EP2080197B1 - Dispositif d'élimination du bruit dans un signal audio - Google Patents

Dispositif d'élimination du bruit dans un signal audio Download PDF

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Publication number
EP2080197B1
EP2080197B1 EP07800169A EP07800169A EP2080197B1 EP 2080197 B1 EP2080197 B1 EP 2080197B1 EP 07800169 A EP07800169 A EP 07800169A EP 07800169 A EP07800169 A EP 07800169A EP 2080197 B1 EP2080197 B1 EP 2080197B1
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Prior art keywords
noise
filter
error
signal
kbe
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EP07800169A
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German (de)
English (en)
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EP2080197A1 (fr
Inventor
Erhard Rank
Gernot Kubin
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Forschungsholding TU Graz GmbH
Technische Universitaet Graz
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Forschungsholding TU Graz GmbH
Technische Universitaet Graz
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    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
    • G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
    • G10L21/0208—Noise filtering
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
    • G10L25/03—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters
    • G10L25/12—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters the extracted parameters being prediction coefficients

Definitions

  • the invention relates to a device according to the preamble of the main claim.
  • noise suppression in audio signals is becoming increasingly important, such as in the telephony, the automatic speech recognition or, as just one of many other examples, in digital hearing aids.
  • Sounds to be suppressed are primarily non-white noise, nonstationary sounds, and strong impulsive noises.
  • Noise suppression methods for audio signals have become known in a wide variety, and examples include: methods in which quiet audio signals are first raised and later lowered again, such as pre / de-emphasis for broadcasting or Dolby noise suppression processes for sound recordings. Further, spectral subtraction method in which e.g. in pauses in the conversation the noise is estimated and then subtracted from the input signal. The latter methods also include Wiener filters as well as Ephraim-Malah filters with adaptive amplification for signals split into several transformation channels.
  • the known methods are in part not very effective because they emanate from a very simplified model of the noise signal, or they result due to a block-wise processing of the input signal to artifacts, which are noticeable as unpleasant noise, as so-called Musical Tones, in the Signal remain after noise reduction. Many methods also result in a relatively large delay in the output signal.
  • a corresponding device such as in the US 2001/0005822 A1 discloses, consists of a lattice filter, which is supplied with an input signal y (n) having a voice / audio component and a noise component.
  • a coefficient calculation unit KBE is provided, which feeds the forward and reverse error signals, which in the first stage also contain the input signal. The coefficient calculation unit then always updates the filter to minimize the prediction error Filter coefficients.
  • a noise reduction using linear prediction filters is among others in the GB 1 520 148 A or in the US 4, 587, 620 disclosed.
  • the prior art methods always proceed from the input signal without sufficient consideration being given to the particular characteristics of the speech signal on the one hand and the noise on the other hand.
  • the input signal is used to determine the coefficients for the prediction filter (units 212 and 312 and 318, respectively), and then an estimation of the speech signal is made on the basis of these coefficients, an estimate using an additional speech activity estimation unit (VAD, units 232 and 332, respectively) of the noise signal, namely in a unit 234 or 334 thereto, by means of a further second filter (unit 240 or 340) to perform a noise suppression.
  • VAD additional speech activity estimation unit
  • the essential features are that the estimation of the coefficients of the linear prediction filter (unit 214) and of the linear prediction filters (units 314 and 320 in FIG Fig. 3 ) is made only by using the input signal (or the error signal of the first prediction filter e ST (n) (path 316)).
  • Another significant difference from the invention is that a speech activity estimation is performed independently of the linear prediction filter 214 from the linear prediction filters 314 and 320, and that the actual noise suppression filter (units 240 and 340) themselves is not a linear prediction filter.
