EP1343351A1 - Verfahren und Vorrichtung zur Verbesserung empfangener gewünschter Signale und Unterdrückung unerwünschter Signale - Google Patents

Verfahren und Vorrichtung zur Verbesserung empfangener gewünschter Signale und Unterdrückung unerwünschter Signale Download PDF

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Publication number
EP1343351A1
EP1343351A1 EP02388021A EP02388021A EP1343351A1 EP 1343351 A1 EP1343351 A1 EP 1343351A1 EP 02388021 A EP02388021 A EP 02388021A EP 02388021 A EP02388021 A EP 02388021A EP 1343351 A1 EP1343351 A1 EP 1343351A1
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EP
European Patent Office
Prior art keywords
signals
band
signal
frequency sub
source
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EP02388021A
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English (en)
French (fr)
Inventor
Nedelko Grbic
Sven Nordholm
Ingvar Claesson
Ulf Lindgren
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Telefonaktiebolaget LM Ericsson AB
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Telefonaktiebolaget LM Ericsson AB
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Priority to EP02388021A priority Critical patent/EP1343351A1/de
Publication of EP1343351A1 publication Critical patent/EP1343351A1/de
Withdrawn legal-status Critical Current

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    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/18—Methods or devices for transmitting, conducting or directing sound
    • G10K11/26—Sound-focusing or directing, e.g. scanning
    • G10K11/34—Sound-focusing or directing, e.g. scanning using electrical steering of transducer arrays, e.g. beam steering
    • 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

