EP1211671A2 - Commande automatique de gain avec suppression de bruit - Google Patents

Commande automatique de gain avec suppression de bruit Download PDF

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Publication number
EP1211671A2
EP1211671A2 EP01309636A EP01309636A EP1211671A2 EP 1211671 A2 EP1211671 A2 EP 1211671A2 EP 01309636 A EP01309636 A EP 01309636A EP 01309636 A EP01309636 A EP 01309636A EP 1211671 A2 EP1211671 A2 EP 1211671A2
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Prior art keywords
noise
level
gain
noise suppression
signal
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EP01309636A
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German (de)
English (en)
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EP1211671A3 (fr
Inventor
Alexander Goldin
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Alst Innovation Technologies
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Alst Innovation Technologies
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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

Definitions

  • the present invention relates generally to processing of audio signals, and specifically to noise reduction and automatic gain control in processing of such signals.
  • AGC Automatic gain control
  • Fig. 1 is a plot that schematically illustrates signals received by a microphone, representing the voices of two speakers.
  • the first speaker (who speaks during intervals marked “A” in the figure) is about 50 cm from to the microphone, while the second speaker (speaking during intervals marked “B") is about 2 m from the microphone. Since the sound pressure level is inversely proportional to the distance from the microphone, the input level of an audio signal 20 received during the A intervals is about four times (12 dB) greater than a signal 22 during the B intervals.
  • a background noise level 24 remains roughly constant.
  • Fig. 2 is a plot that schematically illustrates the result of applying AGC to the signals of Fig. 1.
  • the AGC causes an output signal 32 during the B intervals to have a level that is roughly equal to that of an output signal 30 during the A intervals.
  • a noise level 34 during the A intervals remains reasonably low. Strong amplification of the weak signal in the B intervals, however, causes corresponding amplification of a noise level 36 during these intervals. As a result, while the signals from both speakers are heard at approximately the same output signal level, the noise level has sharp and noticeable variations.
  • Digital noise suppression techniques can be used to reduce the background noise level before AGC amplification of the signal. (Noise suppression must precede AGC, since if the order of operation is reversed, variations in the AGC gain will confuse the noise suppressor's estimate of the noise level.)
  • Common noise suppression techniques typically involve determining the noise spectrum and filtering the signal based on this spectrum in order to remove the noise components insofar as possible. Such techniques are commonly referred to as methods of “spectral attenuation” or “spectral subtraction.” They are described, for example, by Boll in an article entitled “Suppression of Acoustic Noise in Speech Using Spectral Subtraction,” published in IEEE Transactions on Acoustics , Speech and Signal Processing, ASSP-27, No. 2 (April, 1979), which is incorporated herein by reference.
  • U.S. Patent 5,550,924, to Helf et al. whose disclosure is incorporated herein by reference, describes a method for reducing background noise in order to enhance speech.
  • Properties of human audio perception are used to perform spectral and time masking to reduce perceived loudness of noise added to the speech signal.
  • a signal is divided temporally into blocks which are then passed through a plurality of filters to remove narrow frequency band components of the noise.
  • An estimate of the noise level in each of the filters is made by averaging measured noise powers.
  • a FFT Fast Fourier Transform
  • Responsive to the determined noise power a noise-reduced signal is recovered using an inverse FFT.
  • U.S. Patent 5,768,473, to Eatwell et al. whose disclosure is incorporated herein by reference, describes an adaptive speech filter.
  • the filter is a modified version of that described in U.S. Patent 4,185,168, using a noise power estimate of an average of the power.
  • the filter implements an improved adaptive spectral estimator for estimating the spectral components in a signal containing both an information signal, such as speech, and noise. Improvements over 4,185,168 relate to a noise power estimator and a computationally-efficient gain calculation method.
  • the adaptive spectral estimator is said to be particularly suited to implementation using digital signal processing and can be used to provide improved spectral estimates of the information signal.
  • the amount of noise suppressed by a given noise suppressor is adjustable over a certain range.
  • Suppression technologies known in the art can typically provide up to 8-10 dB of noise suppression with a significant improvement in sound quality.
  • noticeable distortion may be introduced in the speech signals. Therefore, in noisy environments, finding the optimal level of noise suppression involves trading off background noise against speech distortion.
  • Figs. 1 and 2 it will be seen that if sufficient noise suppression is applied in order to eliminate the annoying noise modulation effect in the B intervals, the result will likely be undesired distortion in the audio signals in both the A and B intervals.
  • noticeable noise modulation will remain,
  • an audio processor comprises a noise suppression stage and an AGC stage.
  • the amount of noise suppressed is adjusted continually according to the current AGC gain.
