EP1154674B1 - Circuit et méthode pour la suppression adaptive du bruit - Google Patents

Circuit et méthode pour la suppression adaptive du bruit Download PDF

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Publication number
EP1154674B1
EP1154674B1 EP01810057A EP01810057A EP1154674B1 EP 1154674 B1 EP1154674 B1 EP 1154674B1 EP 01810057 A EP01810057 A EP 01810057A EP 01810057 A EP01810057 A EP 01810057A EP 1154674 B1 EP1154674 B1 EP 1154674B1
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sub
signals
output signals
input signals
cross
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German (de)
English (en)
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EP1154674A2 (fr
EP1154674A3 (fr
Inventor
Remo Leber
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Bernafon AG
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Bernafon AG
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    • 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
    • H04R25/50—Customised settings for obtaining desired overall acoustical characteristics
    • H04R25/505—Customised settings for obtaining desired overall acoustical characteristics using digital signal processing

Definitions

  • the present invention relates to a circuit and a method for adaptive noise cancellation according to the preambles of the independent claims. It is used, for example, in digital hearing aids.
  • the sound human hearing system makes it possible to focus on a conversation partner during a conversation in a noise situation disturbed by noise.
  • Many hearing aid wearers suffer from greatly reduced speech intelligibility as soon as noise is present in addition to the desired speech signal.
  • noise cancellation techniques have been proposed. They can be subdivided into single-channel methods which require only one input signal, and multi-channel methods which use the spatial information in the acoustic signal by means of several acoustic inputs.
  • the multi-channel noise suppression methods it is assumed that the acoustic source from which the useful signal is emitted is in front of the listener while the background noise is incident from other directions. This simple assumption proves itself in practice and meets the supportive lip reading.
  • the multi-channel methods can be subdivided further into fixed systems which have a fixed predetermined directional characteristic, and adaptive systems which adapt to the current sound situation.
  • the fixed systems operate either using directional microphones which have two acoustic inputs and provide an input direction-dependent output signal, or using a plurality of microphones whose signals are electrically processed. Manual switching may allow a choice between different directional characteristics. Such systems are available on the market and are increasingly being installed in hearing aids.
  • an optimal convergence behavior with minimal, inaudible distortions and without additional signal delay should be achieved with the least possible effort.
  • the present invention belongs to the group of systems for blind signal separation by means of second order methods, i. H. with the aim of achieving uncorrelated output signals.
  • two microphone signals are separated by means of blind signal separation into useful signal and interference signals.
  • a consistent output behavior can be achieved if the signal-to-noise ratio of a first microphone is always greater than that of a second microphone. This can be achieved either in that the first microphone is placed closer to the user source than the second microphone or in that the first microphone, in contrast to the second microphone has a directional characteristic oriented to the useful source.
  • the calculation of the decorrelated output signals takes place while minimizing a quadratic cost function consisting of cross-correlation terms.
  • a special stochastic gradient method is derived in which expected values of cross correlations are replaced by their instantaneous values become. This results in a fast-reacting and computationally efficient updating of the filter coefficients.
  • signal-dependent transformed versions of the input and output signals are used for the updating of the filter coefficients.
  • the transformation by means of cross-member filters performs a spectral smoothing, so that the signal powers are distributed more or less evenly over the frequency spectrum.
