Residual Echo Suppression Considering Harmonic Distortion and Temporal Correlation

In acoustic echo cancellation, a certain level of residual echo resides in the output of the linear echo canceller because of the nonlinearity of the power amplifier, loudspeaker, and acoustic transfer function in addition to the estimation error of the linear echo canceller. The residual echo in the current frame is correlated not only to the linear echo estimates for the harmonically-related frequency bins in the current frame, but also with linear echo estimates, residual echo estimates, and microphone signals in adjacent frames. In this paper, we propose a residual echo suppression scheme considering harmonic distortion and temporal correlation in the short-time Fourier transform domain. To exploit residual echo estimates and microphone signals in past frames without the adverse effect of the near-end speech and noise, we adopt a double-talk detector which is tuned to have a low false rejection rate of double-talks. Experimental results show that the proposed method outperformed the conventional approach in terms of the echo return loss enhancement during single-talk periods and the perceptual evaluation of speech quality scores during double-talk periods.

Performance enhancement of Echo Cancellation Using a Combination of Partial Update ( PU) Methods and New Variable Length LMS (NVLLMS) Algorithm

In this paper, several combination algorithms between Partial Update LMS (PU LMS) methods and previously proposed algorithm (New Variable Length LMS (NVLLMS)) have been developed. Then, the new sets of proposed algorithms were applied to an Acoustic Echo Cancellation system (AEC) in order to decrease the filter coefficients, decrease the convergence time, and enhance its performance in terms of Mean Square Error (MSE) and Echo Return Loss Enhancement (ERLE). These proposed algorithms will use the Echo Return Loss Enhancement (ERLE) to control the operation of filter's coefficient length variation. In addition, the time-varying step size is used.The total number of coefficients required was reduced by about 18% , 10% , 6%, and 16% using Periodic, Sequential, Stochastic, and M-max PU NVLLMS algorithms respectively, compared to that used by a full update method which is very important, especially in the application of mobile communication since the power consumption must be considered. In addition, the average ERLE and average Mean Square Error (MSE) for M-max PU NVLLMS are better than other proposed algorithms.

An Improved Echo Cancellation Algorithm with Low Computational Complexity

A low-complexity echo canceller integrated with vocoder is proposed in this paper to speed up the convergence process. By making full use of the linear prediction parameters retrieved from decoder and the voice active detection feature of the vocoder, the new echo canceller avoids the need to calculate decorrelation filter coefficients and prewhiten the received signal separately. Simulation results show performance improvement of the proposed algorithm in terms of convergence rate and echo return loss enhancement.

The Dynamic LMS for Line Echo Cancellation

To the best of our knowledge, this study represents the proposal using the dynamic least mean square (DLMS) algorithm to reduce the computation load of LMS. Moreover, three regions of impulse response of line echo path are also proposed to analyze the redundant coefficients. Using the DLMS method, redundant coefficients can be detected and grouped, thereby automatically reducing computation. We employed line echo cancellation (LEC) to evaluate the performance of DLMS. The pure-delay and overlong regions of impulse response of line echo path are grouped and the associated computation load is reduced. The experimental results confirm the excellent performance of DLMS achieving a 35% savings in computation. Moreover, the quality echo return loss enhancement (ERLE) of DLMS also maintains at a level nearly equal to LMS.

Acoustic Echo Cancellation Embedded in Smart Transcoding Algorithm between 3GPP AMR-NB Modes

Acoustic Echo Cancellation (AEC) is a necessary feature for mobile devices when the acoustic coupling between the microphone and the loudspeaker affects the communication quality and intelligibility. When implemented inside the network, decoding is required to access the corrupted signal. The AEC performance is strongly degraded by nonlinearity introduced by speech codecs. The Echo Return Loss Enhancement (ERLE) can be less than 10 dB for low bit rate speech codecs. We propose in this paper a coded domain AEC integrated in a smart transcoding strategy which directly modifies the Code Excited Linear Prediction (CELP) parameters. The proposed system addresses simultaneously problems due to network interoperability and network voice quality enhancement. The ERLE performance of this new approach during transcoding between Adaptive Multirate-NarrowBand (AMR-NB) modes is above 45 dB as required in Global System for Mobile Communications (GSM) specifications.