WO2009096958A1 - Système et procédé de limitation de parasites - Google Patents

Système et procédé de limitation de parasites Download PDF

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Publication number
WO2009096958A1
WO2009096958A1 PCT/US2008/052459 US2008052459W WO2009096958A1 WO 2009096958 A1 WO2009096958 A1 WO 2009096958A1 US 2008052459 W US2008052459 W US 2008052459W WO 2009096958 A1 WO2009096958 A1 WO 2009096958A1
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WIPO (PCT)
Prior art keywords
noise
processed
signal
bands
electrical signals
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Application number
PCT/US2008/052459
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English (en)
Inventor
Tomas Fritz Gaensler
James A. Johanson
Peter Kroon
Min Liang
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Agere Systems Inc.
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Publication date
Application filed by Agere Systems Inc. filed Critical Agere Systems Inc.
Priority to PCT/US2008/052459 priority Critical patent/WO2009096958A1/fr
Publication of WO2009096958A1 publication Critical patent/WO2009096958A1/fr

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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
    • 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
    • G10L21/0216—Noise filtering characterised by the method used for estimating noise
    • G10L21/0232—Processing in the frequency domain

Definitions

  • the present invention relates to a method and system for applying different noise suppression algorithms for noise suppression of a voice signal.
  • a system for noise suppression of a voice signal is based on time domain filtering of the voice signal or is based on spectral subtraction, wherein a spectral estimate or a spectral prediction of the noise wave forms are subtracted from the voice signal.
  • US 6,035,048 discloses a stationary noise suppressor system based on spectral subtraction.
  • the audio (voice) signal is analyzed by an analysis algorithm and divided into frequency sub-bands of noise sub-bands and voice sub-bands.
  • a signal gain function is applied to the sub-bands to obtain suppression gains for the noise sub-bands.
  • the respective voice sub-bands are synthesized into an enhanced signal bandwidth in which the noise-sub- band gains are attenuated.
  • US 2003/0147538 Al discloses a spatial noise suppressor system based on spectral subtraction for attenuating directional noise.
  • Various microphones in an array of two or more microphones receive separate inputs of a voice signal.
  • the directional noise will vary when received by the various microphones, due to propagation speed characteristics and/or phase change characteristics. Such characteristics differ from corresponding characteristics of stationary noise inputs.
  • a spatial noise suppression algorithm is applied to the voice signal arrays to segregate directional noise sub-bands from the desired voice sub- bands. Then, a synthesizer sums the powers of the directional noise sub-bands, and the powers of the input voice signal arrays. Any high-number signals are attenuated to suppress directional noise on an output of the voice signal.
  • US 2007/0150268 Al discloses a system for noise suppression of a voice signal based on spectral subtraction.
  • An array of three microphones provide three voice signal inputs to a stationary noise suppression module and a spatial noise reduction module.
  • the voice signal is converted to sub-bands by a beam- former module, and the stationary noise suppressor removes any residual ambient or instrumental stationary noise.
  • a first processing channel is required for removal of the stationary noise.
  • Another processing channel is required for removal of directional noise.
  • the three voice signal inputs at the microphones are decomposed into two quantities of spatial direction information.
  • a first quantity represents three microphone inputs converted to three sets of sub-bands.
  • a second quantity is based on summed combinations of the three sets of sub-bands.
  • Spatial noise attenuation gains are derived by a process of beam forming.
  • the synthesizer processes the sub-bands of the voice signal for attenuation of the fixed spatial noise gains.
  • An output of the synthesizer is free of the of the spatial noise and is combined with the stationary noise free output from the stationary noise suppressor module.
  • a noise suppressor system that combines different noise suppression systems has required two processing channels; a first processing channel to remove stationary noise, and a second processing channel to remove directional noise.
  • a first processing channel is required in which a stationary noise suppressor removes stationary noise and an output is produced by the stationary noise suppressor
  • a second processing channel is required in which a directional noise suppressor removes directional noise for synthesis with the output of the stationary noise suppressor.
