frequenzverzerrung angepasst. Dies bedeutet insbesondere, dass das Zeitfenster, in welchem Signale als stationär betrachtet werden können, von der Dekorrelierungsstärke der Frequenzverzerrung abhängt. Im Fall eines Levinson-Durbin-Algorithmus kann dies beispielsweise über eine wiederholte Anpassung der Autokorrelationswerte in den genannten Zeitabständen erfolgen, aus welchen die Filterkoeffizienten erneut zu ermitteln sind. Im Fall eines NLMS-Algorithmus kann stattdessen entsprechend die Schrittweite in den genannten Zeitabständen angepasst werden.Particularly preferably, the filter coefficients of, in particular, each linear prediction filter are adapted as a function of the decorrelation strength of the frequency distortion. This means in particular that the time window in which signals can be regarded as stationary depends on the decorrelation strength of the frequency distortion. In the case of a Levinson-Durbin algorithm, this can be done, for example, via a repeated adaptation of the autocorrelation values in the mentioned time intervals, from which the filter coefficients are to be determined again. In the case of an NLMS algorithm, the step size can instead be adjusted accordingly in the time intervals specified.

Durch die beschriebene funktionale Abhängigkeit der Zeitabstände bzw. des stationären Zeitfensters kann beeinflusst werden, welche Signalanteile vom Dekorrelierer noch als stationär wahrgenommen werden, so dass die von der Frequenzverzerrung betroffenen Signalanteile des Störsignals nicht mit dekorreliert werden. Ein Dekorrelierer, welcher ein zu kurzes "stationäres Zeitfenster" aufweist, könnte auch Signalanteile eines frequenzverzerrten ursprünglich monofrequenten Signals als stationär auffassen und daher mit dekorrelieren. Dies wird dadurch umgangen, dass die Anpassungsgeschwindigkeit der Dekorrelierung an den Grad der Frequenzverzerrung, insbesondere an die dieser eigenen Dekorrelierungsstärke, angepasst wird. wird beispielsweise eine zeitabhängige Frequenzverschiebung gewählt, so ist diese bevorzugt schneller durchzuführen, als im Zeitfenster für die Dekorrelierung Signale als stationär betrachtet werden.The described functional dependence of the time intervals or of the stationary time window can influence which signal components are still perceived as stationary by the decorrelator, so that the signal components of the interference signal affected by the frequency distortion are not decorrelated. A decorrelator, which has too short a "stationary time window", could also perceive signal components of a frequency-distorted originally monofrequency signal as stationary and therefore decorrelate it. This is circumvented by adapting the rate of adaptation of the decorrelation to the degree of frequency distortion, in particular to that of its own decorrelation strength. If, for example, a time-dependent frequency shift is selected, then this is preferably carried out more quickly than signals are considered to be stationary in the time window for the decorrelation.