  • all the spectral components are uniformly weighted independently of the currently existing power distribution. This also allows distortion-free processing for real acoustic signals with non-negligible autocorrelation functions while at the same time satisfying convergence behavior.
  • the microphone inputs can be matched with compensation filters.
  • a uniform standard size is used for the updating of all filter coefficients. It is calculated in such a way that only one of the two filters is adapted at maximum speed, depending on whether currently the user signal or interference signals are dominant. This procedure allows correct convergence even in the singular case, where only useful signal or only interference signals are present.
  • the present invention differs significantly from all previously published systems for noise suppression, in particular by the special stochastic gradient method, the transformation of the signals for the updating of the filter coefficients and the interaction of compensation filter and normalization unit in the control of the adaptation speed.
  • the inventive system in a very large range of signal-to-noise ratios on a consistent behavior, ie the signal-to-noise ratio is always improved and never worsened. It can thus optimally contribute to better communication in difficult sound situations.
  • FIG. 1 A general system for adaptive noise cancellation by the method of blind signal separation, as known from the prior art, is known in FIG. 1 shown.
  • Two microphones 1 and 2 provide the electrical signals d 1 (t) and d 2 (t).
  • the following AD converters 3 and 4 determine therefrom digital signals at the discrete times d 1 (n * T) and d 2 (n * T), in abbreviated notation d 1 (n) and d 2 (n) or d 1 and d 2 .
  • T 1 / f s is the sampling period
  • f s is the sampling frequency
  • n is a continuous index.
  • compensation filters 5 and 6 which can make a fixed frequency response correction on the individual microphone signals depending on the application.
  • the resulting input signals y 1 and y 2 are now according to the FIG. 1 led to delay elements 7 and 8 as well as to filters 17 and 18.
  • Subsequent subtractors 9 and 10 provide output signals s 1 and s 2 .
  • processing units 11 and 12 which make any desired linear or non-linear post-processing depending on the application.
  • Their output signals u 1 and u 2 can be converted into electrical signals u 1 (t) and u 2 (t) via DA converters 13 and 14 and made audible by means of loudspeakers or earphones 15 and 16.
  • the aim of blind signal separation is to be obtained, starting from the input signals y 1 and y 2 and by means of the filters 17 and 18, statistically possible independent output signals s 1 and s 2.
  • the requirement of uncorrelated output signals s 1 and s 2 is sufficient.
  • the optimal filter coefficients w 1 and w 2 in the filters 17 and 18 we will minimize a cost function.
  • the operator * stands for complex conjugate in applications where we deal with complex-valued signals.
  • the cross-correlation terms can be expressed with the aid of the output signals s 1 and s 2 .
  • the operator E [] stands for the expected value.
  • R s 1 ⁇ s 2 l e ⁇ s 1 * n ⁇ s 2 ⁇ n + l
  • the output signals s 1 and s 2 can be expressed by the input signals y 1 and y 2 and by means of the filter coefficients w 1 and w 2 .
  • w 1k denote the elements of the vector w 1
  • w 2k denote the elements of the vector w 2 .
  • the adaptive noise suppression system described so far by means of the blind signal separation method does not yet suffice because of the non-negligible autocorrelation function of real acoustic signals in order to achieve distortion-free processing with realistic convergence behavior in a realistic environment.
  • the system can be improved if the updating of the filter coefficients w 1 and w 2 is not based directly on the input signals y 1 and y 2 and the output signals s 1 and s 2 , but on transformed signals.
  • the inventive system according to FIG. 2 uses four cross-link filters 19, 20, 21 and 22 for signal-dependent transformation of the input and output signals.
  • the cross-talk filter structures known from speech signal processing prove to be particularly suitable. They are used there for linear prediction.
  • the coefficients k of the cross-sectional filters there are two cross-divisor decorrelators 31 and 32 and a smoothing unit 33.
