基于嵌入式的助听器回波算法研究与实现

回声会导致助听器产生啸叫,损坏助听器设备,破坏患者的残余听力。为此,本文在助听器回声抵消模型的基础上,针对输入信号的能量变化,研究了基于归一化最小均方（Normalized Least Mean Squares, NLMS）的自适应助听器回声抵消算法。通过对比LMS和NLMS两种算法的MSE,ERLE等性能,研究发现NLMS算法在数字助听器模型中有更好的回声抵消性能。此外,将NLMS算法移植到嵌入式平台中,并通过实验对比算法的性能。因此,本研究对于助听器的回声抵消算法设计具有很强的实用价值。     

基于MVDR后置滤波的多通道回声消除算法研究

视频会议场景中,用户扬声器、麦克风的非线性特性,使得麦克风采集到的回声信号存在明显失真,线性回声消除后仍会残留大量非线性回声,且能量和近端语音相当。此时需要高强度的非线性回声处理保证不漏回声,但近端语音也会被明显抑制甚至消音,影响会议体验。针对上述难点,提出一种基于最小无失真方差响应（Minimum Variance Distortionless Response,MVDR）后置滤波器的多通道回声消除算法,将各通道的信号分别进行线性回声处理,然后使用MVDR后置滤波提升近端语音能量、抑制残留回声能量,最后通过低强度非线性回声抑制器,得到回声消除后的信号。测试表明,本文方案多抑制了6.05%残留非线性回声,同时提升13.51%的近端语音能量,经过低强度的非线性回声抑制（Non-Linear Processing,NLP）处理后,保留了更多的近端语音能量,改善了语音通透性。本文提出的算法可以实时运行于低成本移动平台上。     

VoIP通信中的回声消除方法研究

介绍了语音通信声学回声产生模型和自适应AEC回声消除算法原理,分析了AEC应用于VoIP语音通信中存在的问题,设计了一种基于短时能量的非线性回声消除方法,在NGN网络的VoIP通信中,使用该方法实现了极高的回声抑制比。测试结果表明该方法的消回声效果、算法稳定性和实现复杂度等指标明显优于自适应AEC算法,适合于嵌入式VoIP通信终端设备的开发。     

直接辐射式扬声器的非线性研究

扬声器的非线性是影响扬声器音质的一个重要因素,因此,历来都受到有关声学工作者的高度重视。到目前为止,已有好几种测试指标和方法,除了谐波畸变和互调失真以外,还有差频失真、二阶堂失真等,对扬声器的非线性失真的研究,一般只限于高次谐波的产生。本文将扬声器作为非线性振动与辐射系统来研究,提出该器件产生分谐波以至达到混浊状态的一些实验结果,并说明这一现象对扬声器音质的影响是不容忽视的。     

电动式扬声器单元中的降低失真问题

探讨了在电动式低音扬声器单元中非线性失真的原因,并且提出了减少偶次谐波的带对称磁路的电动式扬声器单元的某些结构方案.介绍了已进行的降低偶次谐波的方法即应用双低频扬声器单元,该方法还能减小声系统箱体的容积.     

能量比检测与连续学习速率结合的改进双话处理算法

利用连续可变学习速率处理回声抵消双话情况时,随着近端语音能量的提高,学习速率的估计偏差增大,导致残留回声增加.提出了一种利用短时能量比显示检测与连续学习速率相结合的改进双话处理算法.该算法利用近端与远端语音的短时能量比,对学习速率估计中的泄露因子参数进行自适应修正,从而调整连续学习速率.实验证明,该算法使得回声抵消双话情况下,自适应滤波器发散程度下降,语音质量得到提升.在近远端能量比-6～6dB范围内,回声返回损失增加度(ERLE)提高0～11 dB,平均意见得分(MOS)提高0.02～ 0.45分.     

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.     

