WO2002011125A1 - Attenuation du bruit de fond et des echos dans un signal audio - Google Patents

Attenuation du bruit de fond et des echos dans un signal audio Download PDF

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Publication number
WO2002011125A1
WO2002011125A1 PCT/EP2001/008827 EP0108827W WO0211125A1 WO 2002011125 A1 WO2002011125 A1 WO 2002011125A1 EP 0108827 W EP0108827 W EP 0108827W WO 0211125 A1 WO0211125 A1 WO 0211125A1
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WIPO (PCT)
Prior art keywords
signal
procedure
follows
sub
per application
Prior art date
Application number
PCT/EP2001/008827
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English (en)
Inventor
László GYIMESI
Rudolf FÖLDVÁRI
Original Assignee
Herterkom Gmbh
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Herterkom Gmbh filed Critical Herterkom Gmbh
Priority to AU2001282047A priority Critical patent/AU2001282047A1/en
Publication of WO2002011125A1 publication Critical patent/WO2002011125A1/fr

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Classifications

    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00—Processing of the speech or voice signal 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 OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
    • G10L19/02—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using spectral analysis, e.g. transform vocoders or subband vocoders
    • G10L19/0204—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using spectral analysis, e.g. transform vocoders or subband vocoders using subband decomposition
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00—Processing of the speech or voice signal 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
    • G10L21/0216—Noise filtering characterised by the method used for estimating noise
    • G10L2021/02161—Number of inputs available containing the signal or the noise to be suppressed
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00—Processing of the speech or voice signal 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
    • G10L21/0216—Noise filtering characterised by the method used for estimating noise
    • G10L2021/02168—Noise filtering characterised by the method used for estimating noise the estimation exclusively taking place during speech pauses