  • the cross-member decorrelators each determine a coefficient vector k 1 and k 2 based on the input signals y 1 and y 2 .
  • the smoothing unit the two coefficient vectors are averaged and temporally smoothed as the coefficient vector k passed to the cross-member filter.
  • a normalization variable p common to the updating of the filter coefficients w 1 and w 2 is calculated.
  • the optimum choice of the standardization quantity p together with the correct setting of the compensation filters 5 and 6 ensure a clean and unambiguous convergence behavior of the method according to the invention.
  • the compensation filters 5 and 6 are according to FIG. 3 and the following relationships apply.
  • the structure corresponds to a general recursive filter of order K.
  • the coefficients b 1k , a 1k , b 2k and a 2k are set so that the average frequency response of one input equals the other input. It is preferably averaged over all possible locations of acoustic signal sources or over all possible directions of incidence.
  • the delay elements 7 and 8 are according to FIG. 4 and the following relationships apply.
  • the necessary delay times D 1 and D 2 depend, above all, on the distance between the two microphones and the preferred sound incidence direction. Small delay times are desirable because it also reduces the overall delay time of the system.
  • f 1 () and f 2 () represent any linear or nonlinear functions of their arguments. They result from the usual hearing aid-specific processing.
  • u 1 n f 1 ⁇ s 1 ( n ) . s 1 ( n - 1 ) . s 1 ( n - 2 ) .
  • u 1 n f 1 ⁇ s 1 ( n ) . s 1 ( n - 1 ) . s 1 ( n - 2 ) . ... ...
  • the filters 17 and 18 are according to FIG. 5 and the following relationships apply.
  • the filter orders N 1 and N 2 result from a compromise between recoverable effect and the computational effort.
  • the cross-member filters 19, 20, 21 and 22 are according to FIG. 6 and the following relationships apply.
  • the filter order M can be chosen quite small.
  • the cross correlators 23 and 24 are according to FIG. 7 and the following relationships apply.
  • the constants g and h which determine the time behavior of the averaged cross-correlations, should be matched to the filter orders N 1 and N 2 .
  • the constants L 1 and L 2 determine how many cross-correlation terms are taken into account in the following calculations.
  • the pre-calculation units of type V 25 and 26 are according to FIG. 8 and the following relationships apply.
  • the normalization was chosen so that the intermediate quantities v 1 and v 2 are dimensionless.
  • the precalculation units of type B 27 and 28 are according to FIG. 9 and the following relationships apply.
  • the standardization was chosen so that the intermediate quantities b 1 and b 2 are dimensionless.
  • the updating units 29 and 30 are according to FIG. 10 and the following relationships apply.
  • the adaptation speed ⁇ can be selected according to the desired convergence behavior.
  • w 1 ⁇ k ⁇ n + 1 w 1 ⁇ k n + ⁇ p n ⁇ v 1 n ⁇ s 2 ⁇ M ( n - k ) + b 1 ( n - k ) ⁇ s 1 ⁇ M n ⁇ 0 ⁇ k ⁇ N 1
  • w 2 ⁇ k ⁇ n + 1 w 2 ⁇ k n + ⁇ p n ⁇ v 2 n ⁇ s 1 ⁇ M ( n - k ) + b 2 ( n - k ) ⁇ s 2 ⁇ M n ⁇ 0 ⁇ k ⁇ N 2
  • the cross-member decorrelators 31 and 32 are according to FIG. 11 and the following relationships apply.
  • the crossbar decorrelators compute the coefficient vectors k 1 and k 2 required for a decorrelation of their input signals.
  • the smoothing unit 33 is according to FIG. 12 and the following relationships apply.
  • the constants f and l are chosen such that the averaged coefficients k get the desired smoothed course.
  • the normalization unit 34 is according to FIG. 13 and the following relationships apply. First, the four powers of y 1M , y 2M , s 1M and s 2M are calculated, and from this the normalization quantity p is determined.
  • the preferred embodiment can be easily programmed on a commercial signal processor or implemented in an integrated circuit. All variables must be suitably quantized and the operations optimized to the existing architecture blocks. Special attention is given to the treatment of the quadratic quantities (powers) and the division operations. Depending on the target system, there are optimized procedures for this. However, these are not in and of themselves subject of the present invention.

