WO2000019605A2 - Dispositif adaptatif de suppression de l'effet larsen a bande limitee destine aux protheses auditives - Google Patents

Dispositif adaptatif de suppression de l'effet larsen a bande limitee destine aux protheses auditives Download PDF

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Publication number
WO2000019605A2
WO2000019605A2 PCT/US1999/022757 US9922757W WO0019605A2 WO 2000019605 A2 WO2000019605 A2 WO 2000019605A2 US 9922757 W US9922757 W US 9922757W WO 0019605 A2 WO0019605 A2 WO 0019605A2
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WIPO (PCT)
Prior art keywords
filter
output
hearing aid
band limiting
feedback
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Application number
PCT/US1999/022757
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English (en)
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WO2000019605A3 (fr
Inventor
Shawn Gao
Sigfrid Soli
Hsiang-Feng Chi
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House Ear Institute
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Application filed by House Ear Institute filed Critical House Ear Institute
Priority to JP2000572997A priority Critical patent/JP2002526961A/ja
Priority to EP99948516A priority patent/EP1118247A2/fr
Priority to AU61680/99A priority patent/AU6168099A/en
Publication of WO2000019605A2 publication Critical patent/WO2000019605A2/fr
Publication of WO2000019605A3 publication Critical patent/WO2000019605A3/fr

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R25/00—Deaf-aid sets, i.e. electro-acoustic or electro-mechanical hearing aids; Electric tinnitus maskers providing an auditory perception
    • H04R25/45—Prevention of acoustic reaction, i.e. acoustic oscillatory feedback
    • H04R25/453—Prevention of acoustic reaction, i.e. acoustic oscillatory feedback electronically
    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03H—IMPEDANCE NETWORKS, e.g. RESONANT CIRCUITS; RESONATORS
    • H03H21/00—Adaptive networks
    • H03H21/0012—Digital adaptive filters