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。     

数字扬声器系统中失配整形技术的设计与实现

为了改善数字扬声器系统中由扬声器单元之间频响不一致引入的非线性谐波失真,在参考前人研究工作的基础上,给出了基于3bit△∑调制编码方式的3种DEM（Dynamic Element Matching）失配整形算法的设计和实现方法,并在全消声室内测试了3种算法的谐波抑制能力,同时基于测试结果评价了这些算法的性能。     

扬声器力学系统的非线性振动

扬声器非线性失真是对扬声器重放音质有极重要影响的一个指标，一般厂家对这个质量指标的考核是十分重视的。造成扬声器非线性失真的原因很多，大致可以分为两类：磁场因素及振动系统的非线性因素。近年来，我们对扬声器振动系统的非线性问题作了一些粗浅的探索，本文目的是将我们以前的一些研究作一个小结，并提出近期的一些研究成果，以与国内同行专家们共同探讨。     

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.      

Cascaded power symmetric IIR filter banks and continuityconstrained adaptive algorithms for acoustic echo cancellation insubbands

Teleconferencing systems and hands-free mobile terminals use acoustic echo cancellation (AEC) for high-quality full-duplex speech communication. The problem of aliasing in subband AEC is addressed. Filter banks with implicit notch filtering are derived from cascaded power symmetric-infinite impulse response (CFS-IIR) filters. It is shown that adaptive filters used with these filter banks must be coupled via continuity constraints to reduce the aliasing in the residual echo. A continuity constrained NLMS algorithm is therefore proposed and evaluated     

Residual echo signal in critically sampled subband acoustic echocancellers based on IIR and FIR filter banks

The residual echo signal characteristics of critically sampled subband acoustic echo cancellers are analyzed. For finite impulse response (FIR) filter banks, the residual echo signal usually has a relatively broad spectral nature around the subband edges. The residual echo signal of power symmetric infinite impulse response (PS-IIR) filter banks, on the other hand, has very narrowband spectral components around the subband edges. These components can be efficiently removed with PS-IIR notch filters that integrate neatly into the filter banks without introducing perceptually noticeable degradation to the near-end speech. This solution has very low computational complexity and does not impinge on the system performance. Simulation studies with recordings from the cockpit of a car, based on a fast QR least-squares adaptive algorithm, demonstrate the potential of this approach for a practical AEC system     

基于谱优势与非线性变换混合的立体声声学回声消除方法

立体声声学回声控制系统中,两通道信号间的强相关性导致自适应算法的解不唯一,滤波器失调较大。为了解决此问题,并尽可能地保留语音质量,该文基于心理声学上的谱优势效应提出一种新型的混合立体声声学回声消除方法。根据谱优势效应,在3个低次谐频处注入能量较弱的正弦信号,以减弱低频相关性。同时对非线性变换法进行改进,以用于中高频去相关处理。与传统方法的多方面性能测试对比结果表明:所提方法能有效改善失调性能并提高收敛速度,且具有较小的语音失真。     

A Signal Decorrelation PNLMS Algorithm for Double-Talk Acoustic Echo Cancellation

Acoustic echo cancellation (AEC) in voiced communication systems is used to eliminate the echo which corrupts the speech signal and reduces the efficiency of signal transmission. Usually, the performance of AEC system based on the adaptive filtering degrades seriously in the presence of speech issued from the near-end speaker (double-talk). In typical AEC scenarios, double-talk detector (DTD) must be added to AEC for improving speech quality. One of the main problems in AEC with DTD is that the DTD errors can result in either large residual echo or distorting the near-end input speech. Considering the strong correlation property of speech signals, this paper presents a novel proportionate decorrelation normalized least-mean-square (PDNLMS) adaptive AEC without DTD for echo cancellation as an interesting alternative to the typical AEC with DTDs. Unlike traditional AEC with a DTD, the proposed PDNLMS uses the difference of near-end speech as the residual error to update adaptive echo channel filter during the periods of double-talk, which can efficiently reduce the double-talk influence on the AEC adaptation process. The experimental results show that not only the proposed PDNLMS without DTD illustrate better stability and faster convergence rate, but it is also of a lower steady-state misalignment and better residual signal than current methods with DTDs at a lower computational cost.     

