Acoustic Echo Cancellation Algorithms Research Articles

A Linear Neural Network-Based Approach to Stereophonic Acoustic Echo Cancellation

We propose a new adaptive filtering algorithm for stereophonic acoustic echo cancellation. This algorithm uses a linear single-layer feedforward neural network to efficiently decorrelate the tap-input vectors. It achieves an improvement in the misalignment convergence by means of applying the resulted decorrelated tap-input vectors to the coefficient update of the adaptive filters. The advantage of our approach as compared with existing techniques is that our algorithm, in use with the nonlinear preprocessor, can achieve a high rate of misalignment convergence without significantly degrading the quality and stereophonic image of the transmitted signals since our neural network operates on the tap-input vectors as opposed to the transmitted audio signals. We then show that we can achieve an efficient implementation for the proposed decorrelation method by considering the structure of the joint-input covariance matrix of the stereophonic signals.

An Accelerated Acoustic Echo Cancellation Algorithm Based on Parallel Subgradient Projection Technique

An Accelerated Acoustic Echo Cancellation Algorithm Based on Parallel Subgradient Projection Technique

Design and evaluation of digital signal processing algorithms for acoustic feedback and echo cancellation

This thesis deals with several open problems in acoustic echo cancellation and acoustic feedback control. Our main goal has been to develop solutions that provide a high performance and sound quality, and behave in a robust way in realistic conditions. This can be achieved by departing from the traditional ad-hoc methods, and instead deriving theoretically well-founded solutions, based on results from parameter estimation and system identification. In the development of these solutions, the computational efficiency has permanently been taken into account as a design constraint, in that the complexity increase compared to the state-of-the-art solutions should not exceed 50% of the original complexity.Full text available at http://hdl.handle.net/1979/2599

A Class of Sparseness-Controlled Algorithms for Echo Cancellation

In the context of acoustic echo cancellation (AEC), it is shown that the level of sparseness in acoustic impulse responses can vary greatly in a mobile environment. When the response is strongly sparse, convergence of conventional approaches is poor. Drawing on techniques originally developed for network echo cancellation (NEC), we propose a class of AEC algorithms that can not only work well in both sparse and dispersive circumstances, but also adapt dynamically to the level of sparseness using a new sparseness-controlled approach. Simulation results, using white Gaussian noise (WGN) and speech input signals, show improved performance over existing methods. The proposed algorithms achieve these improvement with only a modest increase in computational complexity.

A new fast Newton‐type adaptive filtering algorithm for stereophonic acoustic echo cancellation (SAEC)

AbstractThis paper addresses the problem of acoustic echo cancellation. We propose a new version of the fast Newton transversal filter algorithm for stereophonic acoustic echo cancellation applications. This algorithm can be viewed as an efficient implementation of the extended two‐channel fast transversal filter algorithm. Moreover, it fits naturally within the frame of the fast version of the recursive least‐squares (RLS) algorithm, applied to the two‐channel case. To stabilize the proposed two‐channel algorithm, we have adapted and then applied a new numerical stabilization technique that has been proposed recently. The computational complexity of the proposed two‐channel algorithm is less than half the complexity of the fastest two‐channel RLS versions and very close to that of the two‐channel normalized least mean squares algorithm when its predicting part length is chosen to be small. Simulation results and comparisons in term of complexities, convergence speed and tracking with the two‐channel algorithms are presented. Copyright © 2009 John Wiley & Sons, Ltd.

An improved new error estimation algorithm for optimal filter lengths for stereophonic acoustic echo cancellation