Definitions

  • the present invention relates generally to the field of audio amplification, especially for hearing aids. More particularly, the invention provides a method for efficiently cancelling acoustic feedback in the hearing aid.
  • Acoustic feedback in a hearing aid from the electroacoustic transducer (commonly referred to as the "receiver") back to the microphone, is common and difficult to suppress.
  • Feedback may produce an audible whistle, which is irritating to the hearing aid wearer so that the wearer must often reduce the volume to a lower than desired level, thereby reducing the effectiveness of the hearing aid.
  • One of the principal design objectives for hearing aids is miniaturization of physical volume. Most wearers prefer a hearing aid that can be worn entirely within the ear. Advances in microelectronics have vastly improved the signal processing capabilities of in-the-ear (ITE) hearing aids. Even so, the provision of effective feedback cancellation remains a practical design challenge. Prior art techniques necessarily require certain trade-offs. As a result of such trade-offs, the hearing aid may exhibit only a small increase in maximum stable gain, slow filter adaptation, distortion, interference and/or lack of adaptation to individual wearers.
  • the present invention provides an improved method for adaptively cancelling acoustic feedback in hearing aids and other audio amplification devices.
  • Feedback cancellation is limited to a frequency band that encompasses all unstable frequencies.
  • a relatively simple signal processing algorithm may be used to produce highly effective results with minimal signal distortion.
  • unstable feedback frequencies must first be identified. This is accomplished by various techniques with real ear measurements, from which the complex open loop transfer function may be derived. Once the unstable feedback frequencies are identified, a band limited adaptive filter is implemented. By thus limiting the bandwidth of adaptation, the adaptive feedback canceller is able to adapt very quickly within the range of unstable frequencies with relatively low adaptation noise. By limiting the bandwidth of the feedback cancellation signal, the distortion due to the adaptive filter is minimized and limited only to the unstable feedback regions. Compared to broadband feedback cancellation, the band limited feedback canceller of the present invention produces less distortion, and therefore the output sound quality is much improved.
  • Figure 1 is a functional block diagram of a hearing aid in which the present invention may be implemented.
  • Figure 2 is a simplified diagram illustrating the transfer functions of the hearing aid of Figure 1.
  • Figure 3 illustrates a prior art technique for deriving the open loop transfer function of a hearing aid.
  • FIG. 4 is a functional block diagram of a hearing aid which incorporates a generic broadband adaptive feedback canceller.
  • Figure 5 is a functional block diagram of a hearing aid having an internal noise generator for derivation of the open loop transfer function.
  • Figure 6 is a functional block diagram of one embodiment of a hearing aid having a band-limited adaptive feedback canceller in accordance with the present invention.
  • Figure 7 is a functional block diagram of another embodiment of a hearing aid having a band-limited adaptive feedback canceller in accordance with the present invention.
  • Figure 8 illustrates base-2 logarithm quantization as used by the present invention for filter coefficient adaptation.
  • Figure 9 is a functional block diagram illustrating the signal processing used to implement an adaptive digital filter.
  • Figure 10 illustrates the processing used for power estimation.
  • Figure 11 illustrates the processing used for coefficient adaptation.
  • Figure 12 illustrates the processing used for DC removal.
  • Figure 13 illustrates the processing used for bandpass filtering.
  • Figure 14 is a functional flow diagram illustrating the process scheduling implemented by the control unit of Figure 9.
  • Figure 15 is a logic diagram corresponding to the flow diagram of Figure 14.
  • Figure 16 is a functional block diagram of an alternative embodiment of the present invention.
  • Figure 17 is a functional block diagram of another alternative embodiment of the present invention.
  • Figure 18 is a functional block diagram of still another alternative embodiment of the present invention.
  • Figure 19 is a functional block diagram of yet another alternative embodiment of the present invention.
  • Figure 20 is a functional block diagram of adjustable FIR filtering with a power-of-two scaling gain.
  • Figure 21 is an example of open loop transfer function and unstable feedback frequencies measured on KEMAR ear.
  • FIG. 1 is a functional block diagram of a hearing aid 10 in an ear of a hearing aid user.
  • the hearing aid 10 comprises a microphone 12, microphone preamplifier circuitry 14, analog-to-digital converter 16, signal processing circuitry 18, digital-to-analog converter 20 and receiver 22.
  • the signal processing circuitry 18 has a transfer function from point C to point D o ⁇ K(f).
  • the feedback path from point D to point C includes digital-to-analog converter 20, hearing aid receiver 22, acoustic and mechanical coupling between the receiver and microphone, analog conditioning circuitry 14, and analog-to-digital converter 16.
  • ⁇ ( ) is the transfer function of the feedback path.
  • Figure 2 shows a simplified hearing aid model in the ear.
  • a hearing aid may
  • the method and procedure of detecting and digitizing the acoustic signal with a probe microphone used in the current invention are, in part, the subjects of co-owned U.S. Patent No. 5,325,436, "Method of Signal Processing for Maintaining Directional Hearing with Hearing Aids".
  • H lAB (f), H 2AB ( ) and H iAB (f) are closed loop transfer functions from point A to point B in Figure 1 measured with Gl, G2 and G3.
  • Point A is at the hearing aid microphone input and point B is at the hearing aid receiver output, i.e., at the probe microphone.
  • the derived open loop transfer function is thus only an approximation of the open loop transfer function with an open hearing aid vent.
  • the closed loop transfer function measurements are also sensitive to head movement and surrounding environmental changes during the measurements.
