In handsfree tele- or video-communication, acoustic echoes arise due to the coupling between the loudspeakers and microphones. It is much more challenging to remove the undesired acoustic echoes for stereo or multi-channel tele-communication systems than for mono systems due to the non-uniqueness problem. While non-uniqueness can be prevented by introducing independent distortions into the left and right loudspeaker signals, stereo echo cancellation is more challenging in terms of convergence speed and computational complexity than mono echo cancellation. The proposed stereo echo control algorithm circumvents the non-uniqueness problem by using simplified echo path models consisting of delays and short-time spectral modification. It is shown that for reasonably symmetric systems the left and right echo path models are similar enough that a single echo path model can be used for estimating the total echo power spectrum and a gain filter for removing the echo from the microphone channels. The proposed algorithm is also applicable to multi-channel systems and the computational complexity is very low

Faller, Christof

Tournery, Christophe

In handsfree tele- or video-communication, acoustic echoes arise due to the coupling between the loudspeakers and microphones. It is much more challenging to remove the undesired acoustic echoes for stereo or multi-channel tele-communication systems than for mono systems due to the non-uniqueness problem. While non-uniqueness can be prevented by introducing independent distortions into the left and right loudspeaker signals, stereo echo cancellation is more challenging in terms of convergence speed and computational complexity than mono echo cancellation. The proposed stereo echo control algorithm circumvents the non-uniqueness problem by using simplified echo path models consisting of delays and short-time spectral modification. It is shown that for reasonably symmetric systems the left and right echo path models are similar enough that a single echo path model can be used for estimating the total echo power spectrum and a gain filter for removing the echo from the microphone channels. The proposed algorithm is also applicable to multi-channel systems and the computational complexity is very low.LCA