Definitions

  • the object of the invention is a signal cleaning procedure to isolate audio-frequency signals from the background noise.
  • the signal to be cleaned is led into a filter bank and the signals separated into sub-bands will be sent into a transformer unit where a transformation will be performed upon them and this way a cleaned signal will be produced.
  • Patent No. 183.491 can essentially be used as a step of a noise cleaning procedure but it cannot be used appropriately to filter different sounds.
  • the objective of the invention was to eliminate the deficiencies and the creation of such a version that would be able to filter voice and other sounds appropriately from a noisy background.
  • the basis of the invention was the idea that if a non-linear impact model basically consisting of two components is used where the first part being a filter bank consisting of a Zwicker filter series, while the second part being a non-linear transformation producing a generalized amplitude/frequency function, then the task can be performed.
  • the procedure ⁇ to isolate audio-frequency signals from the background noise as per the invention during which the signal to be cleaned is led to a filter bank and the signals separated into sub-bands will be sent into a transformer unit where a transformation will be performed upon them and this way a cleaned signal will be produced — is based on the principle that the instantaneous amplitude or the approximated value of the amplitude of the signal of each sub-band appearing at the output of the filter bank is produced first in the transformer unit, then the instantaneous amplitude values produced this way will be averaged and the signals of the sub-bands will be weighted using the averages, and finally the weighted signals will be summed up and the cleaned signal will be determined this way.
  • Another feature of the invention can be that a Zwicker filter series is used as a filter bank.
  • the signals of the sub-bands are led into a squaring high pass filter (9) and the slowly changing component is separated using the filter and the period is determined from this signal using a null detector (10).
  • the subsequent periods will be determined using the period created by sub-bands, the weighted average of these will be created and the time functions created this way will be summed up.
  • the filtered signal of the squared amplitude of several sub-bands filtered by a high pass filter will be summed and this sum will be used.
  • the degree of curvature of the non-linear characteristics used in determining the weighting factors is controlled by the minimum to be found in a time period in the average of each channel — expediently in the 0.5 ⁇ 1 s time period. In the case of another use of the procedure, the degree of curvature of the non-linear characteristics used in determining the weighting factors is controlled by the minimum and maximum to be found in a time period of the average of each channel.
  • corrections of the amplitude and the delay time will be applied in the particular channels in such a way that the generating and evaluating signal of the standard signal will be led to a loudspeaker, then the amplitude and run time data of the received signal of the surrounding space will be measured at the midrange of the filter series and the values of the corrections will be generated using the measured values and repeating the procedure one or more times (iteration).
  • the microphone producing the input signal and the loudspeaker fed with the output signal are placed in the same space.
  • the instantaneous parameters are generated from the input signal using quadrature modulation and low pass filters in the environment of the zero frequency, then the instantaneous parameters acquired this way will be averaged and using another modulation the cleaned sub-bands will be acquired from these averages and the cleaned output signal will be acquired from summing these up.
  • the input signal will be filtered by a low pass filter bank implementing the asymmetry of the Zwicker filter series and then quadrature modulation will be applied on it.
  • the instantaneous parameters will be separated to DC and AC components by an alternate filter, then the instantaneous parameters of the AC components will be generated, that is, the transformation will be repeated on the result of the GAFT.
  • the advantage of the procedure as per the invention is that musical sounds and other quasi-periodic audio-frequency signals can be separated from the noisy environment with favourable results by using it. This way the same procedure and tool kit can be used in a wide range and in a flexible way for different purposes.
  • the efficiency of hearing aids can be improved, voice and musical sounds can be separated from the background noise but the procedure is also able to enhance the quality of recordings produced in moderate or poor quality studios as well as to restore old sound recordings.
  • the procedure is able to separate quasi-periodic signals, for instance, engine sounds of vehicles from the background noise so as to determine their movement and in addition it also can be used to examine rotating components, e.g. bearings and wheels, and to show the anomalies in their operation.
  • the principles of the procedure, according to the invention, are the creation and application of a non-linear hearing model on the circuit layout level, in which the filter bank, differently to the others, is constructed suitably of Zwicker filters.
  • Zwicker published in 1957, that the human hearing perceives the loudness differently inside of a critical band, than outside of this band.
  • Zwicker and Feldtkeller determined the steepness of cutting territory of the filters from the concealment occurrence.
  • These filters are approximately a third wide, asymmetrical and of a exceptionally steep characteristic on the upper part. This filtering effect takes place already on the tympanic membrane of the middle ear.
  • the data of the filter row is fixed by international standard.
  • the resultant characteristics of the 25 filters covers the entire audible spectrum, for the processing of speech approximately 14-15 is enough, while for studio quality 18 filters are necessary.
  • the output signals of the filters are transformed, namely we generate the instantaneous parameters, which in principle means the function of the instantaneous amplitude and the instantaneous frequency, which we define as follows:
  • x(t) is the output signal of the band-pass filter
  • y(t) is the Hilbert pair