  • the second method does not require a probe microphone measurement. It requires configuring the adaptive feedback canceller in the hearing aid to operate in a broadband mode as shown in Figure 4.
  • the adaptive digital filter (ADF) 30 in the hearing aid provides an estimation of the feedback path including the digital-to- analog converter 20, the receiver 22, the coupling path between the receiver and microphone, the microphone 12, the AGC 14, and the analog-to-digital converter 16.
  • Data is collected with the hearing aid wearer seated in a quiet room.
  • a white noise signal is generated in the sound field through a loudspeaker.
  • the hearing aid is programmed with a known reference response.
  • the hearing aid wearer is instructed to adjust the hearing aid gain below the Uncomfortable Level (UCL).
  • UCL Uncomfortable Level
  • the ADF in the hearing aid adapts itself to match the feedback path.
  • the filter coefficient vector W(n) is read from the hearing aid together with the "delay".
  • the feedback transfer function ⁇ '(f) can be estimated as
  • W n (f) is the frequency response of the ADF at time index n, for which the impulse response is W( «).
  • W(/?,) with different time index n, , can be obtained from the ADF and averaged to compute W n (f) in Equation 3.
  • the hearing aid reference response used during the measurement is replaced by a desired hearing aid response K(f).
  • the complex open loop transfer function associated with the desired hearing aid response K(f) can be estimated by K(f) ⁇ '(f) :
  • the unstable feedback frequencies can then be determined by the estimated open loop transfer function based on Equation 1. Comparing with the first method, this method does not require a probe microphone measurement. Therefore, the venting system of the hearing aid is not blocked during the measurement. The measurement is not sensitive to head movement and surrounding environmental changes. It does not require additional circuitry in the hearing aid to support the measurement.
  • the white noise signal serves as a test signal for the measurement, but it also acts as interference noise to the ADF since the signal directly from the loudspeaker does not carry any information about the feedback path. Thus, it introduces adaptation noise to the ADF coefficients. To achieve the best results, the level of the white noise signal should be kept as low as possible but above the noise floor of the room.
  • the hearing aid gain should be set as high as possible but below UCL and without audible feedback. Furthermore, the hearing aid is configured in a closed-loop during the measurement. The unstable feedback rather than the UCL may be the limiting factor for setting the hearing aid gain.
  • the third method is similar to the second method discussed above.
  • An internal pseudo-random noise generator as shown in Figure 5 is used to replace the external white noise test signal, and the hearing aid processing block is disconnected.
  • This method has two advantages over the second method discussed above: (1) the adaptation interference introduced by the external test signal is removed by using an internal pseudo-random noise generator; and (2) the hearing aid is operated in an open-loop configuration during the measurement.
  • the hearing aid gain can be set as high as possible without instability problems.
  • This method requires adding a noise generator and some control logic to the hearing aid.
  • the open loop transfer function measurement is only required during the initial fitting process.
  • FIGS. 4 and 5 both illustrate a generic broadband adaptive feedback canceller.
  • a digital feedback cancellation signal is generated by passing the hearing aid digital output signal at point B to an ADF 30, which approximates the
  • the ADF 30 comprises an adjustable filter, which uses filter coefficients to generate a feedback cancellation signal.
  • a coefficient adaptation portion 34 adjusts the filter coefficients to approximate the feedback path.
  • various adaptive filtering methods which have different filtering structures and different adaptation algorithms. Some of them exhibit extremely good convergence behavior and accuracy, but require extensive computation.
  • the family of Least-Squares (LS) algorithms belongs to this category.
  • the simple Stochastic-Gradient (SG) algorithms are sufficient to provide acceptable performance.
  • the simplicity of the adaptive filtering algorithm is a very important factor for hearing aid applications since it is desirable to minimize the hardware requirements.
  • the signals coming from external sound sources are usually considered as an interference to the adaptation of the adaptive filter.
  • An external input signal normally introduces bias to the optimal solution for the adaptive filter. The bias varies when the external input signal's property changes.
  • the external input signal also causes misadjustment noise during the adaptation process.
  • the convergence speed of the adaptive filter is governed by the adaptation step-size, which is inversely proportional to the combined signal power of e( ⁇ ) and x(n). Reducing the combined signal power would lead to a larger adaptation step-size, which in return increases the convergence speed. Since we are removing the components that are irrelevant to the oscillation problems from the adaptation signals, the combined signal power of e( ) and x(n) is reduced so that a larger adaptation step-size may be used to increase the convergence speed. With a higher convergence speed, the feedback canceller can better track the dynamic feedback path and the sudden gain change of AGC due to a sharp transition of input signal.
  • the periodicity in the external input signal would cause the cancellation of original signal (external input signal)at the hearing aid output.
  • the periodicity in the adaptation signals which originates from the external input signal, can be reduced. Therefore, the problem of canceling the original input signal at the hearing aid output will be relieved.
  • the adaptive filter always functions better at frequencies where large energy exists.
  • the adaptive feedback canceller actively works at oscillation frequencies only when the energy of the oscillation components existing in the adaptive filter input signal and the error signal is comparable or greater than the peak energy of the spectrum of external input signal.
