An Adaptive Acoustic Echo Cancellation Algorithm Based on Subband Decomposition and Conjugate Gradient Method

1 Introduction In speech communication applications ,the presence ofcoupling fromloudspeaker to the microphone often re-sults in undesired acoustic echo that seriously degradesspeech quality.Current solutions for removingthis echoare based on the real ti me identification of the acoustici mpulse response by using adaptive filtering or AdaptiveEcho Cancellation (AEC) filter techniques . Several AEC algorithms have been proposed for thisproblem. An acoustic echo canceller based upon inputort…     

声回波对消子带分解分析/综合滤波器的设计

基于小波包子带分解的声回波对消方案可减少运算量,加快收敛。然而并不是任何小波函数的子带分解系统都可以加以利用,必须要求它具有好的完美重构性和移不变性,以保证近端话音信号的重构失真小且能有效地对消回声。本文通过分别优化小波包分析/综合滤波函数使系统同时具有较好的重构和移不变性,并保证有好的对消性能。     

Design and discrete re-optimisation of all-pass based powersymmetric IIR filters

Tools are presented which enable the practitioner to efficiently design all-pass based, highly selective low-pass power symmetric-infinite impulse response (PS-IIR) filters which are well suited for sub-band decomposition in applications such as multirate acoustic echo cancellation (MAEC)     

基于子带分解和比例归一化算法的回声消除器设计与仿真

针对稀疏信道条件下的网络回声抵消问题。提出了一种比例归一化子带自适应滤波算法。该算法基于子带分解结构,并利用网络中回声路径的稀疏特性,使得各个系数的步长与该系数的绝对值成比例,加快了活动系数的收敛速度,从而改善了子带分解算法在稀疏信道条件下的性能。仿真结果表明：将所提算法应用于网络回声消除器,能够获得很快的收敛速度和很低的稳态失调。     

Acoustic echo cancellor with sub-band noise cancelling

An acoustic echo canceller with sub-band noise cancelling that employs a cascade configuration is proposed. The adaptation control adopted to match the occurrence of intermittent speech/echo and continuous room noise using the NLMS algorithm is very effective in echo and noise cancellation. Hardware is implemented and its performance evaluated through experiments. The noise cancellation significantly enhances overall echo-cancellation performance.<>     

VoIP回声消除器设计及算法研究

本文提出了一种与线性预测编解码器相结合的新声学回声消除器,由去相关可变步长的NLMS自适应算法和基于回声路径失配方差的双端通话检测算法所组成.Matlab仿真结果表明,与Gordy所提出的回声消除算法相比,本文提出的算法在双端通话和回声路径改变时判别更准确,收敛速度更快;在收敛状态时,ERLE值平均提高了15dB,失调误差平均降低了10dB,具备更好的回声消除性能.     

A Co-Design Methodology for Telecommunication Systems: A Case Study of an Acoustic Echo Canceller

The acoustic echo cancellation with large adaptive filters is a computationally intensive problem and needs real time cost effective solution. To deal with these challenges, designers have increasingly turned to mixed Hardware/Software (HW/SW) implementation of echo canceller algorithms. This paper presents a co-design methodology and environment for both hardware and software modules. We describe how High Level Synthesis (HLS) tools like GAUT and SYNDEX can be efficiently used for rapid prototyping of heterogeneous architecture based on DSP TMS320C40 and ASIC. The HW/SW interface synthesis task is especially discussed since it constitutes a key issue of the whole design. As an illustration, we present a mixed implementation of the GMDF alpha algorithm, an adaptive filter well suited to acoustic echo cancellation, on both ASIC and TMS320C40 DSP.     

Noise robust alternating fixed-point algorithm for stereophonicacoustic echo cancellation

A novel algorithm specifically for use in stereophonic acoustic echo cancellation (SAEC) environments is introduced. It is based on an alternating fixed-point (FP) structure. Analysis provides bounds to ensure that the algorithm has the form of a contraction mapping (CM). Simulation results show improved performance over algorithms with similar computational complexity in the presence of noise     

A Nonlinear Acoustic Echo Canceller Using Sigmoid Transform in Conjunction With RLS Algorithm