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  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Neurosurgery (AREA)
  • Otolaryngology (AREA)
  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Acoustics & Sound (AREA)
  • Signal Processing (AREA)
  • Filters That Use Time-Delay Elements (AREA)
  • Circuit For Audible Band Transducer (AREA)
  • Noise Elimination (AREA)
  • Soundproofing, Sound Blocking, And Sound Damping (AREA)

Claims (11)

  1. Circuit de calcul de deux signaux numériques de sortie (s1, s2) décorrélés à partir de deux signaux numériques d'entrée (y1, Y2) corrélés, lequel circuit contient deux filtres (17, 18) disposés symétriquement en croix dans la direction avant et dotés de coefficients adaptatifs de filtrage (w 1, w 2), deux éléments de retardement (7, 8) et deux soustracteurs (9, 10) qui calculent les signaux de sortie (s1, s2) dans la plage temporelle à partir des signaux d'entrée (y1, y2) en minimisant une fonction quadratique de coût constituée de termes de corrélation croisés,
    caractérisé en ce que
    le circuit contient quatre filtres (19 à 22) à éléments croisés qui transforment les signaux d'entrée en les signaux de sortie (y1, y2; s1, s2) en fonction du signal et en ce que
    toutes les unités de calcul sont raccordées en aval des filtres (19 à 22) à éléments croisés pour assurer la mise à jour des coefficients de filtre (w 1, w 2).
  2. Circuit selon la revendication 1, caractérisé par deux corrélateurs croisés (23, 24), quatre unités de pré-calcul (25 à 28) et deux unités de mise à jour (29, 30) qui mettent à jour les coefficients de filtre ((w 1, w 2) en réaction rapide et à haut rendement de calcul.
  3. Circuit selon les revendications 1 ou 2, caractérisé par deux décorrélateurs (31, 32) à éléments croisés qui suivent les statistiques des deux signaux d'entrée (y1, y2) et par une unité de lissage (33) qui calcule la moyenne lissée (k) des coefficients des filtres (19 à 22) à éléments croisés.
  4. Circuit selon l'une des revendications 1 à 3, caractérisé par une unité de normalisation (34) qui calcule une grandeur optimale de normalisation (p) pour la mise à jour des coefficients de filtre (w 1, w 2).
  5. Dispositif de diminution adaptative du bruit de signaux acoustiques d'entrée, qui contient deux microphones (1, 2) et deux convertisseurs analogiques-numériques (3, 4) qui convertissent les signaux acoustiques d'entrée en deux signaux numériques d'entrée (y1, y2), un circuit de traitement de signaux numériques d'entrée (y1, y2) en signaux numériques de sortie (s1, s2), au moins un convertisseur numérique-analogique (13, 14) et au moins un haut parleur ou écouteur (15, 16) qui convertit les signaux numériques de sortie (s1, s2) en signaux acoustiques de sortie,
    caractérisé en ce que
    le circuit de traitement des signaux numériques d'entrée (y1, y2) en signaux numériques de sortie (s1, s2) est un circuit selon l'une des revendications 1 à 4.
  6. Dispositif selon la revendication 5, caractérisé par au moins un filtre de compensation (5, 6) qui accorde la plage centrale de fréquence d'un microphone (1) à la plage centrale de fréquence de l'autre microphone (2).
  7. Procédé de calcul de deux signaux numériques de sortie (s1, s2) décorrélés à partir de deux signaux numériques d'entrée (y1, y2) corrélés, lequel procédé est exécuté au moyen d'un circuit selon l'une des revendications 1 à 4 et dans lequel au moyen de deux filtres (17, 18) disposés symétriquement en croix dans la direction avant et dotés des coefficients adaptatifs de filtre (w 1, w 2), de deux éléments de retardement (7, 8) et de deux soustracteurs (9, 10), les signaux de sortie (s1, s2) décorrélés sont déterminés dans la plage temporelle à partir des signaux d'entrée (y1, y2) en minimisant une fonction quadratique de coût constituée de termes de corrélation croisés,
    caractérisé en ce que
    au moyen de quatre filtres (19 à 22) à éléments croisés, on entreprend une transformation des signaux d'entrée et de sortie (y1, y2; s1, s2) en fonction des signaux et en ce que pour la mise à jour des coefficients de filtre (w 1, w 2), on n'utilise que les signaux transformés (y1M, y2M; s1M, s2M).
  8. Procédé selon la revendication 7, caractérisé en ce que deux décorrélateurs (31, 32) à éléments croisés suivent la statistique des deux signaux d'entrée (y1, y2) et en ce qu'une unité de lissage (33) calcule la moyenne lissée (k) des coefficients des filtres (19 à 22) à éléments croisés.
  9. Procédé selon les revendications 7 ou 8, caractérisé en ce que dans une unité de normalisation (34), on calcule une grandeur optimale de normalisation (p) pour la mise à jour des coefficients de filtre (w 1, w 2).
  10. Procédé de diminution adaptative du bruit de signaux acoustiques d'entrée, dans lequel les signaux acoustiques d'entrée sont convertis en signaux numériques d'entrée (y1, y2), les signaux numériques d'entrée (y1, y2) sont transformés en signaux numériques de sortie (s1, s2) et les signaux numériques de sortie (s1, s2) sont convertis en signaux acoustiques de sortie,
    caractérisé en ce que
    pour transformer les signaux numériques d'entrée (y1, y2) en signaux numériques de sortie (s1, s2), on applique un procédé selon l'une des revendications 7 à 9.
  11. Procédé selon la revendication 10, caractérisé en ce que pour convertir les signaux acoustiques d'entrée, on utilise deux microphones (1, 2) et en ce que la plage centrale de fréquence d'un microphone (1) est accordée à la plage centrale de fréquence de l'autre microphone (2) au moyen d'au moins un filtre de compensation (5, 6).
EP01810057A 2000-02-02 2001-01-22 Circuit et méthode pour la suppression adaptive du bruit Expired - Lifetime EP1154674B1 (fr)

