Echo Cancellation Using Nonlinear Layered Bilinear IIR Filter

In this paper , a layered bilinear IIR filter structure is proposed, and the performance of the filter is studied with Block-updated Steepest Gradient Algorithm (BSGA) in an echo cancellation framework for high speed data transmission. Computer simulation results show that when the echo path shows significant nonlinearity, the layered bilinear echo canceller which uses the layered bilinear IIR filter and Block-updated Steepest Gradient Algorithm is effective in improving the echo cancellation performance with less computational complexity.

Fast Echo Canceller in IP Telephony Gateway

The length of the echo path in the IP telephony system is very long. Generally, the echo canceller is implemented on the IP telephony gateway which needs to perform concurrently multi-channel echo cancellation and voice compression. Hence, the most key technique to design the echo canceller is to reduce greatly the computational requirement. For this reason a number of innovative features to implement a fast echo canceller are presented. The key components of this canceller include: the separation of adaptive and cancel filters, non-real-time adaptation and real-time cancellation, sharing VAD algorithms with the speech codec, the incorporation of delay indexing with zero coefficients, and windowing the adaptive filter coefficients to reduce the cost of DSP during the cancellation. Finally, the performance of the echo canceller is summarized; the results of evaluation show that the performance gains for echo cancellation are significant.

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

An adaptive conjugate gradient algorithm based on subbands decomposition structure is proposed for acoustic echo cancellation in this paper. Through frequency decomposition technique and conjugate gradient algorithm, adaptive filters operate in each decimated sub-band, This new algorithm can ensure convergence with high speed and reduce computational complexity. Simulation results indicate that the proposed algorithm demonstrates good performance for acoustic echo cancellation.

A nonparametric variable step-size subband adaptive filtering algorithm for acoustic echo cancellation

Acoustic echo cancellation is often applied in communication and video call system to reduce unnecessary echoes generated between speakers and microphones.In these systems,the speech input signal of the adaptive filter is often colored and unstable,which decays the convergence rate of the adaptive filter if the NLMS algorithm is used.In this paper,an improved nonparametric variable step-size subband(NPVSS-NSAF)algorithm is proposed to address the problem.The variable step-size is derived by minimizing the sum of the square Euclidean norm of the difference between the optimal weight vectors to be updated and the past estimated weight vectors.Then the parameters are eliminated by using the power of subband signal noise equal to the power of subband posteriori error.The performance of the proposed algorithm is simulated in the aspects of misalignment and return loss enhancement.Experiment results show a fast convergence rate and low misalignment of the proposed algorithm in system identification.

Nonparametric VSS-APA based on precise background noise power estimate

The adaptive algorithm used for echo cancellation(EC) system needs to provide 1) low misadjustment and 2) high convergence rate. The affine projection algorithm(APA) is a better alternative than normalized least mean square(NLMS) algorithm in EC applications where the input signal is highly correlated. Since the APA with a constant step-size has to make compromise between the performance criteria 1) and 2), a variable step-size APA(VSS-APA) provides a more reliable solution. A nonparametric VSS-APA(NPVSS-APA) is proposed by recovering the background noise within the error signal instead of cancelling the a posteriori errors. The most problematic term of its variable step-size formula is the value of background noise power(BNP). The power difference between the desired signal and output signal, which equals the power of error signal statistically, has been considered the BNP estimate in a rough manner. Considering that the error signal consists of background noise and misalignment noise, a precise BNP estimate is achieved by multiplying the rough estimate with a corrective factor. After the analysis on the power ratio of misalignment noise to background noise of APA, the corrective factor is formulated depending on the projection order and the latest value of variable step-size. The new algorithm which does not require any a priori knowledge of EC environment has the advantage of easier controllability in practical application. The simulation results in the EC context indicate the accuracy of the proposed BNP estimate and the more effective behavior of the proposed algorithm compared with other versions of APA class.

An improved form of the ELMS algorithm

ELMS algorithm is the first two-channel adaptive filtering algorithm that takes into account the cross-correlation between the two input signals. The algorithm does not preprocess input signals, so it does not degrade the quality of the speech. However, a lot of computer simulation results show that ELMS algorithm has a bad performance. The ELMS algorithm is analyzed firstly, then a new algorithm is presented by modifying the block matrix used in ELMS algorithm to approximate input signals self-correlation matrix. The computer simulation results indicate that the improved algorithm has a better behavior than the ELMS algorithm.