  • the noise estimation (“Update Noise Model”) takes place only on the basis of the prediction error (cf. US Pat. No. 7,065,468 ), whereas, as described below, in the invention, the noise estimation is performed based on the internal signals of the LP error filter. This difference is also on hand Fig. 2 of the US Pat. No. 7,065,468 seen.
  • An object of the invention is to provide a device for noise cancellation for audio signals, in particular for voice signals, which provides a virtually instantaneous output audio signal, which also carries no annoying artifacts with it.
  • Linear prediction is usually applied to a speech signal x ( n ), for example to reduce the variance of a speech signal for its transmission.
  • M is the order of the LP filter and b i ( n ) is the filter coefficients, which are estimated on the basis of the signal properties and refreshed frame by frame, eg every 10 ms.
  • Algorithms which directly give the coefficients bi (n) for the filter are the so-called “autocorrelation method” or the "covariance method”.
  • f m ( n ) and b m ( n ) denote the forward and backward errors in the stage m at time n and k m ( n ) the reflection coefficients of the filter.
  • Fig. 1 is a lattice filter as just described schematically shown.
  • claim 6 refers to such a filter.
  • q m n 1 2 ⁇ e f m 2 n + b m 2 ⁇ n - 1 ,
  • the expected value operators E in (6) and (7) are calculated using low-pass filtered instantaneous values of f m ( n ) b m ( n -1) and f m 2 n + b m 2 ⁇ n - 1 evaluated, for example by means of single-pole recursive low-pass filter ("lossy integration", lossy integration, see below).
  • y ( n ) x n + ⁇ n .
  • x ( n ) is the speech component
  • ⁇ ( n ) is an additive background noise component.
  • the object of the noise reduction is to provide a good estimate for the speech signal component x ( n ).
  • this estimation relies exclusively on the observation of the noisy signal y ( n ), ie no additional information is used, such as a second signal from a microphone which only picks up the background noise.
  • a reduction of the amount of reflection coefficients can be made by deriving estimators for r m and q m which minimize the mean square estimation error.
  • Fig. 2 The resulting error in the values of the reflection factors is in Fig. 2 shown. More specifically, values of the reflection coefficient k 1 calculated from the noisy signal without correction are illustrated as a function of an a priori signal / noise ratio for different values of the autocorrelation ⁇ xx (1) of the undisturbed signal x ( n ).
  • Equation (14) can be generalized, resulting in a correction of the other reflection coefficients k m .
  • the invention now provides a method and apparatus for obtaining a correction of the reflection factors based on simple assumptions about the change in the correlation and the power of the speech and noise signals over time.
  • the resulting lattice prediction filter becomes good at the speech signal component predict, whereas the noise component is suppressed.
  • the order M of the LP filter can be chosen to be surprisingly low, even lower than the order commonly used to model the spectral envelope of speech signals.
  • This example contains a repeated occurrence of strong, non-stationary noise bursts, which are well eliminated by the invention.
  • the noise shown comes from a factory hall environment, that is a very unfavorable acoustic environment.
  • the LP error filter may be formed as a filter in direct filter form (DFF), which generates from the input signal a prediction signal at its output, wherein a subtractor subtracts the prediction signal from the input signal and thus the output signal of the LP error filter e ( n ) generated.
  • DFF direct filter form
  • An important feature of the noise suppression according to the invention consists in the evaluation of the expectation operators adapted to the characteristics of the speech and the noise signal and thus the optimal adjustment of the filter coefficients for the linear prediction filter, as well as in the voice activity estimation and their use in the estimation of the noise signal, and for control the effectiveness of the noise cancellation and the amplitude of the output signal.
  • a significant advantage of the invention is that it allows a noise reduction without delay of the speech signal, which is a particular advantage, especially when used in hearing aids.

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  • Engineering & Computer Science (AREA)
  • Human Computer Interaction (AREA)
  • Acoustics & Sound (AREA)
  • Signal Processing (AREA)
  • Health & Medical Sciences (AREA)
  • Audiology, Speech & Language Pathology (AREA)
  • Computational Linguistics (AREA)
  • Physics & Mathematics (AREA)
  • Quality & Reliability (AREA)
  • Multimedia (AREA)
  • Filters That Use Time-Delay Elements (AREA)
  • Noise Elimination (AREA)
  • Transmission Systems Not Characterized By The Medium Used For Transmission (AREA)
  • Signal Processing Not Specific To The Method Of Recording And Reproducing (AREA)
  • Circuit For Audible Band Transducer (AREA)