Infoscience - École polytechnique fédérale de Lausanne

STEREO ACOUSTIC ECHO CONTROL USING A SIMPLIFIED ECHO PATHMODEL1Christof Faller and 1Christophe Tournery1{christof.faller, christophe.tournery}@epfl.ch1Audiovisual Communications Laboratory, EPFL Lausanne, SwitzerlandABSTRACTIn handsfree tele- or video-communication, acoustic echoes arisedue to the coupling between the loudspeakers and microphones.It is much more challenging to remove the undesired acous-tic echoes for stereo or multi-channel tele-communication sys-tems than for mono systems due to the non-uniqueness prob-lem. While non-uniqueness can be prevented by introducing in-dependent distortions into the left and right loudspeaker signals,stereo echo cancellation is more challenging in terms of con-vergence speed and computational complexity than mono echocancellation. The proposed stereo echo control algorithm cir-cumvents the non-uniqueness problem by using simplified echopath models consisting of delays and short-time spectral modi-fication. It is shown that for reasonably symmetric systems theleft and right echo path models are similar enough that a singleecho path model can be used for estimating the total echo powerspectrum and a gain filter for removing the echo from the mi-crophone channels. The proposed algorithm is also applicable tomulti-channel systems and the computational complexity is verylow.1. INTRODUCTIONWhile from a theoretical point of view an acoustic echocanceler (AEC) can perfectly remove the echo without in-troducing distortions, in practice, often problems arise dueto non-linearities in the effective transfer function fromthe loudspeaker signals to the microphone signals. Suchnon-linearities are due to time drift when different clocksare used for audio input and output (e.g. VoIP using aweb-cam), overdriving of small loudspeakers (handsfreeportable devices), auto gain control, flaws in the analogcircuitry, etc.It has recently been shown that not only an acoustic echocanceler (AEC) can provide echo control for duplex com-munication, but also that an acoustic echo suppressor(AES), operating in a short-time spectral domain, can pro-vide a high degree of duplex capability. The above men-tioned problems, indicating the weaknesses of AEC inpractical situations, may suggest that an AES may be aviable alternative to an AEC despite of its potential forartifacts during doubletalk. In [1] AEC and AES werecompared in terms of speech quality during doubletalk,indicating a relatively small quality difference under non-ideal conditions.In [2] echo removal by means of spectral modification wasproposed for improving the robustness of a frequency do-main acoustic echo canceler. An AES without a need forestimating the acoustic echo path impulse response wasproposed in [3]. Recently, we proposed an improved AESusing a simplified echo path model [4], aiming at lowcomputational complexity and high robustness. The echopath is modeled by an overall delay parameter and a col-oration effect filter which captures the effect of the echopath in terms of short-time spectral modification.Since acoustic echo cancellation is more difficult forstereo or multi-channel tele-communication [5], AES mayalso be a viable alternative to AEC for this scenario.In this paper, we are proposing an AES similar to [4],but which is applicable for removing acoustic echoes forstereo and multi-channel tele-communication. To avoidthe non-uniqueness problem, we are assuming that thetele-communication clients use a reasonably symmetricloudspeaker and microphone setup. As will be shown, thesymmetry does not have to be very strict.The paper is organized as follows. Section 2 reviews thepreviously proposed AES algorithm which also forms thebasis of the proposed multi-channel AES algorithm. Theproposed AES algorithm, applicable for multi-channel au-dio signals, is described in Section 3. The results of anumber of simulations are presented in Section 4. Theconclusions are presented in Section 5.2. ACOUSTIC ECHO CONTROL USING ASIMPLIFIED ECHO PATHMODELUnlike AEC, an AES achieves echo attenuation throughmanipulating the magnitude spectrum of the microphonesignal in the frequency domain, while leaving the phasespectrum untouched. For noise suppression, a widelyadopted spectral manipulation algorithm is the paramet-ric Wiener filter (or sometimes called spectral subtraction[6]). If |Yˆ (i, k)| denotes an estimate of the magnitudespectrum of the echo signal with frequency index i andtime index k, a parametric Wiener filter based echo sup-IWAENC 2006 – PARIS – SEPTEMBER 12-14, 2006 1.y(n)x(n)nnSTFT STFTY (i, k)GV (i, k)SMCE ..GFCG(i, k)ISTFT e(n)dXd(i, k)Figure 1: Acoustic echo suppressor (AES) using a simpli-fied echo path model.pression algorithm can be expressed ase(n) = F−1[G(i, k)Y (i, k)] , (1)where e(n) is the echo-suppressed outgoing signal, Y (i, k)is the short time spectrum of the microphone signal, F−1[·]denotes the inverse Fourier transform, andG(i, k) =[max(|Y (i, k)|α − β|Yˆ (i, k)|α, 0)|Y (i, k)|α] 1α(2)is a Wiener gain filter, where α and β are design param-eters to control the echo suppression performance [7]. Ifthe echo is under-estimated, β > 1 is used, and β < 1 if itis over-estimated.Not the acoustic echo path is estimated, but merely aglobal delay parameter and a filter characterizing the col-oration effect of (the early part of) the acoustic echo path[4]. This representation (delay and coloration effect fil-ter) is largely insensitive to acoustic echo path changesand is thus more robust than conventional