In einer weiter vorteilhaften Ausgestaltung der Erfindung werden die Filterkoeffizienten des, insbesondere jedes linearen Prädiktionsfilters in Abhängigkeit von einer Transferfunktion eines Modells des akustischen Systems angepasst, welches das wenigstens eine Mikrofon und wenigstens einen das korrigierte Ausgangssignal wiedergebenden Lautsprecher umfasst. Insbesondere können dabei die Zeitabstände für die Anpassung der Filterkoeffizienten zusätzlich auch von der Dekorrelierungsstärke der Frequenzverzerrung abhängen. Die Transferfunktion kann hierbei die spezifischen Kenndaten des akustischen Systems enthalten, wie z.B. Verstärkungswerte in einzelnen Sub-Bändern. In ein solches Modell kann dabei, wenigstens implizit über Koeffizienten der Transferfunktion, auch die Wahrscheinlichkeit eingehen, dass eine Rückkopplung Störgeräusche bei einer bestimmten Frequenz hervorruft. Ist eine Anregung durch Rückkopplung sehr wahrscheinlich bzw. oberhalb eines vorher festgelegten Grenzwertes für die Wahrscheinlichkeit, kann die Anpassungsgeschwindigkeit der Dekorrelierung verringert werden, um sicherzustellen, dass die frequenzverzerrten Anteile des ursprünglich monofrequenten Störsignals nicht als stationär betrachtet und mit dekorreliert werden. Ist eine Rückkopplung unwahrscheinlich, kann das Zeitfenster für die Anpassung des Dekorrelierers verkürzt werden, so dass tonale Signalkomponenten, welche z.B. durch Sprachaufnahme erzeugt wurden, schnell erkannt werden, und dekorreliert werden.In a further advantageous embodiment of the invention, the filter coefficients of the, in particular each linear prediction filter are adapted in dependence on a transfer function of a model of the acoustic system, which comprises the at least one microphone and at least one speaker reproducing the corrected output signal. In particular, the time intervals for the adaptation of the filter coefficients may additionally depend on the decorrelation strength of the frequency distortion. The transfer function may hereby contain the specific characteristics of the acoustic system, e.g. Gain values in individual sub-bands. In such a model, it is also possible, at least implicitly via coefficients of the transfer function, to enter into the probability that a feedback causes noise at a certain frequency. If a feedback excitation is very likely or above a predetermined probability limit, the decorrelation adaptation rate may be reduced to ensure that the frequency-distorted components of the original monofrequency noise are not considered stationary and decorrelated. If feedback is unlikely, the time window for the decorrelator adaptation can be shortened so that tonal signal components, e.g. generated by voice recording, are quickly detected, and decorrelated.

Die Erfindung nennt weiter ein akustisches System, welches umfassend wenigstens ein Mikrofon zur Erzeugung eines Eingangssignals, wenigstens einen Lautsprecher zur Wiedergabe eines Ausgangssignals, und eine Steuereinheit umfasst, welche dazu eingerichtet ist, ein Störgeräusch, das durch Rückkopplung des über den wenigstens einen Lautsprecher wiedergegebenen Ausgangssignals in das vom wenigstens einen Mikrofon erzeugte Eingangssignal hervorgerufen wird, durch das vorbeschriebene Verfahren unterdrücken. Insbesondere ist das akustische System dabei als ein Hörgerät, und vorteilhaft als ein Hörhilfegerät ausgebildet. Die für das Verfahren und seine Weiterbildungen angegebenen Vorteile können dabei sinngemäß auf das akustische System übertragen werden.The invention further provides an acoustic system comprising at least one microphone for generating an input signal, at least one loudspeaker for reproducing an output signal, and a control unit which is adapted to generate a noise by feedback of the output signal reproduced via the at least one loudspeaker is caused in the input signal generated by the at least one microphone, suppress by the above-described method. In particular, the acoustic system is here as a hearing aid, and advantageous as a Hearing aid formed. The advantages stated for the method and its developments can be transferred analogously to the acoustic system.

Nachfolgend wird ein Ausführungsbeispiel der Erfindung anhand einer Zeichnung näher erläutert. Hierbei zeigen jeweils schematisch:

FIG 1
in einem Blockdiagramm der Ablauf eines Verfahrens zur Unterdrückung eines Störgeräusches in einem akustischen System, und
FIG 2
in einem Blockdiagramm eine weitere Ausgestaltungsmöglichkeit des Verfahrens nach FIG 1.
An embodiment of the invention will be explained in more detail with reference to a drawing. Here are shown schematically in each case:
FIG. 1
in a block diagram of the sequence of a method for suppressing a noise in an acoustic system, and
FIG. 2
in a block diagram, a further embodiment of the method according to FIG. 1 ,

Einander entsprechende Teile und Größen sind in allen Figuren jeweils mit gleichen Bezugszeichen versehen.Corresponding parts and sizes are provided in all figures with the same reference numerals.

