EP2490459A1 - Procédé de mélange de signal vocal - Google Patents

Procédé de mélange de signal vocal Download PDF

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Publication number
EP2490459A1
EP2490459A1 EP11155021A EP11155021A EP2490459A1 EP 2490459 A1 EP2490459 A1 EP 2490459A1 EP 11155021 A EP11155021 A EP 11155021A EP 11155021 A EP11155021 A EP 11155021A EP 2490459 A1 EP2490459 A1 EP 2490459A1
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EP
European Patent Office
Prior art keywords
signal
noise
blending
microphone
level
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Granted
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EP11155021A
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German (de)
English (en)
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EP2490459B1 (fr
Inventor
Bernd Iser
Arthur Wolf
Patrick Hannon
Mohamed Krini
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SVOX AG
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SVOX 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
    • H04R3/00—Circuits for transducers, loudspeakers or microphones
    • H04R3/005—Circuits for transducers, loudspeakers or microphones for combining the signals of two or more microphones
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R2499/00—Aspects covered by H04R or H04S not otherwise provided for in their subgroups
    • H04R2499/10—General applications
    • H04R2499/11—Transducers incorporated or for use in hand-held devices, e.g. mobile phones, PDA's, camera's
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R2499/00—Aspects covered by H04R or H04S not otherwise provided for in their subgroups
    • H04R2499/10—General applications
    • H04R2499/13—Acoustic transducers and sound field adaptation in vehicles
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R3/00—Circuits for transducers, loudspeakers or microphones
    • H04R3/02—Circuits for transducers, loudspeakers or microphones for preventing acoustic reaction, i.e. acoustic oscillatory feedback