  • the noise suppression is reduced in order to eliminate possible distortion.
  • the audio processor can thus be adjusted to give optimal audio quality, balancing noise modulation against signal distortion, over a range of different signal levels.
  • audio processing apparatus including:
  • the noise suppression stage is adapted to apply spectral compression to the input audio signal.
  • the noise controller is adapted to determine the level of noise suppression as a monotonically-increasing function of the gain.
  • the level of noise suppression determined by the noise controller increases in proportion to a power of the gain, wherein the power is less than or equal to one.
  • the AGC stage is adapted to increase and decrease the gain in alternation in response to alternations in the level of the noise-suppressed signal due to receiving the input audio signal from alternating weak and strong audio sources, respectively
  • the noise Controller is adapted to decrease and increase the level of noise suppression, responsive respectively to the gain increasing and decreasing.
  • a method for audio processing including:
  • Fig. 3 is a block diagram that schematically illustrates an audio processor 40, in accordance with a preferred embodiment of the present invention.
  • the audio processor receives a raw audio input signal X ( t ), from a microphone, for example (not shown), and outputs a processed audio signal Y ( t ).
  • Audio processor comprises a noise suppression stage 42, followed by an AGC stage 44.
  • X ( t ) and Y ( t ) are analog signals, and stages 42 and 44 are implemented using suitable analog circuit elements, such as tunable filters and variable-gain amplifiers, as are known in the art.
  • X(t) and Y(t) are digitized, and the processing functions described hereinbelow are implemented using digital logic circuits. Mixed analog and digital implementations may also be used.
  • noise suppression stage 42 implements a method for suppressing near-stationary noises and tones described in U.S. Patent Application 09/605,174, filed June 28, 2000, which is assigned to the assignee of the present patent application and whose disclosure is incorporated herein by reference.
  • the input noise is divided into multiple frequency bands, and the maximum and minimum noise levels in each band are determined over a period of time. Based on these noise levels, a gain is computed in each band using spectral subtraction and/or spectral compression.
  • the gains G NS are applied by noise suppression stage 42 to the respective frequency bands of the input signal X(t) to generate a noise-suppressed input to AGC stage 44.
  • the noise suppression stage may employ other techniques, such as those described in the Background of the Invention, or substantially any other suitable noise suppression method known in the art.
  • AGC stage 44 operates on the audio signals after processing by noise suppression stage 42.
  • the AGC stage determines a variable gain G AGC (t) to be applied to the signals in order to compensate for variations in the input signal level
  • the current value of G AGC (t) is provided to a noise control block 46.
  • the noise control block computes the amount of noise suppression L(t) to be applied by noise suppression stage 42 to the input signal X(t).
  • the values of parameters used in noise suppression stage 42, such as G min are continually adjusted so that the total amount of noise suppression is equal to the current value of L(t) .
  • block 46 is shown in the figure as a separate entity for the sake of clarity of explanation, those skilled in the art will appreciate that the function of this block may alternatively be integrated into either stages 42 or stage 44.
  • L(t) is determined based on the current AGC gain G AGC ( t ) and on a basic noise suppression level L B , which corresponds to the amount of noise suppressed in the output signal when AGC gain is equal to unity.
  • Various functions may be used to relate L ( t ) to G AGC ( t ) and L B .
  • L(t) increases monotonically relative to both G AGC ( t ) and L B .
  • L ( t ) L B + G AGC ( t )
  • the noise suppression levels and AGC gain are specified here in decibels.
  • Equation (4) may not be optimal, however, when large variations in the input signal level can occur, as it may lead to excessive noise suppression, with noticeable distortions in the output signal Y(t) .
  • L B the basic noise suppression level
  • AGC gain is 15 dB
  • the total amount of noise suppression will be 20 dB.
  • a milder dependence between the AGC gain G AGC (t) and noise suppression level L(t) is preferable, such as a dependence of L(t) on a fractional power of the gain ( G AGC ( t )) x , with x ⁇ 1.
  • Fig. 4 is a plot that schematically shows the output signal Y ( t ) obtained by operating on the input signal X(t) shown in Fig. 1 using audio processor 40, in accordance with a preferred embodiment of the present invention.
  • the variable noise suppression L(t) is given by equation (5).
  • Signals 50 and 52 during intervals A and B, respectively, are amplified by AGC stage 44 to give comparable levels of perceptual loudness.
  • Respective noise levels 54 and 56 are suppressed during both intervals A and B, as well.
  • the level of noise suppression during the B intervals is greater than that during the A intervals, but due to the square root factor in equation (5), there is still slightly more residual noise in the B intervals.
  • the parameters governing the dependence of L(t) on G(t) are preferably chosen and adjusted based on the background noise and signal conditions so as to balance the residual noise modulation against distortion effects due to the noise suppression, in a way that gives the most pleasing perceived sound quality.

