Discrete-time signal processing (2nd ed.)
Discrete-time signal processing (2nd ed.)
Adaptive Filtering: Algorithms and Practical Implementation
Adaptive Filtering: Algorithms and Practical Implementation
Acoustic MIMO Signal Processing (Signals and Communication Technology)
Acoustic MIMO Signal Processing (Signals and Communication Technology)
An acoustic human-machine front-end for multimedia applications
EURASIP Journal on Applied Signal Processing
Partitioned block frequency-domain adaptive second-order Volterra filter
IEEE Transactions on Signal Processing
Evaluation of Objective Quality Measures for Speech Enhancement
IEEE Transactions on Audio, Speech, and Language Processing
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Acoustic echoes represent a major source of discomfort in hands free, full-duplex, communication systems. The problem becomes particularly difficult when the loudspeakers are nonlinear as considered in this paper. In contrast to the single-microphone linear and nonlinear acoustic echo cancelation techniques, we take advantage of the spatial diversity offered by the microphone arrays. Indeed, having a set of microphones and multiple sources (i.e., the near and far ends) that can be active at the same time, this problem can be solved using a blind source separation (BSS) algorithm. The performance of the BSS can be further improved when combined with a linear acoustic echo canceler (LAEC). In this paper, we study the potentials of joint BSS and LAEC to cancel the echo signals in two schemes. In the first scheme, the BSS is deployed as a front-end and has a twofold function: reducing the acoustic echo and creating a linearly transformed echo reference that is used by the LAEC as a post-processor. In the second scheme, the BSS operates on multiple LAECs outputs to further reduce the residual echo from the target signal. We show that the first scheme outperforms the second one.