一种改进的自适应回波抵消器的设计与实现

回波是广泛存在于各种通信信道中的噪声干扰.传统的回波抵消器只能滤除缓变的、线性的回波干扰,对一些非线性且较复杂的信道产生的回波,滤波效果并不理想.本文通过比较融合两种经典的自适应算法,LMS算法和RLS算法各自的优点,提出了一种改进的自适应回波抵消器的结构,该回波抵消器已通过MATLAB仿真实现.从仿真的结果来看,该回波抵消器在对信道的兼容性,以及鲁棒性均优于传统回波抵消器.     

Modulated Lapped Transform Domain Acoustic Echo Canceller with Double Talk Detector

A complete acoustic echo cancellation system with double talk detection capability is presented in this paper. The proposed system includes a new acoustic echo canceller (AEC) based on the modulated lapped transform (MLT) domain adaptive structure and a robust two-stage double talk detector (DTD) to cope with MLT domain AEC. The proposed AEC achieves better signal decorrelation via orthogonal MLT of size 2N× N rather than N× N square orthogonal transform such as DCT, DFT, etc. Both the input signal and the desired response are modulated lapped transformed in order to reduce the adaptation error between them so that the signal adaptation is purely operated in MLT domain. As a complementary of this, a two-stage DTD is developed to stabilize the operation of the AEC. The proposed DTD has robust algorithm structure and it allows faster switching according to the talker state change.Several simulation results with a synthetic and real speech are presented to demonstrate the performance of the proposed AEC and DTD. The proposed MLT based AEC proven to be very useful for the echo cancellation applications requiring high convergence speed and good echo attenuation. It can achieves faster convergence rate by more than twice over those of traditional DCT based AEC with an additional advantage of 10–15 dB ERLE improvement. On the other hand, a proposed two-stage DTD is shown to react quickly to both the onset and the end of the double-talk with reasonable high accuracy.     

Fast LMS/Newton Algorithms for Stereophonic Acoustic Echo Cancelation

This paper presents a new class of adaptive filtering algorithms to solve the stereophonic acoustic echo cancelation (AEC) problem in teleconferencing systems. While stereophonic AEC may be seen as a simple generalization of the well-known single-channel AEC, it is a fundamentally far more complex and challenging problem to solve. The main reason being the strong cross correlation that exists between the two input audio channels. In the past, nonlinearities have been introduced to reduce this correlation. However, nonlinearities bring with it additional harmonics that are undesirable. We propose an elegant linear technique to decorrelate the two-channel input signals and thus avoid the undesirable nonlinear distortions. We derive two low complexity adaptive algorithms based on the two-channel gradient lattice algorithm. The models assume the input sequences to the adaptive filters to be autoregressive (AR) processes whose orders are much lower than the lengths of the adaptive filters. This results in an algorithm, whose complexity is only slightly higher than the normalized least-mean-square (NLMS) algorithm; the simplest adaptive filtering method. Simulation results show that the proposed algorithms perform favorably when compared with the state-of-the-art algorithms.     

Proportionate NSAF algorithms with sparseness-measured for acoustic echo cancellation

In acoustic echo cancellation (AEC), the sparseness of impulse responses can vary over time or/and context. For such scenario, the proportionate normalized subband adaptive filter (PNSAF) and μ-law (MPNSAF) algorithms suffer from performance deterioration. To this end, we propose their sparseness-measured versions by incorporating the estimated sparseness into the PNSAF and MPNSAF algorithms, respectively, which can adapt to the sparseness variation of impulse responses. In addition, based on the energy conservation argument, we provide a unified formula to predict the steady-state mean-square performance of any PNSAF algorithm, which is also supported by simulations. Simulation results in AEC have shown that the proposed algorithms not only exhibit faster convergence rate than their competitors in sparse, quasi-sparse and dispersive environments, but also are robust to the variation in the sparseness of impulse responses.