Nonlinearity of amplifiers and/or loudspeakers gives rise to nonlinear echo in acoustic systems, which seriously degrades the performance of speech and audio communications. Many nonlinear acoustic echo cancellation (AEC) methods have been proposed. In this paper, a simple yet efficient nonlinear echo cancellation scheme is presented by using an adaptable sigmoid function in conjunction with a conventional transversal adaptive filter. The new scheme uses the least mean square (LMS) algorithm to update the parameters of sigmoid function and the recursive least square (RLS) algorithm to determine the coefficient vector of the transversal filter. The proposed AEC is proved to be convergent under some mild assumptions. Computer simulations show that the proposed scheme gives a superior echo cancellation performance over the well known Volterra filter approach when the echo path suffers from the saturation-type nonlinear distortion. More importantly, the new AEC has a much lower computational complexity than the Volterra-filter-based method.      

Adaptive Sampling Rate Correction for Acoustic Echo Control in Voice-Over-IP

Hands-free terminals for speech communication employ adaptive filters to reduce echoes resulting from the acoustic coupling between loudspeaker and microphone. When using a personal computer with commercial audio hardware for teleconferencing, a sampling frequency offset between the loudspeaker output D/A converter and the microphone input A/D converter often occurs. In this case, state-of-the-art echo cancellation algorithms fail to track the correct room impulse response. In this paper, we present a novel least mean square (LMS-type) adaptive algorithm to estimate the frequency offset and resynchronize the signals using arbitrary sampling rate conversion. In conjunction with a normalized LMS-type adaptive filter for room impulse response tracking, the proposed system widely removes the deteriorating effects of a frequency offset up to several Hz and restores the functionality of echo cancellation.     

声回声抵消系统中后处理滤波器的研究

提出一种回声抵消系统中残留回声的抑制方法,利用回声信号的估计值和包含残留回声的输出误差信号计算得到的后处理滤波器,将残留回声进一步消除。提出的后处理滤波器可以有效地与频域自适应算法融合,并非常适用于多通道处理。实验和仿真结果均证明了该后处理滤波器的有效性。     

Design and performance of adaptive systems based on structured stochastic optimization strategies

The theory and design of linear adaptive filters based on FIR filter structures is well developed and widely applied in practice. However, the same is not true for more general classes of adaptive systems such as linear infinite impulse response adaptive filters (MR) and nonlinear adaptive systems. This situation results because both linear IIR structures and nonlinear structures tend to produce multi-modal error surfaces for which stochastic gradient optimization strategies may fail to reach the global minimum. After briefly discussing the state of the art in linear adaptive filtering, the attention of this paper is turned to MR and nonlinear adaptive systems for potential use in echo cancellation, channel equalization, acoustic channel modeling, nonlinear prediction, and nonlinear system identification. Structured stochastic optimization algorithms that are effective on multimodal error surfaces are then introduced, with particular attention to the particle swarm optimization (PSO) technique. The PSO algorithm is demonstrated on some representative IIR and nonlinear filter structures, and both performance and computational complexity are analyzed for these types of nonlinear systems.     

A delayless subband adaptive filter architecture

Some adaptive signal processing applications, such as wideband active noise control and acoustic echo cancellation, involve adaptive filters with hundreds of taps. The computational burden associated with these long adaptive filters precludes their use for many low-cost applications. In addition, adaptive filters with many taps may also suffer from slow convergence, especially if the reference signal spectrum has a large dynamic range. Subband techniques have been previously developed for adaptive filters to solve these problems. However, the conventional approach is ruled out for many applications because delay is introduced into the signal path. The paper presents a new type of subband adaptive filter architecture in which the adaptive weights are computed in subbands, but collectively transformed into an equivalent set of wideband filter coefficients. In this manner, signal path delay is avoided while retaining the computational and convergence speed advantages of subband processing. An additional benefit accrues through a significant reduction of aliasing effects. An example of the general technique is presented for a 32-subband design using a polyphase FFT implementation. For this example, the number of multiplies required are only about one-third that of a conventional full band design with zero delay, and only slightly greater than that of a conventional subband design with 16 ms delay     

A Method for Reduced Finite Precision Effects in Parallel Filtering Echo Cancellation

The two-path algorithm is an adaptive filter algorithm based on a parallel filter structure, which has been found to be useful for line echo cancellation as well as for acoustic echo cancellation. It is well known that in finite precision arithmetic, the adaptation process of adaptive algorithms can be reduced or even halted due to finite precision effects. This paper proposes a variant of the two-path scheme where the effects of quantization are reduced, without any significant increase in complexity. The improvement is shown by simulations using bandlimited flat spectrum noise as well as real speech signals.     