  • the magnitudes of the frequency components at unstable feedback frequencies are build up and then suppressed, up and down, around the levels of the external input spectral peaks. This is so-called modulation effect of residual oscillation components.
  • the peak spectral level is much reduced. Therefore, the magnitudes of the residual oscillation components are also significantly reduced.
  • This concept of removing unnecessary frequency components from the adaptation signals is extremely important and beneficial when the external input signal is a speech signal.
  • speech contains most of its energy and periodicity at the low frequencies, at which unstable feedback is unlikely to occur. Therefore, the low frequency components of speech are considered unnecessary for the adaptive filtering and can be easily removed by applying a highpass (or bandpass) filter to the adaptation signals.
  • the cutoff frequency of the highpass filter is normally set at 200 Hz below the lowest unstable feedback frequency.
  • the current invention configures the adaptive feedback canceller in such a way that it limits the bandwidth of adaptation signals to the frequency regions known to contain the oscillation frequencies. By doing so, the adaptive feedback canceller adapts very quickly in the oscillation frequency regions with much less adaptation noise and adapts very slowly in other regions. As a result, the feedback cancellation signal generated by the ADF is also limited to the same frequency regions. Therefore, unlike the broadband scheme, the band-limited feedback canceller produces less distortion, and hence the output sound quality is much improved.
  • FIG. 6 shows one possible structure to implement the band-limited adaptive feedback canceller.
  • BPFl and BPF2 are bandpass filters, which only pass the frequency region containing all the unstable feedback frequencies. BPFl and BPF2 remove most of the unnecessary frequency components from e(n) and x( ) to improve the adaptation process.
  • the hearing aid input signal is filtered by BPF2 and then used as the desired signal for the adaptive filtering so that the adaptive filter only generates the cancellation signal in the passband of BPF2.
  • the filter length of BPF2 may increase the number of oscillation frequencies and shift the oscillation frequency to a lower frequency, the filter length of BPF2 must be minimized.
  • the delay introduced by the filter BPFl must not be too long or the cancellation signal generated by the adaptive filter may lag behind the feedback signal.
  • the group delays introduced by each block must meet the following condition:
  • the optimal delay ⁇ i in samples can be determined based on the measurement of
  • the delay caused by the adaptive filter should be minimized.
  • ⁇ j ram ⁇ D feedhackpalh ⁇ f) + BPF2 ( ) - D BPFX ⁇ f) ⁇ f
  • the output of the ADF is calculated one sample at time.
  • the coefficients of the ADF are updated with a modified Normalized LMS algorithm.
  • the adaptation step-size is reduced when the signal level is high and vice versa.
  • the input signal of the ADF is delayed by
  • e(n) is included for calculating the time-varying step-size as follows:
  • the adaptation signals e(n) and x(n) only contain the frequency components in the oscillation frequency regions.
  • FIG 7 shows another possible structure for implementing an adaptive band-limited feedback canceller.
  • BPFl is mainly used to limit the bandwidth of the cancellation signal and to limit cancellation artifacts to the cancellation bandwidth.
  • BPF2 and BPF3 are used to limit the bandwidth of the adaptation signals to the oscillation frequency regions.
  • BPFl, BPF2 and BPF3 are not necessarily implemented as linear-phase FIR filters, but their passbands must cover all the oscillation frequencies.
  • the filtered adaptation signal samples are used for updating the time- varying step-size and ADF coefficients as follows:
  • x' (n) is the output of the bandpass filter BPF3; and e' (n) is the output of the bandpass filter BPF2.
  • the phase responses of BPF2 and BPF3 must be as close as possible.
  • the passband ripples of BPFl, BPF2, and BPF3 are not critical for good performance as long as the stopband attenuation is sufficient. In our experience, 30 dB stopband attenuation is adequate. Therefore, low-order IIR filters such as 2 nd or 3 rd order Elliptic IIR filters may be used for this application to reduce the hardware and computation complexity.
  • the optimal delay ⁇ j in samples can be obtained in the measurement of the
  • the delay caused by the adaptive filter should be minimized.
  • the delay ⁇ j must meet the following condition: Z ⁇ , (f ) ⁇ D ⁇ Ac(f)+ D comlic feedback pat (f)+ DAOC(/ )— DBPFI( )
  • This band-limited feedback cancellation structure does not introduce any additional delay in the primary signal path and does not introduce additional phase distortion to the hearing aid output.
  • the purpose of the ADF is to estimate the feedback path.
  • BPFl is used to limit the bandwidth of the feedback cancellation signal. Because the frequency response of the feedback path has band-pass characteristics as generally shown in Figure 21, we may use BPFl to approximately match the frequency response of the feedback path. In this way, the ADF can be used mainly to track the variation of the feedback path.
  • the band-limited adaptive feedback canceller can be implemented on a platform with either a general-purpose digital signal processor or a specialized digital signal processor. Due to the size and power constraints of hearing aid circuit design, it is desirable to utilize a fixed-point digital signal processor with limited precision and word length as the adaptive feedback canceller. Thus, the efficient digital realization of the band-limited adaptive feedback canceller is extremely critical for the performance of the feedback cancellation under the constraint of limited hardware and computational resources.
  • the present invention simplifies the computational requirements and addresses issues associated with the limited-precision effects on the adaptation process.
  • the generalized structure contains an adjustable FIR filtering module, a power estimation module, a coefficient adaptation module, a DC removing module, a coefficient bandpass filtering (CBF) module and a control unit.