  • a disadvantage of combining different noise suppressor systems is the need for processor capacity in chip architecture to remove noise in one processing channel, and the need for further processor capacity in chip architecture to remove noise in another processing channel. It would be desirable to combine different noise suppressor systems, while reducing the processor capacity requirements in chip architecture to attenuate noise with the different noise suppressor systems.
  • the invention refers to a method and apparatus combining different noise suppressors of an input signal to provide first and second sub-bands of the input signal and corresponding first and second noise attenuation gains, and combining the first and second attenuation gains with the first sub-bands of the input signal in a gain combiner in a single processing channel, and synthesizing the first and second noise attenuation gains with the first sub-bands to provide an output signal having less noise than the input signal.
  • the invention advantageously eliminates excessive signal processing capacity used in different processing channels to remove noise in one processing channel and to remove noise in another processing channel.
  • the invention advantageously eliminates a need for signal processing capacity to synthesize noise suppression gains with the second sub-bands of the input signal.
  • An embodiment of the invention refers to a method and apparatus combining different noise suppressors of an input signal to provide a first processing channel in which first sub-bands of the input signal are processed to provide a first output comprising first noise attenuation gains, and further to provide a second processing channel in which second sub-bands of the input signal are processed to provide a second output comprising second noise attenuation gains, and to combine the second processing channel and the first processing channel prior to synthesis of the first and second noise attenuation gains with one of, the first sub-bands or the second sub-bands, to form an output signal having reduced noise relative to the input signal.
  • a method includes; (a) analyzing an input signal into first sub-bands in a first processing channel and analyzing the input signal into second sub-bands in a second processing channel, (b) applying a first noise suppressor algorithm to the first sub-bands to calculate first noise attenuation gains (c) applying a second noise suppressor algorithm to the second sub-bands to calculate second noise attenuation gains, (d) combining the first noise suppression gains and the second noise suppression gains and the first sub-bands in a corresponding one of the first and second processing channels; (e) synthesizing the first and second noise suppression gains to attenuate noise in the input signal; and (f) outputting a noise-attenuated signal.
  • a gain combiner is frequency tuned to outputs comprising first and second noise suppression gains of the first and second processing channels; and a processing module synthesizes the first and second noise suppression gains with sub-bands of the input signal in one of, the first processing channel or the second processing channel.
  • Fig. 1 is a block diagram of a noise suppressor system having multiple exemplary noise suppressors.
  • Fig. 2 is a block diagram of a core NSl Module.
  • Fig. 3 is a graph of suppression gain compared to raw gain.
  • Fig. 4 is a block diagram of core modules of another noise suppressor system with another embodiment of two exemplary noise suppressors.
  • Fig. 5 is a block diagram of a signal transmission system. DETAILED DESCRIPTION
  • Fig. 1 discloses an embodiment of a noise suppressor system 100, which processes an input, noisy voice signal X(n) to attenuate noise frequency sub-bands that may be present in the input voice signal.
  • the noise suppressor system 100 comprises a combination of noise suppressors NSl and NS2.
  • Each of the noise suppressors NSl and NS2 comprises either a stationary noise suppressor or a directional noise suppressor, for example.
  • a stationary noise suppressor attenuates omnidirectional or stationary noise, for example, ambient noise (white noise) from internal circuitry operations or resulting from a person breathing into one or more microphones.
  • a voice (audio) signal is analyzed into sub-band signals, includes, but is not limited to an analysis algorithm disclosed by US 6,035,048 to Diethorn, or a beamformer module disclosed by US 2007/0150268 Al of Acero et al., or a single channel Wiener filter disclosed by US 2003/0147538 Al ofElko.
  • a directional noise suppressor attenuates directional noise such as, wind noise and background noise having such dynamics as varied azimuth direction with constant or varying decibels (dB). Further, the stationary noise suppressor is unable to calibrate the noise-to-speech ratio for improving speech intelligibility.
  • a directional noise suppressor for example, the noise suppressor NS2, requires an array of at least two microphones to receive the voice signal.
  • Examples of a directional noise suppressor includes, but is not limited to a spatial noise reduction module of US 2007/0150268 Al of Acero et al. or a multi-channel Weiner filter disclosed by US 2003/0147538 Al of Elko.