MPEG-2音频实时压缩编解码的一种快速算法

该文介绍采用一片TI公司的数字信号处理芯片TMS320C31实现了MPEG-2音频Layer-1,2实时压缩编解码器。为了达到实时的目的,对MPEG建议的子带分析和子带合成方案分别提出了一种新的快速算法,采用该算法的运算量分别是MPEG标准建议算法运算量的1/5和1/10。所有算法都经过了软件模拟和硬件实时仿真,通过仿真器装载到一片TMS320C31上实现了实时编解码运算。     

Acoustic echo control. An application of very-high-order adaptivefilters

We have discussed the application of high-order adaptive filters to the problem of acoustical echo cancellation with particular application to hands free telephone systems. We described a means to achieve robust performance. We further presented methods for reducing computational complexity that allow implementation in low-cost, fixed-point digital signal processors. Progress in technology will allow the use of more sophisticated algorithms at lower cost in the near future     

用于短波接入网的稳健快速收敛的自适应回波抵消器

针对短波电台入网中对皮抵消的要求,本文提出采用基于ＬＳ准则的ＦＴＦ算法,同时把“稳健估计（ＲＥ）”应用于ＦＴＦ算法中,并设计出一种新的自适应回波抵消器结构,理论分析和计算机模拟结果都表明该回波抵消器具有收敛速度快,稳态误差小,稳定可靠,抗干扰能力强等特点,明显地提高了短波电台入网的性能。     

一种改进的双通道滤波回声抵消算法——过采样无延迟子带方法

在强相关大动态范围语音作用下,回声抵消器直接更新上千阶自适应滤波器系数,计算量大、收敛速度慢。采用子带分析与合成的方法能够减少计算量和提高算法的收敛性能,但子带的分析与合成也给线路中引入了信号延迟。提出了一种改进的双通道滤波回声抵消算法,将子带自适应滤波器映射到全频带滤波器,减少了信号的延迟;同时采用双通道滤波器。使系统工作在较小残余回声功率下。仿真结果表明,改进算法在单边会话情况下收敛快．具有较好的回声抵消效果。     

A Low-Complexity Delayless Selective Subband Adaptive Filtering Algorithm

Adaptive filters of significant order, requiring high computational complexity, are necessary in many applications such as acoustic echo cancellation and wideband active noise control. Successful approaches to lessen the computational complexity of such filters are subband methods, and partial updating schemes where only a part of the filter is updated at each instant. To avoid the time delay introduced by the subband-splitting, delayless structures which reconstructs a fullband filter, producing delayless output, from the adaptive subband filters have been proposed. This paper proposes a delayless subband adaptive filter partial updating scheme, where the general idea is to only update the most misadjusted subband filter(s). Analysis in terms of mean square deviation is presented and shows that the fullband filter convergence speed is significantly increased, even for flat spectrum signals, as compared to traditional periodic subband filter update with the same computational complexity. Echo cancellation simulations with an artificial system to verify the analysis, using both flat spectrum signals and speech, is also presented, as well as offline calculations using signals from a real system.      

Bayesian regularization and nonnegative deconvolution for room impulse response estimation

This paper proposes Bayesian Regularization And Nonnegative Deconvolution (BRAND) for accurately and robustly estimating acoustic room impulse responses for applications such as time-delay estimation and echo cancellation. Similar to conventional deconvolution methods, BRAND estimates the coefficients of convolutive finite-impulse-response (FIR) filters using least-square optimization. However, BRAND exploits the nonnegative, sparse structure of acoustic room impulse responses with nonnegativity constraints and L/sub 1/-norm sparsity regularization on the filter coefficients. The optimization problem is modeled within the context of a probabilistic Bayesian framework, and expectation-maximization (EM) is used to derive efficient update rules for estimating the optimal regularization parameters. BRAND is demonstrated on two representative examples, subsample time-delay estimation in reverberant environments and acoustic echo cancellation. The results presented in this paper show the advantages of BRAND in high temporal resolution and robustness to ambient noise compared with other conventional techniques.