  • adjustable FIR filtering module a power estimation module
  • coefficient adaptation module a coefficient adaptation module
  • DC removing module a coefficient bandpass filtering (CBF) module
  • control unit a control unit
  • the adaptive FIR filter is used to approximate the dynamic feedback path and generate a feedback cancellation signal by convolving the input signal x ⁇ (n)
  • the scaling gain G is selected as a power-of-two number 2 and can be implemented by left/right shifting. Normally, it is sufficient for L to be in the range [-3, 3], which provides a dynamic range from -18 dB to 18 dB.
  • Figure 20 shows a functional block diagram of adjustable FIR filtering with a power-of-two scaling gain.
  • Equation 10 is the power estimation of the combined signal e(n) and ( «).
  • T is a positive integer to control the adaptation speed.
  • the range of K is typically from 7 to 10. The smaller value of K provides faster adaptation speed.
  • J is a positive integer to control the time-constant of power estimation. Typically, we choose 6 for J.
  • L is an integer to control the ADF scaling gain. As stated above, the range is from -3 to +3. L is determined based on the feedback measurement during the hearing aid fitting process so that the filter coefficients of adaptive filter are maximized.
  • Q[ ] is a truncation operation.
  • Q[log 2 (p(n))] can be implemented by searching the position index of the most significant bit (MSB) ofp(n).
  • Figure 8 shows a functional block diagram of base-2 logarithm
  • ⁇ is a positive quantity represented in an unsigned binary integer
  • Equation 22 shows that only one multiplication is required for the power estimation.
  • the coefficient adaptation process shown in Equation 23 becomes a multiplication- free process and can be implemented with shifting, negation and addition operations.
  • Figure 10 shows the functional block diagram for power estimation
  • Figure 11 shows the functional block diagram for a multiplication-free coefficient adaptation process in which:
  • ⁇ (n) is the base-2 logarithm quantization of the error signal e(n);
  • ⁇ (n) is the base-2 logarithm quantization of the power estimation p(n);
  • v (n) is the sign of the error signal e(n).
  • Equation 23 may be rewritten as:
  • w k (n + ⁇ ) w k [n) + ⁇ sign(e(n) - x 2 (n - k)), for O ⁇ k ⁇ M - 1
  • ⁇ is a constant. For example, we may choose ⁇ equal to 1 when w k (n) is represented with a 12-bit integer. By doing so, the computations associated with power estimation, MSB search, and shifting that are required for the Normalized LMS are eliminated.
  • both the inputs and internal algorithmic quantities must be quantized to a certain limited precision. These quantization errors may accumulate without bound until overflow occurs, resulting in unacceptable performance. For example, a slight DC offset in e( ⁇ ) and x 2 (n), which results from either the original ADC output or the
  • a DC removing module is included to periodically remove the DC offset from the adaptive filter coefficient.
  • Another bandpass filtering module is provided to filter the adaptive filter coefficients in order to suppress the low frequency and high frequency response build-up in the adaptive filter response. This operation is only needed when the filter coefficient is saturated. In the DC removing module, the following operation is implemented to estimate the DC offset in the filter coefficient and subtract the estimated DC offset from the ADF filter coefficients:
  • Figure 12 illustrates the computational process for DC removal.
  • the DC removal may be scheduled every 256 samples at 16000 Hz sampling rate.
  • a zero-delay bandpass filtering operation on the ADF coefficients is performed as follows:
  • Figure 13 illustrates the computational process for bandpass filtering.
  • This simple bandpass filtering operation doesn't offer a perfectly flat 0 dB magnitude response across the passband, and may introduce minor audible distortion at the hearing aid output. It cannot be applied frequently and is only triggered when any one of the ADF coefficients is saturated.
  • the adaptive filter coefficient adaptation must be performed in company with DC removing and coefficient bandpass filtering operations. Since the DC removing and coefficient bandpass filtering operations don't need to be performed frequently, we schedule only one of these three operations to be performed at each sample period.
  • Figure 14 is a flow chart of the scheduling process. In this way, the DC removing operation is performed periodically, and the coefficient bandpass filtering operation is triggered only when the SAT signal from the coefficient adaptation module is on.
  • Figure 15 is a logical diagram of the control unit, which generates the control signals for the coefficient adaptation module, the DC removal module, and the coefficient bandpass filtering module.
  • the first test of this invention was performed with a computer simulation.
  • the simulation model was developed in SIMULINK and built with a dynamic feedback path.
  • the dynamic feedback path was measured on a KEMAR ear with a clipboard slowly moving toward and away from the ear.
  • Various hearing aid responses for human subjects were used as hearing aid processing for the simulation.
  • the hearing aid response and the dynamic feedback path were used to derive the open loop transfer function and identify the unstable feedback frequencies.
  • the unstable feedback frequencies were used to configure the feedback canceller, specifically the bandwidth of the band-limiting filters.
  • the tests were made with and without the band-limited adaptive feedback canceller.
  • the maximum stable hearing aid gain was recorded under both conditions.
  • the simulated hearing aid outputs were also used for subjective evaluation.
  • the same tests were performed on human subjects with a real-time prototype digital hearing aid.
  • the open loop transfer function of the hearing aid was determined based on closed loop probe tube measurement.
  • the unstable feedback frequencies were identified from the open loop transfer function and used to configure the band-limited adaptive feedback canceller.
  • the maximum stable insertion gains were recorded with and without the adaptive canceller.
  • Figure 21 shows an example of open loop transfer function measured on KEMAR ear.

