Filters For Acoustic Echo Cancellation Research Articles

Proximal Normalized Subband Adaptive Filtering for Acoustic Echo Cancellation

In this paper, we propose a novel normalized subband adaptive filter algorithm suited for sparse scenarios, which combines the proportionate and sparsity-aware mechanisms. The proposed algorithm is derived based on the proximal forward-backward splitting and the soft-thresholding methods. We analyze the mean and mean square behaviors of the algorithm, which is supported by simulations. In addition, an adaptive approach for the choice of the thresholding parameter in the proximal step is also proposed based on the minimization of the mean square deviation. Simulations in the contexts of system identification and acoustic echo cancellation verify the superiority of the proposed algorithm over its counterparts.

Variable tap-length non-parametric variable step-size NLMS adaptive filtering algorithm for acoustic echo cancellation

In teleconferencing and communication systems, the use of Loudspeaker Enclosure Microphone device leads to undesired echoes. To reduce these echoes, an acoustic echo canceller is used. In this paper, we propose a Variable Tap-length Non-Parametric Variable Step-Size NLMS (VT-NPVSS-NLMS) algorithm based on adaptive filtering for acoustic echo cancellation. The step-size is adjusted without the need for tuning too many parameters, using only the square of the average autocorrelation of a priori and a posteriori estimates of error. Moreover, the tap-length is varied to facilitate a high convergence speed and a small bias in tap-length from the optimum length. Hence, such a combination of the variable step-size algorithm with a variable tap-length provides faster convergence and reduced steady-state mean square error. The performance of the proposed algorithm is evaluated in terms of steady-state and transient mean square error. The advantages of the proposed algorithm, as compared to other adaptive algorithms, are presented using simulation results. From the results, we infer that for the VT-NPVSS-NLMS, the convergence speed is increased and the steady-state mean square error is reduced when compared with the conventional NLMS and the variable-step-size NLMS algorithm with a fixed tap-length.

Efficient multichannel acoustic echo cancellation using constrained tap selection schemes in the subband domain

Acoustic echo cancellation (AEC) is a key speech enhancement technology in speech communication and voice-enabled devices. AEC systems employ adaptive filters to estimate the acoustic echo paths between the loudspeakers and the microphone(s). In applications involving surround sound, the computational complexity of an AEC system may become demanding due to the multiple loudspeaker channels and the necessity of using long filters in reverberant environments. In order to reduce the computational complexity, the approach of partially updating the AEC filters is considered in this paper. In particular, we investigate tap selection schemes which exploit the sparsity present in the loudspeaker channels for partially updating subband AEC filters. The potential for exploiting signal sparsity across three dimensions, namely time, frequency, and channels, is analyzed. A thorough analysis of different state-of-the-art tap selection schemes is performed and insights about their limitations are gained. A novel tap selection scheme is proposed which overcomes these limitations by exploiting signal sparsity while not ignoring any filters for update in the different subbands and channels. Extensive simulation results using both artificial as well as real-world multichannel signals show that the proposed tap selection scheme outperforms state-of-the-art tap selection schemes in terms of echo cancellation performance. In addition, it yields almost identical echo cancellation performance as compared to updating all filter taps at a significantly reduced computational cost.

Wavelet based ICA using maximisation of non-Gaussianity for acoustic echo cancellation during double talk situation

In this paper a new wavelet based Independent Component Analysis (ICA) is proposed for Acoustic Echo Cancellation (AEC) in the presence of double talk scenario. Conventional Echo cancellation systems that use adaptive filter for AEC fails in the double talk situation, which demands a double talk detector. In the proposed method, the near end speech is separated from the acoustic echo by using the measure of maximising the Non-Gaussianity of ICA using kurtosis and Negentropy without the need of double talk detector. The simulations show that the proposed wavelet based ICA method provides higher cancellation of echo with less computation time.

A novel sub-band adaptive filtering for acoustic echo cancellation based on empirical mode decomposition algorithm

Acoustic echo cancellation is one of the most severe requirements in hands-free telephone and teleconference communication. This paper proposes an Empirical Mode Decomposition (EMD)-based sub-band adaptive filtering structure, which applies the EMD-based algorithm dealing with the far-end speech signal and the microphone output to obtain two sets of intrinsic mode functions (IMFs). In addition, each IMF set is separated into different bands based on the power spectral density (PSD) of every IMF. Experiment signals were collected from a medium-size office room and simulations were taken under different conditions by three types of EMD-based algorithms. Results show that the proposed structure is able to model the transfer function of the unknown environment and track the change of the room much faster than the normalized adaptive filtering structure. The ensemble EMD (EEMD) algorithm and the noise-modulated EMD (NEMD) are proved to have better performance than the EMD algorithm in terms of echo return loss enhancement.

A Generalized Proportionate Subband Adaptive Second-Order Volterra Filter for Acoustic Echo Cancellation in Changing Environments

The performance of a typical linear echo canceller is limited by changes that occur in the acoustic echo path along with nonlinear echoes arising from electrodynamic loudspeaker distortion. This paper presents a subband structure based on proportionately adapted second-order Volterra filters for acoustic echo cancellation under these adverse conditions. The proposed structure allows the time and frequency domain nature of echo path changes to be exploited, resulting in faster convergence and tracking compared to an equivalent fullband structure while requiring significantly less computational complexity. Experimental results, based on measured data from a practical hands-free environment under changing conditions, demonstrate the improved echo cancellation performance of the proposed structure.