In FIG 1 ist schematisch in einem Blockdiagramm der Ablauf eines Verfahrens 1 zur Unterdrückung eines Störgeräusches g in einem akustischen System 2 dargestellt. Das akustische System 2, welches hier gegeben ist durch ein Hörgerät 3, beispielsweise ein Hörhilfegerät, umfasst dabei ein Mikrofon 4 und einen Lautsprecher 6. Das vom Mikrofon 4 aufgezeichnete Mikrofonsignal m wird in einem Hauptsignalpfad 8 einer Signalverarbeitungseinheit 10 zugeführt, wo es unter anderem verstärkt wird. Am Ende des Hauptsignalpfads 8 wird ein Ausgangssignal xs an das Mikrofon 4 ausgegeben, welches aus dem Ausgangssignal xs ein akustisches Signal p erzeugt. Ein Teil des vom Lautsprecher 6 erzeugten akustischen Signals p wird als Rückkopplung fb erneut vom Mikrofon 4 aufgezeichnet, und findet somit Eingang in das Mikrofonsignal m. Durch die Rückkopplung fb werden Signalanteile des akustischen Signals p im Mikrofonsignal m erneut der Signalverarbeitungseinheit 10 zugeführt und dort weiter verstärkt. Durch die wiederholte Verstärkung, Wiedergabe und Aufnahme in einem geschlossenen Prozess entstehen Störgeräusche g in der Form von nahezu monofrequenten Pfeiftönen. Zur Unterdrückung der Störgeräusche g ist der Signal-Rückkopplungspfad 16 vorgesehen.In FIG. 1 3 shows a schematic block diagram of the sequence of a method 1 for suppressing a noise g in an acoustic system 2. The acoustic system 2, which is given here by a hearing device 3, for example a hearing aid device, comprises a microphone 4 and a loudspeaker 6. The microphone signal m recorded by the microphone 4 is fed to a signal processing unit 10 in a main signal path 8 where it amplifies, among other things becomes. At the end of the main signal path 8, an output signal xs is output to the microphone 4, which generates an acoustic signal p from the output signal xs. A part of the acoustic signal p generated by the loudspeaker 6 is again recorded by the microphone 4 as feedback fb, and thus finds its way into the microphone signal m. By means of the feedback fb, signal components of the acoustic signal p in the microphone signal m are fed again to the signal processing unit 10 and further amplified there. The repeated amplification, playback and recording in a closed process produces noise g in the form of almost monofrequente whistling sounds. To suppress the noise g, the signal feedback path 16 is provided.

Für den Signal-Rückkopplungspfad 16 wird aus dem Hauptsignalpfad 8 das Ausgangssignal xs ausgekoppelt und einem Dekorrelierer 18 zugeführt. Der Dekorrelierer 18 wird hierbei gebildet durch ein lineares Prädiktionsfilter 20.For the signal feedback path 16, the output signal x s is coupled out of the main signal path 8 and fed to a decorrelator 18. The decorrelator 18 is formed by a linear prediction filter 20.

Im Hauptsignalpfad 8 gibt die Signalverarbeitungseinheit 10 ein erstes Zwischensignal x aus, welches durch eine Frequenzverzerrung 22 in das Ausgangssignal xs umgewandelt wird. Die Frequenzverzerrung 22, welche im vorliegenden Fall durch eine Frequenzverschiebung 23 erreicht wird, hat zur Folge, dass das lineare Prädiktionsfilter 20 nicht die den Störgeräuschen g entsprechenden Signalanteile dekorreliert, sondern nur Signalanteile eines Zielsignals. Vom linearen Prädiktionsfilter 20 wird ein zweites Zwischensignal xw als Eingangsgröße an ein adaptives Filter 24 ausgegeben. Das adaptive Filter 24 erzeugt aus dem Ausgangssignal xs ein Kompensationssignal c, welches zur Kompensation der Störgeräusche g vom Mikrofonsignal m subtrahiert wird. Hierdurch wird der Signal-Rückkopplungspfad 16 geschlossen.In the main signal path 8, the signal processing unit 10 outputs a first intermediate signal x, which is converted by a frequency distortion 22 in the output signal xs. The frequency distortion 22, which is achieved in the present case by a frequency shift 23, has the consequence that the linear prediction filter 20 does not decorrelate the signal components corresponding to the noise g, but only signal components of a target signal. From the linear prediction filter 20, a second intermediate signal xw is output as an input to an adaptive filter 24. The adaptive filter 24 generates from the output signal xs a compensation signal c, which is subtracted from the microphone signal m to compensate for the noise g. As a result, the signal feedback path 16 is closed.