Definitions

  • the invention refers to a method and system installed in a car for the communication of people sitting in remote locations. Therefore at least one loudspeaker is installed and at least two microphones, one assigned to each person.
  • the invention relates to method applied to a hands-free telephony system or to an automatic speech recognition system, where conditions and requirements are quite similar. More specifically, the invention relates to a method according to the introductory clause of claim 1 as well as to a software product according to claim 8 and a system according to claim 9.
  • EP1850640B1 shows and describes a typical setup for a basic intercom system with two microphones and one loudspeaker.
  • the mixer in this setup decides depending on a criterion which of the microphone signals shall be switched to the next module or the output.
  • This criterion can depend on the detected occupation of a seat.
  • it has been also proposed in US006549629B2 such decision criterion can depend on the Signal plus Noise to Noise Ratio (SNNR).
  • SNNR Signal plus Noise to Noise Ratio
  • SNR Signal to Noise Ratio
  • a further disadvantage of these systems is a possible change in background-noise level when switching from one speaking person to another (e.g. driver speaks to a passenger in the back while having his window open, and then the co-driver speaks to the passenger in the back having his window closed and driver as well as co-driver are each equipped with a microphone).
  • This change in background-noise level of the signal played back over the loudspeaker might be experienced as unpleasant by a listener.
  • US-A-2005/0265560 discloses a system, where a beamformer is used for microphone signal blending. The, thus, blended output signal is then subjected to feedback suppression.
  • This has the disadvantage that the power of the signals to be blended is relative high and, moreover, the output signal of the beamformer is adulterated by the feedback component of the signal.
  • the suppression is merely the suppression of frequencies, which are just developing resonance oscillations, which means that feedback components remain, and only resonance oscillations are prevented.
  • the feedback suppression or compensation is effected before blending the signals of the at least two microphones. If in this connection the term "feedback suppression or compensation" is used, it is in any case a minimization of feedback components of a signal.
  • a feedback compensation is for example described in EP 1 679 874 B1 .
  • Feedback suppression can be applied by filtering, for example with a notch-filter.
  • Another known compensation method uses frequency shifting. These suppression methods reduce the development of feedback, but existing feedback components remain.
  • the method for voice signal blending is applied in a communication system, such as an indoor communication system, particularly in a vehicle, or in a hands-free telephony system or an automatic speech recognition system, comprising at least two microphones and at least one loudspeaker.
  • the microphone signals are blended with respective weights to be delivered to the at least one loudspeaker.
  • the feedback suppression or compensation is effected before blending the signals of the at least two microphones. This improves the quality of the blended signal and is more robust in relation to feedback components.
  • the feedback components are minimized by estimating the feedback signal or its energy level, preferably its power spectral density, and applying a Wiener filter which eliminates the estimated feedback signal from the signals to be blended.
  • the energies of the microphone signals are determined and at least the energies of the noise components are estimated, wherein for blending, a higher weight is given to at least the sub-band with the highest ratio of signal energy to noise energy.
  • a higher weight is given to at least the sub-band with the highest ratio of signal energy to noise energy.
  • a signal level adjustment of the at least two microphone signals to a predetermined value is carried out particularly immediately before or immediately after blending, wherein the adjustment is depending on the energies of the noise components and minimizes the perceivable difference in the noise level when blending from one microphone to the other. In this way changes of noise levels are better avoided.
  • the signal levels of the microphone signals are adjusted to a predetermined value so that there is no perceivable difference in the speech level when blending from one microphone to the other.
  • the noise level of at least two microphones can be unpleasantly different. An adjustment can be achieved, if the characteristics of claim 5 are fulfilled.
  • the microphone signals comprise different components, each with a certain level. If a person close to a microphone is speaking, then the signal of this microphone comprises this voice with a corresponding voice level.
  • the voice levels of the at least two microphone signals are adjusted substantially to the same level by adjusting the microphone signals. Then the difference of the noise levels of the at least two adjusted microphone signals is determined.
  • the noise suppressions in the microphone signals are controlled by adapting the parameters of the noise suppression characteristic in such a way, that the noise suppressed signals have substantially the same level of residual noise and the same level of speech signal in it for each microphone signal.
  • the respective speaking and/or listening, non-speaking party is detected by one of the following measures:
  • Fig. 1 shows a typical setup for a basic intercom system with two microphones 1 and 2 and one loudspeaker 3.
  • a voice mixer 5 which receives the pre-processed signals of the microphones 1, 2 and decides depending on a criterion which of the microphone signals shall be switched to its output and to the next module 6.
  • Fig. 2a one embodiment of the invention is illustrated, where the signals of the microphones 1, 2, after an optional pre-processing stage 4a, are subjected to feedback suppression or compensation in a stage 7.
  • the first component after some optional pre-processing is a feedback suppression or feedback compensation at 7.
  • This module 7 suppresses or compensates for the portion of the loudspeaker signal that is coupling back into the microphone and therefore being an undesired signal component.
  • noise suppression in a noise suppression module 8 can be effected.
  • This module 8 suppresses the background noise components of the microphone signals resulting from the background noise being present in the car cabin and being picked up by the microphones.
