Gerald Enzner

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A major challenge in acoustic signal processing lies in the uncertainty regarding the current state of the acoustic environment. The relevant applications in the field of speech and audio signal processing include the multichannel sound capture, the signal processing for spatial sound control, and the acoustic echo/interference cancellation. In this paper,(More)
We present a novel recursive Bayesian method in the DFT-domain to address the multichannel acoustic echo cancellation problem. We model the echo paths between the loudspeakers and the near-end microphone as a multichannel random variable with a first-order Markov property. The incorporation of the near-end observation noise, in conjunction with the(More)
Residual echo arises in hands-free telephony equipment due to insufficient echo canceler convergence, but can be suppressed using a postfilter. The most important control parameter for postfilter adaptation is therefore the residual echo power spectral density (PSD). In this contribution we present and compare residual echo PSD estimation techniques. We(More)
Hands-free terminals for speech communication employ adaptive filters to reduce echoes resulting from the acoustic coupling between loudspeaker and microphone. When using a personal computer with commercial audio hardware for teleconferencing, a sampling frequency offset between the loudspeaker output D/A converter and the microphone input A/D converter(More)
Residual echo arises in hands–free telephony equipment due to insufficient echo canceler convergence, but can be suppressed using a postfilter. The residual echo power spectral density is the most crucial control parameter for both frequency–domain acoustic echo cancellation and combined residual echo and noise postfiltering. In this contribution we present(More)
In this paper, we address adaptive acoustic echo cancellation in the presence of an unknown memoryless nonlinearity preceding the echo path. We approach the problem by considering a basis-generic expansion of the memoryless nonlinearity. By absorbing the coefficients of the nonlinear expansion into the unknown echo path, the cascade observation model is(More)
We consider the task of acoustic system identification, where the input signal undergoes a memoryless nonlinear transformation before convolving with an unknown linear system. We focus on the possibility of modeling the nonlinearity with different basis functions, namely the established power series and the proposed Fourier expansion. In this work the(More)
A linear dynamical model can be used to describe the evolution of an unknown system in noisy conditions. However, in most applications model parameters of a dynamical system are not known a priori, bringing into question the optimality of traditional state-only estimators. In this paper, we consider block-frequency-domain dynamical models and formulate an(More)
We present an extremely simple and effective signal processing solution to the acoustic echo control problem. The approach is based on the concept of synchronous statistical adaptation of an acoustic echo canceler and a postfilter for residual echo suppression. The required convergence state of the echo canceler is estimated by a new statistical element of(More)