  • x'(t) and y'(t) are the time differential quotients.
  • This non-linear transformation is called generalized amplitude and frequency transformation.
  • the result or the iterative value of the above transformation can be determined in several ways.
  • the transformation can be interpreted as the simultaneous implementation of a mutually independent ideal AM and FM demodulator, therefore the result of the GAFT can be determined or iterated with every AM and FM demodulator.
  • Fig. 1. shows the diagram of the simplest version of the signal cleaning procedure as per the invention.
  • Fig. 2. shows another possible layout of the signal cleaning process.
  • Fig. 3. is the block diagram of the signal cleaning procedure supplemented with echo reduction.
  • Fig. 4. is the draft diagram of the layout required for the separation of quasi-periodic signals.
  • Fig. 5 shows another layout that is able to separate quasi-periodic signals.
  • Fig.l shows the simplest block diagram of the signal cleaning procedure as per the invention.
  • the X(t) signal to be cleaned and led to the input has been broken down into sub-bands using 1 filter bank containing expediently a Zwicker filter series, then the instantaneous amplitude of each sub-band was determined with the unit implementing the 2 non-linear transformation. After determining the instantaneous amplitude of the sub-bands, their average was produced with the 3 low pass filter. Using the averages and the 4 non-linear characteristics without memory, the weighting factors falling between zero and one as appropriate were determined.
  • the signal of the sub-bands delayed with the 6 delay was weighted with these weighting factors, it was multiplied with the 7 multiplier in the case of the present version, then the cleaned signal will be generated using the 8 adder.
  • the degree of curvature of the 4 non-linear characteristics will be set by the 5 extreme value determiner used for determining the minimum or the minimum and maximum.
  • the "as possible” condition can be formulated in various ways. The condition is easiest to manage when the squared average or the expected value of the error is minimized, that is, if we look for the system where the expected value of the square of the
  • the first part in the non-linear impact model namely the 1 filter bank assembled from the Zwicker filter series is still linear, and based upon the solution of the Wiener-Hopf integral equation, the A k (t) weighting factor is to be set to the following value:
  • the value of the weighting factor will be:
  • a weighting function acquired from an arctg characteristics serves the purpose and can be formulated like this:
  • parameters A and B determining the arctg characteristics can also be determined in such a way that the value of the weighting factor be near 1 at the maximum and be near 0 at the minimum, e.g. 0.9 at the maximum and 0.1 at the minimum.
  • the value of the parameters is determined by the ratio of the minimum and the maximum. It is worth mentioning that only the control considering the minimum is more pleasant for the listener but a speech recognition procedure using both the minimum and the maximum may result in a significant improvement.
  • Fig.2 demonstrates another possible layout of the signal cleaning procedure.
  • the 9 squaring high pass filter removes the slowly changing component and determines the A k (t) signal that is the base frequency of the signal, that is, it is the pitch frequency itself.
  • the base frequency of the A k H (t) signal is acquired by using the 10 null detector or the autocorrelation function.
  • the period times determined by channels are identical only in theory or in the case of no noise.
  • the background noise affects the value of the period times detected in the various sub-bands differently. If the noise does not contain a periodic or quasi-periodic component, that is, the noise spectra in the sub-bands are independent, then period times are summed up in the sum of the period times detected by channels, whilst the components causing the difference will be summed up with the square root of their sum of squares — the identical components "as per voltage", the independent components "as per power”.
  • the time functions within the so determined period times provide the time function of each voiced period. These voiced periods do not change much within a voiced phoneme but in case of a heavy background noise the subsequent voiced periods will be different due to the noise.
  • the echoing speech is hardly intelligible and heavily degrades the efficiency of the speech recognition system.
  • the methods described above are primarily able to separate from the noise but controlling with the minimum and the maximum reduces the effect of the echo as well.
  • Fig. 3. shows the layout of the signal cleaning procedure described above extended with echo-reduction.
  • the value of the 12 amplitude correction member and the 13 run time correction member is set by the 14 measuring generator/analyzer unit in such a way that using the Nyquist method and then iteration, the value of the corrections required in the sub-bands is determined by supplying the 15 loudspeaker with the signal and analyzing the received signal. If possible, the loudspeaker should be placed at the location of the source of the useful sound, e.g. the speaker, or in the vicinity of it.
  • Fig. 4. shows the layout that is able to separate quasi-periodic signals.
  • the quadrature components xw(t), y k o(t)
  • Their instantaneous parameters can be generated by the procedure determining the instantaneous parameters of the 17 quadrature components (GAFT) (A k o(t), W k o(t)).
  • GFT the instantaneous parameters of the 17 quadrature components
  • the 18 filter unit designated to filter the instantaneous parameters and with the 19 transformer unit performing the frequency shift and the inverse transformation, and with the summing of the this way generated Y k (t) signals by the 8 adder, the quasi- periodic signal separated from the background noise is created.
  • the asymmetric Zwicker filter bank is not suitable directly for the implementation with quadrature modulation.
  • the requirement of the asymmetric attenuation is realized first by means of the 20 low pass filter bank implementing the asymmetry of the Zwicker filters in such a way that the attenuation of the remaining part be symmetric on the mid-band — as it is shown on Fig.5. — then the remaining attenuation can be realized with quadrature modulation and low pass filtering ⁇ using the procedure already shown on Fig.4.