In this paper, we propose an new error estimate algorithm (NEEA) for stereophonic acoustic echo cancellation (SAEC) that is based on the error estimation algorithm (EEA) in [Nguyen-Ky T, Leis J, Xiang W. An improved error estimate algorithm for stereophonic acoustic echo cancellation system. In: International conference on signal processing and communication systems, ICSPCS’2007, Australia; December 2007]. In the EEA and NEEA, with the minimum error signal fixed, we compute the filter lengths so that the error signal may approximate the minimum error signal. When the echo paths change, the adaptive filter automatically adjusts the filter lengths to the optimum values. We also investigate the difference between the adaptive filter lengths. In contrast with the conclusions in [Khong AWH, Naylor PA. Stereophonic acoustic echo cancellation employing selective-tap adaptive algorithms. IEEE Trans Audio, Speech, Lang Process 2006;14(3):785–96, Gansler T, Benesty J. Stereophonic acoustic echo cancellation and two channel adaptive filtering: an overview. Int J Adapt Control Signal Process 2000;4:565–86, Benesty J, Gansler T. A multichannel acoustic echo canceler double-talk detector based on a normalized cross-correlation matrix. Acoust Echo Noise Control 2002;13(2):95–101, Gansler T, Benesty J. A frequency-domain double-talk detector based on a normalized cross-correlation vector. Signal Process 2001;81:1783–7, Eneroth P, Gay SL, Gansler T, Benesty J. A real-time implementation of a stereophonic acoustic echo canceler. IEEE Trans. Speech Audio Process 2001;9(5):513–23, Gansler T, Benesty J. New insights into the stereophonic acoustic echo cancellation problem and an adaptive nonlinearity solution. IEEE Trans. Speech Audio Process 2002; 10(5):257–67, Benesty J, Gansler T, Morgan DR, Sondhi MM, Gay SL. Advances in network and acoustic echo cancellation. Berlin: Springer-Verlag; 2001], our simulation results have shown that the filter lengths can be different. Our simulation results also confirm that the NEEA is better than EEA and SM-NLMS algorithm in terms of echo return loss enhancement.

Acoustic Echo Cancellation Using a Pseudocoherence Function in the Presence of Memoryless Nonlinearity

Acoustic echo cancellation (AEC) is critical for telecommunication applications involving two or more locations such as teleconferencing. It is also challenging because of loudspeaker's nonlinearity, real-time implementation requirement, and multipath effects of indoor environments. This paper addresses the nonlinear AEC problem. We use a Hammerstein model to describe the memoryless nonlinearity of loudspeaker concatenated with a linear room impulse response. We propose a method using a pseudo magnitude squared coherence (MSC) function to identify the nonlinearity in the Hammerstein system and develop an on-line AEC algorithm. Our method identifies nonlinearity without knowing the linear block in the Hammerstein system, which guarantees the stability of the algorithm and leads to a faster convergence rate. Moreover, several alternative criteria based on the MSC function are also proposed for nonlinearity identification. Effectiveness of the proposed algorithms is demonstrated through computer simulations.

Variable Step-Size NLMS Algorithm for Under-Modeling Acoustic Echo Cancellation

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> In acoustic echo cancellation (AEC) applications, where the acoustic echo paths are extremely long, the adaptive filter works most likely in an under-modeling situation. Most of the adaptive algorithms for AEC were derived assuming an exact modeling scenario, so that they do not take into account the under-modeling noise. In this letter, a variable step-size normalized least-mean-square (VSS-NLMS) algorithm suitable for the under-modeling case is proposed. This algorithm does not require any a priori information about the acoustic environment; as a result, it is very robust and easy to control in practice. The simulation results indicate the good performance of the proposed algorithm. </para>

An Improvement of the Two-Path Algorithm Transfer Logic for Acoustic Echo Cancellation

Adaptive filters for echo cancellation generally need update control schemes to avoid divergence in case of significant disturbances. The two-path algorithm avoids the problem of unnecessary halting of the adaptive filter when the control scheme gives an erroneous output. Versions of this algorithm have previously been presented for echo cancellation. This paper presents a transfer logic which improves the convergence speed of the two-path algorithm for acoustic echo cancellation, while retaining the robustness. Results from simulations show an improved performance, and a fixed-point DSP implementation verifies the performance in real-time

Double-Talk-Robust Prediction Error Identification Algorithms for Acoustic Echo Cancellation