methods whichestimate the acoustic echo path. Additionally, the compu-tational complexity is significantly lower since much lessparameters need to be estimated.The described AES is illustrated in Figure 1. Short timeFourier transform (STFT) spectra are computed from theloudspeaker and microphone signals. A delay d betweenthe STFTs applied to microphone and loudspeaker signalis chosen such that most of the effect of the echo path im-pulse response is captured. The CE block in the figureestimates a real-valued coloration effect filter, GV (i, k),mimicking the effect of the early echo path. For obtainingan approximate echo magnitude spectrum, the estimateddelay and coloration effect filter are applied to the loud-speaker signal spectra,|Yˆ (i, k)| = GV (i, k)|Xd(i, k)| , (3)where d indicates that the spectrum is computed with awaveform that is delayed by d samples. Time smoothingof the gain filter can compensate for the fact that the latepart of the echo path is ignored. Note that (3) is not a pre-cise echo spectrum or magnitude spectrum estimate, but itcontains the information necessary for gain filter compu-tation (2) (GFC block).The coloration effect filter is computed as the magnitudeof the least squares estimatorGV (i, k) =∣∣∣∣ E{X∗d (i, k)Y (i, k)}E{X∗d (i, k)Xd(i, k)}∣∣∣∣ , (4)where ∗ denotes complex conjugate. Since the acousticecho path is likely to vary in time, GV (i, k) is estimatediteratively byGV (i, k) =a12(i, k)a22(i, k), (5)wherea12(i, k) = |X∗d (i, k)Y (i, k)|+ (1− )a12(i, k − 1)a22(i, k) = X∗d (i, k)Xd(i, k) + (1− )a22(i, k − 1) ,and  ∈ [0, 1] determines the time constant of the expo-nentially decaying estimation windowT =1fs, (6)where fs denotes the STFT spectrum sampling frequency.We use T = 1.5 s.To prevent that during periods of doubletalk the colorationeffect filter GV (i, k) diverges, we use two coloration ef-fect filters, similarly as two echo path models have beenused for conventional AEC [8]. The background filter,GV (i, k), is always adapted and a static foreground fil-ter, HV (i, k), is used. Whenever there is confidence thatGV (i, k) is a good estimate it is copied toHV (i, k), whichis used for echo estimation.3. MULTI-CHANNEL ACOUSTIC ECHOCONTROLWe observed that the coloration correction filters corre-sponding to the echo paths of two loudspeakers in a desk-top stereo system are quite similar for the left and rightloudspeakers (if there is reasonable symmetry, i.e. if themicrophone is not placed much closer to one loudspeakerthan the other). We did this experiment with an omni-directional microphone. If directional microphones areIWAENC 2006 – PARIS – SEPTEMBER 12-14, 2006 2G(i, k)....x1(n)x2(n)xL(n)LSC..MSC...y1(n)y2(n)yM (n)STFTSTFTSTFTSMSMSMISTFTISTFTISTFT..... e1(n)e2(n)eM (n)STFTSTFTSTFT|X(i, k)||Y (i, k)|GFCAEEMono AES.Figure 2: Multi-channel acoustic echo suppressor (AES)using a single simplified echo path model.used, the coloration effect is still similar, but the over-all gain depends on the directions from which the directsound and strongest reflections arrive at the microphone.Often stereo microphones are designed such that the sumof left and right has an omnidirectional property (i.e. thegain of the left and right sum does not depend on direc-tion). This omnidirectional property of the sum signalmotivated us to combine the left and right microphone sig-nal spectra and treat the combined spectrum the same asa single microphone spectra for gain filter G(i, k) com-putation. Spinning this thought further, we also tried tocombine the loudspeaker signals to a single signal for gainfilter computation. In the end, we had a system effec-tively using mono gain filter computation applicable forstereo and multi-channel AES and thus avoiding the non-uniqueness problem. In the following, we are describingthis process in detail.Figure 2 shows how a scheme for mono AES is extendedfor multi-channel acoustic echo suppression. Note that theAEE block in the figure corresponds to a method for esti-mating an echo signal spectrum, e.g. by applying a de-lay and coloration correction to the loudspeaker signal,i.e. (3). A loudspeaker signal combiner (LSC block in thefigure) combines the loudspeaker signal spectra and gen-erates a “combined” magnitude spectrum |X(i, k)|. Theloudspeaker signals are combined as|X(i, k)| = LXl=1gxl |Xl(i, k)|θ! 1θ, (7)where θ controls the combination process and gxl areweighting factors for each signal. We use θ = 2 andgxl = 1.−0.200.20.4x 1−0.200.20.4x 2−0.200.2y 1, e 1−0.200.2y 2, e 20 5 10 15 20 25 30204060ERLE [dB]TIME [s]Figure 3: Shown are: Left and right loudspeaker signals(x1 and x2), left and right microphone signals (y1, y2, dot-ted), left and right echo suppressed signals (e1, e2, solid),and the total ERLE in dB.Similarly, a microphone signal combiner (MSC) com-bines the microphone signal spectra,|Y (i, k)| = MXm=1gym |Ym(i, k)|λ! 1λ, (8)where λ controls the combination process and gym areweighting factors. We use λ = 2 and gym = 1.Given the combined magnitude spectra, |X(i, k)| and|Y (i, k)|, the gain filter, G(i, k), is computed similarly asin the mono AES case, as illustrated in Figure 2. That is,the echo magnitude spectrum |Yˆ (i, k)| is estimated andthe gain filter G(i, k) (2) is computed. Spectral modifi-cation is then applied to each of the microphone signals1 ≤ m ≤ M individually, using the same gain filterG(i, k),Em(i, k) = G(i, k)Ym(i, k) . (9)The echo suppressed output signals em(n) are obtained byapplying the inverse STFT with overlap add to Em(i, k).4. SIMULATIONSThe audio signals are