Robust extended multidelay filter and double-talk detector for acoustic echo cancellation

Buchner, Herbert; Benesty, Jacob; Gänsler, Tomas; Kellermann, Walter

doi:10.1109/tsa.2005.858559

Cited by 58 publications

(37 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Several notable methods have been proposed for this purpose. In [3], [4], [5], and [6] an extra component is employed in the AEC to help avoid filter divergence during DT. This component could be in the form of a DT detector or a step-size controller.…”

Section: Aec and The Double-talk Problemmentioning

confidence: 99%

Blind source separation and acoustic echo cancellation: A unified framework

Ikram

2012

2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

View full text Add to dashboard Cite

We explore interesting connections between blind source separation (BSS) and acoustic echo cancellation (AEC), and develop a framework where the AEC problem is transformed and solved as a BSS problem. We show that by careful selection of the BSS algorithm the double-talk (DT) problem in AEC is solved without the need to use a DT detector or a step-size controller. Furthermore, the echo cancellation performance is maintained even during single-talk when only the far-end speaker is active. The algorithm converges to the true echo path much faster than the normalized least-mean squares adaptation. Moreover, the proposed algorithm does not require a knowledge of the echo-tail length and is robust against under estimation of the echo-filter length. The simple implementation and fast convergence of the proposed method makes it a suitable candidate for implementation on low-power general purpose DSPs.

show abstract

Section: Aec and The Double-talk Problemmentioning

confidence: 99%

Blind source separation and acoustic echo cancellation: A unified framework

Ikram

2012

2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

View full text Add to dashboard Cite

show abstract

“…The time-shift, τ, which is always in range of [τ min ; τ max ] and causes the maximal peak value of the CCF is declared as an estimate of the true echo delay T D . Similarly to the CCF, an estimate of the NCCF is done (Buchner et al, 2006) …”

Section: Algorithms Proceeding In Time-domainmentioning

confidence: 99%

Perceptual Echo Control and Delay Estimation

Sakhnov¹,

Verteletskaya²,

Simak³

2011

Adaptive Filtering Applications

View full text Add to dashboard Cite

“…The coherence function needs to fix the threshold value to identify the double talk. A robust and reliable way to find double talk is to measure the correlation coefficient vector between the far-end speech and the microphone signal [7][8]. The efficiency of the echo cancellation is less in terms of ELRE.…”

Section: Introductionmentioning

confidence: 99%

Acoustic Echo Cancellation Using PEVD Based Adaptive Kalman Filter

Kothandaraman¹,

Pawani²,

Pachaiyappan³

et al. 2017

IJIES

View full text Add to dashboard Cite

Abstract:In this paper a PEVD (Polynomial Eigen Value Decomposition) based adaptive kalman filter is proposed for Acoustic Echo Cancellation (AEC) in the presence of noise. Acoustic echo is the phenomenon when the speaker listens to his own voice after some delay while speaking to his fellow mate on a call. The presence of acoustic coupling between the loudspeakers and the near-end microphone signal produces an undesired acoustic echo, which reduces the speech quality. Existing AEC system implemented adaptive kalman filter which results in less output efficiency in the noisy environment. In the proposed method, the near end speech is separated from the acoustic echo as well as from the surrounding noise by using PEVD based adaptive kalman filter. Initially mixed microphone signal is pre-processed by Polynomial Eigen Value Decomposition which strongly de-correlates the signal and also de-correlates out the noise. The pre-processed signal is passed through adaptive kalman filter for estimation of the acoustic echo. The efficiency of the output is calculated using Echo Return Loss Enhancement (ERLE). If the ERLE lies in the range of 30-40 dB indicates the good echo cancellation. The simulations show that the proposed PEVD based adaptive kalman method provides higher cancellation of echo. The simulations are being carried out in Matlab 2016a.

show abstract

Robust extended multidelay filter and double-talk detector for acoustic echo cancellation

Cited by 58 publications

References 15 publications

Blind source separation and acoustic echo cancellation: A unified framework

Blind source separation and acoustic echo cancellation: A unified framework

Perceptual Echo Control and Delay Estimation

Acoustic Echo Cancellation Using PEVD Based Adaptive Kalman Filter

Contact Info

Product

Resources

About