The performance of an acoustic echo canceller may be severely degraded by the presence of a near-end signal. In such a double-talk situation, the variance of the echo path estimate typically increases, resulting in slow convergence or even divergence of the adaptive filter. This problem is usually tackled by equipping the echo canceller with a double-talk detector that freezes adaptation during near-end activity. Nevertheless, there is a need for more robust adaptive algorithms since the adaptive filter's convergence may be affected considerably in the time interval needed to detect double-talk. Moreover, in some applications, near-end noise may be continuously present and then the use of a double-talk detector becomes futile. Robustness to double-talk may be established by taking into account the near-end signal characteristics, which are, however, unknown and time varying. In this paper, we show how concurrent estimation of the echo path and an autoregressive near-end signal model can be performed using prediction error (PE) identification techniques. We develop a general recursive prediction error (RPE) identification algorithm and compare it to three existing algorithms from adaptive feedback cancellation. The potential benefit of the algorithms in a double-talk situation is illustrated by means of computer simulations. It appears that especially in the stochastic gradient case a huge improvement in convergence behavior can be obtained

Subband Affine Projection Algorithm for Acoustic Echo Cancellation System

We present a new subband affine projection (SAP) algorithm for the adaptive acoustic echo cancellation with long echo path delay. Generally, the acoustic echo canceller suffers from the long echo path and large computational complexity. To solve this problem, the proposed algorithm combines merits of the affine projection (AP) algorithm and the subband filtering. Convergence speed of the proposed algorithm is improved by the signal-decorrelating property of the orthogonal subband filtering and the weight updating with the prewhitened input signal of the AP algorithm. Moreover, in the proposed algorithms, as applying the polyphase decomposition, the noble identity, and the critical decimation to subband the adaptive filter, the sufficiently decomposed SAP updates the weights of adaptive subfilters without a matrix inversion. Therefore, computational complexity of the proposed method is considerably reduced. In the SAP, the derived weight updating formula for the subband adaptive filter has a simple form as ever compared with the normalized least-mean-square (NLMS) algorithm. The efficiency of the proposed algorithm for the colored signal and speech signal was evaluated experimentally.

Stereophonic acoustic echo cancellation employing selective-tap adaptive algorithms

Stereophonic acoustic echo cancellation has generated much interest in recent years due to the nonuniqueness and misalignment problems that are caused by the strong interchannel signal coherence. In this paper, we introduce a novel adaptive filtering approach to reduce interchannel coherence which is based on a selective-tap updating procedure. This tap-selection technique is then applied to the normalized least-mean-square, affine projection and recursive least squares algorithms for stereophonic acoustic echo cancellation. Simulation results for the proposed algorithms have shown a significant improvement in convergence rate compared with existing techniques.

A robust NLMS algorithm for acoustic echo cancellation

When an adaptive filter is applied for an acoustic echo canceler, realization of robustness in the presence of double talk is an important subject. In this paper, based on M-estimation, a robust statistical technique, a cost function expressing the normalized least-mean-square algorithm (NLMS), is modified to derive the gradient-limited NLMS (GL-NLMS) algorithm. This technique makes use of the statistical characteristic that the ratio of the error and reference signal levels has different distributions during single talk and double talk. The gradient used for updating in the NLMS algorithm is limited to a nonlinear form, so high robustness against double talk is achieved. © 2006 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 89(11): 1–9, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.20223

Acoustic echo cancellation and doubletalk detection using estimated loudspeaker impulse responses

In this paper, we present a new approach to acoustic echo cancellation and doubletalk detection for a teleconferencing system including a loudspeaker for which an estimate of the loudspeaker impulse response is available. The approach is general in the sense that it may be applied to most existing acoustic echo cancellation and doubletalk detection algorithms. We show that the new approach reduces the computational complexity for both the echo cancellation and the doubletalk detection algorithms. Furthermore, the numerical examples show that the new approach also may increase the echo cancellation and doubletalk detection performances.

Reduced-Complexity Transform-Domain Adaptive Algorithm With Selective Coefficient Update

This paper proposes a new low-complexity transform-domain (TD) adaptive algorithm for acoustic echo cancellation. The algorithm is based on decomposing the long adaptive filter into smaller subfilters and employing the selective coefficient update (SCU) approach in each subfilter to reduce computational complexity. The resulting algorithm combines the fast converging characteristic of the TD decomposition technique and the benefits of the SCU of low complexity with minimal performance losses. The improvement in convergence speed comes at the expense of a corresponding increase in misadjustment. To overcome this problem, a hybrid of the proposed algorithm and the standard TD LMS algorithm (TDLMS) is presented. The hybrid algorithm retains the fast convergence speed capabilities of the original algorithm while allowing for low final MSE. Simulations show that the hybrid algorithm offers a superior performance when compared to the standard TDLMS algorithm with less computational overhead.