Für die Erzeugung des Kompensationssignals c wird dem adaptiven Filter 24 ein weiteres Zwischensignal ew als Eingangssignal zugeführt. Dieses dritte Zwischensignal ew wird gebildet aus dem Fehlersignal e, welches sich aus dem um das Kompensationssignal, c kompensierten Mikrofonsignal m ergibt. Das Fehlersignal e wird nun ebenso durch ein lineares Prädiktionsfilter 26 dekorreliert und das dekorrelierte Fehlersignal ew als zweite Eingangsgröße dem adaptiven Filter 24 zugeführt. Aus dem dekorrelierten Fehlersignal ew und dem zweiten Zwischensignal xw werden nun in einem Filterblock 28 des adaptiven Filters 24 die Koeffizienten h berechnet, aus welchen ein Signalblock 30 des adaptiven Filters zusammen mit dem Ausgangssignal xs das Kompensationssignal c erzeugt.For the generation of the compensation signal c, the adaptive filter 24 is supplied with an additional intermediate signal ew as an input signal. This third intermediate signal ew is formed from the error signal e, which results from the microphone signal m compensated for the compensation signal, c. The error signal e is now likewise decorrelated by a linear prediction filter 26, and the decorrelated error signal ew is supplied as a second input variable to the adaptive filter 24. From the decorrelated error signal ew and the second intermediate signal xw, the coefficients h are calculated in a filter block 28 of the adaptive filter 24, from which a signal block 30 of the adaptive filter together with the output signal xs generates the compensation signal c.

Durch die Frequenzverschiebung 23 wird hierbei sichergestellt, dass das lineare Prädiktionsfilter 20 keine den Störgeräuschen g zugehörige Signalanteile dekorreliert, wodurch das adaptive Filter 24 diese nicht mehr mit dem Kompensationssignal c kompensieren würde. Die Länge des stationären Zeitfensters T der linearen Prädiktionsfilter 20, 26, und damit ihre Anpassungsgeschwindigkeit, wird dabei in Abhängigkeit der Frequenzverschiebung 23 gesteuert. Eine Steuereinheit 32 im Hörgerät 3 führt dabei alle angegebenen Verfahrensschritte durch.The frequency shift 23 ensures that the linear prediction filter 20 does not decorrelate any signal components associated with the noise g, whereby the adaptive filter 24 would no longer compensate for these with the compensation signal c. The length of the stationary time window T of the linear prediction filters 20, 26, and thus their adaptation speed, is thereby controlled as a function of the frequency shift 23. A control unit 32 in the hearing aid 3 performs all specified method steps.

