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Fast and robust acoustic system identification is still a research topic of interest, because of the typically time-variant nature of acoustic systems and the natural performance limitation of electroacoustic measurement equipment. In this paper, we propose NLMS-type adaptive identification with perfect-sweep excitation. The perfect-sweep is derived from the more general class of perfect sequences...
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 optimal framework for low-latency joint state...
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 often occurs. In this case, state-of-the-art...
In recent publications, continuous-azimuth inference of head related impulse responses (HRIRs) was treated as a time-varying system identification problem on the basis of dynamical measurements. The system identification thus can be handled by LMS-type adaptive filters for which we have the freedom to choose the excitation signal in this application. In order to provide the perspective of reducing...
A new method for fast acquisition of head-related impulse responses (HRIRs) for 3D-continuous-azimuth representation of the auditory sphere is presented. While the continuous HRIR representation in the azimuth direction is important for the rendering of moving sources in binaural sound systems, an HRIR discretization in the elevation is more tolerable. Basically, the paper suggests a multi-channel...
This paper presents an iterative approach to multi-channel blind system identification. The concept includes two subsystems for channel identification and equalization which are specifically tailored for robust mutual interaction. This robustness is a natural prerequisite for the convergence of iterative systems when no suitable a priori information about the channels or the input signal is available...
The design of fast learning and yet robust adaptive filters for acoustic echo control in hands-free voice communication has attracted the research community for decades. This paper presents a fresh and unified view of adaptive filter algorithms in order to change and to generalize some of the previously well-established paradigms. The unified understanding is achieved by introducing state-space dynamical...
Head related impulse responses (HRIRs) are the key to spatial realism in auditory virtual environments (AVEs). However, the measurement of discrete-azimuth HRIRs and their interpolation has been recognized as a tedious and delicate experimental procedure. We therefore suggest an adaptive filtering concept for continuous HRIR acquisition that completely avoids the traditional sampling and interpolation...
In this paper we review state-of-the-art signal processing technologies for enhancing speech and audio signals in hearing aids and assess their benefits and their potential for the purpose of acoustic scene analysis and synthesis. We discuss single and multi microphone techniques for source detection, localization, classification, and enhancement and we emphasize the need for rendering enhanced output...
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