Definitions

  • This invention relates to enhancing of desired sound signals such as speech signals and to suppression of noise and interfering sound sources by using an array of microphones and adaptive beam forming.
  • a single microphone is located near the speaker's mouth.
  • the microphone can be part of a handset or of a headset.
  • the microphone or microphones will usually be in a position more remote to the speaker's mouth than in handheld communication.
  • Hands free communication includes the situations where eg a telephone handset or a microphone is placed on a conference table for picking up the speech of several speakers, and where a microphone is mounted in a car for picking up the speech of a person in the car, typically of the driver.
  • the microphone In hands free communication the microphone will usually be placed in a position more remote from the speaker's mouth than in handheld communications, whereby the received speech signal from the speaker will be weaker, which in turn reduces the signal-to-noise ratio, and the intelligibility of the speech will be reduced.
  • the beam former must be able to delay a plurality of frequencies individually. This is called wide frequency-band beam forming, and signals from a certain location are allowed to pass the system, whereas signals outside that location are attenuated or even cancelled.
  • a common way of achieving this is to use digital linear filters at each microphone signal.
  • beam-forming methods make use of fundamental properties of the spatial and/or the temporal distribution of both the speech source and the noise sources in order to improve the speech signal quality.
  • beam-forming methods are either fixed or adaptive.
  • Fixed beam formers are fundamentally based on modelled assumptions on the speech signal and the noise field. Based on the assumed model optimal beam formers can be constructed. Optimal function is only guaranteed for perfect model matching.
  • Adaptive beam formers are used to track variations and to compensate for model mismatch.
  • adaptive beam formers are based on continuous estimates of spatial and statistical information contained in the received speech and noise signal. In general, they are more complex to implement and require complex computations.
  • VAD voice activity detector
  • DTD double talk detector
  • Optimal beam formers exist such as the Signal-to-Noise plus Interference Beam former (SNIB) [1], and the Minimum Mean Squares Error Beam former (MMSEB).
  • SNIB Signal-to-Noise plus Interference Beam former
  • MMSEB Minimum Mean Squares Error Beam former
  • the mean signal output power is expressed as a function of the filter weights in the beam former, and the optimal weights, which maximises the output signal-to-noise plus interference ratio Q will have to be defined.
  • MSEB Minimum Mean Squares Error Beam former
  • Beam formers can be adequately described both in the time-domain and in the frequency-domain, since the measuring unit of frequency (s -1 ) is the inverse of the measuring unit of time (s).
  • the invention uses an array of two or more microphones, and the broadband signal from each microphone is passed through a bank of band pass filters separating each broadband signal into several frequency sub-bands.
  • the band pass filtered signals pertaining to the same frequency sub-band are beam formed in adaptive beam formers.
  • a single beam formed broadband signal is reconstructed.
  • the sensitivity of the microphone array is thereby focused in a region including the desired sound source, whereby sound signals originating outside that region are suppressed.
  • the beam forming is performed in frequency sub-bands, which requires less computational power than broadband beam forming. The method thus lends itself to the use in mobile communications devices such as mobile telephones.
  • the spatial selectivity of the microphone array is beam formed to the speaker, whereby disturbing sound sources are suppressed.
  • Point sources that can be suppressed include speaking persons other than the user, and loudspeakers such as a loudspeaker of a hands free communications device and the loudspeakers of a car stereo system and even moving sources.
  • Diffuse fields that can be suppressed include ambient noise and reverberation in the room.
  • the invention requires information on the desired signal source. Such information is acquired at times when there is reason to believe that only insignificant noise is present, and the system then records sound signals from the desired sound source alone, eg speech from a speaker, and calculates and stores an estimate of the source correlation matrix and an estimate of the source signal cross correlation vector.
  • the acquisition of the source signal alone can be done in an initial phase where the user selects a mode of operation therefor, or the device using the invention can use eg a voice activity detector to detect voice activity of a speaker, and at instances with only insignificant noise the speaker's voice is recorded and analysed.
  • a first plurality of I microphones M1 - Ml are arranged for receiving sound signals from a speaker.
  • the plurality of microphones have fixed positions relative to each other thus forming a fixed array, and their number I will be adapted to the actual use.
  • a higher number of microphones will typically be used such as four, six or more.
  • any type of microphone can be used.
  • Each microphone outputs an electrical signal representing the sound signal received by the microphone.
  • the electrical output signal from the microphones can be an analogue signal or a digital signal, and in the latter case the microphones will have an analogue-to-digital (A/D) converter.
  • the output signal of each microphone is input to an individual one of a first plurality of I filter banks, which are capable of receiving and processing the signals in analogue or digital form as output by the microphones.