Nonlinear acoustic echo cancellation based on volterra filters

This paper describes a nonlinear acoustic echo cancellation algorithm, mainly focused on loudspeaker distortions. The proposed system is composed of two distinct modules organized in a cascaded structure: a nonlinear module based on polynomial Volterra filters models the loudspeaker, and a second module of standard linear filtering identifies the impulse response of the acoustic path. The tracking of the overall system model is achieved by a modified normalized-least mean square algorithm for which equations are derived. Stability conditions are given, and particular attention is placed on the transient behavior of cascaded filters. Finally, results of real data recorded with Alcatel GSM material are presented.

New transform-domain adaptive algorithms for acoustic echo cancellation

This paper proposes new transform-domain (TD) adaptive algorithms for long order adaptive filters. The scheme is based on decomposing the long adaptive filter into smaller subfilters. Each subfilter uses a different error signal in its update equation thus providing reduced coupling between subfilters and consequent improvement in convergence speed. We consider in this paper least mean-square adaptation of each subfilter along with power normalization, and derive an analytical model for the mean-square performance of the algorithm. Analysis assumes correlated Gaussian input data and will show that gains in convergence speed come at the expense of high misadjustment. A hybrid of the proposed algorithm and the TDLMS is described that offers significant performance improvements since it can be tuned to achieve very fast convergence while allowing low misadjustment. Performance advantages of the hybrid algorithm and theoretical results are verified by simulation examples.

Variable step size filtered sign algorithm for acoustic echo cancellation

A new class of variable step size sign algorithms, tailored for acoustic echo cancellation, is proposed. The choice of the step size depends on the status of the algorithm: transient state, steady state or ‘double talk presence’ state. The switching rules between step sizes depend on the previous state, and employ some kind of hysteresis to ensure algorithm stability and effectiveness. Furthermore, the concept of input pre-whitening is used to drive the adaptive filter, yielding faster convergence rate. Simulation results are presented to support the proposed algorithm and to compare it with classical ones (sign and dual sign algorithms).

A psychoacoustic approach to combined acoustic echo cancellation and noise reduction

This paper presents and compares algorithms for combined acoustic echo cancellation and noise reduction for hands-free telephones. A structure is proposed, consisting of a conventional acoustic echo canceler and a frequency domain postfilter in the sending path of the hands-free system. The postfilter applies the spectral weighting technique and attenuates both the background noise and the residual echo which remains after imperfect echo cancellation. Two weighting rules for the postfilter are discussed. The first is a conventional one, known from noise reduction, which is extended to attenuate residual echo as well as noise. The second is a psychoacoustically motivated weighting rule. Both rules are evaluated and compared by instrumental and auditive tests. They succeed about equally well in attenuating the noise and the residual echo. In listening tests, however, the psychoacoustically motivated weighting rule is mostly preferred since it leads to more natural near end speech and to less annoying residual noise.

Audio recording and reproduction in CARROUSO: Getting closer to perfection?

State-of-the-art systems for spatial audio reproduction utilize two to six discrete playback channels. A problem inherent to these systems is the relatively small area where the listener is able to experience a true 3-D sound sensation. This so-called ‘‘sweet spot’’ can be significantly enlarged by using loudspeaker arrays in combination with wave field synthesis (WFS) technology, initially developed at Delft University. By following this approach, actual sonic spaces can be reproduced in their entirety and not only discrete multichannel representations thereof. While loudspeaker arrays can be used to reproduce sound fields, microphone arrays can be used for sound field capture and analysis. Having high-quality audio reproduction in mind, microphone array designs are presented that need to fulfill stricter requirements than what has been traditionally considered for microphone array applications. Information on acoustic source position is essential for WFS-based rendering techniques. As will be shown, joint audio–video object tracking proves to be efficient for this task. Moreover, full-duplex applications based on WFS technology, like high-quality teleconferencing or remote music teaching, call for sophisticated multichannel acoustic echo cancellation algorithms. The European project ‘‘CARROUSO’’ aims at developing, integrating, and building a real-time system that embraces all previously described technologies in an MPEG-4 context.