Claims (6)

  1. Dispositif d'atténuation du bruit comprenant un circuit de prédiction et d'analyse linéaire avec un filtre d'erreur passe-bas (LFF) qui se compose d'un filtre lattice et qui, sur la base d'un premier signal vocal y(n) - x(n) + ε(η) auquel est superposé du bruit, x(n) représentant un signal vocal non superposé de bruit et ε(η) le bruit, génère un signal de sortie de filtre d'erreur passe-bas e(n), avec une unité de calcul de coefficient (KBE) qui actualise les coefficients du filtre d'erreur passe-bas sur la base des signaux d'erreur avant et arrière fm(n) et bm(n) des étages de filtre lattice du filtre d'erreur passe-bas et sur la base du signal d'entrée et du signal de sortie y(n) et e(n) du filtre d'erreur passe-bas, et avec une unité de soustraction qui soustrait le signal de sortie de filtre d'erreur passe-bas e(n) du premier signal vocal y(n) dans un soustracteur et, après soustraction, sort le reste sous la forme d'un deuxième signal vocal x̂(n) = y(n) - e(n) où le bruit est atténué, où une unité d'évaluation du bruit (GSE) est prévue, laquelle génère sur la base des signaux fm(n), bm(n), y(n) et e(n) du filtre d'erreur passe-bas un signal de puissance du bruit σn 2 et un signal de puissance vocale σx 2, lesdits signaux étant acheminés vers l'unité de calcul de coefficient (KBE) où les coefficients du filtre d'erreur passe-bas sont calculés à chaque moment n,
    caractérisé
    en ce que l'unité de calcul de coefficient (KBE) est en outre prévue pour déterminer la variance d'erreur corrigée q̂ 0 selon q ^ 0 = q 0 - σ n 2
    Figure imgb0040
    et le coefficient de réflexion corrigé k̂ selon k ^ 1 = - r ^ 0 q ^ 0 = - r 0 q 0 - σ n 2
    Figure imgb0041
    avec q0 comme variance d'erreur et r0 comme coefficient de réflexion,
    et en ce que l'unité de calcul de coefficient (KBE) est en outre prévue
    pour déterminer la corrélation d'erreur selon r ˜ m n = λ r ⁢ r ˜ m ⁢ n - 1 + f m n ⁢ b m ⁢ n - 1
    Figure imgb0042
    et la variance d'erreur selon q ˜ m n = λ q ⁢ q ˜ m ⁢ n - 1 + 1 2 ⁢ f m 2 n + b m 2 ⁢ n - 1
    Figure imgb0043
    avec λq > λr,
    λr et λq étant des pôles des équations de filtre passe-bas données pour r̃m (n) et q̃ m (n).
  2. Dispositif selon la revendication 1, caractérisé en ce qu'un filtre passe-bas bipolaire est prévu dans l'unité de calcul de coefficient (KBE) pour l'évaluation de corrélation de la corrélation d'erreur r̃(n).
  3. Dispositif selon la revendication 1 ou la revendication 2, caractérisé en ce qu'une unité d'évaluation d'activité vocale (SAE) est prévue, laquelle génère sur la base des signaux fm(n), bm(n), y(n) et e(n) du filtre d'erreur passe-bas un signal d'activité vocale v qui est acheminé vers l'unité de calcul de coefficient (KBE) et qui est pris en compte par celle-ci en vue d'une optimisation de l'atténuation du bruit.
  4. Dispositif selon la revendication 3, caractérisé en ce que l'unité d'évaluation d'activité vocale (SAE) est prévue pour former un facteur d'atténuation du bruit (kn ) qui est acheminé vers une entrée d'un premier multiplicateur (MU1), vers l'autre entrée duquel est acheminé le signal de sortie du filtre d'erreur passe-bas, ledit multiplicateur étant situé en amont de l'unité de soustraction.
  5. Dispositif selon la revendication 4, caractérisé en ce que l'unité d'évaluation d'activité vocale (SAE) forme un facteur de signal global (kg ) qui est acheminé vers une entrée d'un deuxième multiplicateur (MU2), vers l'autre entrée duquel est acheminé le signal de sortie de l'unité de soustraction.
  6. Cascade composée d'au moins deux dispositifs selon l'une des revendications 1 à 5, montés l'un derrière l'autre.
EP07800169A 2006-09-15 2007-09-06 Dispositif d'élimination du bruit dans un signal audio Not-in-force EP2080197B1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
AT0154706A AT504164B1 (de) 2006-09-15 2006-09-15 Vorrichtung zur gerauschunterdruckung bei einem audiosignal
PCT/AT2007/000424 WO2008031124A1 (fr) 2006-09-15 2007-09-06 Dispositif d'élimination du bruit dans un signal audio