In FIG 2 ist in einem Blockdiagramm eine leichte Abwandlung des in FIG 1 dargestellten Verfahrens 1 gezeigt. Hier wird im akustischen System 2, also insbesondere in einem Hörgerät 3, beispielsweise in einem Hörhilfegerät, das dekorrelierte Fehlersignal ew, welches als Eingangsgröße dem adaptiven Filter zugeführt wird, aus einem im linearen Prädiktionsfilter 26 dekorrelierten Eingangssignal mw und einem dekorrelierten Kompensationssignal cw gebildet. Das dekorrelierte Kompensationssignal cw wird dabei im Filterblock 28 des adaptiven Filters aus dem im linearen Prädiktionsfilter 26 dekorrelierten Fehlersignal ew und dem zweiten Zwischensignal xw gebildet, welches durch das im linearen Prädiktionsfilter 20 dekorrelierten Ausgangssignal xs gegeben ist. Die Länge des stationären Zeitfensters T der linearen Prädiktionsfilter 20, 26, und damit ihre Anpassungsgeschwindigkeit, wird hierbei durch eine Anpassungsregelung 34 bestimmt, in welche der Grad df der Frequenzverschiebung 23, der Gain n der Signalverarbeitungseinheit 10 in einzelnen Sub-Bändern, und eine nicht näher dargestellte Transferfunktion des akustischen Systems 2 Eingang finden und zur Bestimmung des Zeitfensters T herangezogen werden. Ebenso kann dabei auch ein durch die Filterkoeffizienten h bestimmtes Modell des akustischen Rückkopplungspfades fb mit herangezogen werden, so dass die Anpassungsgeschwindigkeit der Dekorrelierung in den linearen Prädiktionsfilter 20, 26 auch in Abhängigkeit der durch dieses Modell geschätzten Rückkopplung bestimmt werden. Die Verwendung einer derartigen Anpassungsregelung 34 ist dabei nicht auf die in FIG 2 dargestellte Form des Signal-Rückkopplungspfades 16 beschränkt, sondern kann prinzipiell in verschiedenen Ausführungsvarianten, insbesondere im in FIG 1 gezeigten Ausführungsbeispiel, Verwendung finden.In FIG. 2 is in a block diagram a slight modification of the in FIG. 1 shown method 1 shown. Here, in the acoustic system 2, ie in particular in a hearing aid 3, for example in a hearing aid, the decorrelated error signal ew, which is supplied as an input to the adaptive filter, is formed from an input signal mw decorrelated in the linear prediction filter 26 and a decorrelated compensation signal cw. The decorrelated compensation signal cw is formed in the filter block 28 of the adaptive filter from the error signal ew decorrelated in the linear prediction filter 26 and the second intermediate signal xw, which is given by the output signal xs decorrelated in the linear prediction filter 20. The length of the stationary time window T of the linear prediction filters 20, 26, and thus their adaptation speed, is hereby determined by an adaptation control 34, in which the degree df of the frequency shift 23, the gain n of the signal processing unit 10 in individual sub-bands, and a non find more detailed transfer function of the acoustic system 2 input and used to determine the time window T. Likewise, a model of the acoustic feedback path fb determined by the filter coefficients h can also be used, so that the adaptation speed of the decorrelation in the linear prediction filters 20, 26 is also determined as a function of the feedback estimated by this model. The use of such an adjustment control 34 is thereby not on the in FIG. 2 illustrated form of the signal feedback path 16 is limited, but can in principle in various embodiments, in particular in. In FIG. 1 shown embodiment, find use.

Obwohl die Erfindung im Detail durch das bevorzugte Ausführungsbeispiel näher illustriert und beschrieben wurde, ist die Erfindung nicht durch dieses Ausführungsbeispiel eingeschränkt. Andere Variationen können vom Fachmann hieraus abgeleitet werden, ohne den Schutzumfang der Erfindung zu verlassen. Although the invention has been illustrated and described in detail by the preferred embodiment, the invention is not limited by this embodiment. Other variations can be deduced therefrom by those skilled in the art without departing from the scope of the invention.

Claims (8)