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  • Engineering & Computer Science (AREA)
  • Computational Linguistics (AREA)
  • Quality & Reliability (AREA)
  • Signal Processing (AREA)
  • Health & Medical Sciences (AREA)
  • Audiology, Speech & Language Pathology (AREA)
  • Human Computer Interaction (AREA)
  • Physics & Mathematics (AREA)
  • Acoustics & Sound (AREA)
  • Multimedia (AREA)
  • Control Of Amplification And Gain Control (AREA)
EP01309636A 2000-11-16 2001-11-15 Commande automatique de gain avec suppression de bruit Withdrawn EP1211671A3 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US24938800P 2000-11-16 2000-11-16
US249388P 2000-11-16

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EP1211671A2 true EP1211671A2 (fr) 2002-06-05
EP1211671A3 EP1211671A3 (fr) 2003-09-10

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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1796082A1 (fr) * 2005-12-09 2007-06-13 QNX Software Systems (Wavemakers), Inc. Système permettant une intelligibilité améliorée par compression des hautes fréquences
EP2460156A1 (fr) * 2009-07-29 2012-06-06 BYD Company Limited Procédé et dispositif d'élimination de bruit de fond
DE102011003477A1 (de) * 2011-02-01 2012-08-02 Siemens Aktiengesellschaft Verfahren und Vorrichtung zur Filterung eines Signals und Regeleinrichtung für einen Prozess
WO2015116608A1 (fr) * 2014-01-31 2015-08-06 Microsoft Technology Licensing, Llc Traitement de signal audio
CN106205631A (zh) * 2015-05-28 2016-12-07 三星电子株式会社 用于消除音频信号的噪声的方法及其电子装置

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4630305A (en) * 1985-07-01 1986-12-16 Motorola, Inc. Automatic gain selector for a noise suppression system
US4658426A (en) * 1985-10-10 1987-04-14 Harold Antin Adaptive noise suppressor

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4630305A (en) * 1985-07-01 1986-12-16 Motorola, Inc. Automatic gain selector for a noise suppression system
US4658426A (en) * 1985-10-10 1987-04-14 Harold Antin Adaptive noise suppressor

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
BOLL S F: "SUPPRESSION OF ACOUSTIC NOISE IN SPEECH USING SPECTRAL SUBTRACTION" IEEE TRANSACTIONS ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, IEEE INC. NEW YORK, US, vol. ASSP-27, no. 2, 1 April 1979 (1979-04-01), pages 113-120, XP002072967 ISSN: 0096-3518 *

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1796082A1 (fr) * 2005-12-09 2007-06-13 QNX Software Systems (Wavemakers), Inc. Système permettant une intelligibilité améliorée par compression des hautes fréquences
EP2460156A1 (fr) * 2009-07-29 2012-06-06 BYD Company Limited Procédé et dispositif d'élimination de bruit de fond
EP2460156A4 (fr) * 2009-07-29 2012-12-26 Byd Co Ltd Procédé et dispositif d'élimination de bruit de fond
DE102011003477A1 (de) * 2011-02-01 2012-08-02 Siemens Aktiengesellschaft Verfahren und Vorrichtung zur Filterung eines Signals und Regeleinrichtung für einen Prozess
DE102011003477B4 (de) * 2011-02-01 2015-07-02 Siemens Aktiengesellschaft Verfahren und Vorrichtung zur Filterung eines Signals und Regeleinrichtung für einen Prozess
WO2015116608A1 (fr) * 2014-01-31 2015-08-06 Microsoft Technology Licensing, Llc Traitement de signal audio
US9924266B2 (en) 2014-01-31 2018-03-20 Microsoft Technology Licensing, Llc Audio signal processing
CN106205631A (zh) * 2015-05-28 2016-12-07 三星电子株式会社 用于消除音频信号的噪声的方法及其电子装置

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EP1211671A3 (fr) 2003-09-10

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