  • a practical embodiment with a noise suppression postponed to the voice blender 5a is shown in Fig. 4b .
  • the signal m i of microphone i is made up of the signal from the speaker in the cabin s i , the feedback of the system from the loudspeaker into the microphone f i and the background noise of the cabin recorded by the microphone b i .
  • i corresponds to the microphone index
  • k to the time interval
  • ⁇ to the frequency band.
  • the noise suppression is located before the voice blender 5a which is not necessarily required (without limitation of generality, see e.g. Fig. 4b ).
  • the blended and noise suppressed signal goes suitably to a NDGC or noise dependent gain control 9.
  • the voice blender module blends the at least two feedback suppressed or compensated and noise suppressed signals according to Fig. 2a together to one output signal following below described criterion. According to Fig. 2b the blended signals are only feedback suppressed or compensated.
  • the blending is made by giving weights to the microphones.
  • the blending or weighting criterion can either be evaluated in a non-frequency selective manner or in a frequency selective manner resulting in a non-frequency selective weighting or in a frequency selective weighting of the microphone signals m i .
  • 4a , 4b , 4c is a function of the ratio of the energy of every microphone signal S mimi subtracted by the feedback ⁇ i (respectively S ⁇ i ⁇ i for the energy of the feedback component at every microphone) due to the coupling of the loudspeaker signal back into the microphone signal and further subtracted by the noise b i (respectively S bibi for the energy of the noise component at every microphone) within the microphone signal resulting from the noise present in the car cabin and being picked up by the microphone (for the setup according to Fig. 2b each microphone signal is only subtracted by the feedback) to the estimated noise present in each microphone signal.
  • Double indices are used for the energy of the signal, and for power spectral densities.
  • N the number of microphones.
  • ß m is a smoothing constant that has to be chosen between zero and one. This means the current short-term power is weighted with ß m and the estimate of the previous time frame is weighted with (1-ß m ).
  • the feedback component S ⁇ i ⁇ i ( k , ⁇ ) is estimated in the feedback compensation or feedback suppression module and is therefore given.
  • ⁇ is a small number depending on the sampling rate.
  • the modified SNR after subtracting the power of the feedback signal and of the background noise from the microphone signal power, is set into relation with the sum over all microphones of the modified SNR.
  • the resulting weight is more robust against misinterpretations of feedback power as desired speech power as would be the case using an SNNR as described in US006549629B2 .
  • the voice blender module 5a determines the difference in noise levels between the different signals and causes noise suppression to adapt the parameters of the noise suppression characteristic to result in a noise suppressed signal having the same level of residual noise in it for each speaker.
  • Equation 8 This allows compensating for different background-noise levels and different speech levels at the same time. No trade off between the both optimization criteria is necessary. This means applying Equation 8 and adjusting the filter coefficients of the noise suppression (e.g. a Wiener filter) to (see Fig.
  • H k ⁇ ⁇ min ⁇ , 1 - ⁇ i w i , speech k ⁇ ⁇ ⁇ S b i ⁇ b i k ⁇ ⁇ S m i ⁇ m i k ⁇ ⁇
  • Fig. 4a shows, how a voice blender for carrying out the method according to the invention may be structured. It is clearly visible that feedback suppression or feedback compensation is done for each of the signals stemming from the microphones 1 and 2 in modules 7a and 7b. The output of these modules 7a, 7b is delivered to the voice blender 5a, i.e. to noise estimation modules 10, 10' (see equations 1-4), to power estimation modules 11, 11' (see equation 8) and to multiplicators 12 and 12' for weighting the incoming signals.
  • multiplicators 12, 12' are each controlled by a module Wi which determines the blender weights for each signal of the microphones 1, 2.
  • a summing point 13 At the output of blender 5a is a summing point 13.
  • the output signal v( ⁇ ,k) of the voice blender 5a can be used to influence noise suppression in module 8. This is shown in Fig. 4b , where the weighting signals W i,speech (k, ⁇ ) are supplied to module 8. Noise suppression down to zero gives mostly a bad feeling to the listener, for which reason it is preferred to adjust noise suppression to a predetermined level to a predetermined minimum level. This level typically equals 0.316 meaning a maximum suppression of -10 dB.
  • Fig. 4c a configuration according to Fig. 4c is possible within the scope of the present invention taking equation 8 in mind.
  • the weighting signals W i,speech (k, ⁇ ) are supplied to module 9, the noise dependent gain control, which, to have an information of noise present in the signal, receives also the output signal S bibi (k, ⁇ ) of the noise estimation modules 10 and 10'.
  • the weighting signal W i of the voice blender 5a could be used to control an equalizer 6a which forms part of the post-processor 6 ( Fig. 1 to Fig. 2b ).
  • the decision of the voice blender module is used for the noise dependent gain control module.
  • the noise dependent gain control module is responsible for increasing the level of the output signal by applying a gain g l,NDGC (S blbl (k, ⁇ ) ),depending on the level of noise perceived by the listening party.
  • This increase of the output signal level depends on a characteristic which maps the level of background noise in the car cabin to a gain applied to the output signal. The characteristic chosen for this mapping depends on which speaker is active. This information is delivered by the voice blender module in the form of the microphone index of the most active microphone l( k ).
  • Equation 12 S blbl (k, ⁇ ) represents the noise component that is present in the microphone signal of the active speaker. Some sample characteristics are depicted in Fig. 6 .
  • equalizer 6a part of post processing 6 of an intercom system is the equalizer 6a.
  • This equalizer 6a can as well be implemented as a multi-channel equalizer individual for each channel.
  • the settings of the equalizer 6a are chosen depending on the voice blender decision of which person is speaking to enhance the perceived quality of the output for the listening party (see Fig.3 and Fig. 5 ).
  • NDGC mapping characteristic and equalizer setting can be chosen in an even more specific manner.
EP11155021.6A 2011-02-18 2011-02-18 Procédé de mélange de signaux vocaux Active EP2490459B1 (fr)