  1. Method (1) for suppressing an interference noise (g) in an acoustic system (2),
    wherein the acoustic system (2) comprises at least one microphone (4) and at least one loudspeaker (6),
    wherein the at least one microphone (4) generates an input signal (m), and wherein the at least one loudspeaker (6) generates an acoustic signal (p) which partially feeds back to the at least one microphone (4),
    wherein a first intermediate signal (x) is formed along a primary signal path (8) as a function of the input signal (m), and an output signal (xs) is formed from the first intermediate signal (x) via a frequency distortion (22),
    wherein the output signal (xs) is coupled out from the primary signal path (8) into a signal feedback path (16),
    wherein a second intermediate signal (xw) is formed in the signal feedback path (16) from the output signal (xs) via a decorrelation (18) by means of a linear prediction filter (20), wherein the filter coefficients of the linear prediction filter (20) are adapted as a function of the decorrelation strength of the frequency distortion (22), wherein the second intermediate signal (xw) is used as an input value for an adaptive filter (24), which generates a compensation signal (c), and wherein the compensation signal (c) is fed to the input signal (m) for compensation,
    wherein a third intermediate signal (ew) is formed from the input signal (m) and/or from the compensated input signal (e), which is used as an input value for the adaptive filter, and
    wherein the output signal (xw) is fed to the at least one loudspeaker (4) for reproduction.
  2. Method (1) according to Claim 1,
    wherein the input signal (m) time-discretized, and wherein a least mean square (LMS) algorithm is used as an adaptive filter.
  3. Method (1) according to Claim 2,
    wherein the increment in the LMS algorithm is normalized over the second intermediate signal (xw) .
  4. Method (1) according to one of the preceding claims,
    wherein the frequency distortion (22) for forming the output signal (xs) from the first intermediate signal (x) is achieved via a frequency shift (23).
  5. Method (1) according to one of the preceding claims,
    wherein time-dependent autocorrelation values of the output signal (xs) and/or an error signal (e) based on the input signal (m) are used for the filter coefficients of the linear prediction filter (20).
  6. Method (1) according to one of the preceding claims,
    wherein the filter coefficients of the linear prediction filter (20) are adapted as a function of a transfer function of a model of the acoustic system (2), which comprises the at least one microphone (4) and at least one loudspeaker (6) reproducing the corrected output signal (xs).
  7. Acoustic system (2), comprising at least one microphone (4) for generating an input signal (m), at least one loudspeaker (6) for reproducing an output signal (xs), and a control unit (32) which is configured to suppress an interference noise (g) due to feedback of the output signal (xs), which is reproduced via the at least one loudspeaker (6), into the input signal (m) generated by at least one microphone (4), via a method (1) according to one of the preceding claims.
  8. Acoustic system (2) according to Claim 7, which is designed as a hearing device (3), in particular as a hearing aid device.
EP16151092.0A 2015-03-05 2016-01-13 Method for suppressing interference noise in an acoustic system Active EP3065417B1 (en)

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106454461A (en) * 2016-10-21 2017-02-22 安徽协创物联网技术有限公司 Live video replaying system
DE102017203631B3 (en) * 2017-03-06 2018-05-17 Sivantos Pte. Ltd. Method for frequency distortion of an audio signal
US11468873B2 (en) * 2017-09-29 2022-10-11 Cirrus Logic, Inc. Gradual reset of filter coefficients in an adaptive noise cancellation system
US11153684B2 (en) * 2018-11-15 2021-10-19 Maxim Integrated Products, Inc. Dynamic debuzzer for speakers

Family Cites Families (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
AU5806400A (en) * 1999-07-19 2001-02-05 Oticon A/S Feedback cancellation with low frequency input
EP1721488B1 (en) * 2004-03-03 2008-11-05 Widex A/S Hearing aid comprising adaptive feedback suppression system
EP2002690B2 (en) 2006-04-01 2019-11-27 Widex A/S Hearing aid, and a method for control of adaptation rate in anti-feedback systems for hearing aids
DK2086250T3 (en) * 2008-02-01 2020-07-06 Oticon As Listening system with an improved feedback suppression system, a method and application
EP2148528A1 (en) * 2008-07-24 2010-01-27 Oticon A/S Adaptive long-term prediction filter for adaptive whitening
US8594173B2 (en) 2008-08-25 2013-11-26 Dolby Laboratories Licensing Corporation Method for determining updated filter coefficients of an adaptive filter adapted by an LMS algorithm with pre-whitening
US8630437B2 (en) * 2010-02-23 2014-01-14 University Of Utah Research Foundation Offending frequency suppression in hearing aids
DE102011006129B4 (en) * 2011-03-25 2013-06-06 Siemens Medical Instruments Pte. Ltd. Hearing device with feedback suppression device and method for operating the hearing device
DK2736271T3 (en) * 2012-11-27 2019-09-16 Oticon As Procedure for Controlling an Update Algorithm for an Adaptive Feedback Estimation System and a De-Correlation Unit
DE102013207403B3 (en) * 2013-04-24 2014-03-13 Siemens Medical Instruments Pte. Ltd. Method for controlling an adaptation step size and hearing device

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
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DK3065417T3 (en) 2019-03-04
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DE102015204010B4 (en) 2016-12-15
DE102015204010A1 (en) 2016-09-08

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