  • noise suppressor NS 1 processing a single signal sequence by a single noise suppressor, for example, the noise suppressor NS 1 , is not effective to suppress noise as would a combination of noise suppressors NSl, NS2, which can apply a combination of noise suppression algorithms, wherein the combination performs better than a single noise suppression algorithm.
  • the invention combines multiple noise suppressors to obtain more effective noise suppression than can be obtained by a single noise suppressor.
  • the combined noise suppressors NS 1 , NS2 advantageously convert the input voice signal to frequency domain sub-bands by applying different sub-band converters, including but not limited to an analysis filter bank as disclosed by US 6,035,048 to Diethorn, or a beam former module as disclosed by US 2007/0150268 A, or a multi-channel Wiener filter as disclosed by US2003/0147538 Al to Elko.
  • the corresponding noise suppressor NSl, NS2 analyzes the output of the beam former or Wiener filter to frequency domain sub-bands.
  • the input voice signal is analyzed into sub-bands to detect the presence of noise sub-bands.
  • the invention compensates for errors in sub-band analysis by using more than one signal-to-sub-band analyzers in respective processing channels.
  • An embodiment of the invention comprises a combination of multiple noise suppressors NSl and NS2, which convert the input voice signal to sub-bands by applying different signal-to-sub-band analyzers in respective processing channels.
  • Embodiments of the invention comprise, a combination of stationary and directional noise suppressors, or a combination of stationary noise suppressors, or a combination of directional noise suppressors.
  • Another embodiment of the invention comprises a combination of multiple noise suppressors NS 1 and NS2 applying different noise suppression algorithms to respective voice signal sub-bands in respective processing channels, and combining their outputs in a single processing channel prior to synthesis with voice signal sub-bands of the single processing channel.
  • a combination of noise suppressors NSl and NS2 share one or more of the microphone inputs X(n), Xl(n) and X2(n) of the input signal to be analyzed for the presence of noise frequency sub-bands. Accordingly, only two microphone inputs Xl(n) and X2(n) are used in an embodiment of the invention.
  • Another embodiment of the present invention provides a single microphone for splitting an input voice signal into one or more input signals, such as, X(n), Xl (n) and X2(n).
  • Each of the noise suppressors NSl and NS2 samples the input (voice) signal by segmenting the signal into frames of fixed millisecond durations, with the frames shifted with a millisecond frame shift to provide buffered, moving frames or windows for sampling.
  • the moving frames of input wave forms are converted to the frequency domain, and correlated into different frequency bins, by applying a waveform transform algorithm including, but not limited to a Fast Fourier Transform (FFT).
  • FFT Fast Fourier Transform
  • the sub-band components include noise frequency sub-band components when noise is present on the input signal. If there is no noise on the input signal the algorithm provides a unity noise suppression gain.
  • the noise suppressor NS 1 , NS2 generates the suppression gain for attenuation of the noise frequency sub-band components according to the following description.
  • Fig. 1 discloses a first exemplary processor module 100 of a first exemplary noise suppressor NSl having core modules to provide noise suppression.
  • Fig. 1 discloses a second exemplary processor module 110 having core modules of another exemplary noise suppressor NS2 to provide additional noise suppression that supplements the noise suppression provided by the first exemplary noise suppressor NS 1.
  • An analog baseband (ABB) chip is capable of supporting a two-channel input of NS2.
  • the second exemplary processor module 110 processes the noisy voice signal input in a corresponding AFB module 112 and a corresponding NS2 Core module 114.
  • the corresponding AFB module 112 performs corresponding operations similar to those described with reference to the AFB module 102 of the first exemplary noise suppressor NSl.
  • Fig. 1 discloses the block diagram modules of the exemplary NSl algorithm and NS2 algorithm.
  • the noise suppressor NS 1 comprises a first processing channel having three modules in cascade: an analysis filter bank (AFB) module 102, a NSl Core module 104 and a synthesis filter bank (SFB) module 106.
  • the exemplary noise suppressor NS2 comprises a second processing channel having three modules in cascade: a LMS based Calibration module 116, an analysis filter bank (AFB) module 112, and a core NS2 module 114.
  • the Analysis Filter Bank (AFB) module and the Synthesis Filter Bank (SFB) Module in a corresponding processing channel are paired operations.
  • the analysis and synthesis filter banks of the modules are based on the weighted overlap-add technique presented in R. Crochiere & L. Rabiner, "Multirate Digital Signal Processing,” Prentice Hall, 1983.
