An online algorithm for echo cancellation, dereverberation and noise reduction based on a Kalman-EM Method

Many modern smart devices are equipped with a microphone array and a loudspeaker (or are able to connect to one). Acoustic echo cancellation algorithms, specifically their multi-microphone variants, are essential components in such devices. On top of acoustic echos, other commonly encountered interference sources in telecommunication systems are reverberation, which may deteriorate the desired speech quality in acoustic enclosures, specifically if the speaker distance from the array is large, and noise. Although sub-optimal, the common practice in such scenarios is to treat each problem separately. In the current contribution, we address a unified statistical model to simultaneously tackle the three problems. Specifically, we propose a recursive EM (REM) algorithm for solving echo cancellation, dereverberation and noise reduction. The proposed approach is derived in the short-time Fourier transform (STFT) domain, with time-domain filtering approximated by the convolutive transfer function (CTF) model. In the E-step, a Kalman filter is applied to estimate the near-end speaker, based on the noisy and reveberant microphone signals and the echo reference signal. In the M-step, the model parameters, including the acoustic systems, are inferred. Experiments with human speakers were carried out to examine the performance in dynamic scenarios, including a walking speaker and a moving microphone array. The results demonstrate the efficiency of the echo canceller in adverse conditions together with a significant reduction in reverberation and noise. Moreover, the tracking capabilities of the proposed algorithm were shown to outperform baseline methods.

Self-Interference Cancellation in Full Duplex Communication using Steepest Descent Method

The present-day communication system uses Frequency Division Duplex (FDD) to emulate the benefits of Full Duplex Communication. But it requires more bandwidth as the cost of the spectrum is very high it becomes a major limitation. To overcome this problem implementation of Full Duplex Communication is the best solution. Implementation of full duplex communication is difficult because of a significant problem called self-interference. while transmitting and receiving signals on the same frequency band, receiving signal is interfered with the transmitted signal this phenomenon is called self-interference. The objective of this project is to minimize that self-interference signal from the received signal by using signal processing technique, LMS echo cancellation. Least Mean Square (LMS) echo canceller whose coefficients are updated iteratively is used to cancel the self-interference. An algorithm based on steepest descent method is used to obtain coefficients that change iteratively with varying step size to solve Weiner-Hopfs equation.

Adaptive Echo Cancellation Analysis

Echo cancellation is a classic problem in DSP and digital communication. Adaptive echo cancellation is an application of adaptive filtering to the attenuation of undesired echo in the telecommunication network. This is accomplished by modeling the echo path using an adpative filter and subtracting the estimated echo from the echo-path output. In this project, the concept of echo cancellation and echo cancellation systems are studied, simulated, and implemented in Matlab and TI TMS3206C6711 DSK. The LMS, NLMS. Fast block LMS and RLS algorithm and investigated for echo canceller and two double talk detection algorithm are presented and combined with NLMS adaptive algorithm against double talk. Finally the adaptive echo cancellation system successfully developled by the NLMS and normalized cross-correlation DTD algorithms meet the general ITU G. 168 requirements and show excellent robustness against double talk.

Adaptive Echo Cancellation Analysis

Echo cancellation is a classic problem in DSP and digital communication. Adaptive echo cancellation is an application of adaptive filtering to the attenuation of undesired echo in the telecommunication network. This is accomplished by modeling the echo path using an adpative filter and subtracting the estimated echo from the echo-path output. In this project, the concept of echo cancellation and echo cancellation systems are studied, simulated, and implemented in Matlab and TI TMS3206C6711 DSK. The LMS, NLMS. Fast block LMS and RLS algorithm and investigated for echo canceller and two double talk detection algorithm are presented and combined with NLMS adaptive algorithm against double talk. Finally the adaptive echo cancellation system successfully developled by the NLMS and normalized cross-correlation DTD algorithms meet the general ITU G. 168 requirements and show excellent robustness against double talk.

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.