Abstract

L'invention concerne une procédure de nettoyage de signal pour isoler des signaux audio-fréquence du bruit de fond. Lors de la procédure, le signal à nettoyer est conduit dans un banc de filtres et les signaux séparés en sous-bandes sont émis dans une unité de transformation où ils subissent une transformation, ce qui produit un signal nettoyé. Il est caractéristique d'observer, lors de cette procédure, que l'amplitude instantanée ou la valeur approximative de l'amplitude du signal de chaque sous-bande apparaissant à la sortie (1a) du banc de filtres (1) est d'abord produite dans l'unité de transformation, puis les valeurs d'amplitude instantanées ainsi produites sont moyennées et les signaux des sous-bandes pondérés au moyen des moyennes. Les signaux pondérés sont finalement additionnés et le signal nettoyé est ainsi déterminé.
PCT/EP2001/008827 2000-07-31 2001-07-31 Attenuation du bruit de fond et des echos dans un signal audio WO2002011125A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
AU2001282047A AU2001282047A1 (en) 2000-07-31 2001-07-31 Attenuation of background noise and echoes in audio signal

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
HU0003010A HUP0003010A2 (en) 2000-07-31 2000-07-31 Signal purification method for the discrimination of a signal from background noise
HUP0003010 2000-07-31

Publications (1)

Publication Number Publication Date
WO2002011125A1 true WO2002011125A1 (fr) 2002-02-07

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HU (1) HUP0003010A2 (fr)
WO (1) WO2002011125A1 (fr)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2009043066A1 (fr) * 2007-10-02 2009-04-09 Akg Acoustics Gmbh Procédé et dispositif pour une amélioration de parole monocanal basée sur un modèle auditif à faible latence
CN111145770A (zh) * 2018-11-02 2020-05-12 北京微播视界科技有限公司 音频处理方法和装置

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Publication number Priority date Publication date Assignee Title
US5574824A (en) * 1994-04-11 1996-11-12 The United States Of America As Represented By The Secretary Of The Air Force Analysis/synthesis-based microphone array speech enhancer with variable signal distortion
US5933495A (en) * 1997-02-07 1999-08-03 Texas Instruments Incorporated Subband acoustic noise suppression
EP1006510A2 (fr) * 1994-03-18 2000-06-07 Mitsubishi Denki Kabushiki Kaisha Système de codage et décodage des signaux
WO2000041169A1 (fr) * 1999-01-07 2000-07-13 Tellabs Operations, Inc. Procede et appareil de suppression du bruit de maniere adaptative

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EP1006510A2 (fr) * 1994-03-18 2000-06-07 Mitsubishi Denki Kabushiki Kaisha Système de codage et décodage des signaux
US5574824A (en) * 1994-04-11 1996-11-12 The United States Of America As Represented By The Secretary Of The Air Force Analysis/synthesis-based microphone array speech enhancer with variable signal distortion
US5933495A (en) * 1997-02-07 1999-08-03 Texas Instruments Incorporated Subband acoustic noise suppression
WO2000041169A1 (fr) * 1999-01-07 2000-07-13 Tellabs Operations, Inc. Procede et appareil de suppression du bruit de maniere adaptative

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Title
CHARBONNIER ET AL: "Design of nearly perfect non uniform QMF filter banks", ICASSP'88, vol. 3, 11 April 1988 (1988-04-11) - 14 April 1988 (1988-04-14), New York, pages 1786 - 1789, XP010072670 *
RUDOLF FÖLDVÁRI AND LÁSZLO GYIMESI: "Very low bit rate voice coder based on a nonlinear hearing model", EUROSPEECH'99, vol. 4, 5 September 1999 (1999-09-05) - 9 September 1999 (1999-09-09), Budapest, Hungary, pages 1547 - 1550, XP002180861 *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2009043066A1 (fr) * 2007-10-02 2009-04-09 Akg Acoustics Gmbh Procédé et dispositif pour une amélioration de parole monocanal basée sur un modèle auditif à faible latence
GB2465910A (en) * 2007-10-02 2010-06-09 Akg Acoustics Gmbh Method and device for low-latency auditory model-based single-channel speech enhancement
GB2465910B (en) * 2007-10-02 2012-02-15 Akg Acoustics Gmbh Method and device for low-latency auditory model-based single-channel speech enhancement
CN111145770A (zh) * 2018-11-02 2020-05-12 北京微播视界科技有限公司 音频处理方法和装置

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HUP0003010A2 (en) 2002-08-28
HU0003010D0 (en) 2000-10-28

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