  • I filter banks which are capable of receiving and processing the signals in analogue or digital form as output by the microphones.
  • there is one filter bank for each microphone but by analogue or digital multiplexing methods one filter bank can be used for several microphones.
  • each filter bank has a second plurality of K band pass filters where each band pass filter lets a predetermined band of frequencies pass through the filter, so that each filter covers a distinct band of frequencies derived from the microphone output signal.
  • each bank of band pass filters thus outputs a second plurality of K band pass filtered signals covering distinct frequency bands.
  • I filter banks each having K band pass filters lends it self to implementation in digital circuits, and in practice the illustrated banks of parallel band pass filters will be implemented using digital signal processing.
  • a second plurality of K beam formers each receive a first plurality of I inputs of band pass filtered signals, ie one from each filter bank, where the I band pass filtered signals all cover the same frequency band.
  • the corresponding beam former focuses the sensitivity of the microphone array to a beam or region including the desired sound source, which in this case is a speaking person.
  • the outputs of the K beam formers are fed as input signals to a unit in which a single channel wide frequency-band output signal is reconstructed by combining the K beam formed signals.
  • FIG. 1 the block diagram in figure 1 is used as an illustration for explaining the invention.
  • the invention is preferably implemented in software controlled digital circuits, in which case the illustrated individual blocks in figure 1 will not be distinct from each other. Rather, the software controlled digital circuits will perform the described operations.
  • the invention uses a new algorithm called the Calibrated Weighted Recursive Least Squares (CW-RLS) algorithm. Characteristic features of this algorithm are the introduction of a weighting factor that is used on the observed signal correlation matrix estimates and the use of pre-calculated source correlation estimates.
  • CW-RLS Calibrated Weighted Recursive Least Squares
  • the MMSE optimal beam former weighting factors in frequency sub-band k can be expressed as follows where k is the frequency sub-band number, N is the sample number, y (k) (n) is the output of the beam former, and s (k) r (n) is reference information on the signal source alone. This information is not directly available, or it cannot be expected to be available, and it therefore has to be measured and estimated separately. This is done in a calibration sequence with no or only insignificant background noise, ie the desired signal from the desired signal source such as a speaking person alone. This calibration signal will represent the temporal and spatial information about the desired source.
  • CW-RLS Calibrated Weighted Recursive Least Squares
  • An algorithm is thereby obtained that follows the statistical variations in the observed sound signals or data, when the beam former operates in a non-stationary environment. Calculation of the sum gives the same relationship as in equation (3), but the correlation matrix estimates of the observed data will be in accordance with the following equation: where the least squares solution is given by equation (5). Since the correlation estimates from the calibration sequence, equation (4), are gathered in advance, a recursive update formula for each sample of the new data observation vector x (k) (n) can be formulated.
  • R ⁇ (k) (n) R ⁇ ( k ) ss ( N ) + R ⁇ xx ( k ) (n) where it is desired to recursively update the inverse of this matrix. This is done using the Matrix-Inversion Lemma [2].
  • the total correlation matrix is updated at sample instance n according to
  • This updating is that the total correlation matrix is weighted, and that both the rank one "correction term" x (k) (n)x (k) H (n) and the fraction (1- ⁇ ) of the estimated source correlation matrix, or calibration correlation matrix, R ⁇ ( k ) ss ( N ) multiplied by the weighting factor, are added.
  • This updating can be implemented directly in a two-step procedure using the Matrix-Inversion Lemma [2], however, this will require complex power and time-consuming calculations of the inverse of the estimated source correlation matrix R ⁇ ( k ) ss ( N ) for each step of updating. Such complex power and time-consuming calculations are undesirable.
  • One way to circumvent the matrix inversion and thus substantially reduce the complexity of the calculations is to update the total correlation matrix by adding scaled eigenvectors of the estimated source correlation matrix, which will result in several, and simpler, rank one updates as where ⁇ ( k ) p is the p:th eigenvalue, and q ( k ) p is the p:th eigenvector of the
  • the weighted optimal recursive least squares solution at sample instant n is then given by where the calibration correlation vector r ⁇ ( k ) s ( N ) is gathered and estimated in advance and is assumed to be uncorrelated with the observed data.
  • the method of beam forming according to the invention has two main phases.
  • the first phase information on the desired signal source alone is gathered.
  • the first phase will be referred to as the calibration phase.
  • the second phase is referred to as the operation phase.
  • the desired signal source such as a speaking person is active alone.
  • sound signals from a speaking person are captured by the array of microphones.
  • Output signals from the first plurality l microphones are filtered in the filter banks, whereby for each microphone a second plurality K of band pass filtered signals covering distinct frequency bands are derived from the microphone signals.