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EP1154674A3 EP1154674A3 (fr) 2007-03-21
EP1154674B1 true EP1154674B1 (fr) 2008-12-10

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US (1) US6928171B2 (fr)
EP (1) EP1154674B1 (fr)
AT (1) ATE417483T1 (fr)
AU (1) AU778351B2 (fr)
CA (1) CA2332092C (fr)
DE (1) DE50114557D1 (fr)
DK (1) DK1154674T3 (fr)

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US6978159B2 (en) * 1996-06-19 2005-12-20 Board Of Trustees Of The University Of Illinois Binaural signal processing using multiple acoustic sensors and digital filtering
AU2001261344A1 (en) * 2000-05-10 2001-11-20 The Board Of Trustees Of The University Of Illinois Interference suppression techniques
US6907017B2 (en) * 2000-05-22 2005-06-14 The Regents Of The University Of California Mobility management in wireless internet protocol networks
EP1413169A1 (fr) * 2001-08-01 2004-04-28 Dashen Fan Faisceau cardioide avec dispositifs acoustiques fondes sur le nul, systemes et procedes correspondants
US7209566B2 (en) * 2001-09-25 2007-04-24 Intel Corporation Method and apparatus for determining a nonlinear response function for a loudspeaker
US7542580B2 (en) * 2005-02-25 2009-06-02 Starkey Laboratories, Inc. Microphone placement in hearing assistance devices to provide controlled directivity
US20060211910A1 (en) * 2005-03-18 2006-09-21 Patrik Westerkull Microphone system for bone anchored bone conduction hearing aids
CN100336307C (zh) * 2005-04-28 2007-09-05 北京航空航天大学 接收机射频系统电路内部噪声的分配方法
DE102006003977A1 (de) * 2006-01-27 2007-08-09 Krauss-Maffei Wegmann Gmbh & Co. Kg Verfahren und Vorrichtung zur Übersteuerung bei einem Fahrzeug im Fahrschulbetrieb
US20110058676A1 (en) * 2009-09-07 2011-03-10 Qualcomm Incorporated Systems, methods, apparatus, and computer-readable media for dereverberation of multichannel signal
WO2014198332A1 (fr) * 2013-06-14 2014-12-18 Widex A/S Procede de traitement de signal dans un systeme d'aide auditive et systeme d'aide auditive

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EP0930801B1 (fr) * 1998-01-14 2008-11-05 Bernafon AG Circuit et procédé pour la suppression adaptative de la réaction acoustique
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CA2332092C (fr) 2008-09-30
CA2332092A1 (fr) 2001-08-02
EP1154674A2 (fr) 2001-11-14
US20010036284A1 (en) 2001-11-01
AU1666901A (en) 2001-08-09
ATE417483T1 (de) 2008-12-15
DE50114557D1 (de) 2009-01-22
US6928171B2 (en) 2005-08-09
DK1154674T3 (da) 2009-04-06
AU778351B2 (en) 2004-12-02
EP1154674A3 (fr) 2007-03-21

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