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EP2080197A1 EP2080197A1 (fr) 2009-07-22
EP2080197B1 true EP2080197B1 (fr) 2011-01-12

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AT (2) AT504164B1 (fr)
DE (1) DE502007006264D1 (fr)
WO (1) WO2008031124A1 (fr)

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2363853A1 (fr) * 2010-03-04 2011-09-07 Österreichische Akademie der Wissenschaften Procédé d'estimation du spectre propre d'un signal
US20150081495A1 (en) * 2013-09-19 2015-03-19 Barclays Bank Plc System and Method for Account Succession
US10251002B2 (en) * 2016-03-21 2019-04-02 Starkey Laboratories, Inc. Noise characterization and attenuation using linear predictive coding
US11289098B2 (en) * 2019-03-08 2022-03-29 Samsung Electronics Co., Ltd. Method and apparatus with speaker recognition registration
CN110047529B (zh) * 2019-05-15 2024-02-20 中国人民解放军海军潜艇学院 一种信号自适应放大的多路音频记录设备及方法
CN115249212B (zh) * 2021-04-27 2026-03-10 上海寒武纪信息科技有限公司 一种用于对图像进行盲去噪的系统的和方法
CN117350099B (zh) * 2023-09-11 2024-04-16 北京五瑞美阳医疗器械有限责任公司 基于有限元分析的呼吸机降噪结构优化方法
CN117037837B (zh) * 2023-10-09 2023-12-12 广州伏羲智能科技有限公司 基于音轨分离技术的噪声分离方法和装置

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GB1520148A (en) 1975-10-09 1978-08-02 Standard Telephones Cables Ltd Adaptive lattice filter
US4587620A (en) 1981-05-09 1986-05-06 Nippon Gakki Seizo Kabushiki Kaisha Noise elimination device
US4720802A (en) * 1983-07-26 1988-01-19 Lear Siegler Noise compensation arrangement
US5913187A (en) * 1997-08-29 1999-06-15 Nortel Networks Corporation Nonlinear filter for noise suppression in linear prediction speech processing devices
JP2001175298A (ja) * 1999-12-13 2001-06-29 Fujitsu Ltd 騒音抑圧装置
US6925435B1 (en) * 2000-11-27 2005-08-02 Mindspeed Technologies, Inc. Method and apparatus for improved noise reduction in a speech encoder
US7065486B1 (en) * 2002-04-11 2006-06-20 Mindspeed Technologies, Inc. Linear prediction based noise suppression
US6892127B2 (en) 2003-02-28 2005-05-10 General Electric Company Methods and apparatus for assessing gas turbine engine damage
DE602004004242T2 (de) * 2004-03-19 2008-06-05 Harman Becker Automotive Systems Gmbh System und Verfahren zur Verbesserung eines Audiosignals
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EP2054882B1 (fr) * 2006-08-15 2011-01-19 Dolby Laboratories Licensing Corporation Mise en forme arbitraire d'une enveloppe de bruit temporelle sans information secondaire

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WO2008031124A1 (fr) 2008-03-20
EP2080197A1 (fr) 2009-07-22
AT504164B1 (de) 2009-04-15
AT504164A1 (de) 2008-03-15
US20100049507A1 (en) 2010-02-25
DE502007006264D1 (de) 2011-02-24
ATE495523T1 (de) 2011-01-15

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