Adaptive combination of subband adaptive filters for acoustic echo cancellation

In hands-free telephones and teleconferencing systems, acoustic echo cancellers are required, which are often implemented by adaptive filters. In these applications, the speech input signal of the adaptive filter is highly correlated and the impulse response of the echo path is very long. These characteristics will slow down the convergence rate of the adaptive filter if the well-known normalized least-mean-square (NLMS) algorithm is used. The normalized subband adaptive filter (NSAF) offers a good solution to this problem because of its decorrelating property. However, similar to the NLMS-based adaptive filter, the NSAF requires a tradeoff between fast convergence rate and small steady-state mean-square error (MSE). In this paper, we propose an adaptive combination scheme to address this tradeoff. The combination is carried out in subband domain and the mixing parameter that controls the combination is adapted by means of a stochastic gradient algorithm which employs the sum of squared subband errors as the cost function. The performance of the proposed combination scheme is evaluated in the context of acoustic echo cancellation (AEC). Experimental results show that the combination scheme can obtain both fast convergence rate and small steady-state MSE.

A Windowing Frequency Domain Adaptive Filter for Acoustic Echo Cancellation

This letter proposes a windowing frequency domain adaptive algorithm, which reuses the filtering error to apply window function in the filter updating symmetrically. By using a proper window function to reduce the negative influence of the spectral leakage, the proposed algorithm can significantly improve the performance of the acoustic echo cancellation for speech signals.

Channel control and post filter for acoustic echo cancellation

An acoustic echo canceller comprising an adaptive filter, a post filter, and an adjustable filter. The adaptive filter receives a reference signal and a near-end signal, cancels a portion of the echo in the near-end signal using the reference signal, and provides an intermediate signal having remaining echo not canceled by the adaptive filter. The post filter calculates the cross-correlation between the near-end signal and intermediate signal, and provides a set of coefficients based on a variable suppression parameter. The adjustable filter processes the intermediate signal based on the coefficients and provides an output signal having at least a portion of the remaining echo removed. The acoustic echo canceller may further comprise a channel control unit that provides control signals, an adjustable amplifier, a noise estimator that estimates the noise in the intermediate signal, and a noise reinsertion unit that reinserts a version of the estimated noise back into the output signal.

Iterated partitioned block frequency-domain adaptive filtering for acoustic echo cancellation

For high quality acoustic echo cancellation long echoes have to be suppressed. classical LMS-based adaptive filters are not attractive as they are suboptimal from a computational point of view. Multirate adaptive filters such as the partitioned block frequency-domain adaptive filter (PBFDAF) are good alternatives and are widely used in commercial echo cancellers nowadays. In this paper the PBFDRAP is analyzed, which combines frequency-domain adaptive filtering with so-called row action projection. Fast versions of the algorithm are derived and it is shown that the PBFDRAP outperforms the PBFDAF in a realistic echo cancellation setup.

Low-complexity nonlinear adaptive filters for acoustic echo cancellation in GSM handset receivers

High-quality mobile services need to compensate for acoustic echoes that may affect modern cellular phone receivers. To this purpose, adaptive linear filters are generally used since their low complexity allows real-time implementations. However, they often have to identify an acoustic echo path that may contain significant nonlinearities. Therefore, in such cases, a nonlinear model is required. It is well known that Volterra filters are well suited for modeling a large class of nonlinear systems, but they often require too many computational resources for a real-time implementation. The purpose of this paper is twofold. First of all, we propose to use a simplified quadratic Volterra filter, derived taking into account the characteristics of the most important nonlinearities that affect cellular receivers. Second, an efficient adaptation algorithm is derived which extends the Affine Projection (AP) algorithm, proposed for linear filters, to quadratic Volterra filters. This adaptation algorithm offers better convergence and tracking capabilities with respect to the standard LMS and NLMS algorithms. The reduced complexity and the fast adaptation rate make the echo cancellers we are proposing attractive for real-time implementations. Copyright © 2003 AEI.

Low-complexity nonlinear adaptive filters for acoustic echo cancellation in GSM handset receivers

Low-complexity nonlinear adaptive filters for acoustic echo cancellation in GSM handset receivers

Analysis of Different Low Complexity Nonlinear Filters for Acoustic Echo Cancellation

Linear filters are often employed in most signal processing applications. As a matter of fact, they are well understood within a uniform theory of discrete linear systems. However, many physical systems exhibit some nonlinear behaviour, and in certain situations linear filters perform poorly. One case is the problem of acoustic echo cancellation, where the digital filter employed has to identify as close as possible the acoustic echo path that is found to be highly nonlinear. In this situation a better system identification can be achieved by a nonlinear filter. The problem is to find a nonlinear filter structure able to realize a good approximation of the echo path without any significant increase of the computational load. Conventional Volterra filters are well suited for modelling that system but they generally need too many computational resources for a real time implementation. In this paper we consider some low complexity nonlinear filters in order to find out a filter structure able to achieve performances close to those of the Volterra filter, but with a reduced increase of the computational load in comparison to the linear filters commonly employed in commercial acoustic echo cancellers.