processed in blocks of length 10ms.The simulations are carried out with 16 kHz sampling fre-quency, for which blocks of 160 samples are processedat a time. A FFT of size 512 is used with a sine win-dow (analysis and synthesis) of length 320 with 50% win-dow hop size. The computational complexity of the pro-posed scheme is much lower than a conventional AEC,since only the real-valued coloration effect filter valuesGV (i, k) need to be estimated as opposed to the echo pathIWAENC 2006 – PARIS – SEPTEMBER 12-14, 2006 3GV510150123H V510150123G  [dB]TIME [s]0 5 10 15 20 25 3051015−30−20−100Figure 4: Shown are the coloration correction filter, GV ,as a function of time and frequency (top panel), the fore-ground filter,HV , that is actually used (middle panel), andthe gain filter G used for echo removal.with many more parameters (filter taps). For further re-ducing complexity, we are combining and jointly process-ing STFT spectral coefficients, mimicking the frequencyresolution of the auditory system. On a 1.6 GHz PentiumM based laptop computer, the proposed algorithm needs1.2 % processing power for two-channel stereo and a sam-pling rate of 16 kHz.We use α = 2 and β = 2.5 in (2). Due to the rela-tively large β parameter, the system becomes less sensitivewith respect to asymmetry of the loudspeaker setup. Ex-tensive testing with our real-time stereo tele-conferencingsystem implies that indeed the symmetry requirement isonly weak, e.g. it is not a problem if the microphone istwice as close to one loudspeaker than the other one.A dialogue sequence is used, starting with far-end onlyspeech on the right (right loudspeaker signal), followedby far-end only speech on the left (left loudspeaker sig-nal), followed by near-end only speech, and concludingwith far-end and near-end speech simultaneously (dou-bletalk). The signal-to-noise ratio of the loudspeaker andmicrophone signals are 20 dB. Impulse responses mea-sured with a stereo desktop system and coincident pairstereo microphone with 4096 taps are used for generatingthe loudspeaker and microphone signals.The top four panels of Figure 3 show the loudspeaker sig-nals, x1(n) and x2(n) and the microphone signals, y1(n)and y2(n) (indicated as dotted lines), resulting from thedescribed dialogue sequence. The third and fourth panelalso show the echo suppressed stereo AES output sig-nals, e1(n) and e2(n) (indicated as solid lines). The bot-tom panel shows the total echo return loss enhancement(ERLE) in dB.The ERLE, e1(n), and e2(n) imply that during far-endonly speech the echo is instantly suppressed. The instantsuppression in the beginning is due to the initial valuesfor GV (i, k) which are such that the echo is overesti-mated initially and thus suppressed. The near-end onlyspeech gets through unimpaired. When the far-end speechchanges from left to right, echo stays fully suppressedas desired. The doubletalk is let through as indicated bye1(n), e2(n), and the ERLE in the figure.Figure 4 shows the coloration effect filter GV (i, k) forthe same simulation. GV (i, k) does not notably changewhen during the first 15 s the far-end speech moves fromright to left, indicating, as assumed, thatGV (i, k) does notstrongly depend on whether sound is emitted from the leftor right loudspeaker. The foreground filter, HV , actuallyused for echo estimation stays relatively constant over thewhole simulation, also during doubletalk, indicating ef-fectivity of the doubletalk control. The gain filter,G(i, k),used for echo removal is also shown in the figure.5. CONCLUSIONSExtension of a previously proposed algorithm for acous-tic echo suppression for stereo and multi-channel tele-conferencing was proposed. For computing the gain filterfor echo removal, single combined loudspeaker and mi-crophone spectra are used. The so-obtained gain filter isapplied to each of the microphone signals. Simulationsand real-time implementation indicate effectivity of theproposed algorithm.6. REFERENCES[1] F. Wallin and C. Faller, “Perceptual quality of hybrid echocanceler/suppressor,” in Proc. ICASSP, May 2004.[2] C. Avendano, “Acoustic echo suppression in the STFT do-main,” in Proc. IEEE Workshop on Appl. of Sig. Proc. toAudio and Acoust., Oct. 2001.[3] C. Faller and J. Chen, “Suppressing acoustic echo in a sam-pled auditory envelope space,” IEEE Trans. on Speech andAudio Proc., vol. 13, no. 5, pp. 1048–1062, Sept. 2005.[4] C. Faller and C. Tournery, “Estimating the delay and col-oration effect of the acoustic echo path for low complexityecho suppression,” in Proc. Intl. Works. on Acoust. Echoand Noise Control (IWAENC), Sept. 2005.[5] M. M. Sondhi, D. R. Morgan, and J. L. Hall, “Stereophonicacoustic echo cancellation - an overview of the fundamentalproblem,” IEEE Signal Processing Lett., vol. 2, pp. 148–151, Aug. 1995.[6] S. F. Boll, “Suppression of acoustic noise in speech usingspectral subtraction,” IEEE trans. Acoust. Speech Sig. Pro-cessing, vol. 27, no. 2, pp. 113–120, Nov. 1979.[7] W. Etter and G. S. Moschytz, “Noise reduction by noise-adaptive spectral magnitude expansion,” J. Audio Eng. Soc.,vol. 42, pp. 341–349, May 1994.[8] K. Ochiai, T. Araseki, and T. Ogihara, “Echo canceler withtwo echo path models,” IEEE trans. on Communications,vol. 25, no. 6, pp. 589–595, June 1977.IWAENC 2006 – PARIS – SEPTEMBER 12-14, 2006 4

Stereo Acoustic Echo Control Using A Simplified Echo Path Model

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Stereo Acoustic Echo Control Using A Simplified Echo Path Model

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