  • the analysis filter banks of the AFB module 102, 112 analyze the time- domain input signal X(n) into signal sub-band components X(k), Ys(n) and Yd(n) in the frequency domain.
  • the AFB modules 102, 112 analyze the input signal X(n) from a beam-former as in US 2007/0150268 Al of Acero et al, or from a multi-channel Weiner filter disclosed by US 2003/0147538 Al ofElko.
  • the NSl Core module 104 operates on X(k) at each noise component sub- band k to generate corresponding noise suppression gains Gd ns (k) for respective noise sub- bands.
  • An embodiment of a noise adaptive algorithm is disclosed by US 6,035,048 to Diethorn.
  • Another embodiment of a noise adaptive algorithm is disclosed by US 2003/0147538 Al to Elko.
  • G dns (k) is applied to the voice sub-band components X(k) at a gain combiner 108 in a single processing channel to generate a corresponding output Y(k).
  • the noise suppression gains are combined at the gain combiner 108 prior to synthesis with the input signal in the single processing channel.
  • the processing channel for the sub- bands X(k) is used for the single processing channel.
  • the single processing channel for the noise suppression gains Gd ns (k) can be used as an alternative, single processing channel.
  • synthesis filter bands of the SFB module 106 apply the noise suppression gains Gd ns (k) to the voice sub-bands X(k) to attenuate the noise sub- bands present in the corresponding, single processing channel.
  • the synthesis filter bands of the SFB module 106 are applied to Y(k) to synthesize the noise-suppressed sub-band components back to time-domain noise-attenuated signals Y(n).
  • Fig. 1 discloses an example of a frequency sub band X(k) for spectral analysis processing. It should be understood that the quantity X(k) represents one or more frequency sub-bands of voice and noise of the input signal to be processed.
  • the number of frequency sub-bands corresponds to the number of frequency bins for processing by the analysis filter bank AFB 102 and 112.
  • the number of sub-bands can be about ten in number or less or more, for example.
  • the processing capacity is lessened by reducing the number of frequency bins for processing.
  • the resolution of quality and trueness of the input signal demands a higher number of sub-bands for processing.
  • the noise suppressor output for each frequency bin is obtained by applying the noise classification algorithm to correlate the sub-band noise waveforms within respective frequency bins, and then applying the noise suppression algorithm to calculate an estimated or predicted, noise suppression gain of each noise frequency bin.
  • the suppression gain is calculated on the central frequency for each frequency bin.
  • Fig. 4 discloses another embodiment of a noise suppressor system comprised of an exemplary processor module 400, similar to the exemplary processor module 100, by having the AFB module 102, the NSl core module 104, the SFB module 106 and the gain combiner 118. Further, Fig. 4 discloses another embodiment of an exemplary processor module 410, similar to the exemplary processor module 110, by having the LMS based Calibration module 116, the AFB module 112 and the NS2 Core module 114.
  • the output GN S i2(k) of the NS2 Core module 114 was required to be applied to the sub-band components Ys(n) and Yd(n) of the AFB module 112 to generate noise suppression gain outputs, respectively, that suppress the noise sub-band components in each channel.
  • Such a processing operation would be similar to that of the NSl core module 104 applying the output GN S ii(k) to the output S(k) of the AFB module 102 to generate noise suppression gains that suppresses the noise sub-band components in the corresponding channel of the processor module 100.
  • two processing operations were required, either as two tandem stacked processing channels to remove noise or two parallel processing channels to remove noise.
  • a gain combiner 118 is frequency tuned to the outputs of the frequency domain noise suppression gains.
  • the output GN S i2(k) of the core NS2 module 114 is applied to the output X(k) of the AFB module 102, wherein the output X(k) includes the sub-band components of the input signal X(n) passed by the AFB module 102.
  • the gain combiner 118 is programmable for gain multiplication, addition, subtraction, or combination thereof. Accordingly, the invention combines frequency based processing of frequency bin sub-bands (especially noise) to calculate noise suppression gains obtained by applying two different algorithms in the single processing channel of the first exemplary noise suppressor processor module 100, and using the single processing channel of the processor module 100.
  • a first processing channel for the processor module 110 was required to calculate suppression gain and perform attenuation of noise, such as, directional noise, for example.
  • a second processing channel of the processor module 100 was required to calculate suppression gain and perform attenuation of noise, such as, fixed point noise (stationary noise) or dynamic noise (NSl), for example.