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Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2816816A1 (fr) * 2013-06-20 2014-12-24 2236008 Ontario Inc. Stabilisateur spatial du champ sonore avec compensation de bruit structurée
US9099973B2 (en) 2013-06-20 2015-08-04 2236008 Ontario Inc. Sound field spatial stabilizer with structured noise compensation
US9106196B2 (en) 2013-06-20 2015-08-11 2236008 Ontario Inc. Sound field spatial stabilizer with echo spectral coherence compensation
US9271100B2 (en) 2013-06-20 2016-02-23 2236008 Ontario Inc. Sound field spatial stabilizer with spectral coherence compensation
US9516418B2 (en) 2013-01-29 2016-12-06 2236008 Ontario Inc. Sound field spatial stabilizer
US11463820B2 (en) 2019-09-25 2022-10-04 Oticon A/S Hearing aid comprising a directional microphone system
US11798576B2 (en) 2014-02-27 2023-10-24 Cerence Operating Company Methods and apparatus for adaptive gain control in a communication system

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5602962A (en) * 1993-09-07 1997-02-11 U.S. Philips Corporation Mobile radio set comprising a speech processing arrangement
US20030026437A1 (en) * 2001-07-20 2003-02-06 Janse Cornelis Pieter Sound reinforcement system having an multi microphone echo suppressor as post processor
US6549629B2 (en) 2001-02-21 2003-04-15 Digisonix Llc DVE system with normalized selection
US20050265560A1 (en) 2004-04-29 2005-12-01 Tim Haulick Indoor communication system for a vehicular cabin
EP1850640A1 (fr) * 2006-04-25 2007-10-31 Harman/Becker Automotive Systems GmbH Système de communication pour un véhicule
EP1679874B1 (fr) 2005-01-11 2008-05-21 Harman Becker Automotive Systems GmbH Réduction du couplage pour des systèmes de communication
US20090316923A1 (en) * 2008-06-19 2009-12-24 Microsoft Corporation Multichannel acoustic echo reduction

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5602962A (en) * 1993-09-07 1997-02-11 U.S. Philips Corporation Mobile radio set comprising a speech processing arrangement
US6549629B2 (en) 2001-02-21 2003-04-15 Digisonix Llc DVE system with normalized selection
US20030026437A1 (en) * 2001-07-20 2003-02-06 Janse Cornelis Pieter Sound reinforcement system having an multi microphone echo suppressor as post processor
US20050265560A1 (en) 2004-04-29 2005-12-01 Tim Haulick Indoor communication system for a vehicular cabin
EP1679874B1 (fr) 2005-01-11 2008-05-21 Harman Becker Automotive Systems GmbH Réduction du couplage pour des systèmes de communication
EP1850640A1 (fr) * 2006-04-25 2007-10-31 Harman/Becker Automotive Systems GmbH Système de communication pour un véhicule
EP1850640B1 (fr) 2006-04-25 2009-06-17 Harman/Becker Automotive Systems GmbH Système de communication pour un véhicule
US20090316923A1 (en) * 2008-06-19 2009-12-24 Microsoft Corporation Multichannel acoustic echo reduction

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9516418B2 (en) 2013-01-29 2016-12-06 2236008 Ontario Inc. Sound field spatial stabilizer
US9949034B2 (en) 2013-01-29 2018-04-17 2236008 Ontario Inc. Sound field spatial stabilizer
EP2816816A1 (fr) * 2013-06-20 2014-12-24 2236008 Ontario Inc. Stabilisateur spatial du champ sonore avec compensation de bruit structurée
US9099973B2 (en) 2013-06-20 2015-08-04 2236008 Ontario Inc. Sound field spatial stabilizer with structured noise compensation
US9106196B2 (en) 2013-06-20 2015-08-11 2236008 Ontario Inc. Sound field spatial stabilizer with echo spectral coherence compensation
US9271100B2 (en) 2013-06-20 2016-02-23 2236008 Ontario Inc. Sound field spatial stabilizer with spectral coherence compensation
US9743179B2 (en) 2013-06-20 2017-08-22 2236008 Ontario Inc. Sound field spatial stabilizer with structured noise compensation
US11798576B2 (en) 2014-02-27 2023-10-24 Cerence Operating Company Methods and apparatus for adaptive gain control in a communication system
US11463820B2 (en) 2019-09-25 2022-10-04 Oticon A/S Hearing aid comprising a directional microphone system

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