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  • Neurosurgery (AREA)
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Abstract

L'invention concerne un procédé amélioré pour supprimer de manière adaptative l'effet Larsen dans les prothèses auditives et dans d'autres dispositifs audio amplifiés. La suppression de l'effet Larsen est limitée à la bande de fréquences qui englobe toutes les fréquences instables. En limitant la bande de fréquences du signal d'annulation de l'effet Larsen, on arrive à réduire au minimum la distorsion provoquée par le filtre adaptatif, qui est limitée uniquement aux zones instables de l'effet Larsen. On utilise un algorithme relativement simple de traitement des signaux pour obtenir des résultats probants, et ce avec une distorsion minimale des signaux.
PCT/US1999/022757 1998-09-30 1999-09-30 Dispositif adaptatif de suppression de l'effet larsen a bande limitee destine aux protheses auditives WO2000019605A2 (fr)

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Application Number Priority Date Filing Date Title
JP2000572997A JP2002526961A (ja) 1998-09-30 1999-09-30 補聴器用の帯域限定適応帰還キャンセラ
EP99948516A EP1118247A2 (fr) 1998-09-30 1999-09-30 Dispositif adaptatif de suppression de l'effet larsen a bande limitee destine aux protheses auditives
AU61680/99A AU6168099A (en) 1998-09-30 1999-09-30 Band-limited adaptive feedback canceller for hearing aids

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US10255798P 1998-09-30 1998-09-30
US60/102,557 1998-09-30

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WO2000019605A2 true WO2000019605A2 (fr) 2000-04-06
WO2000019605A3 WO2000019605A3 (fr) 2000-07-06

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US7324651B2 (en) 2004-03-15 2008-01-29 Phonak Ag Feedback suppression
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US7778426B2 (en) 2003-08-20 2010-08-17 Phonak Ag Feedback suppression in sound signal processing using frequency translation
EP2227915A1 (fr) * 2007-12-07 2010-09-15 Dynamic Hearing Pty Ltd Annulation de retour à résistance d'entraînement
US8351626B2 (en) 2004-04-01 2013-01-08 Phonak Ag Audio amplification apparatus
WO2021207134A1 (fr) * 2020-04-09 2021-10-14 Starkey Laboratories, Inc. Dispositif auditif avec détecteur d'instabilité de rétroaction qui change un filtre adaptatif
EP4117306A1 (fr) * 2021-07-05 2023-01-11 Austrian Audio GmbH Procédé électro-acoustique utilisant un algorithme lms

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JP4492409B2 (ja) * 2005-03-29 2010-06-30 ヤマハ株式会社 ハウリングキャンセラ
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EP1406469A2 (fr) 2002-09-30 2004-04-07 Siemens Audiologische Technik GmbH Compensateur de la rétroaction dans les systèmes d'amplification acoustique, prothèse auditive, procédé pour la compensation de la rétroaction et utilisation de ce procédé dans les prothèses auditives
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US7778426B2 (en) 2003-08-20 2010-08-17 Phonak Ag Feedback suppression in sound signal processing using frequency translation
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WO2000019605A3 (fr) 2000-07-06

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