  • These processing channels when constructed as stacked processing channels, required stacked architectural processing capacity and copious computational load.
  • savings in processing requirements are attained by eliminating the need for combining the calculated gains GN S i2(k) with frequency bin sub-bands of the one processor module 110. Further savings in processing requirements are attained by providing the single SFB module 106 for synthesizing the time- domain signal Z(n) with the combined NSl and NS2 calculated gains, GNSii(k) and GNSi2(k), wherein the input Y(k) includes the combined inputs GN S ii(k) and GN S i2(k).
  • the use of a shared synthesis filter bank of the SFB module 106 reduces computational load, reduces memory requirements and reduces processor capacity for processing two different algorithms in two parallel processing channels, or in stacked processing channels.
  • Processing time is performed at a lower bit-rate in a shared synthesis filter bank as compared to stacked processing channels. Further, a true integration of two processing channels is attained. [0036] In converting back to the time-domain signal Z(n) at the SFB module 106, the
  • SFB module 106 applies a common phase for all n- frequencies of the output time-domain signal Z(n). It is noted that further savings in processing requirements are attained by eliminating the need to process the Ys(k) and Yd(k) frequency bin sub-bands back to the time-domain signals Xi(n) and S 2 Oi).
  • an input, noisy voice signal is processed in different processing channels by corresponding, different noise suppressor algorithms of any type to extract noise waveforms effectively.
  • the noise waveforms are processed in the frequency domain, independent of phase.
  • the two different processing channels can merge into a single processing channel for combining the extracted noise waveforms with suppression gains resulting from the application of two different algorithms, and for converting the noise-attenuated voice signal to the time-domain signal Z(n) for output in a single channel.
  • NS 1 are combined in various ways including, but not limited to serial minimum gains or maximum gains, parallel minimum gains or maximum gains, multiply gains and combinations thereof.
  • Fig. 4 discloses a gain combiner 418 in the form of a Gain Combination Operator which combines suppression gains produced by the exemplary NS2 noise suppressor algorithm with the sub-band waveforms X(k) produced by the exemplary NSl noise suppressor algorithm.
  • the gain combiner 418 is downstream in series with the NSl Core module 104.
  • the gain combiner 118 is upstream in series with the NSl Core module 104.
  • the Gain Combiner Operator 418, Fig. 4 is interchangeable with the gain combiner 118, Fig. 1, and is programmable with different settings enabling different solutions A, B or C to combine the gains of NSl and NS2 that will lead to different subjective qualities.
  • G(k) G dm (k)x G sns (k) for all k (2)
  • Fig. 5 discloses a (voice) signal transmission system 500. Two microphones
  • a switch 506 selectively inputs the voice signals received by both microphones 502 and 504 for combination in a combiner 508.
  • a noise suppressor system block 510 combines the modules 100 and 110 of Fig. 1, or the modules 400 and 410 of Fig. 4.
  • Embodiments of the microphone inputs are suitable for a voice transmission system 500, including but not limited to (a) a cellular telephone appliance, (b) a land-line telephone appliance, (c) a VOIP telephone appliance, (d) a GPS telephone appliance, (e) a wireless microphone, (f) a wireless or plug-in headset or (g) a channel selective voice transceiver for one of, or both of, radio bandwidth and television bandwidth.
  • a voice signal is processed with different noise suppressor algorithms to calculate noise suppression gains for different noise frequency bins, and the suppression gains are combined in a single processing channel to apply noise suppression on a single channel voice signal.
  • the application of different algorithms perform better than a single algorithm, and the single processing channel reduces the processor capacity requirements in chip architecture to attenuate noise in a voice signal with different noise suppression algorithms.
  • the invention combines multiple noise suppressors applying different algorithms. An embodiment of the invention will be described by referring to a dynamic noise suppressor (NSl) combined with a spatial noise suppressor (NS2).
  • NSl dynamic noise suppressor
  • NS2 spatial noise suppressor
  • the spatial noise suppressor NS2 is an adaptive noise suppressor added to two microphone inputs (two audio channel inputs), which provides better performance than one channel input (one microphone). Further, the invention is not limited to a noise suppressor added to two channel inputs, and embodiments of the invention includes noise suppressors added to one or more audio channel inputs to attenuate the level of background noise. [0045] This description of the exemplary embodiments is intended to be read in connection with the accompanying drawings, which are to be considered part of the entire written description.