  • the estimated source correlation matrix R ⁇ ( k ) ss is calculated and stored in a memory. This is done simultaneously for all frequency sub-bands.
  • the calibration may be performed in an initial phase and in quiet environments, but the system will preferably perform the calibration also during the operation phase at times where there are reasons to believe that undesired sounds such as background noise are of minor importance and have a negligible influence on the estimation of the source correlation matrix.
  • the estimated source correlation matrix R ⁇ ( k ) ss is updated currently.
  • Methods of detecting such times for updating the estimated source correlation matrix are known and involve eg a voice activity detector (VAD).
  • the desired signal source eg a speaking person
  • the correlation matrices are stored in diagonalized form:
  • the eigenvectors q ( k ) i , the eigenvalues ⁇ ( k ) i , and the cross correlation vector r ⁇ ( k ) s (N), where 0 ⁇ k ⁇ K -1, are stored in memory for subsequent use in the operation phase.
  • the estimated source correlation matrix R ⁇ ( k ) ss and the estimated source signal spatial cross correlation vector r ⁇ ( k ) s are stored and available, either from a separate initial calibration phase or from a more recent updating.
  • the algorithm is then repeated for the next sample n+1, etc.
  • the microphone output signals are continuously decomposed into discrete frequency sub-bands.
  • the sub-band weighting factors w ( k ) are updated by making use of both the stored correlation estimates and of the actual microphone observations.
  • the totality of beam former output signals which each is a beam formed frequency sub-band time-domain signal, are input to a reconstruction filter bank.
  • the output of the reconstruction filter bank is taken as the estimate of the sound signal from the desired sound source.
  • the algorithm contains a step in which a rank one update of the correlation matrix is performed using scaled eigenvectors, one eigenvector for each new input data vector. This step adds correlation estimates from the source signal, whereby information gathered in the acquisition or calibration phase will remain a constant part of the correlation matrix, while the contributions form the undesired environmental noise will be subject to the forgetting factor ⁇ in the estimates.
  • the number K of frequency sub-bands is large enough for the frequency-domain representation to be accurate.
  • the delay caused by the frequency transformations is related to the number of frequency sub-bands.
  • Time-domain and frequency-domain representations are closely related, and the algorithm of the invention can easily be extended to a combination of time-domain and frequency-domain representations.
  • Each frequency sub-band signal can also be regarded as a time-domain signal samples at a reduced sampling rate, ie proportional to the frequency sub-band bandwidth, and having substantially only the frequencies in the sub-band.
  • the degrees of freedom for the band-pass filters are increased, while the number of sub-bands may be kept constant.
  • the lengths of the sub-band filters may differ between sub-bands, and the consequence is that a multi-resolution sub-band identification is obtained.
  • the definitions of the correlation matrix, the eigenvalue and eigenvector matrices follow directly, and the size of the matrices will be increased by the factor L (k) ⁇ L (k) for frequency sub-band number k .
  • the amount of memory needed to store the eigenvectors and the eigenvalues increases with increasing number of sub-band used.
  • the band-pass filtering or decomposition of the broadband microphone signals into frequency sub-bands is preferably done using a uniform Discrete Fourier Transform (DFT), eg as described in [6], to decompose the full-rate sampled signals x i (n) into K sub-band signals.
  • DFT Discrete Fourier Transform
  • the sub-bands are preferably created in such a way that a prototype filter with a low-pass characteristic is used to ensure that the response from the k -th sub-band is the same as that of the prototype filter, although centred at a normalized frequency 2 ⁇ k / K , whereby the set of K sub-bands will cover the whole frequency range.
  • the prototype filter equals one of the filters in the bank (usually the first filter), and the other filters are modulated versions of the prototype filter. Thus only the prototype filter needs to be created.
  • Each sub-band signal is thereby represented in the base band.
  • the filter bank should cover the entire frequency range, and a redundant, ie over-complete, frequency sub-band decomposition and reconstruction should be used.
  • the invention is not limited to using uniformly distributed frequency sub-bands or a modulated filter bank.
  • the sub-band decomposition is made over-sampled.
  • a time domain signal is reconstructed or synthesized from the beam formed frequency sub-band signals from the beam formers.
  • the beam formed frequency sub-band signals are up-converted from the base band to the actual frequency band, and summed in the reconstruction filter.
  • the microphone array can eg have six microphones in a linear configuration with a spacing of 50 mm between microphones, and the microphone array can be placed at a nominal distance of eg 350 mm from the speaker's mouth.
  • the number K of band pass filters in each filter bank can be in the range from 32 or less to 256 or more, typically 64.
  • n time signal sample number
  • sample instant x ( k ) i (n) observed signal from microphone i in frequency sub-band k at sample n
  • y output signal from beam formers z e j2 ⁇ f
  • xx observed/measured signal correlation matrix for frequency subband k R ⁇ ( k )
  • dd estimated noise (disturbance) correlation matrix for frequency subband k w ( k )
  • ls beam former weighting factors for frequency sub-band