Double-Talk Detection Algorithm Based on the l_2 Norm

Echo canceller generally needs a double-talk detector which is used to keep the adaptive filter from diverging in the appearance of near-end speech. In this paper we adopt a new double-talk detection algorithm based onl 2 norm to detect the existence of near-end speech in an acoustic echo canceller. We analyze this algorithm from the point of view of functional analysis and point out that the proposed double-talk detection algorithm has the same performance as the classic one in a finite Banach space. The remarkable feature of this algorithm is its higher accuracy and better computation complexity. The fine properties of this algorithm are confirmed by computer simulation and the application in a multimedia communication system. Key words acoustic echo cancellation - double-talk, detection - l 2 norm - adaptive FIR CLC number TN 911 Foundation item: Supported by the the National High Technology Development of China (863-306-ZT05)Biography: Wang Shao-wei (1975-) male, Ph. D candidate, research direction: multimedia communication.

OPTIMIZED SUB-BAND ADAPTIVE AEC USING EAR AUDITORY FEATURE

Acoustic echo cancellation based on sub-band filters has the characteristics of rapid con- vergence and small computational complexity. This letter analyses two different sub-band filters design methods which used in acoustic echo cancellation fields and compares them with each other. Fur- thermore, the sub-band filter construction have been optimized, which lead to the improvement of the computational efficiency. At the same time, this letter combines ear auditory feature with acoustic echo cancellation, thus improves the original algorithms by importing a new objective function creatively. At the last part, a simulation environment has been designed and a computer simulation has been carried out. The final results indicate that this method can meet the requirements of actual projects, and some improvements are demonstrated on performance and calculation quantity compared to original algo- rithms.

Performance Evalution of 2B1Q Data Echo Canceller in Digital Subscriber Access Networks

Recently, a lot of digital subscriber loop systems (DSL) and high rate digital subscriber loop systems (HDSL) have been deployed in digital subscriber access networks. Data echo canceller is extensively used in the DSL and HDSL systems to realize full duplex transmission on twisted cable. In such systems, 2B1Q line code is adopted. Therefore, symbol rate is decreased and digital transmission systems get longer reach. In this paper, a performance evaluation method of the echo canceller is proposed based on an autocorrelation matrix of 2B1Q line code. Using this method, the formula of ratio of data signal to echo residual signal is obtained. According to the formula, the ratio of data signal to echo noise depends on FIR filter tap, convergence factor, adaptive algorithm and the correlation matrix of the line code. Computer simulation is carried out to verify theoretical analysis. The simulation results coincided with the theoretical formula in the process estimating the ratio of signal to noise.

Implementation of a LD-CELP Codec with Echo Canceller Functions

In this paper, the authors present a method to handle the Echo Canceller as an on-side job of LD-CELP codec and a circuitry to embed echo canceller into a LD-CELP codec. The Possibility to implement a system with the integration of LD-CELP codec and echo canceller in real time by two chips of TMS320C30 isdiscussed.

An Improved Proportionate Normalized Least Mean Square Algorithm for Sparse Impulse Response Identification

In this paper after analyzing the adaptation process of the proportionate normalized least mean square(PNLMS) algorithm, a statistical model is obtained to describe the convergence process of each adaptive filter coefcient. Inspired by this result, a modified PNLMS algorithm based on precise magnitude estimate is proposed. The simulation results indicate that in contrast to the traditional PNLMS algorithm, the proposed algorithm achieves faster convergence speed in the initial convergence state and lower misalignment in the stead stage with much less computational complexity.

Novel DTD and VAD assisted voice detection algorithm for VoIP systems

Echo cancellation plays an important role in current Internet protocol（IP） based voice interactive systems. Voice state detection is an essential part in echo cancellation. It mainly comprises two parts： double talk detection（DTD） and voice activity detection（VAD）. DTD is used to detect doubletalk and prevent filter divergence in the presence of near-end speech, and VAD is used to determine the near-end voice activity and output silence indicator when near-end is silent. However, DTD straightforwardly proceeded may mistakenly declare double talk under double silent condition, coefficients update under the far-end silence condition may lead to filter divergence, and current VAD algorithms may misjudge the residual echo from the near end to be far-end voice. Therefore, a voice detection algorithm combining DTD and far-end VAD is proposed. DTD is implemented when VAD declares far-end speech, filtering and coefficients update will be halted when VAD declares far-end silence, and the far-end VAD adopted is multi-feature VAD based on short-time energy and correlation. The new algorithm can improve the accuracy of DTD, prevent filter divergence, and exclude the circumstance that far-end signal only contains residual echo from near end. Actual test results show that the voice state decision of the new algorithm is accurate, and the performance of echo cancellation is improved.