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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)
  • Circuit For Audible Band Transducer (AREA)

Abstract

La présente invention concerne un procédé et un appareil pour un système de limitation de parasites comportant un premier algorithme de limitation de parasites qui effectue le traitement d'un signal d'entrée audio pour fournir des gains de première limitation de parasites, un second algorithme de limitation de parasite qui effectue le traitement du signal d'entrée pour fournir des gains de seconde limitation de parasites, et un combineur de gains accordé aux sorties des gains de limitation de parasites et assurant la combinaison les première et seconde suppression de bruit avec des sous-bandes de fréquence des gains du signal d'entrée dans un seul canal de traitement, et un module de synthèse de filtres à bande passante dans l'unique canal de traitement pour former un signal de sortie du domaine temporel de bruit réduit par rapport au signal d'entrée.
PCT/US2008/052459 2008-01-30 2008-01-30 Système et procédé de limitation de parasites WO2009096958A1 (fr)

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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2013030345A2 (fr) 2011-09-02 2013-03-07 Gn Netcom A/S Procédé et système de suppression de bruit d'un signal audio
EP2760020A1 (fr) * 2013-01-29 2014-07-30 QNX Software Systems Limited Maintien de stabilité spatiale au moyen d'un coefficient de gain commun
US9210505B2 (en) 2013-01-29 2015-12-08 2236008 Ontario Inc. Maintaining spatial stability utilizing common gain coefficient
WO2021071970A1 (fr) * 2019-10-11 2021-04-15 Plantronics, Inc. Suppression de bruit hybride
US11475869B2 (en) 2021-02-12 2022-10-18 Plantronics, Inc. Hybrid noise suppression for communication systems

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WO1998002983A1 (fr) * 1996-07-12 1998-01-22 Eatwell Graham P Filtre reducteur de bruit a faible retard
US5933495A (en) * 1997-02-07 1999-08-03 Texas Instruments Incorporated Subband acoustic noise suppression
US6925435B1 (en) * 2000-11-27 2005-08-02 Mindspeed Technologies, Inc. Method and apparatus for improved noise reduction in a speech encoder
WO2007059255A1 (fr) * 2005-11-17 2007-05-24 Mh Acoustics, Llc Suppression de bruit spatial dans un microphone double

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1998002983A1 (fr) * 1996-07-12 1998-01-22 Eatwell Graham P Filtre reducteur de bruit a faible retard
US5933495A (en) * 1997-02-07 1999-08-03 Texas Instruments Incorporated Subband acoustic noise suppression
US6925435B1 (en) * 2000-11-27 2005-08-02 Mindspeed Technologies, Inc. Method and apparatus for improved noise reduction in a speech encoder
WO2007059255A1 (fr) * 2005-11-17 2007-05-24 Mh Acoustics, Llc Suppression de bruit spatial dans un microphone double

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2013030345A2 (fr) 2011-09-02 2013-03-07 Gn Netcom A/S Procédé et système de suppression de bruit d'un signal audio
CN103907152A (zh) * 2011-09-02 2014-07-02 Gn奈康有限公司 用于音频信号噪声抑制的方法和系统
US9467775B2 (en) 2011-09-02 2016-10-11 Gn Netcom A/S Method and a system for noise suppressing an audio signal
EP2760020A1 (fr) * 2013-01-29 2014-07-30 QNX Software Systems Limited Maintien de stabilité spatiale au moyen d'un coefficient de gain commun
US9210505B2 (en) 2013-01-29 2015-12-08 2236008 Ontario Inc. Maintaining spatial stability utilizing common gain coefficient
WO2021071970A1 (fr) * 2019-10-11 2021-04-15 Plantronics, Inc. Suppression de bruit hybride
US11587575B2 (en) 2019-10-11 2023-02-21 Plantronics, Inc. Hybrid noise suppression
US11475869B2 (en) 2021-02-12 2022-10-18 Plantronics, Inc. Hybrid noise suppression for communication systems
US11776520B2 (en) 2021-02-12 2023-10-03 Plantronics, Inc. Hybrid noise suppression for communication systems

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