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  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Acoustics & Sound (AREA)
  • Multimedia (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Otolaryngology (AREA)
  • Signal Processing (AREA)
  • Circuit For Audible Band Transducer (AREA)
  • Obtaining Desirable Characteristics In Audible-Bandwidth Transducers (AREA)
EP02388021A 2002-03-08 2002-03-08 Verfahren und Vorrichtung zur Verbesserung empfangener gewünschter Signale und Unterdrückung unerwünschter Signale Withdrawn EP1343351A1 (de)

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Cited By (9)

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Publication number Priority date Publication date Assignee Title
EP1475997A2 (de) * 2003-05-09 2004-11-10 Harman/Becker Automotive Systems GmbH Verfahren und System zur Kommunikationsverbesserung in einer rauschenden Umgebung
US7643641B2 (en) 2003-05-09 2010-01-05 Nuance Communications, Inc. System for communication enhancement in a noisy environment
US8260442B2 (en) * 2008-04-25 2012-09-04 Tannoy Limited Control system for a transducer array
US8724822B2 (en) 2003-05-09 2014-05-13 Nuance Communications, Inc. Noisy environment communication enhancement system
US9502050B2 (en) 2012-06-10 2016-11-22 Nuance Communications, Inc. Noise dependent signal processing for in-car communication systems with multiple acoustic zones
CN106303838A (zh) * 2015-06-25 2017-01-04 宏达国际电子股份有限公司 声音处理装置及方法
US9613633B2 (en) 2012-10-30 2017-04-04 Nuance Communications, Inc. Speech enhancement
US9805738B2 (en) 2012-09-04 2017-10-31 Nuance Communications, Inc. Formant dependent speech signal enhancement
US10623854B2 (en) 2015-03-25 2020-04-14 Dolby Laboratories Licensing Corporation Sub-band mixing of multiple microphones

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Cited By (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8724822B2 (en) 2003-05-09 2014-05-13 Nuance Communications, Inc. Noisy environment communication enhancement system
EP1475997A2 (de) * 2003-05-09 2004-11-10 Harman/Becker Automotive Systems GmbH Verfahren und System zur Kommunikationsverbesserung in einer rauschenden Umgebung
EP1475997A3 (de) * 2003-05-09 2004-12-22 Harman/Becker Automotive Systems GmbH Verfahren und System zur Kommunikationsverbesserung in einer rauschenden Umgebung
WO2004100602A3 (en) * 2003-05-09 2005-01-06 Harman Becker Automotive Sys Method and system for communication enhancement ina noisy environment
US7643641B2 (en) 2003-05-09 2010-01-05 Nuance Communications, Inc. System for communication enhancement in a noisy environment
US9002028B2 (en) 2003-05-09 2015-04-07 Nuance Communications, Inc. Noisy environment communication enhancement system
WO2004100602A2 (en) * 2003-05-09 2004-11-18 Harman Becker Automotive Systems Gmbh Method and system for communication enhancement ina noisy environment
US8260442B2 (en) * 2008-04-25 2012-09-04 Tannoy Limited Control system for a transducer array
US9502050B2 (en) 2012-06-10 2016-11-22 Nuance Communications, Inc. Noise dependent signal processing for in-car communication systems with multiple acoustic zones
US9805738B2 (en) 2012-09-04 2017-10-31 Nuance Communications, Inc. Formant dependent speech signal enhancement
US9613633B2 (en) 2012-10-30 2017-04-04 Nuance Communications, Inc. Speech enhancement
US10623854B2 (en) 2015-03-25 2020-04-14 Dolby Laboratories Licensing Corporation Sub-band mixing of multiple microphones
CN106303838A (zh) * 2015-06-25 2017-01-04 宏达国际电子股份有限公司 声音处理装置及方法
CN106303838B (zh) * 2015-06-25 2019-08-02 宏达国际电子股份有限公司 声音处理装置及方法

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